Managing and Mining Sensor Data, 2013

Coordinator: Aggarwal Charu C.

Language: English

Approximative price 105.49 €

In Print (Delivery period: 15 days).

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Managing and Mining Sensor Data
Publication date:
Support: Print on demand

Approximative price 105.49 €

In Print (Delivery period: 15 days).

Add to cartAdd to cart
Managing and Mining Sensor Data
Publication date:
534 p. · 15.5x23.5 cm · Hardback

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. 

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.

Structured as a set of survey chapters, the book provides easy access to the material from a vast area in one place

Cross-disciplinary approach with topics related to both data-centric and sensor-centric aspects

Topics include: Stream Management Systems, Event Processing in Sensor Streams, Multimedia Sensor Mining, Social Sensing, Sensing for Mobile Objects