Call Toll Fee - 
81
Total Projects
67
CSE Projects
14
ECE Projects
0
MECH Projects
Smart Vending Machine
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📌 Overview: Traditional vending machines lack real-time monitoring, cashless convenience, and inventory intelligence, leading to stock-outs, losses, and poor user experience. A Smart Vending Machine integrates digital payment and monitoring to improve accessibility, efficiency, and reliability. It addresses the growing demand for automated, contactless services in campuses, offices, hospitals, and public spaces.
🎯 Objectives: Enable cashless and contactless purchasing for user convenience
⚙ Methodology: he project uses embedded control, sensors, and connectivity to automate product dispensing and track inventory. Digital payment integration and a simple monitoring dashboard are employed to manage transactions and machine health. The system is designed for ease of use, reliability, and scalability.
✅ Key Outcomes: Functional smart vending machine prototype with cashless payment.
🌍 Impact: Academically, the project enhances hands-on learning in IoT and automation. Societally and industrially, it supports hygienic, 24/7 access to essentials with reduced manpower. The solution is scalable for multiple locations and can be extended with analytics, AI-based demand prediction, and remote fleet management.
👥 Stakeholders: V. KUSUMANJALI 231801130015
T. SHARON 231801400002
R. SATHISH 231801410007
S. DINESH 231801130016
G. JOGESWAR RAO 231801410004
G. SIDDARDHA 231801130008
S. SYAMALA NEELLAVENI 241801400015
V. INDU 241801130020
K. ANKITHA 241801410018
D NIKHITA SAI DURGA 241801400009
AR-Based Cultural Heritage Preservation Platform
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📌 Overview: The AR Based Cultural Heritage Preservation Platform uses Augmented Reality to digitally preserve and showcase cultural heritage sites, artifacts, and traditions. The platform creates interactive 3D and AR experiences that allow users to explore heritage in an immersive way. It enables virtual access to monuments, making heritage education more engaging and accessible. The system supports tourism, education, and research through guided AR content. Overall, it ensures long-term preservation and promotion of cultural heritage using modern technology.
🎯 Objectives: 1. To digitally preserve cultural heritage using AR and 3D technologies.
2. To provide immersive and interactive heritage learning experiences.
3. To promote cultural awareness among youth and the global audience.
4. To enhance tourism through virtual and on-site AR guidance.
5. To support heritage conservation, research, and restoration efforts.
⚙ Methodology: 1. Collect and digitize cultural heritage data using images, videos.
2. Create accurate 3D models and AR content for monuments and artifacts.
3. Integrate AR features into a mobile apk using AR frameworks in unity 3D.
4. Enable interactive visualization, narration, and guided experiences for users.
5. Deploy, test, and scale the platform for multiple heritage sites and users.
✅ Key Outcomes: 1. Digitally preserves cultural heritage using AR and 3D models.
2. Provides immersive and interactive learning experiences for users.
3. Increases youth engagement and cultural awareness through technology.
4. Enhances tourism with virtual and on-site AR guided experiences.
5. Enables global access and supports heritage restoration and research.
🌍 Impact: The project digitally preserves cultural heritage using Augmented Reality, ensuring its protection for future generations. It makes cultural learning immersive and interactive, increasing public engagement and awareness. The platform enhances education and tourism by providing rich AR-based experiences. It enables global access to heritage sites regardless of location. Additionally, it supports conservation and restoration through accurate digital documentation.
👥 Stakeholders: T. Mouli, Janaki ram, D. Harshit, D. Chandu, K. Thanushri, N. Sunayana.
RFID SMART TROLLY
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📌 Overview: he RFID-Based Smart Trolley System is an intelligent shopping solution designed to automate the billing process in supermarkets and retail stores.
The system uses Radio Frequency Identification (RFID) technology to identify products placed inside a shopping trolley and generate the bill automatically without manual barcode scanning.
Each product is attached with an RFID tag containing a unique identification number.
An RFID reader mounted on the trolley reads these tags and sends the information to a microcontroller unit, which retrieves product details such as name and price from a database.
The total bill is updated in real time and displayed to the customer. This system significantly reduces checkout time, minimizes human errors, and improves shopping efficiency.
🎯 Objectives: The main objectives of the RFID-based smart trolley project are:
To eliminate long queues at billing counters in supermarkets.
To automatically identify products using RFID technology.
To provide real-time bill generation while shopping.
To reduce manual labor and billing errors.
To enable faster and convenient checkout for customers.
To support inventory management by updating product data automatically.
To improve overall customer shopping experience.
⚙ Methodology: The RFID-based smart trolley system operates by integrating RFID technology with an embedded processing unit to automate the shopping and billing process.
Each product in the supermarket is fitted with an RFID tag containing a unique identification code.
An RFID reader mounted on the smart trolley continuously scans for tags when products are placed inside the trolley.
The scanned tag information is transmitted to a microcontroller, which processes the data by comparing the received tag ID with a pre-stored product database containing item names and prices.
Once the product is identified, the corresponding price is added to the total bill and the updated information is displayed on an LCD screen or mobile application in real time.
✅ Key Outcomes: The implementation of the RFID-based smart trolley system results in automated product identification and real-time billing without manual barcode scanning. The system successfully reduces checkout time by enabling customers to view and manage their bills while shopping. It ensures accurate billing by minimizing human intervention and provides seamless integration with digital payment systems. Additionally, the system enables automatic inventory updates, improving stock monitoring and control for retail stores.
🌍 Impact: The RFID-based smart trolley system has a significant impact on both customers and retailers. For customers, it enhances shopping convenience by eliminating long queues and providing transparency in pricing. For retailers, it reduces labor dependency at billing counters, increases operational efficiency, and improves inventory accuracy. The system also supports faster customer turnover, leading to better store management and improved service quality.
👥 Stakeholders: N.Ananth 231801131041
S.Pavan 231801400004
Dilesh Bhanu 231801400006
FIRE FIGHTING ROBOT
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📌 Overview: A Fire Fighting Robot is an automated or semi-automated system designed to detect and extinguish fires in hazardous environments where human intervention is risky. The robot is equipped with sensors to detect fire, smoke, or high temperature and uses a fire-extinguishing mechanism such as water, foam, or CO₂. It can be remotely controlled or work autonomously, ensuring faster response and improved safety.
🎯 Objectives: To design and develop a robot capable of detecting and extinguishing fire.
To minimize human risk in fire-hazard environments.
To provide a cost-effective and reliable fire safety solution.
To demonstrate the application of robotics and embedded systems in real-world safety systems.
⚙ Methodology: Fire Detection,Use flame sensors, smoke sensors, or temperature sensors to identify fire.,Control System,A microcontroller (Arduino / Raspberry Pi) processes sensor data.,Movement Mechanism,DC motors with motor drivers enable robot navigation.,Fire Extinguishing Unit,Water pump or extinguisher nozzle activated when fire is detected.,Power Supply,Rechargeable battery for continuous operation.,Testing & Validation,Robot performance tested under controlled fire conditions.
✅ Key Outcomes: Successful detection of fire sources,Efficient movement towards fire location,Automatic or remote-controlled fire suppression,Improved response time compared to manual firefighting,Demonstration of interdisciplinary engineering concepts.
🌍 Impact: Enhances safety by reducing human exposure to dangerous fires.
Useful in industries, warehouses, hospitals, and residential buildings.
Supports disaster management and emergency response systems.
Promotes innovation in robotics and automation.
Can be upgraded with AI, IoT, and camera surveillance.
👥 Stakeholders: CH . GANESH(221801130003 )
K . GANESH(221801130005 )
J . HEMANTH(221801130014 )
A . KULA VARDHAN(221801130020)
M . DURGA PRASAD(221801410003)
CH . SATYA SAI(221801410017 )
M . SRI SAI (221801410018 )
Smart grass cutter and pesticide spraying robot
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📌 Overview: built with Arduino Uno and HC-05 Bluetooth module that combines lawn mowing and pest control capabilities. The robot can be wirelessly controlled via smartphone to navigate across fields, cut grass efficiently, and spray pesticides in targeted areas, reducing manual labor and improving precision in farm maintenance.
🎯 Objectives: To Develop a multi-functional robot that can autonomously or remotely perform grass cutting and pesticide spraying operations To Design and integrate a Bluetooth-based control system that enables real-time remote operation via smartphone
⚙ Methodology: The Smart Grass Cutter and Pesticide Spraying Robot operates by integrating Bluetooth wireless communication with an Arduino-based control system to automate lawn maintenance and pest control operations. The robot chassis is equipped with DC motors for movement, a rotating blade mechanism for grass cutting, and a pump-driven spraying system for pesticide application. An HC-05 Bluetooth module mounted on the robot establishes wireless connectivity with a paired smartphone, enabling the user to send control commands remotely.Based on the received command (forward, backward, left, right, cut grass, or spray pesticide), the Arduino triggers the appropriate motors for navigation or activates the cutting blade and spraying pump. .
✅ Key Outcomes: developed a fully functional wireless-controlled robot that performs both grass cutting and pesticide spraying operations with minimal human intervention.
Implementation of a reliable Bluetooth-based remote control system enabling safe smartphone operation.
🌍 Impact: Reduces farmer exposure to harmful pesticides and physical strain from manual grass cutting operations.
Applicable in agriculture, horticulture, landscaping services, golf courses, public parks, and residential gardens.
Supports sustainable farming practices by enabling precise pesticide application and reducing chemical overuse.
Promotes innovation in agricultural automation and smart farming technologies for developing regions.
👥 Stakeholders: I.PAVAN AKHILESH(221801130006)
D.DORAMMA(221801130008)
K.KUSHAL KUMAR(221801130010)
G. THARUN(221801130019)
B.AJAY(221801131023)
S.V.S RAKESH SARMA(221801131025)
Robotic prosthetic 3d printed hand using EMG sensor
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📌 Overview: This project focuses on the design and fabrication of a low-cost robotic prosthetic hand controlled using Electromyography (EMG) signals. The prosthetic hand is 3D-printed to reduce manufacturing cost and weight, while EMG sensors capture muscle signals from the user’s forearm to enable intuitive control of hand movements such as gripping and releasing.
🎯 Objectives: To design and fabricate a functional 3D-printed robotic prosthetic hand,
To acquire and process EMG signals from human muscles,
To translate EMG signals into real-time hand movements,
To develop a cost-effective and user-friendly prosthetic solution
⚙ Methodology: Literature Review
Study existing prosthetic hand designs, EMG signal processing techniques, and control algorithms.
Mechanical Design
Design the prosthetic hand using CAD software
3D print hand components using suitable materials (PLA/ABS)
✅ Key Outcomes: A fully functional EMG-controlled robotic prosthetic hand
Successful conversion of muscle signals into mechanical motion
Lightweight and low-cost prosthetic prototype
🌍 Impact: Provides an affordable prosthetic solution for amputees
Enhances accessibility to assistive technology in low-resource settings
Encourages interdisciplinary learning (biomedical, mechanical, electronics)
👥 Stakeholders: S.Pavan(221801400007) K.Santosh(221801400003)
Self-Navigating Multi-Sensor Robot for Disaster Rescue Operations
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📌 Overview: Natural and man-made disasters such as earthquakes, fires, and building collapses often create environments that are unsafe or inaccessible for human rescuers. This project focuses on the design and development of a self-navigating robotic system equipped with multiple sensors to assist in search and rescue operations.The robot is capable of autonomous movement, obstacle detection, environmental monitoring, and victim detection, thereby reducing risk to human responders and improving rescue efficiency.
🎯 Objectives: To design a mobile robot capable of autonomous navigation
To integrate multiple sensors for real-time environment perception
To detect obstacles, hazardous conditions, and human presence
To assist rescue teams by operating in dangerous or inaccessible areas
To improve speed, safety, and accuracy of disaster rescue operations
⚙ Methodology: Sensor Integration for Navigation: Ultrasonic and infrared sensors enable the robot to detect obstacles and plan safe paths through debris and unstable terrain.
Environmental Monitoring: Gas, temperature, and smoke sensors continuously track hazardous conditions to detect unsafe levels.
Autonomous Control: A control algorithm processes sensor data to make real-time navigation decisions without human intervention.
Wireless Data Transmission: Live sensor data and alerts are sent to the rescue team via a wireless communication module.
Efficient Disaster Operation: The integrated system ensures accurate navigation, effective hazard detection, and reliable performance in disaster-affected areas.
