AIoT pothole detection system using YOLOv5

Mahendran, Thiveya (2023) AIoT pothole detection system using YOLOv5. Project Report. Melaka, Malaysia, Universiti Teknikal Malaysia Melaka. (Submitted)

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Abstract

The AIoT Pothole Detection System using YOLOv5 is an innovation that is made to help the society. The elements implemented in the project are artificial intelligence primarily focusing on object detection, IoT device integration and YOLOv5 algorithm. The objectives of this innovation is to implement object detection to detect potholes present on the road, measure the performance of two different YOLO models detection accuracy for pothole detection and evaluate the performance of the chosen YOLO model. The problems that can be solved from this innovation are plenty and they are to improve road safety of drivers and riders providing them enhanced driving experience, reducing damage to vehicles and provides efficient road maintenance helping reduce infrastructure damage. In addition to that, this project is a way to embody the state-of-the-art potentials like IoT (Internet of Things) and AI (Artificial Intelligence) technologies, especially incorporating them and producing futuristic innovations. Pothole detection system using YOLOv5 deployed to a Raspberry Pi 4 offers a holistic solution to a common urban infrastructure challenge and has a lot to contribute to the overall well-being and safety of communities.

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