An autonomous navigation system using ROS 2 with SLAM, AMCL, and a comparison of path planning algorithms like Dijkstra, A*, BFS, and Theta* in complex maze environments.
Design of an autonomous robot using computer vision for line detection and trajectory tracking, inspired by ADAS systems. Implemented advanced computer vision algorithms for real-time lane detection and autonomous navigation.
A deep learning project using a CNN to classify traffic signs from images, featuring a real-time prediction interface.
A distributed embedded system for real-time mobile robot control using ESP32 and STM32, with Wi-Fi communication, position tracking, and a web-based control interface.
A deep learning project using LSTM networks to predict future stock prices based on historical data from 19 major tech companies.
Simulation of an ADAS system to detect vehicles and vacant spots in a parking lot, with autonomous navigation and obstacle avoidance.
A comprehensive 4-level elevator automation system using GRAFCET methodology and Ladder programming. Industrial Programmable Logic Controller project implementing automated cabin movement, intelligent door control, position indicators, and safety features using Schneider Electric Modicon TM221CE16R PLC.
Designed a 4-DOF robotic arm with computer vision for object sorting. Implemented YOLO-based detection to classify objects by shape and color. Integrated inverse kinematics for precise movement.
Designed and implemented a 16-bit processor using VHDL, featuring an ALU, control unit, registers, and memory interface. Simulated and verified functionality using ModelSim and synthesized the design in Quartus.
An intelligent driver assistance system that combines eye state detection and LiDAR distance sensing with fuzzy logic to enhance driving safety. Real-time driver monitoring through computer vision and precise obstacle detection using TF-Luna LiDAR sensor, with adaptive speed control and emergency stop capabilities.
Educational cybersecurity project demonstrating keylogging and monitoring techniques. Developed for academic learning in ethical hacking and cybersecurity research. ⚠️ Strictly for educational purposes only.
Smart safe design with dual authentication methods: RFID card and keypad password. Developed as part of embedded electronics coursework to strengthen skills in secure system design and Arduino programming.
Intelligent seismic detection system using Arduino platform with specific sensors to detect ground vibrations and trigger corresponding actions. Features real-time monitoring with predefined threshold alerts and automatic safety responses.
Automated surface treatment solution using KUKA robotics at Neo Motors Morocco. Design and implementation of precision-controlled robotic sandblasting system improving safety, quality, and productivity by 100-200%.
Hybrid anomaly detection system for vehicle CAN Bus data, combining Isolation Forest for outlier detection and LSTM networks for sequence-based classification. Enhances cybersecurity and predictive maintenance by detecting unusual sensor patterns.