基于物联网(Iot)的汽车事故检测和报告系统*

Oguntimilehin A, A.A. Oyefiade, K. A. Olatunji, O. Abiola, S.E Obamiyi, B. Badeji-Ajisafe
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引用次数: 0

摘要

道路使用者人数的增加、危险驾驶、糟糕的道路和恶劣的天气等都增加了道路事故,造成重大的生命和财产损失,主要是由于应急服务不足。2021年,世界卫生组织(世卫组织)估计,每年约有130万人因道路交通事故丧生。事故发生后死亡率增加的主要因素是应急反应的延迟。本研究开发的系统通过利用物联网(IoT)技术为这一问题提供了解决方案。该系统由安装在车辆上的硬件子系统和用于应急服务操作的web应用程序组成。微控制器与振动传感器、倾斜传感器、火焰传感器、GPS模块和用于互联网连接的网络模块交互。当振动传感器检测到振动大于定义的阈值时,就会检测到事故。微控制器通过倾斜传感器确定车辆的方向,从火焰传感器检查是否起火,并从GPS模块获得车辆的位置。微控制器将信息延迟45秒发送到web应用程序,因此如果错误地检测到事故,驾驶员可以重置系统,之后有关事故的信息被发送到web应用程序,并确定离事故现场最近的医院。硬件子系统采用$\mathbf{C}++$编程,web应用程序采用超文本标记语言(HTML)、超文本预处理器(PHP)和MySQL开发。
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Internet of Things (Iot) Enabled Automobile Accident Detection and Reporting System *
The increase in number of road users, dangerous driving, bad roads and bad weather among others have increased road accidents, resulting in significant loss of lives and properties mostly due to inadequate emergency services. In 2021, the World Health Organization (WHO) estimated that about 1.3 million lives are lost due to road mishaps yearly. The major factor that increases mortality after an accident occurs is the delay in emergency response. The system developed in this study provides a solution to this problem by leveraging on the Internet of Things (IoT) technology. The system consists of a hardware subsystem installed in a vehicle and a web application for emergency service operations. A microcontroller interacts with a vibration sensor, a tilt sensor, a flame sensor, GPS module and a network module for internet connection. An accident is detected when the vibration sensor detects a vibration greater than the defined threshold value. The microcontroller determines the orientation of the vehicle through the tilt sensor, checks for fire from the flame sensor and gets the vehicle's location from the GPS module. The microcontroller delays sending the information to the web application for 45 seconds so the driver can reset the system if an accident is falsely detected, after which the information about the accident is sent to the web application and the closest hospitals to the accident scene are identified. The hardware subsystem was programmed with $\mathbf{C}++$ and the web application was developed using Hypertext Markup Language (HTML), Hypertext Preprocessor (PHP) and MySQL.
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