A new collaborative knowledge-based approach for wireless sensor networks.
This work presents a new approach for collaboration among sensors in Wireless Sensor Networks. These networks are composed of a large number of sensor nodes with constrained resources: limited computational capability, memory, power sources, etc. Nowadays, there is a growing interest in the integration of Soft Computing technologies into Wireless Sensor Networks. However, little attention has been paid to integrating Fuzzy Rule-Based Systems into collaborative Wireless Sensor Networks. The objective of this work is to design a collaborative knowledge-based network, in which each sensor executes an adapted Fuzzy Rule-Based System, which presents significant advantages such as: experts can define interpretable knowledge with uncertainty and imprecision, collaborative knowledge can be separated from control or modeling knowledge and the collaborative approach may support neighbor sensor failures and communication errors. As a real-world application of this approach, we demonstrate a collaborative modeling system for pests, in which an alarm about the development of olive tree fly is inferred. The results show that knowledge-based sensors are suitable for a wide range of applications and that the behavior of a knowledge-based sensor may be modified by inferences and knowledge of neighbor sensors in order to obtain a more accurate and reliable output.
Telecommunication Department, University of Jaen, Alfonso X El Sabio 28, 23700 Linares, Jaen, Spain. jcbago@ujaen.es
Joaquin
J
Canada-Bago
Jose Angel
JA
Fernandez-Prieto
Manuel Angel
MA
Gadeo-Martos
Juan Ramón
JR
Velasco
D000465:Algorithms; D003195:Computer Communication Networks / Q000295:instrumentation*; D003299:Cooperative Behavior; D011211:Electric Power Supplies; D017143:Fuzzy Logic; D051188:Knowledge Bases; D008954:Models, Biological; D008962:Models, Theoretical; D058998:Remote Sensing Technology / Q000295:instrumentation* / Q000379:methods; D059015:Wireless Technology / Q000295:instrumentation*