POTHOLE DETECTION AND COMPLAINT MANAGEMENT SYSTEM USING DEEP LEARNING

Registration ID: IJNRD_195916

Published ID: IJNRD2305565

DOI: Click Here to Get

Shubham Tanaji Barangule , Nandakishor Ankush More , Omkar Tanaji Mote , Abhishek Tanaji Doke , Prof.Arunadevi Khaple

Pothole detection, Convolutional neural networks, Deep learning, Road maintenance, Image processing

One of the biggest issues in emerging nations is the maintenance of roads, which includes potholes. However, manually reviewing and assessing visual road data is a time consuming and expensive procedure. In addition, the results are highly influenced by the subjectivity and experience of the human raters. With the advance of science and technology and popularity of the deep learning model in the engineering field, sophisticated and low-cost systems with intelligence can be used to detect potholes instead of humans. Detection of a pothole is an important function of avoiding road accidents. Today, road pressures are hand-picked, requiring time and effort. In this system, we will be using advanced learning algorithms to find holes in real-time. Using an in-depth learning method we will create a CNN model, train it by providing a pothole dataset in it and then see if the citizen-provided image is valid and then PWD (Department of Public Works) can take the necessary steps in it.

Published Paper   E-Certificate

Shubham Tanaji Barangule, Nandakishor Ankush More, Omkar Tanaji Mote, Abhishek Tanaji Doke, & Prof.Arunadevi Khaple (May-2023). POTHOLE DETECTION AND COMPLAINT MANAGEMENT SYSTEM USING DEEP LEARNING. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(5), f391-f395. https://ijnrd.org/papers/IJNRD2305565.pdf

Volume 8 Issue 5, May-2023

Pages : f391-f395

Paper Reg. ID: IJNRD_195916

Published Paper Id: IJNRD2305565

Downloads: 000121980

Research Area: Engineering

Country: Pune, maharashtra, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2305565.pdf

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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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