Improving the Science Return from Coastal Sensor Webs Using Autonomous Predictive Control and Resource Management

We describe the use of model predictive control as an integrated framework for optimal resource management in an ocean monitoring and predictive sensor network. The technique is used to adapt the operation of all the sensor and communication resources of the network to changing events in the area being monitored. The optimal control output determines the sampling rates of static sensors, paths of underwater unmanned vehicles, and wireless communication parameters. The system operates on data obtained from a variety of sources including static sensors, unmanned underwater vehicles, and sensors attached to passing cruise ships. Our sensor web adaptive control solution was found to improve the accuracy of event modeling and prediction by 50%. This novel solution is directly applicable to a variety of sensor webs and paves the way for coordinating multiple ground and space assets for faster, better detection, tracking and characterization of earth and extra-terrestrial environments.