International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 11 Issue: 01 | Jan 2024
p-ISSN: 2395-0072
www.irjet.net
Pothole Detection for Safer Commutes with the help of Deep learning and IOT Device’s Narayan Dasadhikari1, Abhishek Bagade2, Tejas Gaikwad 3, Sojwal Magar 4 1Zeal College of Engineering and Research Narhe, Pune, India.
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Abstract – Accidents caused by potholes have become a
and maintenance. This project acknowledges the importance of sustainability, safety, and efficiency in urban mobility. It aligns with the broader scope of smart city initiatives aimed at utilizing technology for urban improvement. The introduction of a system that enhances the adaptability and flexibility of road infrastructure aims to offer residents and visitors a more efficient, secure, and environmentally friendly commuting experience. This project seeks to contribute to the evolution of urban road systems, making them more responsive and adaptive to the needs of modern urban center’s while addressing critical issues such as congestion and road quality. By making a pothole detecting vehicle system an establishing an inter-vehicular communication, it is possible to reduce the accidents. The project's significance lies in its potential to revolutionize the way road hazards are addressed, ultimately making commutes safer and more convenient for everyone. In this introduction, we embark on a journey to explore how IoT and deep learning can be harnessed to transform the urban commuting experience, reduce accidents, and ensure smoother, more secure journeys on our roadways.
pressing concern in modern life. To address this problem effectively, a multi-step approach is proposed. The first crucial step involves the development of a dedicated device integrated into vehicles. This device is designed to continuously scan the road surface, identifying potholes in real-time. When a pothole is detected, it promptly alerts the driver, allowing them to take evasive action to avoid the hazard. The second step entails the implementation of a technique that enables the device to determine the precise location of each detected pothole using the Global Positioning System (GPS). This GPS data can be collected and stored locally, either through a GPRS (General Packet Radio Service) module or a Bluetooth module. In the third aspect of the solution, the stored database is linked to a network system that incorporates mapping software, such as Google Maps or OpenStreetMap. This integration allows for a comprehensive representation of pothole locations and conditions, making the data accessible to authorities and other road users. Furthermore, to ensure data accessibility and realtime updates, the system can transfer the database to the cloud using Wi-Fi or advanced 5G technology. This connectivity ensures that the information is readily available to all stakeholders, enhancing safety measures and enabling timely road maintenance. This project, "IoT Infused Movable Road Dividers for Enhanced Urban Mobility," aims to address the challenges of urban traffic congestion and road management by introducing innovative technology solutions. The project focuses on the integration of Internet of Things (IoT) technology with movable road dividers to enhance urban mobility.
2.LITERATURE SURVEY 1) Mohan Prakash, Sriharipriya K.C proposed a theoretical paper on the topic “Enhanced Pothole Detection System Using YOLOx Algorithm” which stated or gave the basic information on the YOLO algorithm and its version and there performance based on the number of epoch with model are trained and also gets the detailed execution time need for each version of yolo algorithm the result it gets that the YOLOx give high precision value than other models with the minimum number of epochs YOLOX-nano model outperforms all other lightweight detectors by a large margin and performs less when compared with heavyweight models only by a small margin .which was published around May 2022 which threw light on the machine learning algorithms.
1.INTRODUCTION This Roads are a fundamental component of our society and serve as the primary means of transportation. Over time, our reliance on road networks has significantly increased, reflecting their crucial role in our daily lives. However, the evolving demands on road infrastructure call for innovative solutions to address various challenges. This project center’s on the integration of Internet of Things (IoT) technology with conventional, static road dividers, transforming them into dynamic elements capable of real-time adjustments. Leveraging IoT, these road dividers become responsive to changing traffic patterns, events, and the dynamic nature of urban environments. The primary goal is to enhance traffic flow and alleviate congestion, which are persistent issues in urban mobility. In addition to traffic-related challenges, potholes pose a significant problem in road development
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2) Rupsha Debnath, Sayandeep Dutta, Soumajit Karmakar researched on how fast the YOLO algorithm works and how is the functioning of the YOLO algorithm on their paper “Fast Pothole Detection With The YOLO Algorithm” introduce the innovative system for pothole detection with the configuration of raspberry pi gsm module, camers module for detention and with the help of yolo algorithm it get the high precision and accuracy.the published around January 2022 in order to deal with increasing number of potholes in West Bengal.
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