✅ Key Outcomes: Successful development of a self-navigating rescue robot
Accurate obstacle detection and avoidance
Reliable sensing of hazardous conditions
Effective identification of human presence
Stable real-time data communication
Reduced dependence on manual intervention
🌍 Impact: Enhances safety of rescue personnel
Enables operations in high-risk environments
Reduces rescue response time
Improves chances of locating survivors
Cost-effective and scalable solution for disaster management
Applicable to military, firefighting, and industrial safety domains
👥 Stakeholders: T . VASU 221801410014
A . SAI 221801130011
Y . GOVINDA 221801410010
T . DAMODHAR RAO 221801130012
P . KARTHIKEYAN 221801130009
P . DINAKAR 221801131024
FINGER PRINT BASED ATTENDANCE SYSTEM
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📌 Overview: The Fingerprint Based Attendance System is a biometric solution designed to automate and manage attendance using fingerprint recognition technology. Unlike traditional attendance methods such as manual registers or ID cards, this system uniquely identifies individuals based on their fingerprint patterns. The system captures a user’s fingerprint, verifies it against stored biometric data, and records attendance automatically in a digital database. This improves accuracy, security, and efficiency in attendance management for institutions such as schools, colleges, and organizations.
🎯 Objectives: To eliminate manual and proxy attendance.
To ensure accurate and reliable attendance recording.
To reduce administrative workload and time consumption.
To provide secure authentication using biometric data.
To generate attendance reports automatically for easy monitoring and analysis.
To improve transparency and accountability in attendance management.
⚙ Methodology: Fingerprint Enrollment
Fingerprint Authentication
Verification and Attendance Marking
Data Storage and Management
Report Generation
✅ Key Outcomes: Accurate and tamper-proof attendance records.
Elimination of fake or duplicate attendance entries.
Reduced paperwork and administrative effort.
Faster attendance process compared to manual methods.
Secure storage of attendance data.
Easy retrieval and analysis of attendance information.
🌍 Impact: Educational Institutions: Improves discipline and attendance monitoring among students.
Organizations: Enhances workforce management and productivity.
Security: Prevents unauthorized access and identity fraud.
Efficiency: Saves time and operational costs.
Digital Transformation: Supports automation and modernization of record-keeping systems.
👥 Stakeholders: N. BHARATHI(231801410006)
N. ASHA(231801130027)
K. TARUN(231801130001)
S. RAVI KUMAR(231801130026)
S. YASWANTH(231801131001)
Identifying Taxonomy and Assessing Biodiversity from eDNA Datasets
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📌 Overview: Deep-sea eDNA studies are limited by incomplete reference databases and high computational costs, which hinder biodiversity assessment. This project develops an AI-driven, reference-light pipeline that clusters raw eDNA reads using unsupervised learning before any database lookup. By annotating only cluster representatives and estimating abundance from cluster sizes, it reduces alignment time while still enabling discovery of novel deep-sea taxa.
🎯 Objectives: Develop an AI-driven pipeline that clusters raw deep-sea eDNA reads into taxa-like units using unsupervised learning.
Assign taxonomy to cluster representatives where possible and estimate biodiversity from per-cluster abundances.
Provide an easy-to-use interface for non-experts to upload eDNA data and receive taxonomic and novelty-aware summaries.
⚙ Methodology: Convert raw deep-sea eDNA sequences into numerical fingerprints that capture DNA patterns without needing prior labels.
Use unsupervised AI to group similar fingerprints into taxa-like clusters and estimate biodiversity from cluster sizes.
Compare one representative per cluster to curated DNA marker databases to attach taxonomic names where possible, while still detecting novel taxa.
✅ Key Outcomes: A working AI-driven pipeline that clusters raw deep-sea eDNA reads into taxa-like groups and quantifies their relative abundances.
Taxonomy-aware outputs that attach names to cluster representatives where possible and highlight unlabeled clusters as candidates for novel or poorly represented taxa.
Prototype-ready CSVs and a planned user interface that together enable non-experts to explore biodiversity patterns and download reports for deep-sea monitoring applications.
🌍 Impact: For industry and conservation, the approach can be integrated into observatories and monitoring services to provide rapid, cost-effective biodiversity summaries that inform marine planning, protected areas, and restoration efforts.
👥 Stakeholders:
K.Bharathi -231801360013
Y.Lakshmi Chandana231-801380022
C.Venkat Dhanush-23180138007
K.Shashank Varma-231801371093
B.Tharun Kumar-231801380013
WOODEN ROBO
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📌 Overview: Wooden Robotics refers to the design and development of a robot using wood as the primary structural material instead of metal or plastic. The project integrates basic mechanical design, electronics, and programming to demonstrate robotic motion and control in a low-cost, eco-friendly, and lightweight manner. Despite using wood, the robot performs essential tasks such as movement, object handling, or sensing.
🎯 Objectives: To design a low-cost and eco-friendly robotic structure using wood
To understand basic robotic mechanisms like motion and control
To integrate electronics and programming with a mechanical system
To promote sustainable materials in engineering applications
To enhance hands-on learning in robotics and embedded systems
⚙ Methodology: Design Phase
Mechanical Assembly
Electronic Integration
Programming
Testing and Optimization
✅ Key Outcomes: Successful development of a functional wooden robot
Improved understanding of robotics fundamentals
Hands-on experience with embedded systems and motor control
Demonstration of cost-effective robot design
Enhanced teamwork and problem-solving skills
🌍 Impact: Encourages sustainable and eco-friendly engineering practices
Makes robotics accessible for students due to low cost
Useful for educational demonstrations and STEM learning
Reduces dependency on expensive materials
Inspires innovation using locally available resources
👥 Stakeholders: S.Pravallika-231801130013
L.Satyavathi -231801130014
P.Kiran kumar -231801131040
B.Durga prasad-231801410021
T .Hemanth kumar-231801130006
VOICE CONTROL WHEEL CONTROL
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📌 Overview: The Voice Controlled Wheelchair is an assistive mobility system designed to help people with physical disabilities move independently using simple voice commands. The system interprets spoken instructions (such as forward, backward, left, right, stop) and converts them into motor actions that control the wheelchair. It integrates speech recognition, a microcontroller, motor drivers, and safety features to provide hands-free and user-friendly mobility.
🎯 Objectives: To enable independent mobility for people with severe motor impairments.
To design a hands-free control system using voice commands.
To develop a low-cost and reliable assistive wheelchair solution.
To ensure safe navigation with accurate command recognition and quick response.
To improve quality of life and reduce dependency on caregivers.
⚙ Methodology: The voice controlled wheelchair works by capturing the user’s voice commands through a microphone or mobile application and converting them into control signals using a speech recognition module. These signals are processed by a microcontroller, which controls the motor driver circuit to move the wheelchair in the required direction. This method enables smooth, hands-free and safe movement of the wheelchair using simple voice commands.
✅ Key Outcomes: Social Impact: Enhances independence and dignity of people with disabilities.
Health Impact: Reduces physical strain and mental stress on users and caregivers.
Technological Impact: Promotes the use of embedded systems and AI-based voice recognition in healthcare.
Economic Impact: Offers a low-cost alternative to expensive commercial powered wheelchairs.
🌍 Impact: Addresses a real-world problem faced by physically challenged individuals.
Encourages inclusive design and accessibility in engineering solutions.
Demonstrates practical application of embedded systems, signal processing, and control systems.
Can be further enhanced with IoT, GPS, obstacle avoidance, and AI-based learning for smarter mobility.
👥 Stakeholders: D. ANUSHA (231801130004)
N. POORNESH (231801130018)
N. YAMUNA (231801130007)
K. RAMU (231801400012)
P. JOHN (231801400011)
V. MAHENDRA (231801440001)
T.SRIVARSHITH (231801130022)
voice control writing robot
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📌 Overview: A voice control writing robot is an automated system that converts spoken commands into written text or drawings.
It uses speech recognition technology to understand user voice inputs. The recognized commands are processed by a microcontroller or processor.
Motors and mechanical parts control the movement of a pen on paper. This system reduces manual effort and improves writing accuracy. It is useful for education, assistance for disabled persons, and automation applications.
🎯 Objectives: To design a robot that writes using voice commands.
To convert human speech into machine-understandable signals.
To control motor movements precisely for accurate writing.
To minimize human involvement in repetitive writing tasks.
To assist physically challenged individuals in writing activities.
To demonstrate the integration of speech recognition and robotics.
⚙ Methodology: The user gives a voice command through a microphone or mobile application.
The voice input is converted into text using a speech recognition module.
The processed command is sent to the microcontroller for decision making.
The microcontroller generates control signals for the motor driver circuit.
Motors move the pen mechanism according to the given command.
The robot writes the required text or pattern accurately on paper.
✅ Key Outcomes: Successful conversion of voice commands into written text.
Accurate control of pen movement using motor mechanisms.
Reduced manual effort in writing tasks.
Improved accessibility for physically challenged users.
Effective integration of speech recognition and robotic control.
Demonstration of a reliable and user-friendly automation system.
🌍 Impact: Enables hands-free writing, improving convenience and efficiency.
Provides strong support for physically challenged and elderly users.
Reduces human effort and time in repetitive writing tasks.
Enhances learning by combining voice recognition with robotics.
Encourages the use of automation in everyday applications.
Demonstrates the practical impact of human–machine interaction technology.
👥 Stakeholders: J.SIREESHA (221801130016)
D.DHARANI (221801130015)
P.KAVYA (221801130018)
S.VARDHAN(221801130001)
P.BHARGAV(221801410016)
B.PRANEETH(221801130013)
LoRa BASED DISASTER MANAGEMENT ALERT SYSTEM
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📌 Overview: This project uses LoRa wireless technology to send emergency alerts during disasters. It helps in communication even when mobile networks fail.
🎯 Objectives: To provide fast and long-range disaster warning messages. To ensure people get alerts safely with low power and low cost.
⚙ Methodology: Sensors detect disaster conditions like flood or fire. The data is sent through LoRa modules to a receiver, which triggers an alert message or alarm.
✅ Key Outcomes: Quick disaster alerts can be delivered over long distances. The system works reliably even in remote areas.
Impact
It improves public safety by giving early warnings. It reduces damage and helps in faster rescue operations.
🌍 Impact: LoRa is best for disaster management because it works with low power and long-range coverage. It is a useful solution for emergency communication.
👥 Stakeholders: P.SUNEEL[231801130030]
M.POOJITHA[231801410021]
V.DINESH[231801130012]
M.YASHODHA KRISHNA[231801130034]
Travel Management
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📌 Overview: This project focuses on building a centralized travel management system to plan, track, and manage travel bookings efficiently. It addresses issues like manual planning, poor tracking, and lack of transparency. The system improves user convenience and operational efficiency for travelers and administrators.
🎯 Objectives: • Simplify travel planning and bookings
• Track travel details and expenses
• Improve coordination between users and admins
⚙ Methodology: A web-based application developed using React for UI and Node–Express for APIs. MongoDB stores travel data. The system follows a role-based workflow with real-time updates.
✅ Key Outcomes: • Online travel planning module
• Centralized booking records
• Efficient travel tracking system
🌍 Impact: Enhances travel organization and reduces manual errors. Can be scaled for corporate, educational, or tourism sectors.
👥 Stakeholders: GUDLA AMRUTHA – 221801380006
MERUGU MOUNIKA RATNAM – 221801380013
MUDIMUKKI PRAVEEN KUMAR – 221801380021
YEDLURI UDAYA RAJU – 221801380027
TIPPANA SAI KIRAN – 221801380034
Data Clinic – Smart Data Preprocessing and Cleaning AI Assistant
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📌 Overview: The project provides an AI-powered assistant to automate data cleaning and preprocessing tasks. It addresses the challenge of handling noisy and inconsistent datasets. This tool improves data quality for analytics and machine learning applications.
🎯 Objectives: • Automate data preprocessing tasks
• Reduce manual data cleaning effort
• Improve data quality for analysis
⚙ Methodology: The system uses a React-based interface with Node–Express APIs. AI-based preprocessing logic is applied, and MongoDB stores datasets and processing history.
✅ Key Outcomes: • Automated data cleaning assistant
• Preprocessed datasets ready for analysis
• Reduced preprocessing time
🌍 Impact: Supports data science education and industry use cases. Scalable for large datasets and analytics platforms.
👥 Stakeholders: SANA SRIVALLI – 221801380029
DVV KALYAN – 221801380022
BODANKI BALA SAI – 221801120005
RONGALI JITENDRA – 221801120004
CHEVALA SIVAMANI – 221801380036
Parking Lot Management
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📌 Overview: This project automates parking slot allocation and monitoring. It solves problems like manual parking tracking and congestion. The system provides real-time parking availability and efficient space utilization.
🎯 Objectives: • Automate parking slot allocation
• Monitor parking availability
• Reduce congestion and manual effort
⚙ Methodology: A full-stack web application with real-time updates. React handles the dashboard, Node–Express manages logic, and MongoDB stores vehicle and slot data.
