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.
From the reviews:
In this excellent book, editor Charu C. Aggarwal offers a comprehensive overview of the management and mining of sensor data. The book succeeds in delivering a good balance of breadth versus depth, making it useful for graduate students, researchers, and practitioners & . this book serves as a compact yet authoritative compendium of methods for sensor data collection and mining, with a good balance between theory and practice. I definitely recommendl³n