Knowledge discovery from sensor data / 
edited by Auroop R. Ganguly. [et al.]. 
 - 1 online resource (xix, 216 pages) 
 - Industrial innovation series .
 - Industrial innovation series. .
<br/><br/> Probabilistic framework for mining distributed sensory data under data sharing constraints /  General framework for mining massive data streams /  Sensor network data model for the discovery of spatio-temporal patterns /  Requirements for clustering streaming sensors /  Principal component aggregation for energy-efficient information extraction in wireless sensor networks /  Anomaly detection in transportation corridors using manifold embedding /  Fusion of vision inertial data for automatic georeferencing /  Electricity load forecast using data streams techniques /  Missing event prediction in sensor data streams using Kalman filters /  Mining temporal relations in smart environment data using TempAl /  Joydeep Ghosh --  Pedro Domingos and Geoff Hulten --  Betsy George, James M. Kang, and Shashi Shekhar --  Pedro Pereira Rodrigues, Joao Gama, and Luis Lopes --  Yann-Ael Le Borgne, Jean-Michel Dricot, and Gianluca Bontempi --  Amrudin Agovic. [et al.] --  Duminda I. B. Randeniya, Manjriker Gunaratne, and Sudeep Sarkar --  Joao Gama and Pedro Pereira Rodriques --  Nithya N. Vijayakumar and Beth Plale --  Vikramaditya R. Jakkula and Diane J. Cook. 
<br/><br/><label>ISBN: </label>9780429143076 
<br/><br/><label>Standard No.: </label>10.1201/9781420082333   doi 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Data mining.<br/>Sensor networks.<br/>Multisensor data fusion.
<br/><br/><label>LC Class. No.: </label>QA76.9.D343  / K564 2009 
<br/><br/><label>Dewey Class. No.: </label>005.74  / K733