✅ Key Outcomes: • Real-time parking status
• Automated slot assignment
• Improved parking efficiency
🌍 Impact: Useful for campuses, malls, and smart cities. Can be integrated with IoT-based parking systems.
👥 Stakeholders: NEELIROTHU HYMAVATHI – 221801370009
S VANDANA – 221801370052
JANA MOUNIKA – 221801370065
TADAKA KAVYA – 221801370068P
CHARISHMA – 221801370074
Skill Course Management
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📌 Overview: This system manages skill-based courses, enrollments, and progress tracking. It addresses difficulties in managing multiple courses manually. The platform supports structured learning and skill development.
🎯 Objectives: • Manage skill courses digitally
• Track student enrollment and progress
• Improve course accessibility
⚙ Methodology: Developed using MERN stack with role-based access. MongoDB stores course and user data, while dashboards provide insights.
✅ Key Outcomes: • Centralized course management
• Student progress tracking
• Organized skill repository
🌍 Impact: Encourages skill development and supports employability-focused education. Easily scalable for institutions.
👥 Stakeholders: THUMMALA AKASH – 221801370067
KODA MAYANK – 221801370002
NADIPINTI MURALI – 221801370005
GUNTAREDDI LAKSHMI – 221801370022
ALAJANGI MANASA – 221801370023
AI-Enhanced Ride Booking Web App (Cycle)
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📌 Overview: This project builds a smart cycle ride booking platform with AI-based enhancements. It addresses urban mobility and eco-friendly transport needs. The system optimizes ride allocation and user experience.
🎯 Objectives: • Enable cycle ride booking online
• Optimize ride availability using AI
• Promote eco-friendly transport
⚙ Methodology: React-based booking UI with Node–Express backend. MongoDB stores ride data, and AI logic supports smart suggestions.
✅ Key Outcomes: • Online cycle booking system
• Optimized ride allocation
• User-friendly interface
🌍 Impact: Supports sustainable transport initiatives and smart campus solutions. Can expand to city-level deployment.
👥 Stakeholders: N HARINI DEVI MADDULA – 221801380030
M D G MAHESH BABU – 221801380024
NUTI VENKATA MANI DEEPIKA – 221801380009
ABOTHULA SAI – 221801370013
AI-Driven Worker Management Platform
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📌 Overview: This platform manages workers using AI-driven insights for task allocation and monitoring. It solves inefficiencies in manual workforce management. The system improves productivity and transparency.
🎯 Objectives: • Automate worker management
• Optimize task allocation using AI
• Track worker performance
⚙ Methodology: Built using MERN stack with AI-based decision logic. MongoDB stores worker and task data with dashboards for monitoring.
✅ Key Outcomes: • Smart worker allocation system
• Performance tracking dashboards
• Reduced management effort
🌍 Impact: Applicable to industries, construction, and service sectors. Scalable for enterprise-level workforce systems.
👥 Stakeholders: S SHYAM KOUSHIK – 221801370016
DATHI HIMA BINDU – 221801370050
KOLA MADHUMITHA – 221801120003
TETAKALI YAMINI – 221801370053
College Talent Hub
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📌 Overview: This project creates a centralized platform to showcase and manage student talents. It addresses the lack of structured talent recognition systems. The hub connects students with opportunities.
🎯 Objectives: • Identify and showcase student talent
• Provide opportunity visibility
• Encourage holistic development
⚙ Methodology: A web portal built with React and Node–Express. MongoDB stores talent profiles, achievements, and event data.
✅ Key Outcomes: • Central talent repository
• Student achievement tracking
• Improved engagement
🌍 Impact: Strengthens student visibility and institutional reputation. Can be linked with placement and event systems.
👥 Stakeholders: URJANA HARIKA – 221801120001
NEELIROTHU HEMAVATHI – 221801380004
RAMBHA JHANSI – 221801380019
MOYYA TEJASRI – 221801380026
D.S.H.S SUDHEER – 221801380032
BizBoost: Automated Social Media Promotion Tool
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📌 Overview: BizBoost automates social media promotions for businesses. It solves the challenge of manual content scheduling and performance tracking. The tool improves marketing efficiency for small businesses.
🎯 Objectives: • Automate social media posting
• Analyze engagement performance
• Improve digital marketing reach
⚙ Methodology: Developed using MERN stack with automation logic. MongoDB stores campaigns and analytics data.
✅ Key Outcomes: • Automated promotion tool
• Engagement analytics dashboard
• Reduced marketing effort
🌍 Impact: Supports startups and small businesses. Scalable for digital marketing agencies and enterprises.
👥 Stakeholders: GAVARA LOKESH – 221801370034
BRUNDAVANA PAVAN SAI – 221801370045
VUPPULURI KALYAN KUNDHAN – 221801370041
PANDI PAANDU RANGA GANESH – 221801370061
NAGADEVARA ARYATEJA – 221901370063
Faculty Management System
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📌 Overview: A web-based system to manage faculty profiles, workload, schedules, and academic records efficiently. It reduces manual paperwork and improves administrative accuracy. The system ensures easy access and better coordination within the institution.
🎯 Objectives: • Digitize faculty records
• Simplify workload & timetable management
• Improve administrative efficiency
⚙ Methodology: Develop a role-based web application with CRUD operations, secure authentication, and centralized data storage using MongoDB.
✅ Key Outcomes: • Digital faculty database
• Automated workload tracking
• Improved admin efficiency
🌍 Impact: Enhances institutional productivity and supports scalable academic management solutions.
👥 Stakeholders: L Poojitha – 221801350004
D Niharika – 221801350008
S Sai Manikanta Reddy – 221801350009
M Haarini Sree – 221801390029
B Jithendra – 221801390002
Vehicle Entry / Exit System using QR Code
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📌 Overview: This system automates vehicle entry and exit using QR code scanning. It improves campus security and minimizes manual verification delays. The system maintains accurate vehicle movement records.
🎯 Objectives: • Automate vehicle access
• Improve security monitoring
• Maintain digital logs
⚙ Methodology: Implement QR-based authentication integrated with a web dashboard for monitoring and reporting.
✅ Key Outcomes: • QR-based access system
• Real-time vehicle logs
• Reduced manual errors
🌍 Impact: Useful for campuses, gated communities, and industries for secure vehicle management.
👥 Stakeholders: Raja Prem Sai Maddula – 221801390008
Naga Sai Preetham Maddula – 221801350007
Bhaskar Viswanadh Devisetti – 221801350019
Rohith Vinay Cherukuri – 221801350017
Sai Kiran Suvvari – 221801350002
Food Order System using React, Express and MongoDB
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📌 Overview: An online food ordering platform that allows users to browse menus, place orders, and track status digitally. It streamlines restaurant operations and improves customer experience.
🎯 Objectives: • Enable online ordering
• Reduce order processing time
• Improve user convenience
⚙ Methodology: Build a responsive web app with order management, authentication, and database-driven menu handling.
✅ Key Outcomes: • Online ordering portal
• Order tracking system
• Efficient restaurant workflow
🌍 Impact: Helps small restaurants digitize operations and scale online services.
👥 Stakeholders: P. Harshitha – 221801340021
A. Varshitha – 221801340022
M. Mahesh – 221801340019
Ch. Srujana – 221801340015
B. Vasu – 221801340010
P. Gani Babu – 221801340016
Agrismart: All-in-One Intelligent Farming Portal
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📌 Overview: A digital platform designed to support farmers with crop information, weather updates, and market insights. It aims to modernize agriculture through technology-driven decision support.
🎯 Objectives: • Support farmers digitally
• Provide real-time information
• Improve agricultural productivity
⚙ Methodology: Develop an integrated portal with dashboards, APIs, and database-driven insights.
✅ Key Outcomes: • Smart farming portal
• Centralized agri information
• Improved decision-making
🌍 Impact: Promotes smart agriculture and supports sustainable farming practices.
👥 Stakeholders: Senapathi Suresh – 221801340007
K. V. Ganesh – 221801340005
S. Rakesh – 221801340014
V. Jagadeesh – 221801340018
K. Lavanya – 221801390020
Centralized Wallet with AI Chat Bot
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📌 Overview: A digital wallet system integrated with an AI chatbot for user assistance. It enables secure transactions and provides instant query resolution through conversational AI.
🎯 Objectives: • Enable secure payments
• Provide AI-based assistance
• Improve user engagement
⚙ Methodology: Implement wallet services with chatbot integration for FAQs and transaction support.
✅ Key Outcomes: • Digital wallet system
• AI chatbot support
• Secure transaction handling
🌍 Impact: Useful for fintech applications and scalable digital payment ecosystems.
👥 Stakeholders: R. Dhillee Rao – 221801350016
B. Tejaswarao – 221801390024
G. Abhishek – 221801390028
K. Venkata Sai Teja – 221801390021
T. Prasanna – 221801390026
Room Usage Management System (Classroom / Hall / Gallery Hall)
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📌 Overview: A scheduling system to manage room allocation linked with timetables. It avoids conflicts and optimizes infrastructure usage.
🎯 Objectives: • Automate room scheduling
• Avoid clashes
• Optimize space utilization
⚙ Methodology: Create a timetable-linked booking system with admin controls and real-time availability.
✅ Key Outcomes: • Digital room scheduler
• Conflict-free allocations
• Efficient space usage
🌍 Impact: Improves academic infrastructure planning and institutional resource management.
👥 Stakeholders: B. Aditya – 221801390010
D. Sasikanth – 221801390011
D. Purushotham – 221801390018
K. Lavanya – 221801390023
A. Greshma – 221801350006
P. Satwik – 221801350015
(Zoom-like) e-Meeting Application
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📌 Overview: A web-based video meeting platform for online collaboration. It supports virtual communication for academics and organizations.
🎯 Objectives: • Enable online meetings
• Support collaboration
• Reduce physical dependency
⚙ Methodology: Build a real-time meeting system with authentication and session management.
✅ Key Outcomes: • Online meeting platform
• Real-time collaboration
• Secure access
🌍 Impact: Supports remote education and digital workplaces.
👥 Stakeholders: P. Satyanarayana – 221801340020
M. Vamsi Krishna – 221801340009
Y. Chenna Pavan Reddy – 221801340008
G. Karthik Srinivas – 221801340012
P. Laya Vardhan – 221801340017
Vehicle Usage Management System
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📌 Overview: A system to track and manage vehicle usage, fuel logs, and allocation. It ensures transparency and efficient utilization of vehicles.
🎯 Objectives: • Track vehicle usage
• Maintain usage logs
• Improve accountability
⚙ Methodology: Develop a management dashboard with usage records and reports.
✅ Key Outcomes: • Vehicle tracking system
• Usage analytics
• Reduced misuse
🌍 Impact: Suitable for institutions and organizations managing vehicle fleets.
👥 Stakeholders: M. Guru Manohar – 221801350014
S. Madhuri – 221801350010
Nandyala Giridhar – 221801340011
Botchu Koteswara Rao – 221801340013
Face Recognition Voting Web Application
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📌 Overview: A secure online voting system using face recognition for authentication. It ensures voter identity verification and reduces fraudulent voting.
🎯 Objectives: • Ensure secure voting
• Prevent impersonation
• Automate vote counting
⚙ Methodology: Implement face recognition authentication integrated with a voting portal.
✅ Key Outcomes: • Secure voting platform
• Automated verification
• Accurate results
🌍 Impact: Useful for secure digital elections and organizational voting systems.
👥 Stakeholders: Yerra Rohan Kumar – 221801350001
Mallada Naveen – 221801350003
Juttu Manikanta – 221801390009
Balla Harsha Vardhan – 221801390030
TITAN STOCK SALES PREDICTION USING PYTHON
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📌 Overview: An accurate way to predict the sales of a company
🎯 Objectives: 1. To analyze historical Titan stock/sales data and identify trends and patterns using data analysis techniques.
2. To build a predictive model using Python and machine learning algorithms to forecast future stock sales.
3. To evaluate the accuracy of predictions using suitable performance metrics and improve model reliability.
4. To help investors and decision-makers make informed financial decisions based on predicted stock sales behavior.
⚙ Methodology: Data Collection: Historical Titan stock/sales data is collected from reliable sources and stored in a structured format for analysis.
Data Preprocessing: The collected data is cleaned by handling missing values, removing noise, and normalizing data to make it suitable for modeling.
Model Building: Machine learning algorithms such as Linear Regression or Time Series models are implemented using Python to train the prediction model.
Evaluation & Prediction: The model’s performance is evaluated using accuracy metrics, and the trained model is used to predict future Titan stock sales.
✅ Key Outcomes: Accurate analysis of historical Titan stock/sales data with clear identification of trends and patterns.
A trained and tested machine learning model capable of predicting future stock sales.
