Design of Intelligent Drunk Driving Detection System Based on Internet of Things
Journal on Internet of Things
In recent years, with the rapid development of China's economy and the continuous improvement of people's living standards, the number of motor vehicles and the number of drivers in the country have grown rapidly. Due to the increase in the number of vehicles and the number of motorists, the traffic accident rate is increasing, causing serious economic losses to society. According to the traffic accident statistics of the Ministry of Communications of China in 2009, more than 300,000 car
... 300,000 car accidents occurred in the year, most of which were caused by drunk driving. Therefore, this paper proposes a design scheme based on the Internet of Things-based vehicle alcohol detection system. The system uses STM8S003F3 single-chip microcomputer as the main control chip of the system, combined with alcohol sensor MQ-3 circuit, LCD1602 liquid crystal display circuit, buzzer alarm circuit and button circuit to form a complete alcohol detection module hardware system. The main functions of the system are as follows: the alcohol sensor in the car detects the driver's alcohol concentration value, and displays the value on the LCD screen. The buzzer alarm is exceeded and the information is sent to the traffic police department and the family's mobile phone through the GPRS module. The system can effectively make up for the shortcomings of traffic police detection, which has certain research significance. Wang, J. (2014): The design of multifunctional positioning alarm system to prevent drunk driving. Chinese Journal of Electron Devices, vol. 37, no. 3, pp. 529-534. Yang S.; Li, Y. E.; Zhang, C. H. (2015): Design and research of anti-drunk driving system based on STC89C52RC SCM. Journal of Shanxi University, vol. 38, no. 3, pp. 494-500. Zhao, X. R.; Fan, H. H.; Fu, Z. J.; Chen, D.; Fu, H. Y. (2016): The drunk driving automatic detection system based on internet of things. International Journal of Control and Automation, vol. 9, no. 2, pp. 297-306. Zhu, H. J.; Fan, H. H.; Ye, F. Y.; Zhu, S. S.; Gan, P. Z. (2016): A novel method for moving vehicle tracking based on horizontal edge identification and local autocorrelation images. DYNA-Ingeniería e Industria, vol. 91, no. 1, pp. 61-68.