Ebook: Managing and Mining Sensor Data
- Tags: Data Mining and Knowledge Discovery, Database Management, Information Storage and Retrieval, Computer Communication Networks, Information Systems Applications (incl. Internet)
- Year: 2013
- Publisher: Springer US
- Edition: 1
- Language: English
- pdf
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.
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.
Content:
Front Matter....Pages i-xiv
An Introduction to Sensor Data Analytics....Pages 1-8
A Survey of Model-based Sensor Data Acquisition and Management....Pages 9-50
Query Processing in Wireless Sensor Networks....Pages 51-76
Event Processing in Sensor Streams....Pages 77-102
Dimensionality Reduction and Filtering on Time Series Sensor Streams....Pages 103-141
Mining Sensor Data Streams....Pages 143-171
Real-Time Data Analytics in Sensor Networks....Pages 173-210
Distributed Data Mining in Sensor Networks....Pages 211-236
Social Sensing....Pages 237-297
Sensing for Mobile Objects....Pages 299-348
A Survey of RFID Data Processing....Pages 349-382
The Internet of Things: A Survey from the Data-Centric Perspective....Pages 383-428
A Survey of Datamining Methods for Sensor Network Bug Diagnosis....Pages 429-458
Mining of Sensor Data in Healthcare: A Survey....Pages 459-504
Earth Science Applications of Sensor Data....Pages 505-530
Back Matter....Pages 531-534
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.
Content:
Front Matter....Pages i-xiv
An Introduction to Sensor Data Analytics....Pages 1-8
A Survey of Model-based Sensor Data Acquisition and Management....Pages 9-50
Query Processing in Wireless Sensor Networks....Pages 51-76
Event Processing in Sensor Streams....Pages 77-102
Dimensionality Reduction and Filtering on Time Series Sensor Streams....Pages 103-141
Mining Sensor Data Streams....Pages 143-171
Real-Time Data Analytics in Sensor Networks....Pages 173-210
Distributed Data Mining in Sensor Networks....Pages 211-236
Social Sensing....Pages 237-297
Sensing for Mobile Objects....Pages 299-348
A Survey of RFID Data Processing....Pages 349-382
The Internet of Things: A Survey from the Data-Centric Perspective....Pages 383-428
A Survey of Datamining Methods for Sensor Network Bug Diagnosis....Pages 429-458
Mining of Sensor Data in Healthcare: A Survey....Pages 459-504
Earth Science Applications of Sensor Data....Pages 505-530
Back Matter....Pages 531-534
....