Wireless Integrated Network Sensors WINS The Web Gets Physical

Gregory J. Pottie Electrical Engineering Department University of California, Los Angeles 

Centralized methods of sensor networking make impractical demands on cable installations and network bandwidth. The burden on communication system components, networks, and human resources can be drastically reduced if raw data are processed at the source and the decisions conveyed. The same holds true for systems with relatively thin communications pipes between a source and the end network or systems with large numbers of devices. The physical world generates an unlimited quantity of data that can be observed, monitored, and controlled, but wireless telecommunications infrastructure are finite. Thus, even as mobile broadband services become available, processing of 

In the next section, I briefly describe some design heuristics. This is followed by a discussion of current research on the deployment of large networks in areas without infrastructure support. The next section focuses on how sensor networks in vehicles can be linked with the Internet. 

Pottie and Kaiser (2000) described some of the fundamental physical constraints on the cost of sensing, detection, communication, and signal processing. They identified five basic design constraints  

For reliable detection in many sitnations, sensors mnst be in close proximity to a physical event (e.g., physical obstmctions to cameras) thus large numbers of sensors may be needed. The type of information obtained with large numbers of sensors is qualitatively different from the information obtained with remote arrays. 

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Wireless Integrated Network Sensors (WINS) The Web Gets Physical... 

Wireless Integrated Network Sensors (WINS) The Web Gets Physical Gregory J. Pottie, University of California, Los Angeles... 

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