Drowsiness Detection System

As a developer, I worked on a personal project called "Drowsiness detection system" that was designed to detect if a person is asleep while driving and also detect the presence of Carbon monoxide in the car. The inspiration for this project came from the tragic incidents of people dying in their cars due to carbon monoxide poisoning in my country.

The project was an IoT product that utilized sensors and machine learning algorithms to detect drowsiness and the presence of carbon monoxide. It consisted of two primary components - a gas sensor and a camera.

The gas sensor was used to detect the presence of Carbon monoxide, a highly toxic gas that can be fatal when inhaled in high quantities. The sensor was connected to a microcontroller which was programmed to send a notification to the driver's mobile phone and their next of kin in case of high carbon monoxide levels in the car. The notification would also include the GPS location of the car so that emergency services could be alerted in case of an emergency.

The camera component of the project was used to detect if the driver was asleep or not. The camera was attached to the car's dashboard and was connected to a machine learning algorithm that was trained to recognize the signs of drowsiness in a person's face, such as drooping eyelids, yawning, and nodding off. If the algorithm detected signs of drowsiness, it would play an alarm to alert the driver and send a notification to the driver's mobile phone and their next of kin. The notification would include the GPS location of the car, as well as a video feed of the driver so that emergency services could be alerted if necessary.

The deliverables of this project included a fully functional IoT product that could detect the presence of carbon monoxide and drowsiness while driving. The project was designed to help prevent accidents and save lives by alerting drivers when they were in danger of falling asleep at the wheel or inhaling toxic gases.

In addition to the hardware components of the project, I also developed a mobile application that could receive notifications from the device and display real-time data on carbon monoxide levels and drowsiness detection. The app was designed to be user-friendly and easy to use, with simple instructions for setting up and using the device.

Overall, this project was a testament to my passion for using technology to solve real-world problems and make a positive impact on people's lives.