Beschreibung:
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.
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.
