Micro-Sleep Accident Prevention by SMART Vehicle Using AI and Image Processing

This research paper proposes a novel approach to prevent accidents caused by microsleep in smart vehicles through the integration of image processing and artificial intelligence. Microsleep is a brief period of unconsciousness that can occur during monotonous driving, leading to serious accidents. The proposed system aims to detect signs of microsleep in drivers and alert them to take corrective measures. The system uses a camera to capture images of the driver's face, which are analysed using image processing techniques to detect signs of fatigue or drowsiness. Apart from this we have come up with a smart steering wheel proposition, that monitors the data from pressure sensor installed in the wheel and launches an alert when the value drops or deviates from the normal threshold. An artificial intelligence model is then used to classify the level of fatigue and trigger appropriate alerts, such as auditory warnings, to the driver. The proposed system was tested on a dataset of real-world driving scenarios, and the results showed promising accuracy in detecting microsleep and preventing accidents. This system could potentially improve road safety and reduce the risk of accidents caused by driver fatigue in smart vehicles.