Smart Vehicle Management System for Accident Reduction by Using Sensors and An IoT Based Black Box

Mohammad Minhazur Rahman, A. Z. M. Tahmidul Kabir, Shoumic Zaman Khan, Nahin Akhtar, Abdullah Al Mamun, S. Hossain
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引用次数: 6

Abstract

Reckless driving is one of the prominent causes of human-based vehicle collisions, which are gradually increasing. Furthermore, due to a lack of real-time evidence, very few further investigations are done to determine the actual causes of these accidents. The central theme of this titled paper is to construct a few sensor-based black box systems that will assist us in reducing traffic collisions by giving accurate instructions to the driver constantly. At the same time, it will upload the evidence to its server for further analysis. Firstly, there is a variety of sensors in this black box system, including LIDAR, alcohol sensors, a camera, and RFID. This technology also has a method for detecting the driver's drowsiness. All of the information will be shown on a monitor directly in front of the driver's seat. Lastly, the relevant authority will receive information on the vehicle's condition and location via GPS and GSM.
利用传感器和基于物联网的黑匣子减少事故的智能车辆管理系统
鲁莽驾驶是造成人为车辆碰撞的主要原因之一,此类事故正在逐渐增多。此外,由于缺乏实时证据,很少进行进一步调查以确定这些事故的实际原因。这篇标题论文的中心主题是构建一些基于传感器的黑匣子系统,这些系统将通过不断向驾驶员提供准确的指令来帮助我们减少交通碰撞。与此同时,它将把证据上传到服务器上进行进一步分析。首先,这个黑匣子系统中有各种各样的传感器,包括激光雷达、酒精传感器、摄像头和RFID。这项技术还有一种检测驾驶员睡意的方法。所有的信息都将显示在驾驶员座位正前方的显示器上。最后,相关部门将通过GPS和GSM接收车辆状况和位置信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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