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Energy efficiency is a critical factor in wireless sensor networks (WSNs). Understanding how energy is being consumed by sensor nodes allows researchers and practitioners to more effectively evaluate and optimize the development of real-world WSN applications. In WSN deployments for environmental monitoring, the external environment affects the performance of the application, influencing the energy...
In this paper, the ASWP testbed, a long-term wireless sensor network (WSN) deployment for environmental monitoring, is presented. This testbed implements a periodic sampling application for external sensors exposed to a forested outdoor environment in western Pennsylvania, USA. It has been running for the past two years using TinyOS-based WSN platforms and the commercially available routing software...
ASWP testbed, a long-term wireless sensor network (WSN) deployment for environmental monitoring, is presented. This testbed integrates 42 MICAz nodes that implement a periodic sampling application for external sensors exposed to a forested nature reserve at the Audubon Society of Western Pennsylvania (ASWP), USA. It has been running for the past two years using TinyOS-based platforms and the commercially...
In this paper we present a novel systematic approach for inference of missing observations in environmental monitoring wireless sensor networks (WSNs). This capability is important in that it enables sensor networks to effectively estimate the missing data when observation is incomplete to address two critical challenges in WSNs: (1) how to achieve sensor node failure tolerant and robust data collection...
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