Paper Title
RoadEye - A Safer Drive
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Abstract
Potholes are a major nuisance for drivers, and can also cause significant damage to vehicles. RoadEye is a pothole detection system that uses dashcam footage to identify and report potholes to road maintenance authorities. This system can help to make roads safer and more efficient, and can also save drivers money on repairs. RoadEye uses a deep learning model to identify potholes in dashcam footage. The model has been trained on a large dataset of images of potholes. When the model is presented with a new image, it can identify whether or not it contains a pothole, and if so, it can easily add its location on a map, so that users can be alerted while approaching a pothole. RoadEye can help to improve data collection on road conditions. This data can be used to make informed decisions about road maintenance and infrastructure planning. RoadEye can be used to create a crowdsourced database of potholes. This database can be used by drivers to plan their routes and avoid potholes.
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How To Cite (APA)
Rohit Kinkar Ghorui, Sakshi Dinesh Negi, Vinay Janardhan Chippa, & Saniket Kudoo (April-2024). RoadEye - A Safer Drive. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(4), b153-b162. https://ijnrd.org/papers/IJNRD2404121.pdf
Issue
Volume 9 Issue 4, April-2024
Pages : b153-b162
Other Publication Details
Paper Reg. ID: IJNRD_217500
Published Paper Id: IJNRD2404121
Downloads: 000122008
Research Area: Computer Science & TechnologyÂ
Author Type: Indian Author
Country: Mumbai, Maharashtra, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2404121.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2404121
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