Sensors 2009, 9(6), 4941-4954; doi:10.3390/s90604941
Article

Improving Temporal Coverage of an Energy-Efficient Data Extraction Algorithm for Environmental Monitoring Using Wireless Sensor Networks

Pervasive Systems Group, Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente, P.O. Box 217, 7500AE, Enschede, The Netherlands
* Author to whom correspondence should be addressed.
Received: 6 March 2009; in revised form: 19 May 2009 / Accepted: 5 June 2009 / Published: 23 June 2009
(This article belongs to the Special Issue Workshop Sensing A Changing World)
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Abstract: Collecting raw data from a wireless sensor network for environmental monitoring applications can be a difficult task due to the high energy consumption involved. This is especially difficult when the application requires specialized sensors that have very high energy consumption, e.g. hydrological sensors for monitoring marine environments. This paper introduces a technique for reducing energy consumption by minimizing sensor sampling operations. In addition, we illustrate how a randomized algorithm can be used to improve temporal coverage such that the time between the occurrence of an event and its detection can be minimized. We evaluate our approach using real data collected from a sensor network deployment on the Great Barrier Reef.
Keywords: wireless sensor networks; environmental monitoring; adaptive sampling

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MDPI and ACS Style

Chatterjea, S.; Havinga, P. Improving Temporal Coverage of an Energy-Efficient Data Extraction Algorithm for Environmental Monitoring Using Wireless Sensor Networks. Sensors 2009, 9, 4941-4954.

AMA Style

Chatterjea S, Havinga P. Improving Temporal Coverage of an Energy-Efficient Data Extraction Algorithm for Environmental Monitoring Using Wireless Sensor Networks. Sensors. 2009; 9(6):4941-4954.

Chicago/Turabian Style

Chatterjea, Supriyo; Havinga, Paul. 2009. "Improving Temporal Coverage of an Energy-Efficient Data Extraction Algorithm for Environmental Monitoring Using Wireless Sensor Networks." Sensors 9, no. 6: 4941-4954.

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