Smart Drowning Detection System using RSSI Zigbee

DOI

10.2991/978-94-6463-718-2_158How to use a DOI?

Keywords

Drowning detection; RSSI; Zigbee communication; real-time monitoring; motion analysis; wearable technology; environmental monitoring

Abstract

Drowning is an important global health issue and a major cause of accidental death, especially in vulnerable populations including children and the elderly. Traditional drowning prevention methods, which are primarily dependent on human vigilance and visual observation, tend to be insufficient because of their inconsistency caused by factors such as human error, distractions, and environmental elements. We propose a new drowning detection system based on the current technologies using a wearable device equipped with RSSI technology and Zigbee communication protocol. It also monitors environmental conditions including temperature and humidity to make the product a more complete safety solution. By integrating motion and environmental data, the system can alert swimmers to adverse conditions in addition to identifying tragedies like drowning. The system will give immediate alerts when detecting abnormal behavior abnormal behavior patterns typical of drowning e.g., prolonged immobility or erratic movements, detecting unsafe environmental conditions thresholds e.g. temperature ≤ 30 ℃ or high humidity. This alert contains the victim’s location and other key environmental information, which is communicated to nearby lifeguards or monitoring staff through a ZigBee connected network. The system allows for real-time detection of drowning events, with notifications sent directly to lifeguards or nearby citizens for immediate response, ultimately minimizing response times and maximizing survival rates during potential drowning situations, providing scalable, economical, and effective means to improve water safety at swimming pools, beaches, and water parks.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - V. Jhanavarshan
AU  - J. Prajan
AU  - T. Sindhu
PY  - 2025
DA  - 2025/05/23
TI  - Smart Drowning Detection System using RSSI Zigbee
BT  - Proceedings of the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024)
PB  - Atlantis Press
SP  - 1918
EP  - 1930
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-718-2_158
DO  - 10.2991/978-94-6463-718-2_158
ID  - Jhanavarshan2025
ER  -