Narrative :
The I3-4-Seaweed project aims at scaling, demonstrating, and ensuring market readiness of business ventures within the macroalgae/seaweed sector. It relies on an international collaboration, comprising 16 partner entities from 6 EU countries, between universities, research institutes, tec-hubs, SMEs and industry clusters to promote transformative, transnational value chain rooted in new sustainable seaweed cultivation techniques and algal biotechnological applications.
Through the project’s investment cases, spanning the food industry, biofertilizers, and cosmetics, seaweed demonstrates its vast versatility and potential to revolutionize multiple sectors, marking a paradigm shift towards a more sustainable future, from healthier diets to lower CO2 emissions.
In the I3-4-Seaweed project, HAEDES is responsible for the implementation of a business case concerning the development of a customized functional prototype Digital Twin (Aquaculture 4.0) for seaweed aquaculture systems. Aquaculture 4.0 aims at delivering real-time insights into farm health, yield and efficient planning based on forecasted production conditions. The service seeks not only to refine maintenance strategies for open sea seaweed farming but also to limit operational risks, potentially boosting yields. One main objective of the tool is to lead to a reduction in maintenance and operation (M&O) costs of aquaculture facilities while equipping farmers with advanced tools to better forecast yields and thus reduce uncertainty in the seaweed production.
Our touch :
Shape the Digital Twinning service to represent the specific conditions of aquaculture farms and farming needs.
Introduce tailored sensors and probes onsite for real-time data collection of parameters required for yield forecasting (water quality, salinity levels, weather, etc.) and choose relevant post-processing data to consider.
Offer real-time insights and predictive expertise using machine learning (ML) and artificial intelligence (AI), with a focus on anomaly detection, predictive maintenance, and future statuses forecasting.
Ensure the system embodies flexibility, adaptability, and practical relevance.
