Development of an AI IoT-based smart system to support improved beach visitor safety

Abstract

The high rate of sea accidents at Indonesian coastal tourist destinations, such as those occurring at Parangtritis and Pangandaran beaches, underscores the limitations of conventional safety systems that rely on manual surveillance. The objective of this research is to develop the Smart Beach Visitor Safety System (Smart BEVISAT), an integrated system based on artificial intelligence (AI) and the Internet of Things (IoT) to enhance beachgoer safety through preventive and reactive functions. The system development method employs the waterfall model, which includes stages of requirements analysis, design, implementation, and testing. The system is composed of three primary components: an AI surveillance camera, an IoT safety buoy, and a ground station. The AI camera utilizes advanced algorithms such as YOLOv11 for object detection, ByteTrack for tracking, and DeepLabv3+ for waterline segmentation, enabling it to monitor visitors and detect safety zone violations in real-time. In the event of an incident, the system automatically sends the victim's coordinates to the IoT Safety Buoy, an Unmanned Surface Vehicle (USV) designed to autonomously navigate to the victim's location for rapid evacuation. The implementation results show a functional prototype with measurable technical specifications, where the buoy achieves a total gross buoyancy of 205.8 kg, a net carrying capacity of approximately 190 kg, and a measured operational speed of 1.20–1.53 m/s under varying load conditions, demonstrating effective rescue capability. The development of Smart BEVISAT is expected to provide a technological solution to minimize accident risks and strengthen the maritime tourism sector in Indonesia