Improved understanding of how data science and Python can be applied to real-world financial problems.
Useful predictive insights that support better investment and business decision-making.
🌍 Impact: Helps investors and analysts make informed decisions by providing reliable forecasts of Titan stock sales.
Reduces financial risk by enabling early identification of market trends and potential fluctuations.
Demonstrates the practical application of Python and machine learning in real-world stock market analysis.
Supports data-driven planning and strategy development for businesses and financial institutions.
👥 Stakeholders: ELURU SATYA YAMINI -24KD1A0588
G.PRASUNA -24KD1A05C4
G.JAYA RANJITHA - 24KD1A0592
RFID based Library gate register using VL53 LASER sensor
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📌 Overview: used two RFID readers for login and logout and also used VL53 laser sensor for detecting the legit pass and ardunio
🎯 Objectives: solved the problem of writing the logs of students manually
⚙ Methodology: obj 1: solved the issue of writing the logs book obj:2 reduced the work of the faculty to reenter the log details of students
✅ Key Outcomes: log details of students in excel sheet with just a click
🌍 Impact: used in the GAYATRI VIDYA PARISHAD COLLEGE FOR DEGREE AND PG COURSES Rushikonda campus which let a lot of time saving for the students and as well as faculty
👥 Stakeholders: M.lokesh reddy, G.Vamsi krishna
Smart Helpdesk Ticketing Solution for IT Services
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📌 Overview: The Smart Helpdesk Ticketing Solution for IT Services is a web-based system designed to manage and resolve IT-related issues efficiently within an organization. Instead of using emails or multiple platforms, users can raise tickets through a single centralized system. The solution helps IT teams track, prioritize, and resolve issues faster, improving overall service quality and user satisfaction.
🎯 Objectives: The main objectives of this project are:
⚙ Methodology: The project is developed using a structured approach:
✅ Key Outcomes: A fully functional smart helpdesk system
Faster and more efficient handling of IT issues
Easy tracking of ticket status by users
Reduced manual workload for IT administrators
Improved organization and reporting of IT service data
🌍 Impact: This project significantly improves IT service management by reducing delays and manual errors. It increases productivity by minimizing system downtime and provides better transparency in issue resolution. The solution is scalable and can be used in educational institutions, corporate offices, and large organizations, making it highly impactful and relevant.
👥 Stakeholders: Akshaya (231801370013)
Language Agnostic Chatbot
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📌 Overview: The Language Agnostic Chatbot is an AI-powered conversational system designed to communicate with users in multiple languages without language barriers. The chatbot can understand, process, and respond to user queries regardless of the input language. It uses Natural Language Processing (NLP), language detection, and translation technologies to provide meaningful and accurate responses.
🎯 Objectives: To develop a chatbot that supports multilingual communication
⚙ Methodology: Language Detection – Identify the language of user input
✅ Key Outcomes: Successful multilingual communication support
🌍 Impact: Helps users from different language backgrounds
👥 Stakeholders: S. Hindu – 231801370021
Andhra Pradesh Smart Tourism Recognition Chatbot
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📌 Overview: The Andhra Pradesh Smart Tourism Recognition Chatbot is an AI-powered conversational system designed to assist tourists by providing accurate, real-time information about tourist destinations across Andhra Pradesh. The chatbot interacts with users through natural language, recognizes user intent, and delivers personalized recommendations related to places, culture, transportation, accommodation, food, and travel plans. This system aims to enhance the tourism experience by making information easily accessible through an intelligent virtual assistant.
🎯 Objectives: To develop an AI-based chatbot that provides smart tourism assistance
⚙ Methodology: Natural Language Processing (NLP) isused to understand user queries
✅ Key Outcomes: A functional AI chatbot capable of handling tourism-related queries
🌍 Impact: Enhances digital tourism services in Andhra Pradesh
👥 Stakeholders: R.Dinesh (2318013700050)
Language Agnostic Chatbot
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📌 Overview: The Language Agnostic Chatbot is an intelligent conversational system designed to communicate with users in multiple languages seamlessly. It allows users to interact with the chatbot in their preferred language without any language barrier. The system automatically detects the user’s input language, processes the request, and responds accurately, making it suitable for global users and multilingual environments.
🎯 Objectives: The main objectives of this project are:
⚙ Methodology: The project follows a systematic development approach:
✅ Key Outcomes: A fully functional language-independent chatbot
🌍 Impact: This project plays a vital role in bridging communication gaps caused by language differences. It enhances inclusivity by allowing users from different linguistic backgrounds to access information easily. The Language Agnostic Chatbot can be effectively used in customer support systems, educational platforms, healthcare services, and government portals, making it highly impactful and relevant in today’s globalized digital world.
👥 Stakeholders: D. Harshith - 231801370006
Smart Helpdesk Ticketing System for IT Solutions
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📌 Overview: This project is a smart, AI-enabled helpdesk ticketing system designed to manage IT issues efficiently. Users can raise tickets in multiple languages (English, Telugu, Hindi), and the system automatically categorizes and prioritizes issues. Admins resolve tickets and notify users via email or SMS once the issue is fixed.
🎯 Objectives: To automate IT issue management
⚙ Methodology: User raises a ticket via web interface
✅ Key Outcomes: Faster issue resolution
🌍 Impact: This system helps organizations manage IT support more efficiently than traditional methods. By using AI, it reduces delays, improves accuracy, and provides better communication compared to tools like basic ticket systems.
👥 Stakeholders: Name of the Students
Smart Helpdesk Ticketing for IT Solutions with Voice Assistance
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📌 Overview: The Smart Helpdesk Ticketing for IT Solutions with Voice Assistance project focuses on improving the efficiency of IT support services by integrating voice-based interaction into a helpdesk ticketing system. In many organizations, users face difficulties in explaining technical issues through traditional text-based systems, which can lead to delays and errors in ticket handling.
🎯 Objectives: The main objectives of this project are :
⚙ Methodology: The Project is developed using a step-by-step and structured approach:
✅ Key Outcomes: Voice-enabled helpdesk ticket submission
🌍 Impact: This project enhances IT service management by making helpdesk systems more user-friendly and efficient. Voice assistance simplifies issue reporting, especially for non-technical users, and helps organizations resolve IT problems quickly. The system improves productivity, reduces downtime, and supports scalable IT operations.
👥 Stakeholders: M. Sri CHARAN 231801120020
AI DRIVEN CHATBOT FOR INGRES
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📌 Overview: AI Driven Chatbot for INGRES is an intelligent, mobile-first conversational assistant designed to streamline institutional communication and enhance user engagement within the INGRES platform. It is a full-stack application powered by a high-performance FastAPI backend and a responsive Vanilla JavaScript frontend. The system incorporates a Hybrid AI Engine that combines cloud-based Large Language Models with a reliable local response mechanism to ensure uninterrupted assistance. Additionally, the chatbot supports voice interaction and multilingual communication, enabling users to access information quickly and efficiently regardless of language or technical expertise.
🎯 Objectives: Improve User Experience: Deliver instant, accurate, and context-aware responses to user queries related to INGRES services.
⚙ Methodology: Hybrid AI Architecture: Implements intelligent routing that prioritizes cloud-based reasoning while seamlessly switching to predefined local responses during connectivity issues.
✅ Key Outcomes: Smart Conversational Support: Successfully developed a chatbot capable of handling diverse institutional queries with high accuracy.
🌍 Impact: Enhanced Institutional Efficiency: Automates repetitive queries, allowing administrative systems to function more effectively.
👥 Stakeholders: Manikanta – 231801370063
AI-Powered Conversational Interface for ARGO Ocean Data Discovery & Visualization
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📌 Overview: FloatChat is an AI-based web application that enables users to interact with global oceanographic data collected by the Argo Program through a conversational interface. Instead of manually searching complex datasets, users can ask questions in natural language and receive meaningful visualizations such as graphs and maps along with AI-generated explanations. The system simplifies ocean data access for students, researchers, and non-experts.
🎯 Objectives: The main objective of this project is to design and develop an AI-powered conversational system that makes ARGO ocean data easy to discover, analyze, and visualize by allowing users to interact with the data using simple natural language queries.
⚙ Methodology: ARGO ocean data is collected from global data sources.
✅ Key Outcomes: Successfully developed a conversational interface for ocean data exploration
🌍 Impact: FloatChat reduces technical barriers in oceanographic data analysis and promotes data accessibility. It supports climate change studies, academic research, and ocean education by transforming raw scientific data into interactive and understandable insights. The project demonstrates the effective use of AI in environmental data analysis.
👥 Stakeholders: B.Bobby-231801370017
Digital Health Record Management System for Migrant Workers in Kerala
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📌 Overview: This project focuses on developing a centralized digital health record management system for migrant workers in Kerala. The system enables secure storage, retrieval, and monitoring of health records to support early disease detection, continuous healthcare access, and effective public health surveillance. The solution is aligned with Sustainable Development Goals (SDGs) and supports equitable healthcare delivery under the initiatives of the Government of Kerala through the Health Services Department.
🎯 Objectives: 1.To create a centralized digital repository for migrant workers’ health records
2.To enable early identification and tracking of infectious diseases
3.To improve access to fair and impartial healthcare services for migrant populations
4.To support public health surveillance and disease elimination programs
5.To align healthcare management with Sustainable Development Goals (SDGs)
⚙ Methodology: 1.Design a secure, web-based health record management platform
2.Collect and store individual health data such as medical history, test reports, and vaccination records
3.Implement role-based access for healthcare providers and authorities
4.Enable data analytics for disease trend monitoring and outbreak prediction
5.Ensure data privacy, security, and compliance with healthcare standards
✅ Key Outcomes: The project enables the digitization and centralization of health records for migrant workers, ensuring accurate and easily accessible medical data. It improves disease monitoring by supporting early detection of potential outbreaks and enables faster, more efficient healthcare service delivery. The system provides reliable, data-driven insights to assist public health authorities in informed decision-making and enhances coordination between healthcare providers and government bodies for effective health management.
🌍 Impact: The solution significantly reduces the risk of infectious disease transmission within communities by enabling proactive monitoring and timely intervention. It strengthens Kerala’s public health surveillance infrastructure while promoting inclusive and equitable access to healthcare services for migrant workers. Additionally, the project supports long-term disease prevention and elimination strategies and contributes directly to the achievement of national and global Sustainable Development Goals.
👥 Stakeholders: G. Susmitha Reddy - 231801360008
K. Gayathri - 231801360012
K. Eswar Guptha - 231801380001
Ch. Srija - 231801380002
L. Ravi - 231801380003
M. Manoj Kumar - 231801380028
Smart Attendance and Timetable Generator System
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📌 Overview: Manual attendance and timetable management in educational institutions is time-consuming, error-prone, and difficult to scale. This project proposes a Smart Attendance and Timetable Generator System that automates student attendance and dynamically generates optimized class timetables. The system reduces administrative workload and improves accuracy, transparency, and efficiency. It supports digital transformation in academic management systems.
🎯 Objectives: • To automate student attendance recording using a smart digital system. • To generate optimized and conflict-free timetables for classes and faculty. • To reduce manual errors and administrative workload in institutions. • To provide real-time access to attendance and timetable information for stakeholders.
⚙ Methodology: The system is developed as a web-based application with secure login for students, faculty, and administrators. Attendance is captured digitally through authenticated user inputs or QR-based verification. A timetable generation module uses predefined rules and constraints to automatically create schedules. The platform stores data in a centralized database and provides dashboards for monitoring and reporting.
✅ Key Outcomes: • Functional smart attendance management system with real-time tracking. • Automated timetable generator with conflict-free scheduling. • Centralized digital records for students, faculty, and administrators. • User-friendly dashboard for monitoring attendance and schedules.
🌍 Impact: Academically, the project enhances learning in web development, databases, and system design. Institutionally, it improves operational efficiency by reducing paperwork and manual scheduling conflicts. Societally, it promotes digital adoption in education management. The system is scalable for larger institutions and can be extended with biometric integration, mobile apps, analytics, and AI-based timetable optimization in the future.
👥 Stakeholders: Molli.Rohith_231801340014
AI-Powered Crop Disease Detection App
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📌 Overview: Crop diseases significantly reduce agricultural yield and farmers’ income due to delayed or inaccurate diagnosis. This project develops an AI-powered mobile application that detects crop diseases from leaf images and provides early alerts and basic guidance. The system improves decision-making and promotes precision agriculture. It supports timely intervention to reduce losses and improve productivity.
🎯 Objectives: • To detect crop diseases from images using AI-based models. • To provide early alerts and basic guidance to farmers. • To improve crop yield through timely disease identification. • To make disease diagnosis accessible via a mobile app.
