With marine accidents (3,000 cases/year) and fatalities (100/year) on the rise, small vessels (10 tons) now represent 40–45% of all incidents. To address this, we are developing a ship-borne 'Integrated Safety Edge AI Platform' that enables real-time data fusion. The platform integrates multi-camera SMV 360° imaging, AIS tracking, M-IoT sensor data (engine/hull status), and LiDAR-based object detection to enhance maritime safety.
Establishment of camera/LiDAR placement standards; multi-camera synchronization, preprocessing, and stitching for SMV (Safe Marine View) generation and optimal encoding
Estimation of position, speed, and heading of neighboring vessels within a 150–200m radius through AIS message collection and analysis
Real-time diagnosis of vessel status using M-IoT, including engine failure, listing (tilting), flooding, and fire
Classification of vessels, terrain, nets/fishing grounds, buoys, and floating debris; calculation of distance and movement data using LiDAR
Calculation of risk indices and alert levels based on fused data; integrated verification of video and sensor data
Investigation and definition of accident types; construction of real-world environment datasets for AI training and integrity verification
Autonomous navigation along designated coastal routes; hazard recognition and automatic collision avoidance; autonomous return to predefined routes during emergencies
Automated notification systems for external agencies (VTS/Rescue); actual vessel pilot testing, stabilization, and commercialization
Standard Model: SMV-based hazard detection & alerts + AIS integration
Advanced Model: M-IoT convergence + predictive analysis by accident type
Premium Model: LiDAR integration + emergency autonomous transition + automatic collision avoidance + V2V/V2I connectivity
General Scope: Target distribution for fishing boats, leisure/tourism vessels, and workboats; includes installation, after-sales service (AS), and insurance linkage
Accident Prevention: Prevention of collisions, groundings, capsizing, and entanglement with floating debris
Casualty Reduction: Decrease in major fatalities through early warning systems and evasive maneuvering
Cost Efficiency: Reduction in property/operational losses and insurance/risk management costs
Operational Optimization: Enhanced efficiency in predictive maintenance for vessels
Industrial Competitiveness: Strengthening industry edge through the accumulation of core Maritime Edge AI convergence technologies and datasets
Policy Paradigm Shift: Establishing a foundation for shifting maritime policy from post-accident response to proactive prevention
