This proposal develops, deploys and evaluates a prototype pervasive dynamic oceanographic ecosystem that integrates sensors, networks, observatories, and computational algorithms to enable dynamic data driven application systems research (DDDAS) in oceanography and in particular the study of anoxia and hypoxia off the coast of New Jersey. The research findings are also incorporated in cross-disciplinary research curricula (across SOE, FAS and MCS) to provide students with the skills needed by the rapidly expanding network of research and applied observatories being constructed. New research methods in distributed resource allocation, distributed simulation environments, nonlinear dynamic system theory for swarming and computer vision learning methods are used to achieve the proposed goals. The result and impact of this DDDAS framework, is to integrate computational infrastructure that includes computers, networks, data archives, instruments, observatories, experiments, and embedded sensors and actuators, to address important national and global challenges such as(1) safe and efficient navigation and marine operations, (2) efficient oil and hazardous material spill trajectory prediction and clean up, (3) monitoring, predicting and mitigating coastal hazards, (4) military operations, (5) search and rescue, and (6) prediction of harmful algal blooms, hypoxic conditions, and other ecosystem or water quality phenomena.
|Effective start/end date||9/1/08 → 8/31/11|
- National Science Foundation (National Science Foundation (NSF))
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