Objectives: The key objective of this proposal is to employ a state-of-the-art autonomous sensing swarm and leverage its mobility to obtain relevant measurements (temperature, pH, salinity) of the ocean surface (continuously optimally positioned sensors). The buoys communicate with each other and form an intelligent swarm that is capable of obtaining a more accurate reconstruction of an underlying environmental field than non-collaborative sensors or a small number of high-quality sensors could provide. The sensed data (temperature, pH, salinity), obtained at key areas tracking large gradients, will be provided to support multi-fidelity models to improve the prediction of ocean acidification in Mass Bay.
Methodology: We will use 30 fully instrumented autonomous mobile buoys as a part of a smart swarm system to measure surface temperature, salinity and pH data. The field tests will be conducted at Stellwagen Bank, MA, covering the area of 10~100 km^2 deployed for weeks at a time.
Rationale: Ocean acidification (OA) is threatening marine ecosystems and maritime food industry. Monitoring OA involves collecting data over a long period of time from a large number of measuring stations. Distributed systems are a cost-effective strategy for pervasive and persistent measuring and monitoring of environmental fields. They offer unparalleled system robustness, and with our proposed framework, would exhibit real-time collaborative distributed computing capabilities that would lead to much higher measured data quality.