Grant Number: 131691 Description: Standard Grant Associated Project: Award Date: 2001-09-18 Award Period: 2001-09-15 to 2003-05-31 Amount: $ 100000.00 Primary Investigator: Paul Flikkema Researchers Paul Flikkema George Koch Thomas Sisk Technology: Biodiversity Data Sharing & Integration Government Domain: Natural Resource Management

Primary Institution:
Northern Arizona Univ

Project Home Page:
http://www.cet.nau.edu/Projects/WNRL

Abstract:
EIA-0131691 Flikkema, Paul Northern Arizona University BDEI: Reconfigurable Wireless Sensor Networks for Dense Spatio-Temporal Environmental Monitoring Summary Improving understanding of ecosystem processes requires the acquisition of multi-component environmental time series at high spatial resolution. Current environmental sensing systems typically rely on stand alone data loggers or wired sensor arrays. Research and resource management that depend on such systems are currently limited by initial cost and/or the effort required to acquire the data. The nexus of this project is to integrate cutting-edge, low-cost circuit and system technology into a wireless environmental sensing network based on an evolvable architecture that will meet an immediate and critical need: to dramatically improve coverage and spatial density while greatly reducing the total cost. This first-generation network will also serve as an experimental testbed for fundamental research in wireless sensor networking that targets the unique characteristics of environmental monitoring applications. This research includes distributed, adaptive source coding of spatio-temporally correlated vector processes, multi-hop protocols with inter-layer interaction, and coded macrodiversity for energy-constrained multi-hop networks. Since this project brings together wireless networking and ecosystems and microclimate researchers, it also provides an opportunity to initiate the development of a new interdisciplinary program of study: Ecosystem Sciences and Informatics. This program will educate a new generation of students who can develop and use technology for ecosystem monitoring and modeling.