Authors: Patricia Morreale, Feng Qi, Paul Croft
Addresses: Department of Computer Science, Kean University, 1000 Morris Avenue, Union, NJ 07083, USA. ' Department of Geology and Meteorology, Kean University, 1000 Morris Avenue, Union, NJ 07083, USA. ' Department of Geology and Meteorology, Kean University, 1000 Morris Avenue, Union, NJ 07083, USA
Abstract: A sensor-based community network for environmental data gathering and predictive analysis has been developed. A mesh network of wireless sensors reports data to a central site for environmental monitoring and risk identification. Data analysis and visual presentation is provided in a geographical and temporal context. This network is considered green due to decreased energy usage by the overall network as well as its actual application, which permits environmental information to be contextually presented and communicated with concerned urban community as well as decision makers. Periodic data reporting from the sensor network, in contrast with the usual timestamp synchronisation, reduces the amount of communication required between network nodes, resulting in an overall energy saving, while not compromising the nature of the data gathered. The sensor network applications provide an outstanding representation of green networking as sparse but sufficient environmental monitoring, accompanied by real-time data analysis, and historical pattern identification permits risk identification in support of public safety and protection.
Keywords: green WSNs; wireless sensor networks; environmental monitoring; risk identification; visualisation; GIS; geographic information systems; environmental data gathering; predictive analysis; energy consumption; energy saving; energy efficiency; green networking; urban sensing networks; wireless networks; public safety.
International Journal of Sensor Networks, 2011 Vol.10 No.1/2, pp.73 - 82
Received: 06 Apr 2010
Accepted: 30 Sep 2010
Published online: 26 Jun 2011 *