AICGSep 30, 2012

Exhaustive Search-based Model for Hybrid Sensor Network

arXiv:1210.0167v14 citations
Originality Synthesis-oriented
AI Analysis

This addresses safety-critical monitoring in domains like nuclear power plants, but appears incremental as it builds on an extended conventional search algorithm.

The authors proposed a new model for hybrid sensor networks with multiple sub-clusters, specifically targeting early warning systems in large-scale monitoring applications like nuclear power plants. They claim the model achieves high accuracy for real-time safety-critical systems with fewer parameters, though no concrete performance numbers are provided.

A new model for a cluster of hybrid sensors network with multi sub-clusters is proposed. The model is in particular relevant to the early warning system in a large scale monitoring system in, for example, a nuclear power plant. It mainly addresses to a safety critical system which requires real-time processes with high accuracy. The mathematical model is based on the extended conventional search algorithm with certain interactions among the nearest neighborhood of sensors. It is argued that the model could realize a highly accurate decision support system with less number of parameters. A case of one dimensional interaction function is discussed, and a simple algorithm for the model is also given.

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