Road Safety Monitoring using deep learning and Unmanned Aerial Vehicle
Saksham Kumar Jha, Rohan Srivastava, Chiranjit Behuria, Aniket Mishra, Sribananda Panda, Devendra Kumar Yadav · 2024
This paper presents a novel system utilizing Un-manned Aerial Vehicles (UAVs) for real-time object detection and road safety monitoring. The proposed system leverages deep learning (DL) identify and classify object like potholes on congested Indian roads, particularly during late hours for enhanced accident prevention. A camera mounted on the drone captures images, which are then processed to detect and classify objects based on their characteristics and severity. The system employs Internet of Things (IoT) for data transmission and cloud storage for ubiquitous access and analysis. The results demonstrate the feasibility of the proposed system for intelligent road safety monitoring, offering timely alerts to authorities for prompt action. Whilst achieving an decent accuracy of 85 % for correct classification of potholes from the live-feed, the system works immaculately well in various conditions for detection.