architecture for redundant knowledge reduction in embedded fuzzy rule-based systems into wireless sensor network nodes
Nowadays, growing interest exists in the integration of artificial intelligence technologies into Wireless Sensor Networks. However, little attention has been paid to integrate Fuzzy Rule-Based Systems in these networks. The objective of this work is to optimize the design of embedded Fuzzy Rule-Based Systems by means of redundant knowledge reduction considering the lack of accuracy. Results have shown that a right redundant knowledge reduction produces a great increase in time of battery discharge and a remarkable decrease in battery consumption.
fuzzy rule-based systems wireless sensor networks