An Intelligent System to Enhance Mental and Physical Health through Sleep Monitoring and Recommendations using Motion Detection and Environmental Sensors

Abstract

This study introduces a new approach to tackling insomnia aimed at international students. It offers a comprehensive solution using environmental sensors and an integrated app. The motivation for this comes from many young students who have insomnia triggered by a new environment. The absence of sleep due to moving around and joining a new culture make it hard to accomplish many things. This app records sleep variables such as motion, light, ambient light, temperature, humidity, and sound. The data is then sent to a database to be pulled and analyzed. The app allows users to quickly and easily view sleep data and trends in real time with a calendar for date selection and viewing trends. When an environmental variable is deemed out of the range of widely accepted ideal sleep values, the app will give the user suggestions on what to correct. Experimental testing was conducted to assess the accuracy of the sensors and the algorithms used to translate that to viewable qualitative data for the user. We found that with using a frame differencing algorithm, there would need to be no motion of the physical camera throughout the night. A second discovery was that multiple people within the frame may affect the user's sleep data. Compared to existing methodologies, the app distinguishes itself by considering a range of environmental factors that offer subjective as well as objective sleep quality tracking. It also gives users the opportunity to form bonds and help each other on the community page. In conclusion, this product presents a reliable, cheap, and easy-to-use method to evaluate and correct sleep health as well as tackle sleep-related medical issues such as insomnia.