Managing and Mining Sensor Data

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.

Table of Contents

Chapter 1 An Introduction To Sensor Data Analytics
Chapter 2 A Survey Of Model-Based Sensor Data Acquisition And Management
Chapter 3 Query Processing In Wireless Sensor Networks
Chapter 4 Event Processing In Sensor Streams
Chapter 5 Dimensionality Reduction And Filtering On Time Series Sensor Streams
Chapter 6 Mining Sensor Data Streams
Chapter 7 Real-Time Data Analytics In Sensor Networks
Chapter 8 Distributed Data Mining In Sensor Networks
Chapter 9 Social Sensing
Chapter 10 Sensing For Mobile Objects
Chapter 11 A Survey Of Rfid Data Processing
Chapter 12 The Internet Of Things: A Survey From The Data-Centric Perspective
Chapter 13 A Survey Of Datamining Methods For Sensor Network Bug Diagnosis
Chapter 14 Mining Of Sensor Data In Healthcare: A Survey
Chapter 15 Earth Science Applications Of Sensor Data