Browse and filter through our complete project catalog
Real-time drowsiness monitoring using computer vision and deep learning
This project develops a real-time driver drowsiness detection system using computer vision and Convolutional Neural Networks. A camera continuously captures facial information and the trained model analyzes eye states and yawning behavior to detect drowsiness. When drowsiness is detected, an immediate alert is triggered to warn the driver.
IoT-based system for real-time crop monitoring and automated irrigation
This project implements an IoT smart agriculture system using ESP32 microcontroller and multiple sensors. The system monitors environmental parameters in real-time and sends data to a cloud platform for analysis. Automated irrigation is triggered based on soil moisture levels, and farmers receive alerts through a mobile app.
Complete home automation with smart lighting, temperature, and security
This project implements a smart home system using ESP32 as the central controller. Users can control various home appliances through a mobile app via Wi-Fi connectivity. The system includes real-time monitoring, automation schedules, and integration with voice assistants.
Decentralized supply chain management using blockchain technology
This advanced project implements a distributed supply chain tracking system using Ethereum blockchain and smart contracts. Each product is assigned a unique token and tracked through multiple supply chain stages. All stakeholders can verify product authenticity and origin in real-time, eliminating counterfeits and ensuring product integrity throughout the supply chain.
Implementing quantum-secure cryptography for secure communication
This project demonstrates quantum key distribution using the BB84 protocol implemented in Python. It simulates quantum bit transmission, eavesdropping detection, and secure key generation. The system proves the fundamental advantage of quantum cryptography: any attempt to intercept quantum states causes detectable disturbances, making the communication inherently secure.
Hardware-accelerated deep learning using FPGA
This project develops a hardware accelerator for deep learning inference on FPGA using high-level synthesis. The system implements parallel processing units for matrix operations critical to neural networks. Compared to CPU execution, the FPGA implementation achieves 10-50x speedup with significantly reduced power consumption, making it ideal for edge AI applications.
Advanced 5G NR channel models and network performance analysis
This comprehensive project simulates 5G NR communication systems with realistic channel models including 3GPP standardized propagation scenarios. The simulation includes beamforming for millimeter-wave transmission, resource allocation optimization, and MIMO channel estimation. Performance is evaluated under urban, rural, and indoor scenarios with detailed SNR analysis.
Multi-agent coordination for autonomous drone swarms
This advanced robotics project implements a swarm intelligence system for multiple autonomous drones. Each drone runs decentralized algorithms for cooperative navigation, collective mapping, and obstacle avoidance. The system uses ROS for communication and SLAM for simultaneous localization and mapping, enabling drones to collaboratively explore unknown environments.
Deep learning for automated medical image classification
This project implements state-of-the-art convolutional neural networks for medical image analysis. The system uses transfer learning with pre-trained models (ResNet, DenseNet) and segmentation networks (U-Net) for precise lesion detection. Integrated grad-CAM visualization explains AI predictions to medical professionals, ensuring interpretability and trust in automated diagnosis.
Emergency alert system with GPS tracking and SMS notifications
This project creates a wearable safety device that transmits real-time GPS location and emergency alerts via GSM module to multiple contacts. The system includes a panic button, vibration sensor for automatic trigger, and voice call capability for immediate communication.
Smart door lock using facial recognition and RFID
This system combines face recognition technology with IoT to create a secure door lock. The system recognizes authorized users, logs access history, and sends notifications. It includes RFID card backup and emergency access options.
IoT-enabled smart meter for real-time energy consumption monitoring
This project implements a smart energy meter using current and voltage sensors connected to an ESP32. The system calculates power consumption, cost, and sends data to a cloud server. Users can monitor their energy usage through a web dashboard.
Autonomous robot that follows a black line using IR sensors
This is a beginner-level robotics project where a robot uses infrared sensors to detect a black line and automatically follows it. The robot uses PWM-based speed control to navigate curves and obstacles efficiently.
Autonomous robot with ultrasonic sensor-based obstacle detection
This robot uses ultrasonic sensors to detect obstacles in its path and changes direction autonomously. It uses servo motors for scanning and decision-making logic to find the best path.
IoT-based automated parking management and guidance system
This system uses IR sensors to detect parked vehicles in each slot and displays available parking spaces on electronic boards. Users can check availability on a mobile app. The system also manages parking fees automatically.
Real-time detection and alert system for fire and gas hazards
This system uses temperature, smoke, and gas sensors to detect hazardous conditions. Upon detection, it triggers local alarms, sends SMS alerts, and contacts emergency services automatically.
Real-time monitoring and optimization of solar power generation
This system monitors voltage, current, and temperature of solar panels to optimize their performance. Data is transmitted to a cloud server for analysis and users receive recommendations for efficiency improvement.
Deep learning model for automatic plant disease identification
Using convolutional neural networks, this project identifies various plant diseases from leaf images. Farmers can use a mobile app to take photos and get instant disease diagnosis with recommended treatments.
Automated attendance system with facial recognition and database
This system uses computer vision to recognize faces and automatically mark attendance. It includes a database for storing records, generating reports, and tracking attendance patterns.
Complete VLSI design of a 4-bit microprocessor from logic gates
This project involves designing a basic microprocessor from logic gates using Verilog. It includes ALU, control unit, registers, and memory modules. The design is verified through simulation and implemented on FPGA.
Signal filtering, analysis, and visualization using MATLAB
This project demonstrates signal processing concepts including filtering, FFT analysis, and noise reduction. It includes practical examples with audio and biomedical signals.