Multi-Parameter Smart Fatigue Monitoring and Alert System using Machine Learning

In today's date, everyone uses smart devices, but the usage should be limited or under control. Just because of excess use of such devices can lead to problems like exhaustion, eye tiredness and it also reduces productivity of a person, which is very important in current industry. Without any breaks if one continuously uses such devices with screen then it might as well affect their mental and physical health. After performing a detailed study on different fatigue monitoring approaches and comparing them efficiently. We are proposing a ‘Multi-parameter Smart Fatigue Monitoring and Alert System’ which combines behavior and physical analysis with help of IoT. As the name suggests we combine multiple parameters like screen time, typing speeds, blink rate of the person, heart rate, etc. All of this data is collected and processed and tested by multiple machine learning algorithms. This results in the thorough understanding of user's behavior patterns and normal Vs. abnormal behavior and physical states. The system uses ESP32, microcontroller and multiple sensors to continuously monitor the health of user. After the analysis of user behavior, the system is able to notify them and provide different suggestions so that the user takes break time to time. This ultimately helps to improve productivity and health of the user.