Knowledge Discovery from Sensor Data
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advanced sensor data analytics applications
Aggregation Service
anomaly
Anomaly Detection
Anomaly Detection Methods
Case Study
Category=UN
Category=UYQE
Data Set
datasets
detection
distributed data analysis
Dynamic Linear Model
environment
environmental monitoring systems
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eq_computing
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Gps Outage
heterogeneous sensor integration
home
Im En
INESC Porto
ISOMAP
Its
Kalman Filter
Massive Data Streams
METAR Data
Network Load
partially
real-time data mining
relations
Routing Tree
sensor fusion techniques
Sensor Graph
Sensor Networks
Sensor Node
smart
Smart Environment
Smart Home
Spatio Temporal Data Mining
synthetic
Synthetic Datasets
temporal
temporal pattern recognition
Tra Ld
WSN
Product details
- ISBN 9781420082326
- Weight: 544g
- Dimensions: 156 x 234mm
- Publication Date: 10 Dec 2008
- Publisher: Taylor & Francis Inc
- Publication City/Country: US
- Product Form: Hardback
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As sensors become ubiquitous, a set of broad requirements is beginning to emerge across high-priority applications including disaster preparedness and management, adaptability to climate change, national or homeland security, and the management of critical infrastructures. This book presents innovative solutions in offline data mining and real-time analysis of sensor or geographically distributed data. It discusses the challenges and requirements for sensor data based knowledge discovery solutions in high-priority application illustrated with case studies. It explores the fusion between heterogeneous data streams from multiple sensor types and applications in science, engineering, and security.
Auroop R. Ganguly, João Gama, Olufemi A. Omitaomu, Mohamed Medhat Gaber, Ranga Raju Vatsavai
