TOWARDS ZERO ACCIDENTS: A SURVEY OF DETECTION AND PREVENTION SYSTEMS
DOI:
https://doi.org/10.29121/shodhkosh.v5.i6.2024.3567Keywords:
Smart Irrigation, Machine Learning, Internet of Things, ApplicationAbstract [English]
The increase in the number of vehicles being owned has resulted in a corresponding increase in road accidents, requiring the development of sophisticated methods for detecting and preventing accidents. This study provides a thorough examination of current technology and systems designed to reduce the consequences of road accidents. We analyze a diverse array of methodologies, including IoT-based systems, machine learning techniques, and sensor-based solutions. Although there have been notable advancements in accident detection, emergency response, and driver behavior analysis, there are still obstacles to overcome in terms of infrastructure, data protection, and practical use in real-world scenarios. The study highlights significant areas of research that have not been addressed and provides a clear plan for future research to improve the efficiency of accident detection and prevention systems. This article outlines the creation and use of a cutting-edge Automatic Speed Control System (ASCS) for cars, using up-to-the-minute geolocation data. The ultimate objective is to formulate all-encompassing approaches that use technology progress to provide safer conditions on roads.
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