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Feasibility evaluation of a LoRa-based IoT framework for real-time drowning detection and prevention - Computing

The framework of this paper focuses on the evaluation of the performance of LoRa technology, particularly for individuals exposed to drowning risks in a real environment. It concerns the conception and development of a prototype for monitoring swimmers in a large area, allowing for the prevention of the ongoing drowning situation. This system allows long-range data transfer from multiple sensors to the server via an MQTT broker and then analyzes them for proper decision-making (SOS mode or not). This paper discusses a full low-power communication setup (LoRa network) that uses the Internet of Things and looks at important technical details like RSSI, latency, and packet loss. The experimental results demonstrate a communication range of about 150 m, an average latency between 4.5 and 17 ms, a packet loss rate below 12%, and RSSI values ranging from − 50 dBm to -127 dBm. The device operates with an average power consumption of approximately 80 mA, and the overall prototype completion rate reached nearly 80%, confirming its functional reliability. The study also examines the impact of varying environmental conditions on the performance of the LoRa network, providing researchers useful information for optimizing its deployment in real-world scenarios. Additionally, the PPG sensor monitors vital signs like heart rate, blood pressure, and oxygen levels. Thus, this architecture implements a GPS module to locate the drowning. Consequently, the potential benefits of implementing such systems are numerous, including the anti-drowning measures, lifeguards, staff, and society in general.

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