Published Paper Details:

Road maintenance, particularly pothole repair, poses significant challenges for transportation authorities worldwide. Traditional methods of pothole detection and repair are often inefficient and costly. This project introduces a semi-automated robotic system for pothole identification and repair cost estimation, aiming to streamline road maintenance processes. The system employs an ultrasonic sensor for pothole detection, a GPS module for location tracking, and a Node MCU controller for data integration. An Arduino ATmega328 controller manages robot movement via servo and DC motors. The robot utilizes the depth measurements from the ultrasonic sensor to estimate repair costs based on the thickness of road layers. Real-time data is displayed on an LCD screen and transmitted wirelessly through Bluetooth and the Blynk IoT platform. Initial tests demonstrate the system's ability to accurately detect potholes, measure their depth, and estimate repair costs. The robot successfully navigates road surfaces, providing precise location data for each identified pothole. Cost estimations show a strong correlation with actual repair expenses, varying based on pothole depth and corresponding road layer thickness. This semi-automated approach offers a promising solution for enhancing road maintenance efficiency. By automating pothole detection and providing accurate cost estimates based on depth and road layer thickness, the system has the potential to optimize resource allocation and improve overall road quality. Future work will focus on expanding the system's capabilities and conducting large-scale field trials.