Internet of wearable things-based on lora and wi-fi healthcare monitoring system for medical applications

• Main Author: Suliman Abdulmalek, Hamood Ahmed
• Format: Thesis
• Language: English
• Published: 2024
• Subjects: T Technology (General); TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://umpir.ump.edu.my/id/eprint/42474/1/ir.Internet%20of%20wearable%20things-based%20on%20lora%20and%20wi-fi%20healthcare%20monitoring%20system%20for%20medical%20applications.pdf; http://umpir.ump.edu.my/id/eprint/42474/

The Internet of Things (IoT) connects various devices over the Internet to gather, store, exchange, and monitor data. In healthcare, IoT has the potential to significantly impact human well-being. Specifically, the Internet of Wearable Things (IoWT) enables wearable devices to exchange data with cloud-based IoT servers. Continuous monitoring of vital parameters is crucial for managing chronic diseases effectively. However, there is a need for improvement in heart disease monitoring, particularly in the case of hypertension, as well as enhancing wireless communication for remote monitoring, with a focus on utilizing LoRa and Wi-Fi technologies. Additionally, existing IoT healthcare systems using microcontrollers have limitations in terms of data accuracy, transmission reliability, and embedded microcontrollers. The thesis presents the design and development of an Internet of Wearable Things-based on Lora and Wi-Fi Healthcare Monitoring System (IoWT-LWHMS) for medical applications, which includes the development of an IoWT-based healthcare system utilizing wearable sensing units for remotely and conveniently monitoring patients' health conditions such as Blood Pressure (BP), Heart Rate (HR), and Body Temperature (BT) in real-time and development of a LoRa and Wi-Fi networks for IoWT-LWHMS to support short-and long-range connectivity using the FiPy microcontroller with an integrated algorithm for data acquisition and update to the IoT platform. Moreover, assessment of the system's performance, focusing on data accuracy, communication reliability, power consumption, and time latency has been conducted. The developed system follows a five-stage process: data gathering, processing, transmission, storage, and visualization. Wearable sensors collect patient data, which is processed by the FiPy MCU. The data is transmitted through LoRaWAN and Wi-Fi networks and stored in the cloud for remote monitoring via a dashboard. The system underwent thorough testing, showing stable and accurate readings for vital parameters. The Wi-Fi and LoRaWAN networks performed reliably, covering a range of up to 1.5 km with no data loss. The system operated continuously for 13 hours on a portable battery and exhibited fast response times of up to 2 seconds for data transmission to the cloud. It can be concluded that the developed IoWT-LWHMS could be implemented for remotely and conveniently monitoring patients' health conditions (BP, HR, BT) in real-time using LoRaWAN and Wi-Fi networks efficiently and effectively.