The increasing prevalence of alcohol-impaired driving is a significant public health concern, contributing to a substantial number of road traffic accidents, injuries, and fatalities worldwide. According to the World Health Organization (WHO), alcohol consumption is a leading risk factor for road traffic injuries, with an estimated 1.35 million fatalities occurring annually due to road traffic accidents [1]. Traditional methods of combating this issue, such as law enforcement checkpoints and breathalyzer tests, have limitations in terms of accessibility, effectiveness, and the ability to provide real-time intervention.

This paper presents a comprehensive study on the development of a Smart Internet of Things (IoT) system designed to detect and prevent alcohol-impaired driving. The proposed system integrates various advanced technologies, including alcohol detection sensors, machine learning algorithms, and cloud computing, to monitor driver behavior and alcohol levels in real-time. By leveraging these technologies, the system aims to provide timely alerts and interventions to prevent potential accidents, thereby enhancing road safety.

The architecture of the Smart IoT system is designed to facilitate continuous monitoring of the driver’s blood alcohol concentration (BAC) levels and driving patterns. The system employs a combination of breath analysis and behavioral analysis to assess impairment, allowing for proactive measures to be taken before an accident occurs. The paper discusses the system's components, functionality, and implementation, as well as the results of initial testing, which demonstrate the system's effectiveness in accurately detecting alcohol impairment with a high degree of reliability.

Furthermore, the potential impact of the Smart IoT system on public safety is explored, highlighting its advantages over traditional detection methods. The findings suggest that the integration of IoT technology in vehicles can significantly reduce the incidence of alcohol-related traffic incidents, ultimately saving lives and promoting responsible driving behavior. This research contributes to the growing body of knowledge on the application of IoT in transportation safety and sets the stage for future advancements in smart driving technologies.