IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

A Framework for Data Warehousing and Mining in Sensor Stream Application Domains

A Framework for Data Warehousing and Mining in Sensor Stream Application Domains
View Sample PDF
Author(s): Nan Jiang (Cedarville University, USA)
Copyright: 2010
Pages: 16
Source title: Movement-Aware Applications for Sustainable Mobility: Technologies and Approaches
Source Author(s)/Editor(s): Monica Wachowicz (Wageningen University of Research Centre for Geo-Information, The Netherlands)
DOI: 10.4018/978-1-61520-769-5.ch016

Purchase

View A Framework for Data Warehousing and Mining in Sensor Stream Application Domains on the publisher's website for pricing and purchasing information.

Abstract

The recent advances in sensor technologies have made these small, tiny devices much cheaper and convenient to use in many different applications, for example, the weather and environmental monitoring applications, the hospital and factory operation sites, sensor devices on the traffic road and moving vehicles and so on. The data collected from sensors forms a sensor stream and is transferred to the server to perform data warehousing and mining tasks for the end user to perform data analysis. Several data preprocessing steps are necessary to enrich the data with domain information for the data warehousing and mining tasks in the sensor stream applications. This chapter presents a general framework for domain-driven mining of sensor stream applications. The proposed framework is able to enrich sensor streams with additional domain information that meets the application requirements. Experimental studies of the proposed framework are performed on real data for two applications: a traffic management and an environmental monitoring site.

Related Content

Sachin Kumar Gupta, Aabid Rashid Wani, Santosh Kumar, Ashutosh Srivastava, Diwankshi Sharma. © 2020. 27 pages.
Samyak Jain, K. Chandrasekaran. © 2020. 37 pages.
Kavi Priya S., Vignesh Saravanan K., Vijayalakshmi K.. © 2020. 29 pages.
Deepti Kakkar, Gurjot Kaur, Parveen Kakkar, Urvashi Sangwan. © 2020. 31 pages.
Ankur Shrivastava, Nitin Gupta, Shreya Srivastav. © 2020. 20 pages.
Nisha Kandhoul, Sanjay K. Dhurandher. © 2020. 24 pages.
Vikash, Lalita Mishra, Shirshu Varma. © 2020. 24 pages.
Body Bottom