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International Journal for Research Trends and Innovation
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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
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| Paper Title: | REAL-TIME POTHOLE DETECTION USING MACHINE LEARNING TECHNIQUES |
| Authors Name: | Karan Kumar Gupta , Rujuta Subhash Ekhande , Ashish Raj , Sagar Kumar Yadav |
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| Author Reg. ID: |
IJRTI_186674
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| Published Paper Id: | IJRTI2305177 |
| Published In: | Volume 8 Issue 5, May-2023 |
| DOI: | |
| Abstract: | In this project, we propose a stereo vision system which detects potholes during driving. The objective is to benefit drivers to react to potholes in advance. We use parameters obtained from video or image calibration with checkerboard to calculate the disparity map. 2-dimensional image points can be projected to 3dimensional world points using the disparity map. With all the 3-dimensional points, we use the bi-square weighted robust least squares approximation for road surface fitting. All points below the road surface model can be detected as pothole region. The size and depth of each pothole can be obtained as well. The experiments we conducted show robust detection of potholes in different road and light conditions. Motivated from the above reasons, we decided to investigate a system to detect potholes on roads while driving. The proposed system will produce the 3dimensional information of potholes and determine the distance from pothole to car for informing the driver in advance. Currently, the main methods for detecting potholes still rely on public reporting through hotlines or websites, for example, the potholes reporting website in Ohio. However, this reporting usually lacks accurate information of the dimensional and location of potholes. Moreover, this information is usually out of date as well. Pothole detection is import to decrease accidents across the world. Many researches have been done but they require some specific devices or tools to acquire sensor data. In this project, we propose a handy way to implement pothole detection using a laptop, and classification is performed using Machine Learning. The experimental result shows that the proposed approach provides us efficiency from the view point of implementation and performance. |
| Keywords: | Potholes, Machine Learning |
| Cite Article: | "REAL-TIME POTHOLE DETECTION USING MACHINE LEARNING TECHNIQUES", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 5, page no.1177 - 1187, May-2023, Available :http://www.ijrti.org/papers/IJRTI2305177.pdf |
| Downloads: | 000205356 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
| Publication Details: |
Published Paper ID: IJRTI2305177
Registration ID:186674
Published In: Volume 8 Issue 5, May-2023
DOI (Digital Object Identifier):
Page No: 1177 - 1187 Country: Pune, Maharashtra, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2305177 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2305177 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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