-Motivation: around 330,000 drowsy driving crashes occur annually. About 6,400 people were killed in such incidents.” -Our idea is to use embedded IoT device to identify drivers drowsiness according to drivers’ eye position and mouth position. When a driver is identified to be drowsy while driving, alarms will be triggered to warn the driver,
-Techniques used: Machine Learning-Classification -Algorithm: CNN (Convolutional neural network) -Model: pre-trained model “Resnet50” from the Tensorflow library.