By Topic

Demand Forecasting Based on Internet of Things

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Jian-ping Qiu ; Sch. of Comput. Sci., Taiyuan Univ. of Sci. & Technol., Taiyuan, China ; Li-Chao Chen

The advancement of ubiquitous computing technologies, such as wireless networks and mobile devices, has greatly increased the availability of digital information and services in demand forecasting and changed how we access and use them. A kind of technology that extends digital resources to demand forecasting is the Internet of Things, which connects such resources with everyday objects with RFID. This way, real-world objects get digital identities and can then be integrated into a network and associated with digital information or services. These objects can facilitate access to digital resources and support interaction with them, decision makers who wish to make even better decisions based on deeper insight from process innovation as well as right-time analysis of real-time data can use information from tagged objects through mobile devices. In this paper, an algorithm for demand forecasting based on Internet of Things is proposed.

Published in:

Computational Aspects of Social Networks (CASoN), 2010 International Conference on

Date of Conference:

26-28 Sept. 2010