From a Genetic Fuzzy Rule-Based System to a Intelligent Sensor Network

Nowadays, intelligent systems, e.g. fuzzy systems, are being incorporated into sensor networks. In this way, this paper presents an intelligent sensor network which has been developed as a genetic fuzzy rule-based system. The objectives of the present work include: first, the design of the fuzzy rule-based sensor which incorporates a new inference engine specially designed for the intelligent sensor; and, second, the design of an evolutionary algorithm, which is adapted to the sensor and based on genetic algorithm, in order to evolve the knowledge of the system. The sensor network is composed of a computer and a set of sensors. Two possible implementations of the sensor are presented: the first one includes a fuzzy ruled-based sensor; the second implementation is based on a genetic fuzzy rule-based sensor. The sensor network can incorporate expert knowledge and evolve the knowledge bases. This intelligent sensor has been tested using a sensor which is based on an 8051 microcontroller, and an inference engine which has been designed for this sensor. The evolutionary algorithm has been tested using a simulated system. In conclusion, sensor networks can incorporate fuzzy rule-based system and evolutionary algorithms. The former group allows controlling a system by the knowledge base; the latter allows evolving knowledge bases in order to obtain new knowledge.