Title
Fishing Fleet Environmental Tracker
Digital platform helping fishing fleets comply with environmental regulations and report marine observations.
Summary
The AI-Powered Coastal Monitoring Network represents a breakthrough in environmental risk management, combining cutting-edge artificial intelligence with satellite imagery and ground
sensors to provide real-time assessment and prediction of coastal erosion patterns across
vulnerable areas in Puglia.
This solution addresses the critical need for early warning systems that can detect erosion
trends before they become irreversible, enabling timely intervention and resource allocation.
The system has been successfully deployed across 150km of coastline, protecting communities,
infrastructure, and valuable ecosystems.
The Challenge
Risk Context
Coastal erosion in Puglia has accelerated over the past decade due to climate change, increased storm intensity, and human activities. Traditional monitoring methods were reactive, expensive, and unable to predict erosion patterns with sufficient accuracy for preventive action.
Impact Scale
Over 40 coastal communities at risk, 1,200
hectares of protected ecosystems
threatened, €85M in infrastructure
vulnerable to erosion damage.
Urgency
Erosion rates increasing 15% annually, with
critical infrastructure at risk within 5-10 years
without intervention.
Our Approach
AI-Driven Analysis
Developed a proprietary machine learning model trained on 15 years of satellite imagery, weather data, and ground measurements.
Integrated Sensor Network
Deployed 180 IoT sensors measuring wave action, sediment movement, and structural stress on coastal defenses.
Early Warning System
Automated alert system notifies authorities and communities when erosion thresholds are exceeded.
Knowledge Sharing
Established data-sharing protocols with initiatives in Albania and Montenegro for comparative analysis.
Results & Impact
Environmental Protection
Early detection enabled preventive measures that protected 850 hectares of coastal ecosystems, including critical seagrass meadows.
Infrastructure Savings
Predictive alerts allowed reinforcement of vulnerable areas, avoiding an estimated €12M in infrastructure damage.