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Design and development of a smart drowning detection system

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posted on 2024-07-10, 04:15 authored by Yujie Zhu

Drowning is a global public health concern, causing an estimated 236,000 deaths in 2019. It is usually the result of inadequate swimming skills, panic, or unattended children. The process of drowning is always quick and silent, and the most effective traditional drowning prevention effort is lifeguard monitoring, but it is costly and less efficient in large areas. There are two primary methods of intelligent drowning detection, including image processing-based systems and sensor-based wearable devices. Sensor-based devices are cost-effective and have high underwater detection capabilities which make them worthy of further development. This thesis proposes two novel wearable devices for drowning prevention: a Smart Wearable Drowning Detector (SWDD) and a Smart Life Vest (SLV). The SWDD consists of a sensing device equipped with multiple sensors and a GPS beacon, which evaluates various parameters to detect drowning, while the GPS beacon will send location data when drowning is detected. Meanwhile, the SLV will deploy via the designed actuator and start inflating automatically to provide buoyancy for the victims. This proposed system achieves timely drowning detection, and real-time localisation, while buying more time for victims to be rescued, which is expected to significantly reduce casualties from drowning. 

History

Table of Contents

Chapter 1. Introduction -- Chapter 2. Literature Review -- Chapter 3. System Design -- Chapter 4. Testing and Results -- Chapter 5. Conclusion and Future Work -- Appendix -- References

Awarding Institution

Macquarie University

Degree Type

Thesis MRes

Degree

Master of Research

Department, Centre or School

School of Engineering

Year of Award

2024

Principal Supervisor

Mohsen Asadniaye Fard Jahromi

Additional Supervisor 1

Shuying Wu

Rights

Copyright: The Author Copyright disclaimer: https://www.mq.edu.au/copyright-disclaimer

Language

English

Extent

81 pages

Former Identifiers

AMIS ID: 311800

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