- Full Description
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
Table of Contents
- 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.
- 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.
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