Title: Closed-loop architecture for distributed collaborative adaptive sensing of the atmosphere: meteorological command and control

Authors: Michael Zink, Eric Lyons, David Westbrook, Jim Kurose, David L. Pepyne

Addresses: Electrical and Computer Engineering Department, University of Massachusetts, Amherst, MA, USA. ' Computer Science Department, University of Massachusetts, Amherst, MA, USA. ' Computer Science Department, University of Massachusetts, Amherst, MA, USA. ' Computer Science Department, University of Massachusetts, Amherst, MA, USA. ' Electrical and Computer Engineering Department, University of Massachusetts, Amherst, MA, USA

Abstract: Distributed Collaborative Adaptive Sensing (DCAS) of the atmosphere is a new paradigm for detecting and predicting hazardous weather using a dense network of short-range, low-powered radars to sense the lowest few kilometres of the earth|s atmosphere. DCAS systems are collaborative in that the beams from multiple radars are actively coordinated in a sense-and-respond manner to achieve greater sensitivity, precision and resolution than possible with a single radar. DCAS systems are adaptive in that the radars and their associated computing and communications infrastructure are dynamically reconfigured in response to changing weather conditions and end-user needs. This paper describes an end-to-end DCAS architecture and evaluates the performance of the system in an operational testbed with actual weather events and end-user considerations driving the system. Our results demonstrate how the architecture is capable of real-time data processing, optimisation of radar control and sensing of the atmosphere in a manner that maximises end-user utility.

Keywords: closed-loop architecture; adaptive sensing; experimental evaluation; environmental sensor networks; testbed; collaborative sensing; distributed sensing; hazardous weather; multiple radar; atmospheric monitoring; weather conditions; radar control; meterorological conditions.

DOI: 10.1504/IJSNET.2010.031846

International Journal of Sensor Networks, 2010 Vol.7 No.1/2, pp.4 - 18

Available online: 26 Feb 2010 *

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