Browse By Repository:

 
 
 
   

Development of sleeping pattern monitoring system using internet of things

Md Shahrum, Muhammad Nur Ikhwan (2024) Development of sleeping pattern monitoring system using internet of things. Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)

[img] Text (Full Text)
Development of sleeping pattern monitoring system using internet of things.pdf - Submitted Version

Download (3MB)

Abstract

Lack of adequate sleep can cause various health problems such as heart disease, obesity and diabetes. Therefore, this study aims to develop a system that monitors human sleep patterns using the Internet of Things (IoT) and Raspberry Pi. The system is designed to help individuals improve their sleep quality and overall health by providing insight into their sleep patterns. Therefore, establishing an effective sleep monitoring system is essential to maintaining good health. In this work, the Raspberry Pi microcontroller. motion sensors and a cloud-based database will be used to develop the system. During sleep, the system will record any detected movements and store the information, i.e. data in the cloud, which can be accessed remotely through a mobile application or web interface. the system records motion data and stores it in a cloud-based database, which can be accessed remotely through a mobile application or web interface. In addition, the system will provide valuable insight into a person's sleep patterns, such as sleep duration, time taken to fall asleep, and frequency of waking up. This information is useful for providing personalized feedback and recommendations based on an individual's sleep patterns. The system's user interface is user-friendly, making it easy for individuals to monitor their sleep patterns and make the necessary adjustments to improve their sleep quality. Implementation of the system can help individuals improve their sleep quality and maintain good health. In conclusion, developing a sleep monitoring system using IoT with Raspberry Pi is an effective way to monitor and improve sleep quality. This system provides valuable insight into an individual's sleep patterns, allowing them to make the necessary adjustments to improve their sleep quality and overall health

Item Type: Final Year Project (Project Report)
Uncontrolled Keywords: Sleep monitoring, Machine learning, Posture detection
Subjects: T Technology > T Technology (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Library > Final Year Project > FTKEK
Depositing User: Norfaradilla Idayu Ab. Ghafar
Date Deposited: 16 Nov 2024 07:31
Last Modified: 16 Nov 2024 07:31
URI: http://digitalcollection.utem.edu.my/id/eprint/33175

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year