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AI-Based Parking Management Application
CS-B-13
Ben Pahima; bmpahima@gmail.com Meir Haimov; meir965@gmail.com Raz Kalfon; razh10@gmail.com
Advisors: Dr. Erez Manor1, Prof. Shlomo Greenberg1 1SCE - Shamoon College of Engineering, Be’er-Sheva
Finding parking in busy areas is a daily challenge for drivers, while parking-lot managers struggle to track occupancy, detect unauthorized vehicles, and manage spaces efficiently. This project created a smart parking management system using deep learning for real-time vehicle and license plate recognition. A Raspberry Pi device with a connected camera monitors the lot, using OpenCV and YOLO to detect vehicles. A React Native mobile app lets users view available spots and reserve them in advance. The system provides lot managers with live data, and automated alerts for better control over parking activity. By streamlining the parking experience for both drivers and managers, the system reduces search time, traffic congestion, and the need for manual supervision.
Keywords: app development, artificial intelligence, computer vision, deep learning, object detection, parking
Inventory Management Based on AI and Microcontroller
CS-B-14
Oleg Muraviov; oleg.lafer@gmail.com Daniel Dahan; daniel5810005@gmail.com
Advisors: Dr. Erez Manor1, Prof. Shlomo Greenberg1 1SCE - Shamoon College of Engineering, Be’er-Sheva
This project designed a hands-free warehouse management system powered by a Raspberry Pi device equipped with computer vision. A connected camera detects and identifies objects in real-time, ensuring automatic inventory updates without manual input. By integrating various hardware components, the system streamlines inventory tracking, enhancing efficiency and accuracy in warehouse operations.
Keywords: computer vision, embedded systems, IoT, Raspberry Pi