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 hascreated 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.
Overview
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 hascreated tremendous opportunities in integrating social aspects of sensor data ...