Microservice-Oriented Cloud-Based Driver Vigilance System for Accident Protections

A smart city that frequently experiences accidents is prone to economic failures. Presenting accurate information that could prevent accidents is one of the primordial tasks for travelers/officials. This article proposes a microservice-oriented cloud-based driver vigilance system that aggregates and visualizes the driver's facial emotions on a Google-based travel map. IoT sensors such as ultrasonic and light sensors are utilized in the proposed system to distinguish streets that have poor driving conditions such as low lighting or overtaking vehicles along a path of travelers' journey. Experiments were carried out at our IoT cloud research laboratory by demonstrating the real-world traffic situations and pointing drivers' emotions on Google maps. We achieved a peak data transfer rate of 1.428 Mb/s and attained 3.548 seconds on average when executed on cloud systems.