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Managing and Mining Sensor Data [electronic resource] / edited by Charu C. Aggarwal.

By: Aggarwal, Charu C [editor.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookPublisher: Boston, MA : Springer US : Imprint: Springer, 2013Description: XIV, 534 p. 66 illus., 43 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9781461463092.Subject(s): Computer science | Computer Communication Networks | Database management | Data mining | Information storage and retrieval systems | Computer Science | Data Mining and Knowledge Discovery | Database Management | Information Storage and Retrieval | Computer Communication Networks | Information Systems Applications (incl. Internet)DDC classification: 006.312 Online resources: Click here to access online
Contents:
An Introduction to Sensor Data Analytics -- A Survey of Model-based Sensor Data Acquisition and Management -- Query Processing in Wireless Sensor Networks -- Event Processing in Sensor Streams -- Dimensionality Reduction and Filtering on Time Series Sensor Streams -- Mining Sensor Data Streams -- Real-Time Data Analytics in Sensor Networks -- Distributed Data Mining in Sensor Networks -- Social Sensing -- Sensing for Mobile Objects -- A Survey of RFID Data Processing -- The Internet of Things: A Survey from the Data-Centric Perspective -- Data Mining for Sensor Bug Diagnosis -- Mining of Sensor Data in Healthcare: A Survey -- Earth Science Applications of Sensor Data.
In: Springer eBooksSummary: Advances in hardware technology have lead to an ability to collect data with the use of a variety of sensor technologies. In particular sensor notes have become cheaper and more efficient, and  have even been integrated into day-to-day devices of use, such as mobile phones. This has lead to a much larger scale of applicability and mining of sensor data sets. The human-centric aspect of sensor data has created tremendous opportunities in integrating social aspects of sensor data collection into the mining process.  Managing and Mining Sensor Data is a contributed volume by prominent leaders in this field, targeting advanced-level students in computer science as a secondary text book or reference. Practitioners and researchers working in this field will also find this book useful. 
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An Introduction to Sensor Data Analytics -- A Survey of Model-based Sensor Data Acquisition and Management -- Query Processing in Wireless Sensor Networks -- Event Processing in Sensor Streams -- Dimensionality Reduction and Filtering on Time Series Sensor Streams -- Mining Sensor Data Streams -- Real-Time Data Analytics in Sensor Networks -- Distributed Data Mining in Sensor Networks -- Social Sensing -- Sensing for Mobile Objects -- A Survey of RFID Data Processing -- The Internet of Things: A Survey from the Data-Centric Perspective -- Data Mining for Sensor Bug Diagnosis -- Mining of Sensor Data in Healthcare: A Survey -- Earth Science Applications of Sensor Data.

Advances in hardware technology have lead to an ability to collect data with the use of a variety of sensor technologies. In particular sensor notes have become cheaper and more efficient, and  have even been integrated into day-to-day devices of use, such as mobile phones. This has lead to a much larger scale of applicability and mining of sensor data sets. The human-centric aspect of sensor data has created tremendous opportunities in integrating social aspects of sensor data collection into the mining process.  Managing and Mining Sensor Data is a contributed volume by prominent leaders in this field, targeting advanced-level students in computer science as a secondary text book or reference. Practitioners and researchers working in this field will also find this book useful. 

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