Call for Papers:Vol.10 Issue.6

Submission
Last date		 30-Dec-2024
Acceptance Status In One Day
Paper Publish In Two Days
Submit ManuScript

News & Updates

Submit Article

Dear Authors, Article publish in our journal for Volume-10,Issue-6. For article submission on below link: Submit Manuscript


Join As Board

Dear Reviewer, You can join our Reviewer team without given any charges in our journal. Submit Details on below link: Join As Board


Paper Publication Charges

IJARIIE APP
Download Android App

For Authors

Archives

IJARIIE Board

Downloads

Android App

Download IJARIIE APP

Authors

Title: :  Real-Time Pothole Detection: A YOLO-Based Approach for Safer Roads
PaperId: :  23070
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 10 Issue 2 2024
DUI:    16.0415/IJARIIE-23070
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Nithin RBannari Amman Institute of Technology
Shailesh PBannari Amman Institute of Technology
Mohammed Aswath SBannari Amman Institute of Technology

Abstract

Computer Science and Engineering
Deep Learning, Potholes, Road Safety,YOLO Algorithm, Object Detection, Convolutional Neural works, Real-time Detection, Yolo Version 8
Potholes are a major hazard on highways since they are the primary cause of accidents. Preventing accidents requires early detection and correction. These traffic dangers are a difficulty for drivers, especially during the rainy season. To solve this problem, a variety of methods have been used, including vibration-based sensors and manual examination. Fixing potholes is an essential part of maintaining roads, and regulating organizations always struggle to keep an eye on the state of the pavement. An easier way to detect potholes is required because the current approach requires tedious manual picture processing. But there are disadvantages to the current approaches, namely high prices and dangers associated with detection. A non-invasive method using the YOLO (You Only Look Once) algorithm has been proposed to get around these restrictions. Convolutional neural networks (CNNs) are used by YOLO, a real-time object identification system, to identify and classify potholes in photographs. This deep learning project also tries to address pothole issues encountered by self-driving or autonomous automobiles. Real-time pothole identification is provided by this method using emphasized visual clues. By simultaneously predicting bounding boxes and object classes, the CNN-based system improves accuracy and responsiveness. For training, testing, and validation purposes, a dataset including 720x720 pixel quality photos that capture various pothole scenarios in natural road conditions was employed. Using CNN-based object identification algorithms, this unique approach seeks to enable real-time pothole detection and highlighting. This study offers a thorough assessment of YOLOv8, an object identification model, with a focus on identifying potholes and other road hazards.

Citations

Copy and paste a formatted citation or use one of the links to import into a bibliography manager and reference.

IJARIIE Nithin R, Shailesh P, and Mohammed Aswath S. "Real-Time Pothole Detection: A YOLO-Based Approach for Safer Roads" International Journal Of Advance Research And Innovative Ideas In Education Volume 10 Issue 2 2024 Page 2411-2415
MLA Nithin R, Shailesh P, and Mohammed Aswath S. "Real-Time Pothole Detection: A YOLO-Based Approach for Safer Roads." International Journal Of Advance Research And Innovative Ideas In Education 10.2(2024) : 2411-2415.
APA Nithin R, Shailesh P, & Mohammed Aswath S. (2024). Real-Time Pothole Detection: A YOLO-Based Approach for Safer Roads. International Journal Of Advance Research And Innovative Ideas In Education, 10(2), 2411-2415.
Chicago Nithin R, Shailesh P, and Mohammed Aswath S. "Real-Time Pothole Detection: A YOLO-Based Approach for Safer Roads." International Journal Of Advance Research And Innovative Ideas In Education 10, no. 2 (2024) : 2411-2415.
Oxford Nithin R, Shailesh P, and Mohammed Aswath S. 'Real-Time Pothole Detection: A YOLO-Based Approach for Safer Roads', International Journal Of Advance Research And Innovative Ideas In Education, vol. 10, no. 2, 2024, p. 2411-2415. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/Real_Time_Pothole_Detection__A_YOLO_Based_Approach_for_Safer_Roads_ijariie23070.pdf (Accessed : ).
Harvard Nithin R, Shailesh P, and Mohammed Aswath S. (2024) 'Real-Time Pothole Detection: A YOLO-Based Approach for Safer Roads', International Journal Of Advance Research And Innovative Ideas In Education, 10(2), pp. 2411-2415IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/Real_Time_Pothole_Detection__A_YOLO_Based_Approach_for_Safer_Roads_ijariie23070.pdf (Accessed : )
IEEE Nithin R, Shailesh P, and Mohammed Aswath S, "Real-Time Pothole Detection: A YOLO-Based Approach for Safer Roads," International Journal Of Advance Research And Innovative Ideas In Education, vol. 10, no. 2, pp. 2411-2415, Mar-App 2024. [Online]. Available: https://ijariie.com/AdminUploadPdf/Real_Time_Pothole_Detection__A_YOLO_Based_Approach_for_Safer_Roads_ijariie23070.pdf [Accessed : ].
Turabian Nithin R, Shailesh P, and Mohammed Aswath S. "Real-Time Pothole Detection: A YOLO-Based Approach for Safer Roads." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 10 number 2 ().
Vancouver Nithin R, Shailesh P, and Mohammed Aswath S. Real-Time Pothole Detection: A YOLO-Based Approach for Safer Roads. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2024 [Cited : ]; 10(2) : 2411-2415. Available from: https://ijariie.com/AdminUploadPdf/Real_Time_Pothole_Detection__A_YOLO_Based_Approach_for_Safer_Roads_ijariie23070.pdf
BibTex EndNote RefMan RefWorks

Number Of Downloads



Save in Google Drive

Similar-Paper

TitleArea of ResearchAuther NameAction
Enhancing Diabetic Retinopathy Management Through Personalized Recommendations with Reinforcement LearningComputer EngineeringH.M.A.I.B Herath Download
Development Of Novel Speech To Text Medical App On Patient’s Data using Artificial Intelligence and Edge Computingcomputer engineeringKriti prasad Download
The Role of Artificial Intelligence in HealthcareComputer engineeringMandla Tirumala Sai Download
Speech Sentiment Classification with MLMachine LearningSagar M Prajapathi Download
BIPOLAR AND SLEEP APNEA DETECTIONSComputer ScienceKarthik V Download
Quantum Computing in Cryptography: Revolutionizing Security in the Digital EraComputer EngineeringAnanya T Download
Exploring Audio Features for Enhanced Bird Identification Using Neural NetworksMachine LearningAshwin Bhatt Download
The Impact of Emerging Technologies on Modern E-Commercecomputer scienceAnisha shermi A Download
Transforming Emergency Response and Personalized Health Management with AI and Quantum InnovationsComputer ScienceTapaswini Kar Download
Harnessing Artificial Intelligence for the Future of Personalized HealthcareComputer EngineeringShravani A Download
Optimisation de l’apprentissage des données météorologique déséquilibrées basé sur la modélisation du formule d’Itô et le k-NNIntelligence artificiel, InformatiqueRAMAHEFY Tiana Razefania Download
Comparative Analysis of Machine Learning Techniques for Human Stress Level Prediction: Performance Metrics and InsightsBiomedical EngineeringA. Rasheedha Download
Natural Language Processing Techniques for Ranking Subjective ResponsesComputer ScienceMohammed Ayub G Download
Decision Support System for predicting Diseases using A.I.AI in HealthcareRitika Chatterjee Download
REVIEW ON MACHINE LEARNINGartificial intelligenceBHUMIKA S K Download
12