Journal Homepage: www.ijcst.org

Abstract – Wireless Sensor Networks (WSN) generates a huge amount of data for efficient application of discovering essential knowledge from it is important. Usually, WSN data is generated in streams and forwarded to a sink. Raw data leads to higher communication overhead adversely affecting WSN performance. Association mining processes data to locate frequent patterns. Thus, when association mining is applied to WSN network data only frequent raw data patterns are sent to the sink, thereby reducing communication overhead. This paper proposes mining of WSN data through an association rule to extricate patterns. A Fuzzy based genetic algorithm is used with the rule for efficient extraction of rules from data