Deep Learning-based Internet of Vehicles Framework for Real-Time Traffic Rules Violation Detection. Lead a team of 4 colleagues to implement CNN Based YOLOv5 and DeepSORT using a custom dataset to successfully detect : 1- Speeding vehicles 2- Opposite direction violations 3- Possible car crashes/accidents. Using only a camera installed into a moving vehicle and computer vision techniques and edge computing. Then it sends a summary of data over a 3G/4G network using a module to stakeholders' servers. Graduation project grade: A+ GPA: 4.0.

Completed paperwork, recognizing discrepancies and promptly addressing for resolution. Used Microsoft Word and other software tools to create documents and other communications. Maintained energy and enthusiasm in fast-paced environment.

Mobile software project supervision and project management. Created a timeline and project schedule for delivery. Made sure every feature or requirement is held correctly and works as required. Worked with the team on creating the front-end of the application using Flutter. Developed a Point of sale system for the company to start selling it commercially. Created the official website of the company and worked on web administrating it.

technical support intern

Basic Communication Course

Successfully created face recognition model (Python, OpenCV3, Eigen/Fisher faces) to detect and predict users and used a solenoid door lock to create a smart door security system that's fully functional and uses logs to save data of door entries and multiple events. Later in August 2019. Managed to implement my system to a Smart Home system which we participated with. Egyptian Engineering day 2019.