⚙ Methodology: The solution uses image capture via a mobile app and a trained machine learning model to identify disease patterns. A backend service processes images and returns predictions with confidence levels. The app provides simple recommendations and stores detection history for tracking. The system is designed for usability, scalability, and future model updates.
✅ Key Outcomes: • Functional mobile app for crop disease detection. • Trained AI model for identifying common crop diseases. • Real-time disease prediction with basic guidance. • Detection history and reporting dashboard.
🌍 Impact: Academically, the project builds skills in AI, machine learning, and mobile app development. Societally, it supports farmers with accessible, low-cost decision support to reduce crop losses. Industrially, it aligns with smart agriculture and agri-tech solutions. The system is scalable to multiple crops and regions and can be extended with weather data, multilingual support, expert advisory, and integration with IoT sensors.
👥 Stakeholders: Sadi Teja - 231801350001
Cafe Management System
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📌 Overview: Manual order handling and billing in cafes leads to delays, errors, and poor customer experience, especially during peak hours. This project develops a Cafe Management System to automate order taking, billing, and basic inventory tracking. The system improves operational efficiency and service speed. It supports digital transformation for small and medium food outlets.
🎯 Objectives: • To automate order management and billing processes in cafes. • To reduce manual errors and waiting time for customers. • To manage menu items and basic inventory digitally. • To provide simple reports for daily sales and performance.
⚙ Methodology: The system is developed as a web-based application with separate modules for admin, staff, and billing counter. Orders are placed digitally and processed in real time, with automatic bill generation. A centralized database stores menu, orders, and sales data. The application provides simple dashboards for monitoring daily operations.
✅ Key Outcomes: • Functional cafe order and billing management system. • Digital menu and order processing workflow. • Automated bill generation and sales records. • Basic inventory and daily sales reports.
🌍 Impact: Academically, the project strengthens skills in web development, databases, and software design. Practically, it helps small cafes streamline operations, reduce service time, and improve customer satisfaction. The system is scalable for multiple outlets and can be extended with online ordering, QR-based menus, payment gateway integration, and analytics for demand forecasting.
👥 Stakeholders: K V.Aruna Kumari-231801390019
AI-Powered Crop Yield Predictor
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📌 Overview: Accurate crop yield prediction is challenging due to varying weather conditions, soil quality, and farming practices, leading to uncertainty for farmers and planners. This project develops an AI-powered system to predict crop yield using historical data and key environmental factors. The solution supports better planning, resource allocation, and decision-making in agriculture. It promotes data-driven and smart farming practices.
🎯 Objectives: • To predict crop yield using AI and historical agricultural data. • To analyze the impact of weather, soil, and crop parameters on yield. • To support farmers and planners in making informed decisions. • To promote data-driven agriculture practices.
⚙ Methodology: The system uses a machine learning model trained on historical crop yield, weather, and soil datasets. Users input basic parameters through a web or mobile interface to get yield predictions. The backend processes data and returns estimated yield with insights. The platform is designed for scalability and future integration with real-time weather APIs and IoT sensors.
✅ Key Outcomes: • Functional AI-based crop yield prediction system. • Trained machine learning model for yield estimation. • User interface for input and result visualization. • Basic analytics and reporting of predictions.
🌍 Impact: Academically, the project builds practical skills in machine learning, data analysis, and application development. Societally, it empowers farmers with predictive insights to optimize crop planning and resource usage. Industrially, it aligns with smart agriculture and agri-tech solutions. The system is scalable to multiple crops and regions and can be extended with real-time data integration, multilingual support, and advanced analytics for improved accuracy.
👥 Stakeholders: M. Akhil yadav - 231801390023
Enhanced Jharkhand Tourism App
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📌 Overview: Tourism in Jharkhand is rich in natural, cultural, and heritage attractions, but lacks a unified digital platform to guide visitors effectively. This project develops an enhanced tourism app that provides curated information, maps, and recommendations for travelers. The app improves tourist experience through digital guidance and accessibility. It supports the promotion of local destinations and sustainable tourism.
🎯 Objectives: • To provide a comprehensive digital guide for Jharkhand tourism. • To offer location-based information on attractions, routes, and amenities. • To enhance tourist experience through interactive and user-friendly features. • To promote local culture, heritage, and sustainable tourism.
⚙ Methodology: The solution is developed as a mobile application with curated content for tourist spots, routes, and nearby services. It integrates maps for navigation and provides basic recommendations based on user preferences. A simple backend manages content updates and user feedback. The app is designed for scalability and future integration with booking services and local guides.
✅ Key Outcomes: • Functional tourism mobile app for Jharkhand. • Digital catalog of tourist attractions with maps and details. • Interactive user interface for trip planning. • Basic recommendation and feedback features.
🌍 Impact: Academically, the project enhances skills in mobile app development and content management systems. Societally, it supports tourism promotion, local businesses, and cultural awareness. The app can help improve visitor engagement and regional visibility. The solution is scalable for other regions and can be extended with multilingual support, offline maps, AR-based guides, booking integrations, and analytics for tourism insights.
👥 Stakeholders: M.Pradeep - 231801390016
Digital Learning Platform for Rural School Students in Nabha
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📌 Overview: Rural school students often face limited access to quality learning resources, digital content, and personalized academic support. This project develops a digital learning platform to provide structured educational content, practice materials, and basic assessments for students in Nabha. The platform bridges the digital learning gap and supports inclusive education. It enables anytime, anywhere access to learning resources for rural learners.
🎯 Objectives: • To provide accessible digital learning resources for rural school students. • To support self-paced learning through structured content and practice modules. • To improve digital literacy and learning outcomes among rural learners. • To enable teachers to share content and track basic student progress.
⚙ Methodology: The platform is developed as a web-based application optimized for low-bandwidth usage and simple devices. It hosts learning materials such as notes, videos, and quizzes with basic user authentication. A simple backend manages content and student progress tracking. The system is designed for ease of use, scalability, and future offline support.
✅ Key Outcomes: • Functional digital learning platform for rural students. • Repository of learning materials and basic assessments. • Student login and progress tracking features. • Simple teacher/admin content management module.
🌍 Impact: Academically, the project builds skills in web development and educational technology systems. Societally, it supports inclusive and equitable education for rural communities. The platform helps reduce the digital divide and encourages self-learning. The solution is scalable to other rural regions and can be extended with offline access, mobile apps, multilingual content, live classes, and analytics for learning outcome improvement.
👥 Stakeholders: G AJAY KUMAR 231801340005
Design and Development of an Application for Heavy Metal Pollution Indices
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📌 Overview: Monitoring heavy metal pollution is essential for assessing environmental and public health risks, but existing data is often fragmented and difficult to interpret. This project proposes the design and development of an application that calculates and visualizes heavy metal pollution indices from environmental samples. The system supports standardized assessment and easier interpretation of pollution levels. It aids researchers and authorities in data-driven environmental monitoring and awareness.
🎯 Objectives: • To develop an application for calculating heavy metal pollution indices. • To enable easy visualization and interpretation of pollution data. • To support environmental monitoring and basic decision-making. • To promote awareness of environmental pollution and health risks.
⚙ Methodology: The application is developed as a web-based platform where users can input sample data for heavy metal concentrations. The system computes standard pollution indices using predefined formulas and displays results through simple charts and indicators. A backend database stores historical data for comparison and trend analysis. The platform is designed for usability, scalability, and future integration with field sensors or datasets.
✅ Key Outcomes: • Functional application for computing heavy metal pollution indices. • Data input, processing, and visualization modules. • Historical data storage and basic trend analysis. • User-friendly dashboard for environmental reporting.
🌍 Impact: Academically, the project strengthens skills in application development, data processing, and visualization. Environmentally and societally, it supports awareness and basic assessment of pollution levels that impact public health. The solution can assist researchers and local authorities in preliminary monitoring. It is scalable and can be extended with GIS mapping, real-time sensor integration, automated reports, and decision-support analytics.
👥 Stakeholders: M.JAYENDRA - 231801120014
Automatic Timetable Generator
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📌 Overview: Manual timetable preparation in educational institutions is complex, time-consuming, and prone to conflicts among classes, rooms, and faculty schedules. This project develops an Automatic Timetable Generator to create optimized, conflict-free schedules based on predefined constraints. The system improves efficiency, accuracy, and flexibility in academic scheduling. It supports digital transformation of academic administration.
🎯 Objectives: • To automatically generate class timetables based on predefined rules and constraints. • To reduce scheduling conflicts among faculty, rooms, and courses. • To minimize manual effort and time spent on timetable preparation. • To allow easy updates and regeneration of timetables when changes occur.
⚙ Methodology: The system is developed as a web-based application where administrators define constraints such as subjects, faculty availability, rooms, and time slots. A scheduling algorithm generates optimized timetables and validates conflicts. The platform stores schedules in a centralized database and provides simple views for faculty and students. The design focuses on usability, scalability, and easy modification of constraints.
✅ Key Outcomes: • Functional automatic timetable generation system. • Conflict-free class schedules based on defined constraints. • Admin interface for configuring rules and regenerating timetables. • Digital timetable views for students and faculty.
🌍 Impact: Academically, the project builds understanding of algorithms, databases, and system design. Institutionally, it improves operational efficiency by reducing manual scheduling effort and human errors. The solution is scalable for larger institutions and can be extended with AI-based optimization, room utilization analytics, faculty workload balancing, and integration with attendance and academic management systems.
👥 Stakeholders: G.Y.Sai-231801390010
Gamified Environmental Education Platform for Schools and Colleges
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📌 Overview: Environmental awareness among students is often limited due to low engagement with traditional learning methods. This project develops a gamified digital learning platform that teaches environmental concepts through interactive games, quizzes, and challenges. The platform makes learning engaging while promoting sustainable practices. It supports environmental education for school and college students in an interactive way.
🎯 Objectives: • To create an engaging digital platform for environmental education. • To use gamification to improve student participation and learning outcomes. • To promote awareness of sustainability and environmental protection. • To provide interactive quizzes, challenges, and learning modules for students.
⚙ Methodology: The platform is developed as a web-based application with gamified learning modules, quizzes, and reward mechanisms. Educational content is structured into levels and challenges to motivate continuous learning. A backend manages user progress, scores, and content updates. The system is designed for usability, scalability, and future mobile app support.
✅ Key Outcomes: • Functional gamified learning platform for environmental education. • Interactive quizzes, challenges, and learning modules. • User progress tracking and basic reward system. • Admin module for content management.
🌍 Impact: Academically, the project enhances skills in web development, UI/UX design, and educational technology. Societally, it promotes environmental awareness and responsible behavior among youth. The platform supports schools and colleges in delivering engaging sustainability education. The solution is scalable and can be extended with mobile apps, community challenges, leaderboards, AR-based learning experiences, and analytics to measure learning impact.
👥 Stakeholders: T.chakradhar - 231801350013
Attendance Management System
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📌 Overview: Manual attendance tracking in educational institutions is time-consuming, error-prone, and difficult to analyze over time. This project develops a digital Attendance Management System to record, store, and monitor student attendance efficiently. The system improves accuracy, transparency, and accessibility of attendance records. It supports digital transformation of academic administration.
🎯 Objectives: • To digitize and automate student attendance recording. • To reduce manual errors and paperwork in attendance management. • To provide real-time access to attendance records for faculty and students. • To generate basic attendance reports for academic monitoring.
⚙ Methodology: The system is developed as a web-based application with secure login for faculty and administrators. Attendance is recorded digitally through class-wise student lists and stored in a centralized database. The platform provides basic reporting and filtering features to view attendance trends. The design focuses on usability, data security, and scalability for larger class sizes.
✅ Key Outcomes: • Functional digital attendance management system. • Centralized attendance database with reporting features. • Faculty interface for easy attendance marking. • Student view for attendance status and summaries.
🌍 Impact: Academically, the project strengthens skills in web development, database design, and system implementation. Institutionally, it improves administrative efficiency and transparency in attendance management. The solution is scalable for larger institutions and can be extended with mobile apps, QR/biometric integration, analytics for attendance trends, and integration with timetable and academic management systems.
👥 Stakeholders: M.Venkatesh - 231801120005
Faculty Permission Dashboard
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📌 Overview: Permission requests by faculty for leave, OD, or academic activities are often handled manually, causing delays, lack of transparency, and poor tracking. This project develops a Faculty Permission Dashboard to digitize and streamline the permission request and approval process. The system improves communication, record-keeping, and approval turnaround time. It supports efficient academic administration.
🎯 Objectives: • To digitize faculty permission and approval workflows. • To reduce delays and manual paperwork in permission processing. • To provide transparent tracking of request status. • To maintain a centralized record of permissions and approvals.
