Challenge
Marine biofouling, i.e., the settlement of organisms on marine man-made structures, generates extensive operational challenges for industries working in the marine environment worldwide. Many of those industries, as for example aquaculture, include installations and submerged equipment which are deployed at sea for extensive periods of time. For those industries, the improper management of biofouling (a) increases substantially (direct and indirect) costs, (b) questions the environmental integrity of the operations, and (c) threatens the public perception of the industry.
Approach
iMAq aims to deliver a data analytics platform tailored for the design of efficient strategies for biofouling management in aquaculture operations. This is achieved through the concept of data analytics in aquaculture decision support mechanisms. iMAq will employ theory-guided, machine learning algorithms to (a) detect frequent spatiotemporal patterns of quantitative indicators of biofouling pressure in aquaculture operations, and (b) unveil potential “cause-and-effect” relationships between environmental factors and biofouling indicators. Detecting these patterns and understanding how they emerge could facilitate the development of more effective prevention-based management measures.
This framework will be tested for a specific region of the Norwegian coastal waters and for biofouling species that are considered relevant for aquaculture operations of this region. Nonetheless, the architectural design of the system will target to maximize its flexibility so that it can be readily transferable in other marine environments globally.
Impact
Situational intelligence
iFOS introduces satellite-derived water quality products and model-based forecast into decision making, filling information gaps in space and time. A web-based, operational platform will facilitate interoperability among existing user’s data flows and modelled services, turning disconnected streams of raw data into actionable intelligence.
Regulatory compliance at low cost
Continuous monitoring of the critical environmental parameters affecting desalination supports the increasingly stricter compliance requirements. Though the seamless modelling of complex and dynamic systems, desalination operators can describe in an innovative way the cause-and-effect relationships that guide them in making quick and data-informed decisions.
Adaptive planning.
Forecasting ten days ahead the response of complex systems provides the ability to assess adaptive scenarios and strategies at scale, reducing the impacts from water quality deterioration.
Early detection and rapid response
The early warning functionality of the service can increase the responsiveness level of desalination operators against possible short-to-medium term changes of the quantity and quality of seawater and, thus, enable proactive informed decision making. In principle, the early warning functionality adheres on the generic concepts underlying the development of an effective Early Warning System, that is: Risk knowledge, Monitoring and warning service, Dissemination and communication and Response capability.
Increased operational intelligence
The DSS provides insight into operations, enabling clients to understand and improve the day-to-day performance of their plants. Operational analytics that combine past and current data with predictive simulations, inform complex operational and business decisions.
OPEX & CAPEX efficiency
The industry-tailored DSS for the chemical – energy nexus provides opportunities to reduce the costs of seawater treatment, generating both more revenue and higher profit margin. At the same time, efficiently operating treatment facilities can extend asset life and delay capital investments.Highlights
Fully automated operational models of coastal hydrodynamics and water quality, using cloud computing services
Operational assimilation of satellite data to improve the predictive power of forecasts
Machine-learning algorithms to assist process optimization in desalination plants
Complete integration into the customer’s existing business processes and processing chains using ICT
