Knowledge Discovery from Sensor Data

Editors Ganguly (computational sciences and engineering, Oak Ridge National Laboratory), Gama (LIACC, FEP, U. of Porto, Portugal), Omitaomu (industrial engineering, U. of Tennessee, Knoxville), Gaber (distributed systems and software engineering, Monash U.) and Vatsavai (computer science, U. of Minnesota) present this textbook on offline data mining and real-time analysis of sensor or geographically distributed data for students and practitioners of knowledge modeling in data operations. Contributors describe the requirements for clustering data from sensor streams by using methods currently employed in real-world domains such as national security, resource management, energy distribution and sustainable technologies. The emergence of knowledge discovery from sensor data (Sensor-KDD) as a separate field of study is emphasized, especially since there is currently a lack of a theoretical foundation for such spatio-temporal data. Annotation c2009 Book News, Inc., Portland, OR (booknews.com)