Monitoring and Analysing the Performance of Runners using the Internet of Things
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Nur Farhana Zainuddin
Azrul Amri Jamal
M.D. Zakaria
Elsayed Makki Elbishr Ali Hassan
Azwa Abdul Aziz
Hani Mohammed Al-Duais
Abstract
Running is a common and easily accessible physical activity that greatly enhances mental and cardiovascular health. The development of technology has completely changed the way we think about fitness. However, the absence of a sophisticated and intelligent running tracking system poses several problems. Among the problems running enthusiasts face is recording the data and analysing the runner for coaches to monitor their health in field paces, heart rate, and distances using wearable devices. In the absence of monitoring, the runner is incautious about their condition while running to avoid injury. The objectives are: to design the implementation of wearable devices equipped with sensors to record comprehensive data during a runner's activity; to develop a system for coaches to monitor and track the health and performance of runners in real-time; and to test the effectiveness of the sensor monitoring system in promoting runner awareness and preventing injuries during running. The methodology is to create a wearable device sensor using IoT components that can easily attach and detect the runner’s health accurately. In this project we can expect that the system should seamlessly function once installed on the runners, the data will be forwarded to the server attached to the laptop where the coaches and admin can view the runner's health status. Also, the device can trace and record the data without causing any problems. Hence, the objective of the result is to study a better-running tracking system by analysing its limitations, especially concerning accurate data storage, real-time performance analysis, and personalized insights. The embedded device can record the health status and able to be monitored by the coach. The combination of embedded technology and monitoring systems will effectively prevent injuries among runners. The technologies/tools used are MKR1010, Arduino IDE, Laravel, Firebase, PHP, and Processing IDE.
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This work is licensed under a Creative Commons Attribution 4.0 International License.