Development of an IoT-Based Electric Safety Buoy with Autonomous Navigation System for Coastal Water Rescue Operations

Abstract

This research aimed to develop and evaluate an IoT-based electric safety buoy equipped with an autonomous navigation system to support Search and Rescue (SAR) operations in coastal environments. The system integrates dual‐thruster propulsion, GPS and Inertial Measurement Unit (IMU) sensors, IoT telemetry, and a Return-to-Home (RTH) mechanism, enabling both manual and autonomous operation modes. Prototype testing was conducted in a controlled aquatic environment under light wave conditions (10–25 cm) and mild surface currents (0.18–0.32 m/s), with calm weather and unobstructed line-of-sight communication. The buoy was evaluated in both unloaded and 2 kg payload conditions, traveling at an average speed of 1.25–1.35 m/s across test sessions lasting 12–18 minutes. Three predefined GPS waypoints were used to assess navigation accuracy, motion stability, RTH reliability, and telemetry performance. Results show that the autonomous mode achieved a mean positioning error of 1.12 m, a cross-track deviation of 0.35 m, and a waypoint success rate of 96%, outperforming manual navigation by 52%. The RTH function maintained a success rate of 100% under low-battery conditions and 92% during communication loss, while IoT telemetry remained stable up to 200 meters with less than 1% packet loss. These findings confirm that integrating IoT-based telemetry with adaptive autonomous navigation enhances rescue mission efficiency and operational safety, while indicating the need for further validation under more challenging open-sea conditions.This research aimed to develop and evaluate an IoT-based electric safety buoy equipped with an autonomous navigation system to support Search and Rescue (SAR) operations in coastal environments. The system integrates dual‐thruster propulsion, GPS and Inertial Measurement Unit (IMU) sensors, IoT telemetry, and a Return-to-Home (RTH) mechanism, enabling both manual and autonomous operation modes. Prototype testing was conducted in a controlled aquatic environment under light wave conditions (10–25 cm) and mild surface currents (0.18–0.32 m/s), with calm weather and unobstructed line-of-sight communication. The buoy was evaluated in both unloaded and 2 kg payload conditions, traveling at an average speed of 1.25–1.35 m/s across test sessions lasting 12–18 minutes. Three predefined GPS waypoints were used to assess navigation accuracy, motion stability, RTH reliability, and telemetry performance. Results show that the autonomous mode achieved a mean positioning error of 1.12 m, a cross-track deviation of 0.35 m, and a waypoint success rate of 96%, outperforming manual navigation by 52%. The RTH function maintained a success rate of 100% under low-battery conditions and 92% during communication loss, while IoT telemetry remained stable up to 200 meters with less than 1% packet loss. These findings confirm that integrating IoT-based telemetry with adaptive autonomous navigation enhances rescue mission efficiency and operational safety, while indicating the need for further validation under more challenging open-sea conditions.