⚙ Methodology: The system is developed as a web-based application with role-based access for faculty and administrators. Faculty can submit permission requests digitally, and authorities can review, approve, or reject them through a dashboard. A centralized database stores all requests and decisions with timestamps. The platform provides basic notifications and reporting features for monitoring workflows.
✅ Key Outcomes: • Functional faculty permission request and approval system. • Role-based dashboard for faculty and administrators. • Centralized records of permissions with status tracking. • Basic notifications and reporting features.
🌍 Impact: Academically, the project enhances skills in web application development and workflow system design. Institutionally, it improves administrative efficiency, transparency, and accountability in faculty permission management. The solution is scalable for larger institutions and can be extended with mobile app support, automated notifications, document uploads, analytics on approval timelines, and integration with ERP/HR systems.
👥 Stakeholders: A.vijay kumar - 231801390031
One Stop Personalized Career & Education Advisor
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📌 Overview: The project addresses the difficulty students face in choosing the right career and educational path due to lack of personalized guidance. It provides a unified platform that analyzes individual interests, skills, and academic background. The system connects students with suitable career options and education pathways in a structured manner.
🎯 Objectives: • Personalized career guidance
⚙ Methodology: User data collection, assessments, and rule-based recommendation system.
✅ Key Outcomes: • Career recommendations
🌍 Impact: Helps students make informed career decisions and reduces confusion.
👥 Stakeholders: usha shree 231801350017
Al-Based Internship Recommendation Engine for PM Internship Scheme
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📌 Overview: The PM Internship Scheme receives applications from youth across India, including rural areas, tribal districts, urban slums, and remote colleges. Many of these candidates are first-generation learners with
🎯 Objectives: To design an AI-based system that recommends relevant internships to students based on their skills, education, interests, and location.
⚙ Methodology: Student profiles: education, skills, certifications, interests, location, language.
✅ Key Outcomes: Accurate and personalized internship recommendations for students.
🌍 Impact: Promotes equal opportunity and digital inclusion.
👥 Stakeholders: Ch d ravichandra-231801121031
AI Crop Recommendation for Farmers
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📌 Overview: AI Crop Recommendation for Farmers is an intelligent decision-support system designed to help farmers choose the most suitable crops based on soil, weather, and environmental conditions. The system uses machine learning models to analyze parameters such as soil nutrients (N, P, K, pH), temperature, humidity, and rainfall. It provides personalized crop suggestions, disease alerts, weather forecasts, and income estimation through a simple dashboard. The goal is to support farmers in making data-driven agricultural decisions.
🎯 Objectives: To recommend the best crops based on soil and climate data
⚙ Methodology: Data Collection: Soil data, weather data, and crop datasets are collected from reliable sources.
✅ Key Outcomes: Accurate crop recommendations based on local conditions
🌍 Impact: Promotes smart and sustainable farming practices
👥 Stakeholders: D. Jeevan – 231801370011
AI-Powered Crop Yield Prediction and Optimization
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📌 Overview: AI-Powered Crop Yield Prediction and Optimization is an intelligent, data-driven agricultural decision support system designed to predict crop yield and recommend optimized farming practices using machine learning and artificial intelligence. Traditional farming decisions are often based on experience or limited historical observation, which leads to inefficiencies in water usage, fertilizer application, crop selection, and risk management.
🎯 Objectives: The primary objective of this project is to design and implement an AI-powered system that accurately predicts crop yield and provides optimization recommendations to improve agricultural productivity, resource efficiency, and decision-making.
⚙ Methodology: Data Collection:
✅ Key Outcomes: Developed an AI-based crop yield prediction system.
🌍 Impact: This project contributes to the adoption of precision agriculture by enabling data-driven farming decisions. It helps reduce wastage of resources such as water and fertilizers, improves yield predictability, and supports sustainable agriculture. The system can assist small-scale farmers, agricultural consultants, and policymakers in planning cultivation strategies and managing risks related to climate variability.
👥 Stakeholders: M.Akshaya – 231801370013
Smart AI-Based Crop Yield Forecasting and Farm Optimization System
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📌 Overview: The Smart AI-Based Crop Yield Forecasting and Farm Optimization System is an advanced agricultural analytics platform designed to support farmers in making informed decisions through artificial intelligence and machine learning. Agriculture today faces numerous uncertainties due to changing climate conditions, soil variability, and inefficient resource utilization. Many farming decisions still rely on traditional knowledge, which may not always deliver optimal productivity.
🎯 Objectives: The main goal of this project is to develop an intelligent agricultural support system capable of forecasting crop yield while recommending strategies that improve resource utilization and farm performance.
⚙ Methodology: Data Acquisition:
✅ Key Outcomes: Successfully developed an AI-enabled crop yield forecasting system.
🌍 Impact: This project supports the transition toward precision agriculture by enabling evidence-based decision-making. It contributes to better management of resources such as water and fertilizers, enhances production predictability, and promotes sustainable farming practices.
👥 Stakeholders: Sunayana – 231801370034
Smart Classroom & Timetable Scheduler
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📌 Overview: Creating class timetables manually is a time-consuming and complex process. It is prone to human errors, scheduling conflicts, and difficulty in managing multiple faculty members, classrooms, laboratories, and elective subjects. Frequent changes in faculty availability or classroom resources further increase the complexity. Hence, there is a need for a smart and automated system that can efficiently generate and manage academic timetables.
🎯 Objectives: Automated and conflict-free timetable generation
• Hybrid algorithm approach for speed and optimization
• Centralized dashboard for admins, teachers, and students
• Real-time updates for schedule changes
• Export options for timetables in PDF and Excel formats
• Simple and interactive interface with color-coded schedules
⚙ Methodology: Input Data: Admin enters faculty, subjects, rooms, and time slots.
✅ Key Outcomes: The Smart Classroom & Timetable Scheduler offers an efficient and intelligent solution for academic scheduling. By automating timetable creation and eliminating conflicts, the system saves time, improves accuracy, and supports institutional digital transformation. The combination of optimized algorithms and a user-friendly interface makes it a reliable and scalable solution aligned with modern educational requirements.
🌍 Impact: Positive Impact:
👥 Stakeholders: R. Nirmal – 231801370002
AR-Based Cultural Heritage Preservation Platform
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📌 Overview: AR-Based Cultural Heritage Preservation Platform is an innovative system designed to preserve, document, and showcase cultural heritage sites using Augmented Reality (AR) and Artificial Intelligence. The platform allows users to visualize historical monuments, artifacts, and ancient structures in interactive 3D form through mobile or web applications. By combining AR, AI, and digital archiving, the system enhances cultural awareness, tourism experiences, and educational engagement while protecting heritage from physical degradation.
🎯 Objectives: To digitally preserve cultural heritage sites and artifacts
To provide immersive AR-based visualization of historical structures
To reconstruct damaged or lost heritage using AI and 3D modeling
To enhance learning and tourism through interactive experiences
To make cultural heritage accessible to a global audience
⚙ Methodology: Data Collection:
Historical records, images, videos, architectural drawings, and cultural datasets are collected from museums, archives, and heritage organizations.
Data Preprocessing:
Data cleaning, image enhancement, annotation, and 3D reconstruction preparation are performed.
Model Development:
Computer Vision models for image recognition and artifact identification
AI-based 3D reconstruction and restoration models
AR modules for real-time visualization and interaction
System Integration:
AI models and AR components are integrated into a user-friendly mobile/web platform.
Testing & Validation:
Accuracy of object recognition, AR alignment, and user experience testing are conducted.
✅ Key Outcomes: Realistic AR visualization of heritage sites and artifacts
Digital preservation of endangered cultural assets
Interactive educational content for students and researchers
Enhanced virtual tourism experiences
AI-assisted reconstruction of damaged heritage
🌍 Impact: Preserves cultural heritage for future generations
Promotes awareness of historical and cultural values
Supports tourism and digital museums
Reduces physical damage to heritage sites
Encourages the use of advanced technology in cultural conservation
👥 Stakeholders: K. Thanu Sree -231801370038
2. D. Harshith -231801370006
3. T. Mouli -231801370060
4. P. Janaki ram -231801370037
5. A. Maneesh kumar -231801370039
Image Based Breed Recognition for Cattle and Buffaloes of India
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📌 Overview:
Image Based Breed Recognition for Cattle and Buffaloes of India is an AI-powered system that identifies the breed of cattle and buffaloes using image processing and deep learning techniques. The system analyzes animal images and classifies them into specific Indian breeds. This helps farmers, researchers, and livestock managers in breed identification, record maintenance, and decision-making for breeding and dairy production. The solution supports digital livestock management and promotes smart agriculture practices.
🎯 Objectives: To automatically identify cattle and buffalo breeds using images
To assist farmers in accurate breed recognition
To reduce manual errors in livestock identification
To support better breeding and dairy management decisions
To promote AI usage in the livestock sector
⚙ Methodology: Data Collection: Images of various Indian cattle and buffalo breeds are collected from datasets and field sources.
Data Preprocessing: Image cleaning, resizing, labeling, and augmentation are performed.
✅ Key Outcomes: Accurate identification of cattle and buffalo breeds
Faster and automated livestock classification
Reduced dependency on manual breed identification
Improved livestock record management
Practical AI application in agriculture and dairy farming
🌍 Impact: Helps farmers in breed selection and management
Supports dairy industry productivity
Encourages digital transformation in livestock farming
Saves time and reduces identification errors
Contributes to modern and sustainable agriculture
👥 Stakeholders: I. Koushik – 231801370058
S. Hindu – 231801370021
R. Renuka – 231801370026
N. Giri – 231801370045
CH. Shashank – 231801370059
S. Vinodh – 231801370061
Image Based Breed Recognition for Cattle and Buffaloes of India
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📌 Overview: India has a wide variety of indigenous cattle and buffalo breeds that play a vital role in agriculture and dairy production. Identifying these breeds manually requires expert knowledge and is often time-consuming.
This project proposes an image-based breed recognition system that uses computer vision and deep learning techniques to automatically identify Indian cattle and buffalo breeds from images. The system learns distinctive features such as color patterns, horn shape, face structure, body size, and skin texture to accurately recognize the breed.
🎯 Objectives: To design an automated system for recognizing Indian cattle and buffalo breeds using images
To reduce manual effort and human errors in breed identification
To apply deep learning models for accurate breed classification
To support farmers and livestock management authorities
⚙ Methodology: Dataset Collection
Collect images of different Indian cattle and buffalo breeds from trusted datasets and field sources
Image Preprocessing
Resize images, remove noise, normalize pixel values
Apply data augmentation techniques
Feature Extraction
Use Convolutional Neural Networks (CNNs) to extract important visual features
✅ Key Outcomes: Accurate recognition of Indian cattle and buffalo breeds
Faster breed identification process
Reliable results without expert intervention
Scalable system for large livestock datasets
🌍 Impact: Helps farmers in breed selection and dairy planning
Supports conservation of indigenous Indian breeds
Assists veterinary services and livestock research
Encourages adoption of AI in Indian agriculture
Improves decision-making in animal husbandry
👥 Stakeholders: M.SRI CHARAN 231801120020
P.LIKITH SAI KRISHNA 231801120025
G.SUKANYA 231801370032
J.LAKSHMI PRASANNA 231801370027
B.BOBBY 231801370017
V.MEENAKSHI PRASAD 231801370065
Gamified Environmental Education for School and College Students
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📌 Overview: Gamified Environmental Education is an interactive learning system designed to educate school and college students about environmental awareness through game-based activities. The project uses simple games, quizzes, challenges, and reward systems to make learning about environmental issues more engaging. It helps students understand topics such as pollution, climate change, waste management, and environmental conservation in an enjoyable way.
🎯 Objectives: To promote environmental awareness among students
To make learning environmental concepts interactive and engaging
To encourage eco-friendly habits through gamified learning
To increase student participation in environmental education
⚙ Methodology: Environmental learning content is prepared and organized
Interactive quizzes and simple games are designed
Points, levels, and badges are used to motivate students
Students learn by completing tasks and answering questions
Progress is tracked to encourage continuous participation
Technology Used
Python – For implementing game logic, quizzes, and score tracking
Web Technologies (HTML, CSS, JavaScript) – For creating the user interface
Flask (Python Framework) – To connect the frontend with backend logic
Database (Optional – SQLite/MySQL) – To store user progress and scores
✅ Key Outcomes: Increased student engagement in environmental studies
Better understanding of environmental concepts
Interactive and enjoyable learning experience
Improved motivation through rewards and gamification
🌍 Impact: Encourages environmental responsibility among students
Makes learning more effective through gamification
Supports sustainable and eco-friendly initiatives
Can be expanded into a larger educational platform
👥 Stakeholders: R.Dinesh(231801370050)
J.Akash(231801370016)
D.Chandu(241801370041)
P.Mohith(231801370056)
Ch.Deepika(231801370033)
K.Surya Akash(231801370005)
AI based Internship Recommendation Engine
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📌 Overview: The AI based Internship Recommendation Engine is a specialized web platform engineered to simplify the internship search process for fresh graduates and individuals from rural backgrounds. Unlike traditional job portals that are often complex and overwhelming, this system offers a minimalist, intuitive interface. It integrates a Machine Learning engine and a resume parser to automatically extract skills from user profiles and match them with relevant internship opportunities, ensuring that users with limited digital literacy can easily connect with valuable career options.
