Document Type

Journal Article

Publication Title

Sensors

Volume

24

Issue

2

PubMed ID

38257424

Publisher

MDPI

School

School of Engineering

Comments

Jalalifar, S., Belford, A., Erfani, E., Razmjou, A., Abbassi, R., Mohseni-Dargah, M., & Asadnia, M. (2024). Enhancing water safety: Exploring recent technological approaches for drowning detection. Sensors, 24(2), article 331. https://doi.org/10.3390/s24020331

Abstract

Drowning poses a significant threat, resulting in unexpected injuries and fatalities. To promote water sports activities, it is crucial to develop surveillance systems that enhance safety around pools and waterways. This paper presents an overview of recent advancements in drowning detection, with a specific focus on image processing and sensor-based methods. Furthermore, the potential of artificial intelligence (AI), machine learning algorithms (MLAs), and robotics technology in this field is explored. The review examines the technological challenges, benefits, and drawbacks associated with these approaches. The findings reveal that image processing and sensor-based technologies are the most effective approaches for drowning detection systems. However, the image-processing approach requires substantial resources and sophisticated MLAs, making it costly and complex to implement. Conversely, sensor-based approaches offer practical, cost-effective, and widely applicable solutions for drowning detection. These approaches involve data transmission from the swimmer’s condition to the processing unit through sensing technology, utilising both wired and wireless communication channels. This paper explores the recent developments in drowning detection systems while considering costs, complexity, and practicality in selecting and implementing such systems. The assessment of various technological approaches contributes to ongoing efforts aimed at improving water safety and reducing the risks associated with drowning incidents.

DOI

10.3390/s24020331

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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