Fuzzy query processing in wireless sensor networks for Animal Health Monitoring

Abstract

In Wireless Sensor Network (WSN), Fuzzy query processing approach provides common natural language specification of the desired data, eliminating the usage of numerical threshold values as predicates. The fuzzy query results are associated with a degree of membership measurement that indicates how closely each returned data value matches the semantic intent of the fuzzy query, providing applications with additional information that can be used to reason about the query result. Fuzzy queries are applicable for applications that demands single query that can compute values for spatial objects with different threshold values thus reducing message transmission at the sensor network and the post-hoc analysis at the external server. The proposed system can handle different types of fuzzy queries for different scenarios for animal monitoring application. Efficient query processing depends on the routing algorithm used. This work utilizes Minimum Bounding Rectangle (MBR) based routing with static nodes as cluster head and mobile nodes as cluster member to efficiently and reliably disseminate query and retrieve the query results.