🎯 Objectives: The primary objective of this project is to democratize access to career opportunities by developing a simple, AI-driven platform that accurately matches candidate profiles with internships, thereby removing the technical barriers and friction commonly associated with online job applications.
⚙ Methodology: Candidate and Internship data is managed using a PostgreSQL database with a Flask backend.
Users create profiles or upload resumes, which are processed by a Python-based Resume Parser (using PyMuPDF and OCR) to extract text and skills.
A Random Forest Regressor model analyzes the candidate's skills against internship requirements.
The system calculates a "match score" based on skill overlap and similarity metrics.
Personalized recommendations are ranked and displayed on a user-friendly dashboard.
✅ Key Outcomes: Developed a working prototype with a user flow significantly easier than traditional job portals.
Implemented an automated resume parser for seamless skill extraction.
Successfully integrated a Random Forest model to provide accurate, ranked internship recommendations.
Created a two-sided ecosystem allowing employers to post jobs and candidates to find matches.
🌍 Impact: This project enhances inclusivity in the employment landscape by making internship discovery accessible to users with lower digital literacy. It bridges the gap between talent and opportunity for underserved communities by automating data interpretation and personalizing the search process. The system demonstrates how AI can be used to solve social challenges in the career development sector.
👥 Stakeholders: K. Surya Tej - 231801370031
AI-Based Automated Project Evaluation System Using Code Understanding + Report Analysis
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📌 Overview: This Project Demonstrates the Uses Of A Code Analyzer to Analyze the code in a very short time and deliver an outstanding analysis of the code based on the given input
This Project Targets the Efficiency of the Code Analysis for Evaluation. The Format Of the Provided Document is compared with the Project and is analyzed so that the Project Code and the Given Document Sync Properly and then it delivers proper Evaluation Results
🎯 Objectives: Analysing the Project Done By A Student, And Grading A Student's Performance According To The Code Value And PDF Reports
⚙ Methodology: Backend
python+FastAPI
SQL ALCHEMY
Ollama
Open AI/Anthropic API's
Frontend
React 18 + TypeScrpit
Tailwind CSS
React Router
AI/ML
SciKit - learn
NumPy/Pandas
PyPDF2
DEVOPS
Docker + Docker Compose
Pytest
✅ Key Outcomes: Automated Project Evaluation System Providing Instant AI-Powered Scoring, Ultra-Detailed Code Analysis, comprehensive tech stack identification, and actionable improvement feedback with 95% reduction in evalution time.
🌍 Impact: AI-Powered automated project evolution system transforming education and corporate training with instant comprehensive code analysis, reducing evaluation code by 90% while scaling to handle thousands of submissions with consistent quality assessment across multiple industries
👥 Stakeholders: R.Nirmal 2321801370002
L.Nitish Kumar 2321801370009
N.Laasya 2321801370046
S.Jayanth 2321801370051
S.Vignesh 2321801370052
T.Sai Devanand 2321801370070
T.Veera Siva Krishna 2321801370025
AI Powered Smart Academic Survelliiance System With Behavioral Intelligence
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📌 Overview: Educational institutions face challenges in monitoring student behavior, ensuring discipline, and maintaining academic integrity. Traditional surveillance methods (manual invigilation, CCTV monitoring) are often limited, reactive, and lack intelligent analysis. With advancements in Artificial Intelligence (AI), there is an opportunity to build a smart system that not only observes but also interprets student behavior in real time.
🎯 Objectives: Analyse student behaAutomate Classrom Monitoring, Analviour
⚙ Methodology: Frontend - ReactJs, HTML, CSS, JAVAScript,Chart.js Backend- Node.js, MongoDB OpenCV, CNN, Webcam
✅ Key Outcomes: Automatically mark attendence, Detect suspicious behaviours in classroom, provide Ai chatbot for teachger queries , send alerts for dicipline issues
🌍 Impact: The EdTech industry is increasingly adopting AI-powered surveillance and behavioral analytics to enhance academic integrity and student engagement.
👥 Stakeholders: P. YAMINI DEVI- 231801370004, R. RENUKA - 231801370027, B. HARSHITHA- 231801370010, D. HARSHITH -231801370006, T. MOULI- 231801370060, P. LIKITH- 231801120025, M.SRI CHARAN- 231801120020
AI Based real-time cyberattack detection system
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📌 Overview: Rising cyber threat landscape : modern organizations faces increasing cyberattacks such as Dos,bruteforce attempts,and network probing.traditional rule-based intrusion detection system struggles to detect evolving or unknown threats,machine learning enables systems to learn patterns from network traffic and identify anomalies dynamically ,improving detection accuracy compared to static signatures based methods , there is a growing need to combine ai driven detection with real time dashboards and secure access control
🎯 Objectives: To develop an AI-driven medical pre-diagnosis system that analyzes multi-modal patient data such as symptoms.
⚙ Methodology: frontend-html,css,java script,chart.js backend- flask,flask-limiter,werkzeug,python-dotenv
✅ Key Outcomes: successfully trained an integrated ml model achieved measurable classification accuracy built a real time attack monitering dashboard implemented secured authentication system
🌍 Impact: security operation centers ,managed security service providers ,enterprise network monitering system ,cloud security monitering platforms ,siem tools ,ids/ips systems
👥 Stakeholders: D.jeevan-231801370011,B.bobby-231801370017,K.prasanth-231801370040,B.venkat rao-231801370048,S.vinod-231801370061,R.balaji-231801370069
Multi Modal Emotion Recognition System For Student Mental Health Monitoring
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📌 Overview: This Project focuses on early detection of student stress and emotional well being using Artiificial Intelligence.It analyzes facial expressions,voice tone and text sentiment together to estimate the students mental health status in real time.The system helps provide early alerts and encourages preventive mental health care
🎯 Objectives: To provide early alerts and recommendation that promote student well being and preventive mental health care
⚙ Methodology: python,streamit,open cv,NumPy,deepface,Tensorflow
✅ Key Outcomes: Developed a working AI system that detects student emotions using face,voice,and text inputs.Successfully calculated a combined stress score using a multi modal fusion approach
🌍 Impact: The system can be integrated into Ed Tech platforms and learning management systems to monitor student well being during online classes and exams
👥 Stakeholders: K.Suryatej-231801370031,G.Yashwanth Roy-231801370019,CH.Sashank-231801370059,V.M.prasad-231801370065,B.Ashish-231801370067,I.Koushik-231801370058
AI-Based Automatic Medical Pre-Diagnosis System using Multi-Modal Data
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📌 Overview: The project focuses on developing an intelligent medical pre-diagnosis system that assits healthcare professionals by analyzing multiple types of patient data simultaneously.The system leverages artifical intelligence and machine learning to process multi-modal data,such as patient symtoms(text),medical images,vital signs,lab reports,and electronic health records.
🎯 Objectives: To develop an AI-driven medical pre-diagnosis system that analyzes multi-modal patient data such as symptoms.
⚙ Methodology: html,css,javascript,python,opencv,Numpy,tensorflow
✅ Key Outcomes: Improved early disease detection results generated from multi-modal medical data analysis.
🌍 Impact: The AI-Based Automation medical pre-diagnosis system is highly relevant to the healthcare and medical technology indusrty.
👥 Stakeholders: R.Dinesh-231801370050,J.Akash-231801370016,P.Mohith-231801370056,Ch.Deepika-231801370033,D.Chandu-231801370041,K.Surya Akash-231801370005
Generative AI-Based Personalized Learning Assistant for Students
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📌 Overview: Education is becoming digital,but students often struggle to revise large amounts of material quickly.Many learners cannot get personalized help outside classrooms.This project uses AI to support students in studying smarter.It focuses on summarizing notes and helping in exam preparation.
🎯 Objectives: To build an AI based tool that helps students understand and revise topics easily .To convert long notes into short ,exam ready summaries.To make learning faster ,smarter,and more efficient
⚙ Methodology: React.js,Typescript,css,Tailwand,Google gemini AI API
✅ Key Outcomes: students can upload notes and recieve clear summaries instantly.Learneres can quickly grasp key concepts and definitions.It generates quiz based on their requirements
🌍 Impact: EdTech companies use AI for personalized learning solutions.Many industries adopt AI tutors and smart learning platforms.This project reflects real world AI applications in education
👥 Stakeholders: S.HIndu-231801370021,J.Lakshmi Prasanna-231801370027,G.Sukanya-231801370032,K.Thanu Sree-231801370038,S.Revathi-231801370062,B.Pravallika-231801370066,Y Sai Keerthana-231801370068
AI Powered automatic Lecture content generator from ppt's and notes
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📌 Overview: Converts ppt slides and written notes into structured lecture material. It helps educators save time by automatically creating explanations, summarries and teaching flow from raw content.
🎯 Objectives: To design an AI based system that automatically transforms ppt slides and digital notes into well structured lecture content, enabling fast course preparation, consistent teaching matr=ertial and improved learning accessibility for students.
⚙ Methodology: react, python, open ai api keys, postgre sql
✅ Key Outcomes: automatic conversion of ppt slides and notes into structured, easy to understand lecture content. improve learning accessibility for students through well organised digital lectures.
🌍 Impact: The AI powered automatic lecture content generator fix into the growing EdTech and AI automation industry where organisations aim to digitize and scale education
👥 Stakeholders: M.Akshaya-231801370013, Y.Tejaswini-231801370014, P.Martin-231801370064, B.Hari Prasad-231801370055, K.Kiran-231801370036, S.Sanjay- 231801370018
One-Stop Personalized Career & Education Advisor
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📌 Overview: Creation a one stop application for students that would showcase all possible paths that could be opted,couse recomendemdation according to the quizes.
🎯 Objectives: Bridge a gap between students and all available opportunities in govt collages
⚙ Methodology: React For Web,React Native for App Using Frontend
✅ Key Outcomes: Empowered students with access to reliable, localized career guidance.
🌍 Impact: Education
👥 Stakeholders: 231801380005 - P. Puspalatha
231801380004 - D Satya Sai Sri
231801380018 - Sindhura Bure
231801380023 - Sai Pranathi Pesapati
231801380025 - S Keerthi Priya
231801380027 - Gopi T
Al-Based Internship Recommendation Engine for PM Internship Scheme
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📌 Overview: Receives applications from youth across India, including rural areas, tribal districts, urban slums, and remote colleges.
🎯 Objectives: to provide personalized and relevant internship recommendations to candidates based on their educational qualifications, skills, interests, and location preferences.
⚙ Methodology: Frontend : HTML5, CSS3, Java Script(Vanilla JS) Backend : Python 3.8+, Flask - CORS
✅ Key Outcomes: Personalized Internship recommendations, Improved Application Accuracy, Increased selection Probability
🌍 Impact: Education
👥 Stakeholders: 231801380006- S. Jaswanth
231801380008 - A. Sanjana Priya
231801380015 - B. Krishna
231801380014 - N. Aman
231801380021 - N. Srikar
231801380026 - K. Praveen
Predictive Analytics Framework for Cybercrime Complaints
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📌 Overview: With nearly 8000 cybercrime complaints daily, there is a critical need for an AI/ML-based predictive system that shifts from reactive response to proactive prevention by identifying high-risk withdrawal locations in advance.
🎯 Objectives: Predict where fraud money will be withdrawn before it happens, and alert police + banks in real time.
⚙ Methodology: Python, XGBoost, Scikit-learn, KMeans, Random Forest, Flask, REST API
✅ Key Outcomes: Predicts high-risk withdrawal locations, enabling proactive intervention, real-time monitoring, and faster fund recovery.
🌍 Impact: Fraud Prevention
👥 Stakeholders: 231801380011-S.Suryaprabhakar
231801380012-K.Satwika
231801380016-B.Chandini
231801380017-S.Yogeshwari
231801380020-M.Mallikarjuna
231801380024-A.Bowthya sree
Smart Tourist Safety Monitoring & Incident Response System
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📌 Overview: Rising Tourist Safety Concerns in India,Lack of Integrated Safety Infrastructure
🎯 Objectives: To develop an AI-powered, blockchain-secured smart system that ensures real-time tourist monitoring, geo-fencing alerts, and rapid emergency response.
