IOT-based sleep analysis using machine learning technique

• Main Author: Wong, Kah Wai
• Format: Final Year Project / Dissertation / Thesis
• Published: 2020
• Subjects: T Technology (General); TA Engineering (General). Civil engineering (General)
• Online Access: http://eprints.utar.edu.my/3832/1/15ACB00465_FYP.pdf; http://eprints.utar.edu.my/3832/

The final year project is about developing a smart pillow with IoT and machine learning capability. It utilizes a popular microprocessor readily available in the market which is the Raspberry Pi. Reason why Raspberry Pi was chosen is because it is relatively simple to use and can be obtained at a very low cost. How the system is able to categorize the sleep level is by the machine learning technology. As for the wireless capability of the device, it can be demonstrated in the Ubidots part of the system. The Ubidots function as a platform wirelessly to have full control and viewing of all the data collected by the system. Since now insomnia has been a common problem among the public, this increase the need to develop a product to overcome this problem. Even though, there are some readily available smart pillow in the market, most of them are very costly. Hence, this a low-cost smart pillow with all the latest technology has to be created to stratify the needs of the public.