Objectives: To develop a novel, paradigm-shifting framework based on an autonomous, collaborative robotic swarm/fleet and on new advanced adaptive swarming strategies; to optimize the quality and quantification of coastal ocean acidification (COA) measurements by using prior sensed data to direct real-time swarm re-positioning; and to advance the cost-effective hardware technology (autonomous mobile buoys) tailored for COA in terms of sensing capabilities, mobility, communication, and computational capabilities.
Methodology: We will use autonomous mobile buoys as a part of a smart swarm system to measure surface pH data, augmented as necessary by select sensing of other relevant quantities (e.g. temperature, salinity). The field tests will be conducted at Stellwagen Bank, MA, where relevant data will be collected.
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.