In general, the mental state of a driver is a crucial aspect when a vehicle is on the road. In this study, we design a vehicle safety monitoring system based on the Internet of things and physiological characteristic identification. The developed monitoring system, which is based on Zigbee, comprises two parts: (1) the network coordinator and router, which are installed on the road, and (2) the network-end devices, which are installed in the vehicle. The queen honey bee migration algorithm is used to improve the performance of the Zigbee network. Moreover, a fuzzy controller with a photoplethysmography signal is used as input to analyze the mental state of the driver. The developed system provides the driving status, such as normal, slow, pause, or stop.

通常，当车辆在道路上时，驾驶员的精神状态是至关重要的方面。在这项研究中，我们设计了一个基于物联网和生理特征识别的车辆安全监控系统。基于Zigbee的已开发监控系统包括两部分：（1）安装在道路上的网络协调器和路由器，以及（2）安装在车辆中的网络端设备。女王蜂的迁移算法用于提高Zigbee网络的性能。此外，带有光电容积脉搏波信号的模糊控制器被用作输入来分析驾驶员的精神状态。开发的系统提供了行驶状态，例如正常，缓慢，暂停或停止。