Managing and Mining Sensor Data

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Aggarwal, Charu C. (Επιμελητής έκδοσης)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Boston, MA : Springer US : Imprint: Springer, 2013.
• Θέματα: Computer science.; Computer communication systems.; Database management.; Data mining.; Information storage and retrieval.; Computer Science.; Data Mining and Knowledge Discovery.; Database Management.; Information Storage and Retrieval.; Computer Communication Networks.; Information Systems Applications (incl. Internet).

 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.