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A wireless sensor network can be used to collect and process environmental data, which is often of multivariate nature. This work proposes a multivariate sampling algorithm based on component analysis techniques in wireless sensor networks. To improve the sampling, the algorithm uses component analysis techniques to rank the data. Once ranked, the most representative data is retained. Simulation results...
Wireless sensor networks (WSNs) are an important tool for monitoring distributed remote environments. Faults occurring to sensor nodes are common due to the sensor device itself and the harsh environment where the sensor nodes are deployed. It is well known that the distributed fault detection (DFD)scheme checks out the failed nodes by exchanging data and mutually testing among neighbor nodes in this...
Wireless sensor network is need of present era or advanced technology. In this paper we have presented the details of methodology followed for implementation of a wireless sensor network in a process plant for based solution for data acquisition in a process plant. Due to its specific approach the solution not only acquires the data but also serves very effectively as a maintenance and diagnostic...
Detecting event regions in a monitored environment is a canonical task of wireless sensor networks (WSNs). It is a hard problem because sensor nodes are prone to failures and have scarce energy. In this paper, we seek distributed and localized algorithms for fault-tolerant event region detection. Most existing algorithms only assume that events are spatially correlated, but we argue that events are...
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