Multisource Data Fusion-based Driver Vigilance State Estimation using Arduino Mega and Node MCU

The quantity-based measurement of a driving person's vigilance is extremely valuable for ensuring the safety as well as avoiding accidents while driving. Decreased vigilance in driving activities of the driver is a key cause for the fatal collisions and as a result, the transportation safety of the general population gets exposed to risk. However, there are not much effective methods available for assessing the real-world driving situations. This paper presents the creation of an advanced driver safety system that uses an Arduino microcontroller interfaced with several sensors to increase transport safety and prevent accidents caused by driver fatigue, intoxication, and obstructions by estimating the driver vigilance state. Our system relies on multisource data fusion. Our proposed framework based on driver vigilance state that considers the vigilance lowering factors like driver weariness, alcohol impairment, and hindrances will be able to show promising performance in ensuring the driver safety and lowering accidents. Finally, the performance validation was done and the implementation screenshots along with the graphical comparisons were presented.