Objectives of the Product

HABTRAIL addresses the challenges posed by Harmful Algal Blooms (HABs), which impact aquaculture, public health, tourism, and insurance sectors. HABs contaminate seafood, disrupt aquaculture operations, cause economic losses, and pose risks to human health. Traditional monitoring methods rely on costly, time-consuming water sampling and lab tests, often leading to delayed responses.

HABTRAIL provides an AI-driven early warning system that accurately predicts HAB occurrences and bivalve toxicity up to three days in advance. The platform integrates satellite and in situ data with advanced machine-learning models to deliver real-time insights.

Users access the predictions through a web dashboard, where they can visualise HAB severity, receive species-specific interdiction forecasts, and configure personalised alerts. Aquaculture operators can optimise harvesting schedules, public health offices can make informed safety decisions, and tourism and insurance entities can manage risks proactively.

By offering predictive analytics and automated alerts, HABTRAIL shifts HAB management from reactive to proactive, reducing financial losses, improving food safety, and ensuring sustainable marine resource use. The platform’s expansion will enhance its accuracy, cover more geographic regions, and incorporate additional environmental factors to support decision-making and regulatory compliance further.

---

Customers and their Needs

HABTRAIL targets aquaculture entities, national regulatory bodies, public health offices, tourism businesses, and insurance companies. These customers face significant challenges due to Harmful Algal Blooms (HABs), which disrupt operations, endanger public health, and cause economic losses.

• Aquaculture entities (fish and bivalve farms) rely on HABTRAIL’s predictive insights to minimise losses by adjusting harvesting schedules and ensuring seafood safety. Their challenge lies in obtaining timely, cost-effective, and reliable data to mitigate production risks.
• National regulatory bodies oversee seafood safety and environmental monitoring. They need accurate, real-time data to issue interdictions and ensure compliance, but current monitoring methods are reactive, costly, and slow.
• Public health offices must prevent foodborne illnesses from toxic seafood. They require predictive tools to safeguard consumers and optimise response measures.
• Tourism businesses (beach operators, tour agencies) suffer from reduced visitor numbers when HABs affect water quality. They need timely forecasts to adjust plans and avoid reputational damage.
• Insurance companies rely on environmental risk assessments to price policies and process claims. A lack of reliable historical data makes risk evaluation difficult.

HABTRAIL directly involves these stakeholders by providing an AI-powered web dashboard with real-time predictions, automated alerts, and risk assessments, enabling data-driven decisions to mitigate the impact of HABs.

---

Targeted customer/users countries

HABTRAIL initially targets Portugal for deployment, focusing on its coastline and estuarine zones. Expansion is planned for Spain, France, and Italy in Europe (Year 2), followed by the USA and Chile in the Americas (Year 3), and later Japan and South Korea in Asia (Year 4-5). These countries have significant aquaculture industries, regulatory bodies for marine monitoring, and coastal tourism sectors affected by Harmful Algal Blooms (HABs).

---

Product description

HABTRAIL is an AI-powered web-based platform that predicts, monitors, and issues early warnings for Harmful Algal Blooms (HABs). It integrates satellite data with machine learning models to forecast HAB severity and bivalve toxicity with over 90% accuracy for the next three days. Users interact with the platform through a web dashboard, where they can visualise HAB severity maps, access species-specific interdiction forecasts, and configure custom alerts via email or SMS.

Innovative Aspects

• AI-Driven Predictions: Unlike traditional reactive monitoring methods, HABTRAIL uses deep learning to analyse satellite imagery and identify patterns in HAB development.
• Multi-Algorithmic Approach: Combines clustering, pixel segmentation, and deep neural networks to improve detection accuracy and reduce false positives.
• User-Friendly Interface: Provides real-time, interactive dashboards tailored for aquaculture operators, regulatory bodies, public health officials, and insurers.
• Scalability & Regional Adaptation: The model is designed to expand to new coastal areas with minimal additional data collection.

User Interaction

• Aquaculture entities optimise harvesting schedules and reduce economic losses.
• Regulators receive interdiction forecasts and cross-validate decisions.
• Tourism and insurance entities monitor risk levels to adjust policies and business operations.

By shifting from a reactive to a proactive approach, HABTRAIL ensures safer, more sustainable management of marine resources.

---

Added Value

HABTRAIL brings significant added value compared to traditional monitoring methods and existing competitors by offering a proactive, AI-driven approach to Harmful Algal Bloom (HAB) prediction.

Key Differentiators

1. AI & Multi-Algorithmic Analysis – Unlike competitors that rely on threshold-based methods, HABTRAIL uses deep learning to detect patterns in satellite imagery, reducing false positives and increasing predictive accuracy.
2. Real-Time & Predictive Alerts – While current monitoring systems rely on costly, delayed lab testing, HABTRAIL delivers three-day advance forecasts, allowing aquaculture businesses and regulators to act before contamination occurs.
3. User-Centric Dashboard & Automation – Unlike government-provided raw data portals, HABTRAIL offers a visual, user-friendly dashboard with customisable alerts, making it accessible to non-experts.
4. Regional Adaptability & Scalability – Many existing solutions are site-specific or limited to post-event analysis. HABTRAIL’s AI models are scalable and adaptable to new coastal areas without requiring extensive new data collection.
5. Comprehensive Stakeholder Support – Unlike competitors that focus solely on aquaculture or research, HABTRAIL supports national regulators, public health, tourism, and insurance sectors, integrating multiple industry needs into one solution.

By transitioning from a reactive to proactive strategy, HABTRAIL minimises financial losses, improves food safety, and enhances environmental protection better than any existing alternative

---

Current Status

HABTRAIL is in an advanced development phase, with key achievements including the successful implementation of AI-driven predictive models, achieving over 90% accuracy in forecasting HAB severity and bivalve toxicity. A functional web dashboard has been developed, providing real-time data visualisation and customisable alerts.

Current work focuses on expanding geographic coverage from the initial L7C2 (Algarve) test zone to the entire Portuguese coastline, refining species-specific interdiction forecasts, and enhancing model precision using additional environmental data.

Upcoming activities include user onboarding for aquaculture entities and national regulators, gathering feedback for system optimisation, and integrating new features such as pixel-based HAB, SST, and CHLOR_A predictions. Future expansion plans target Spain, France, and Italy in the next phase. The project is progressing on schedule, with ongoing validation efforts ensuring operational readiness for commercial deployment.