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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
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.