Early Warning and Real-Time Ship Tracking using AIS Data and Smartphone GPS

Abstract

The high risk of maritime accidents in congested waters such as the Malacca Strait requires an affordable safety system specifically for small fishing vessels. This research proposes and evaluates a mobile-based early warning framework that integrates shore-based AIS data with fishermen’s smartphone GPS. The system was tested under 3 operational scenarios using 4G cellular networks over a coastal area of Bengkalis, involving 60 collision simulation events and 180 API requests. Performance evaluation shows an average system latency of 2.3 seconds with a maximum latency of 4.8 seconds. The early warning mechanism successfully detected dangerous proximity (≤50 meters) with an accuracy of 93.3% and an error rate of 6.7%. Position logging via JSON POST achieved a success rate of 96.1% during continuous operation for 2 hours. Although this study demonstrates improved situational awareness and reliable last-known position recording, the system currently uses distance-based detection and does not yet implement CPA/TCPA prediction, which remains future work. The framework contributes as a low-cost monitoring and early warning solution with potential support for SAR operations through reliable historical position data.