[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-127474-en":3,"doc-seo-127474-105":29,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":11,"language":21,"language_code":22,"site_id":23,"html_lang":22,"table_of_contents":24,"faqs":25,"seo_title":26,"seo_description":14,"update_tm":27,"read_time":28},127474,962084925290,"Ophelia","https://ap-avatar.wpscdn.com/davatar_085a072bc5b1113ac321206ff7593b45",8,"Research & Report","Pothole detection model for road safety using computer vision and machine learning - Article","Potholes threaten vehicular movement by damaging vehicles and increasing risks to drivers and pedestrians, creating significant financial losses for owners and repair budgets for governments. Traditional pothole detection methods are described as impractical, motivating an accurate detection system for real-time identification. The proposed Pothole Detection Model uses computer vision and machine learning so vehicles can adapt behavior, such as reducing speed or stopping, to prevent damage, support safer roads, and improve maintenance efficiency in intelligent transportation systems.","Pothole detection model for road safety using computer vision  \nand machine learning  \nVijaykumar S. Bidve1, Kiran S. Kakade2, Rahul H. Bhole3, Pakiriswamy Sarasu4, Ashfaq Shaikh5, Pradnya Samit Mehta6, Santosh P. Borde7, Shailesh O. Kediya8  \n1School of Computer Science and Information Technology, Symbiosis Skills and Professional University, Pune, India 2Symbiosis Institute of Management Studies, Symbiosis International (Deemed University), Pune, India 3MIT Art, Design and Technology University, Pune, India  \n4Department of Computer Science and Engineering, Chennai Institute of Technology, Chennai, India 5Department of Information Technology, M. H. Saboo Siddik College of Engineering, Mumbai, India 6Department of Computer Science and Engineering-AI, Vishwakarma Institute of Information Technology, Pune, India 7Student Progression and Industry Relations Office, JSPM’s Rajarshi Shahu College of Engineering, Pune, India 8School of Logistics and Supply Chain Management, Symbiosis Skills and Professional University, Pune, India  \nArticle history:  \nReceived Feb 24, 2024 Revised Jun 15, 2024 Accepted Jun 21, 2024  \nKeywords:  \nComputer vision; Intelligent transportation systems;  \nMachine learning; Pothole; Vehicular safety  \nCorresponding Author:  \nPotholes pose significant threats to vehicular movement, causing damage to vehicles and risking the safety of drivers and pedestrians. The escalating issue of potholes has led to substantial financial losses for vehicle owners and drivers. Traditional methods of pothole detection are impractical, necessitating an innovative approach. The study focuses on implementing a detection system capable of accurately identifying potholes, empowering vehicles to adapt their speed or halt to prevent damage. The transformative solution presented in this research leverages cutting-edge technologies, specifically computer vision and machine learning, aiming to enhance road safety and streamline maintenance efforts. By addressing the interdependence of modern civilization on road networks, the Pothole Detection Model promises improved road safety, efficient maintenance practices, and the emergence of an era in intelligent transportation systems. The integration of technology into transportation infrastructure highlights the proactive measures needed to combat road imperfections, ensuring a safer and more efficient road network for the benefit of society.  \nThis is an open access article under the CC BY-SA license.  \nVijaykumar S. Bidve  \nSchool of Computer Science and Information Technology, Symbiosis Skills and Professional University Kiwale, Pune, India  \n[Email: vijay.bidve@gmail.com](Email: vijay.bidve@gmail.com)  \nArticle Info ABSTRACT  \n1. INTRODUCTION  \nPotholes on roads are hard to pass for vehicles as they cause much damage to them. As each and every pothole cannot be converted to a proper road, it is better to make a pothole detection model by which vehicles are able to detect potholes so it can lower down its speed or stop itself [1], [2] . So, no harm will becaused to the vehicle and it directly saves an enormous amount of money. Infrastructure adds significantly toa country's economic overall growth [3], [4] . Road surface of cement and other types are commonly used as mobility facilities in the world [5] .  \nPotholes, irregular manholes and other irregularities are examples of roadways. Potholes can arise asa result of poor construction, poor design that causes groundwater to gather [6] . Annually, potholes do a significant damage to both people and their assets. Potholes immediately affect and disappoint significant amount of people [7], [8] . Approximately drivers have spent over Rs. 10 ,000 crores in five to seven years on  \nautomobiles to repair damage caused by potholes. Each motorist incurred a cost of almost Rs. 10 ,000 on an average. The survey in India states that around 5,000 accidents on an average takes place. Governments also spends a huge amount of money in repairing these ","cbCaiux0JNdyNIKW","https://ap.wps.com/l/cbCaiux0JNdyNIKW","pdf",293689,1,"English","en",105,"# ABSTRACT\n# 1. INTRODUCTION","[{\"question\":\"Why is pothole detection important for road safety?\",\"answer\":\"Potholes cause significant vehicle damage and create safety risks for drivers and pedestrians, leading to costly repairs and disruptions.\"},{\"question\":\"What problem do traditional pothole detection methods face?\",\"answer\":\"Traditional approaches are described as impractical, which motivates the need for a more innovative and accurate detection system.\"},{\"question\":\"How does the proposed model help vehicles respond to potholes?\",\"answer\":\"By detecting potholes using computer vision and machine learning, vehicles can lower speed or stop to prevent damage.\"}]","Pothole detection model for road safety using computer vision and machine learning - Article | PDF",1785939161,20,{"code":4,"msg":30,"data":31},"ok",{"site_id":23,"language":22,"slug":32,"title":13,"keywords":33,"description":14,"schema_data":34,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":27},"pothole-detection-model-for-road-safety-using-computer-vision-and-machine-learning-article","",{"@graph":35,"@context":85},[36,53,68],{"@type":37,"itemListElement":38},"BreadcrumbList",[39,43,47,50],{"item":40,"name":41,"@type":42,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":44,"name":45,"@type":42,"position":46},"https://docshare.wps.com/document/","Document",2,{"item":48,"name":12,"@type":42,"position":49},"https://docshare.wps.com/document/research-report/",3,{"item":51,"name":13,"@type":42,"position":52},"https://docshare.wps.com/document/pothole-detection-model-for-road-safety-using-computer-vision-and-machine-learning-article/127474/",4,{"url":51,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":22,"description":14,"dateModified":61,"datePublished":62,"encodingFormat":60,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":40,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-08-23","2026-08-05",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why is pothole detection important for road safety?","Question",{"text":75,"@type":76},"Potholes cause significant vehicle damage and create safety risks for drivers and pedestrians, leading to costly repairs and disruptions.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What problem do traditional pothole detection methods face?",{"text":80,"@type":76},"Traditional approaches are described as impractical, which motivates the need for a more innovative and accurate detection system.",{"name":82,"@type":73,"acceptedAnswer":83},"How does the proposed model help vehicles respond to potholes?",{"text":84,"@type":76},"By detecting potholes using computer vision and machine learning, vehicles can lower speed or stop to prevent damage.","https://schema.org",{"og:url":51,"og:type":87,"og:title":13,"og:site_name":58,"og:description":14},"article",{"robots":89,"canonical":51},"index,follow",{"doc_id":7,"site_id":23},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,127,130,134],{"id":20,"doc_module":4,"doc_module_name":45,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":46,"doc_module":4,"doc_module_name":45,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":52,"doc_module":4,"doc_module_name":45,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":45,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":45,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":45,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":45,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":45,"category_name":125,"show_sort_weight":28,"slug":126},9,"Religion & Spirituality","religion-spirituality",{"id":28,"doc_module":4,"doc_module_name":45,"category_name":128,"show_sort_weight":28,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":45,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":45,"category_name":136,"show_sort_weight":106,"slug":137},19,"General","general"]