Periyasamy Mariappan

I am an aspiring Software Developer, driven by a desire to innovate and continuously evolve in this dynamic field. I thrive in collaborative environments, where I can harness my technical skills to transform ideas into reality. My passion for learning fuels my commitment to staying current with emerging technologies and industry best practices.

Work List:

1. Researched and studied different algorithms and techniques for driver drowsiness detection.

2. Collected a dataset of images and videos of drivers in various states of drowsiness.

3. Preprocessed the dataset by resizing images, converting videos to frames, and annotating the data with labels indicating drowsiness levels.

4. Implemented a convolutional neural network (CNN) model using Python and TensorFlow for drowsiness detection.

5. Trained the CNN model

Impact:

• Improved road safety by preventing accidents caused by drowsy driving
• Increased awareness about the dangers of driver drowsiness
• Provided a solution for early detection of driver fatigue
• Reduced the risk of injuries and fatalities on the roads
• Enhanced the overall driving experience by alerting the driver when they are drowsy
• Contributed to the development of advanced driver-assistance systems (ADAS)
• Helped in the implementation of regulations and policies related to driver

• Driver drowsiness detection is a computer vision system that can automatically detect driver drowsiness in a real-time video stream and then play an alarm if the driver appears to be drowsy..

The model can be improved incrementally by using other parameters like blink rate, yawning, state of the car, etc. If all these parameters are used it can improve the accuracy by a lot. We plan to further work on the project by adding a sensor to track the heart rate in order to prevent accidents caused due to sudden heart attacks to drivers.