⚙ Methodology: Advanced Technologies: AI/ML , Blockchain (Ethereum/Hyperledger for Digital Tourist ID),
Cloud Deployment (AWS/Azure/GCP) with JWT-based secure authentication.
Frontend & Backend: Flutter , FastAPI (Python), PostgreSQL, Google Maps API.
✅ Key Outcomes: Faster incident handling with automated anomaly detection and E-FIR generation for police authorities.
Improved tourist safety through real-time monitoring, geo-fencing alerts, and instant emergency (SOS) response.
🌍 Impact: Tourism, Public Safety, and Smart City industries
👥 Stakeholders: 231801380028-M.Manojkumar
231801380002-CH.S.C.S.S.Srija
231801380007-C.Venkat dhanush
231801380001-K.Eswar gupta
231801380003-L.Ravi
231801380029-K.Anusha Devi
Crowdsourced Civic lssue Reporting and Resolution System
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📌 Overview: Smart Civic Grievance Management Platform for Real-Time Issue Reporting and Transparent Urban Governance
🎯 Objectives: To develop a web-based civic issue reporting system that enables citizens to submit location-based complaints and allows authorities to efficiently track, manage, and resolve issues through a centralized platform.
⚙ Methodology: React.js & Tailwind CSS (Frontend),
Node.js & Express.js (Backend),
MongoDB (Database),
Google Maps JavaScript API (Mapping),
✅ Key Outcomes: Users can easily report civic issues with accurate location details through the web application.
Authorities can efficiently view, manage, and track reported issues using a centralized system.
🌍 Impact: Clean & Green Technology
👥 Stakeholders: 231801380013-B.Tharun Kumar
231801380022-Y.Lakshmi Chandana
231801120002-J.Kiran Kumar
231801120003-K.Charan Teja
231801380009-T.Bala Murali Krishna
231801120013-D.Ram Ganesh naidu
FPGA- BASED DIGITAL MANUFACTURING SYSTEM FOR APPAREL PRODUCTION USING EMBEDDED MONITORING AND CONTROL
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📌 Overview: The apparel manufacturing industry faces challenges such as inconsistent quality, machine downtime, and limited real-time monitoring due to reliance on manual supervision. This project proposes an FPGA-based digital manufacturing system integrated with embedded sensors for real-time monitoring and control of cutting, stitching, and finishing processes. The FPGA enables high-speed, parallel processing for precise and reliable control decisions. The system enhances automation, efficiency, and transparency, making it suitable for smart apparel manufacturing environments.
🎯 Objectives: To design and develop an FPGA-based digital manufacturing system for apparel production.To implement real-time embedded monitoring and control of apparel manufacturing processes.To improve production efficiency, accuracy, and consistency through hardware-level control.To enable fault detection and performance monitoring of machines used in apparel production.To reduce manual intervention, downtime, and operational errors in manufacturing.To create a scalable and reconfigurable system suitable for Industry 4.0–based smart factories.
⚙ Methodology: 1)System Design:-
Identify key apparel production stages to be monitored and controlled.Select appropriate sensors (speed, temperature, load, proximity, etc.).
2)Hardware Implementation:-
Develop FPGA-based control architecture.Interface sensors and actuators with FPGA through embedded modules.
3)Embedded Monitoring:-
Capture real-time production parameters.Display status and alerts through indicators or dashboards.
4)Control Algorithm Development:-
Implement control logic using HDL (VHDL/Verilog).Enable fault detection and automatic corrective actions.
5)Testing and Validation:-
Test system under normal and abnormal operating conditions.Evaluate performance improvements in efficiency and accuracy.
6)Optimization:-
Fine-tune timing, resource utilization, and response speed.Ensure scalability for future expansion.
✅ Key Outcomes: A fully functional FPGA-based embedded control system for apparel manufacturing.Real-time monitoring of machine performance and production parameters.Improved production speed and reduced machine downtime.Enhanced product quality through precise and consistent control.Early fault detection and preventive maintenance capability.A modular and reconfigurable system adaptable to different apparel machines.
🌍 Impact: Industrial Impact:
Enables smart automation in apparel manufacturing, improving productivity and reducing operational costs.
Technological Significance:
Demonstrates the application of FPGA technology in digital manufacturing and embedded control systems.
Economic Impact:
Reduces wastage, energy consumption, and labor dependency, leading to cost-effective production.
Academic and Research Value:
Provides a strong foundation for further research in Industry 4.0, smart textiles, and cyber-physical systems.
Societal Impact:
Supports modernization of the apparel industry, improving competitiveness and sustainability.
👥 Stakeholders: P.SUNEEL - 231801130030
N.ASHA - 231801130027
N.ANANTH - 231801131041
D.GOWTHAM - 231801130029
RISC-V–Integrated Hardware-Accelerated AES Encryption Engine for Secure Embedded Systems
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📌 Overview: This project focuses on designing and integrating a hardware-accelerated AES (Advanced Encryption Standard) encryption engine with a RISC-V processor to enhance security and performance in embedded systems.
Instead of executing AES purely in software (which is slower and power-intensive), the encryption process is offloaded to a dedicated hardware module. This improves:
Encryption speed
Energy efficiency
Security against software attacks
Real-time data protection
The system is ideal for IoT devices, secure communication modules, smart cards, and embedded controllers.
🎯 Objectives: 1)Design a hardware-based AES encryption engine
Support AES-128 (or AES-256 if extended)
Optimize for speed and area efficiency
2)Integrate AES engine with RISC-V processor
Connect via memory-mapped I/O or custom instruction interface
Enable processor-controlled encryption/decryption
3)Improve performance over software AES
Reduce clock cycles
Minimize latency
4)Ensure secure data handling
Protect against timing attacks
Maintain secure key storage
5)Evaluate system performance
Compare hardware vs software AES execution time
Measure power consumption and throughput
⚙ Methodology: 1) System Design
Select a RISC-V core (e.g., RV32I architecture)
Design AES hardware module using Verilog/VHDL
Define interface between processor and AES engine
2) AES Engine Implementation
Implement AES stages:
SubBytes
ShiftRows
MixColumns
AddRoundKey
Use pipeline architecture for faster execution
3) Integration
Connect AES module to:
RISC-V data bus
Control registers
Create instruction or control signals to trigger encryption
4)Simulation & Verification
Use tools like:
ModelSim / Vivado
GTKWave
Test with known AES test vectors
5) Performance Analysis
Measure:
Execution time
Throughput
Power usage
Compare with software-only AES implementation
✅ Key Outcomes: Functional hardware AES encryption module
Successfully integrated AES with RISC-V processor
Measurable performance improvement over software AES
Reduced latency and power consumption
Demonstrated secure data transmission in embedded system
🌍 Impact: 1. Enhanced Security
Hardware implementation reduces vulnerability to:
Software exploits
Malware attacks
Reverse engineering
2. Faster Encryption
Hardware AES performs encryption in fewer clock cycles
Suitable for real-time secure communication
3. Energy Efficiency
Lower power consumption
Ideal for battery-operated IoT devices
4. Scalable & Open Architecture
Since RISC-V is open-source:
Custom extensions can be added
No licensing cost
Highly adaptable for research and innovation
👥 Stakeholders: D.ANUSHA - 231801130004
CH. VARUN KUMAR - 231801130021
V.DINESH - 231801130012
Non- Invasive Glucose Monitoring System
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📌 Overview: GlucoMonitor is a non-invasive blood glucose monitoring system that estimates glucose levels, heart rate, and SpO₂ (blood oxygen saturation) using MAX sensors integrated with an ESP32 microcontroller. Unlike traditional glucometers, it eliminates the need for finger-pricking, providing a painless and user-friendly solution. The system enables continuous monitoring and real-time data acquisition. This makes GlucoMonitor suitable for daily health monitoring and preventive care applications.
🎯 Objectives: To design and develop a non-invasive blood glucose monitoring system using optical sensors.
To measure blood glucose level, heart rate, and SpO₂ using MAX sensors integrated with an ESP32.
To eliminate the need for finger-pricking, making glucose monitoring painless and user-friendly.
To enable real-time data acquisition and continuous health monitoring.
To improve accessibility and convenience for diabetic and health-conscious users.
To provide a low-cost, portable solution suitable for home and remote healthcare applications.
⚙ Methodology: System Design and Component Selection
Sensor Data Acquisition
Signal Processing and Calibration
Embedded System Development
Data Display and Communication
Testing and Validation
✅ Key Outcomes: Non-Invasive Glucose Monitoring System
Real-Time Measurement of Glucose, Heart Rate, and SpO₂
Painless and User-Friendly Operation
Wireless Data Transmission and Monitoring
Improved Convenience for Daily Health Tracking
Portable and Low-Cost Prototype
🌍 Impact: Advancement in Non-Invasive Healthcare Technology
Improved Patient Comfort and Compliance
Support for Continuous Health Monitoring
Reduction in Dependency on Invasive Glucose Testing
Applicability in Home and Remote Healthcare
Contribution to Preventive and Digital Health Systems
👥 Stakeholders: TADI SHARON 231801400002
K. VIJAYA LAXMI 231801400008
S. PRASHANTH 231801400001
P. JOHN 231801400011
G. SHANMUKA RAO 231801400003
Network Strategies in VLANs
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📌 Overview: Modern educational institutions require secure and scalable network infrastructures to handle large numbers of users and devices.
VLAN-based segmentation helps isolate departments such as Admin, Faculty, Students, and Labs to improve security and performance.
Integrating firewalls, Web servers, and DNS servers enables real-world service deployment in campus networks.
🎯 Objectives: To design a secure campus network using VLAN-based segmentation.
To implement Inter-VLAN routing with controlled access using firewall policies.
To deploy Web and DNS servers within a protected server zone (DMZ/Server VLAN).
To simulate and test real-world campus network scenarios.
⚙ Methodology: Cisco Packet Tracer / GNS3
VLAN, Trunking
Inter-VLAN Routing
Firewall
✅ Key Outcomes: Designed a secure campus network using VLANs and firewall rules.
Successfully deployed and tested Web and DNS servers in the network.
🌍 Impact: Used in company and campus networks for secure communication.
Helps protect servers and departments using VLANs and firewalls.
👥 Stakeholders: A.USHA SREE
Secure Automatic Network
Topology Creation Tool
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📌 Overview: Modern networks require fast, secure, and error-free design and configuration.
Manual network topology creation is time-consuming and prone to configuration mistakes.
There is a need for an automated system that can generate secure network topologies and configurations based on user requirements.
🎯 Objectives: To design an automated tool for generating network topologies.
To apply security policies such as firewall rules and ACLs automatically.
To generate device configuration files automatically.
To integrate the generated topology with GNS3 for simulation.
To reduce network design time and human errors.
⚙ Methodology: Frontend: HTML, CSS, JavaScript
Backend: Node.js, Express.js
Simulation Tool: GNS3
Networking: Cisco IOS Images
Database: Firebase / MongoDB
Tools: VS Code, GitHub
✅ Key Outcomes: Automated generation of network topology.
Automatic VLAN and IP address assignment.
Secure configuration generation.
Successful simulation in GNS3
User-friendly interface for network designers.
🌍 Impact: Useful for IT infrastructure companies.
Applicable in enterprise network design.
Helpful for network administrators and trainees.
Can be extended for cloud and data center environments
👥 Stakeholders: S.Teja
Network Intrusion Detection with Port Security + DHCP Snooping
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📌 Overview: Many college and enterprise networks face threats like unauthorized device access, MAC flooding attacks, and rogue DHCP servers.
Traditional networks without Layer 2 security are vulnerable to IP spoofing, man-in-the-middle attacks, and internal intrusions.
This project focuses on implementing Layer 2 security mechanisms to detect and prevent network-level attacks using Cisco technologies
🎯 Objectives: To prevent unauthorized devices from connecting to the network.
To block rogue DHCP servers and prevent IP spoofing.
To detect and mitigate MAC flooding attacks.
To configure secure VLAN-based network architecture.
To gain practical experience in switch-level security implementation
⚙ Methodology: Frontend:HTML, CSS , JavaScript ,Bootstrap
Backend:Python, Flask,REST API
Simulation Tools:Cisco Packet Tracer,GNS3,,EVE-NG
Networking:VLAN, Trunking, Port Security, DHCP SnoopingACL
Database:MySQL
Tools:VS Code,GitHub, Cisco IOS CLI
✅ Key Outcomes: Unauthorized devices are automatically blocked.
Rogue DHCP servers are detected and prevented.
Network becomes protected against MAC flooding and IP spoofing attacks
🌍 Impact: Used in IT companies, data centers, and campus networks to protect internal LAN infrastructure.
Helps prevent internal security breaches and insider attacks.
Essential security configuration in organizations using Cisco switching environments
👥 Stakeholders: V.SRINIVAS