A system-of-systems approach to real-time integrated ocean environmental monitoring

The state of the oceans and marine life is an essential factor in the Earth’s climate and primary production, as well as sustainable production of seafood through fisheries and aquaculture. The oceans are huge and complex, with important phenomena ranging from micro- to macro-scales in space and time. Our ability to acquire data, analyze the data and build scientific knowledge about the oceans is strongly limited by the technologies that available for ocean observation. The approach taken is to develop methods to design, implement and operate a system-of-systems (SoS) consisting of small satellites, marine robots and drones, innovative bio-sensor systems, internet of things, AI/autonomy/algorithms and ocean modelling. Out hypothesis is that the use of model-based systems engineering will offer a powerful and novel technology platform that can be used to build a system for ocean monitoring with high resolution across space, time, and features. The project will develop a general framework for real-time integrated ocean environmental monitoring, implement a proof-of-concept based on existing assets of Grieg Seafood and Moen Marine, and demonstrate the usefulness in a challenging application. The selected case study is real-time monitoring of harmful algal blooms (HABs) in the context of aquaculture. The success of this highly ambitious project is disruptive and interdisciplinary, and it will enable digital transformation and sustainability in ocean sciences and aquaculture.

The state of the oceans and marine life is an essential factor in the Earth’s climate and primary production, as well as sustainable production of seafood through fisheries and aquaculture. The oceans are huge and complex, with important phenomena ranging from micro- to macro-scales in space and time. Our ability to acquire data, analyze the data and build scientific knowledge about the oceans is strongly limited by the technologies that available for ocean observation. The approach taken is to develop methods to design, implement and operate a system-of-systems (SoS) consisting of small satellites, marine robots and drones, innovative bio-sensor systems, internet of things, AI/autonomy/algorithms and ocean modelling. Out hypothesis is that the use of model-based systems engineering will offer a powerful and novel technology platform that can be used to build a cyber-physical SoS for ocean monitoring with significantly enhanced resolution across space, time, and features when compared to what can be achieved with the individual technologies and assets. The project will develop a general framework for real-time integrated ocean environmental monitoring, implement a proof-of-concept based on existing assets available to the partners, and demonstrate the usefulness in a challenging application. The selected case study is real-time monitoring of harmful algal blooms (HABs) in the context of aquaculture. The success of this highly ambitious project is disruptive and interdisciplinary, and it will enable digital transformation and sustainability in ocean sciences and aquaculture.