TL;DR
iWatchRoad is an end-to-end system that automates pothole detection, geospatial mapping, and visualization to aid road maintenance in smart cities, especially in challenging environments like India.
Contribution
The paper introduces a scalable, cost-effective system combining deep learning, OCR, and geospatial visualization for pothole detection and mapping in developing regions.
Findings
Achieved high detection accuracy under diverse conditions.
Successfully integrated GPS, OCR, and mapping for real-time pothole geotagging.
Provided a web interface for accessible road maintenance data.
Abstract
Potholes on the roads are a serious hazard and maintenance burden. This poses a significant threat to road safety and vehicle longevity, especially on the diverse and under-maintained roads of India. In this paper, we present a complete end-to-end system called iWatchRoad for automated pothole detection, Global Positioning System (GPS) tagging, and real time mapping using OpenStreetMap (OSM). We curated a large, self-annotated dataset of over 7,000 frames captured across various road types, lighting conditions, and weather scenarios unique to Indian environments, leveraging dashcam footage. This dataset is used to fine-tune, Ultralytics You Only Look Once (YOLO) model to perform real time pothole detection, while a custom Optical Character Recognition (OCR) module was employed to extract timestamps directly from video frames. The timestamps are synchronized with GPS logs to geotag each…
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