Location Prediction in a Smart Environment

Abstract

The context prediction and especially the location prediction is an important feature for improving the performance of smart systems. Predicting the next location or context of the user make the system proactive, so the system will be capable to offer the suitable services to the user without his involving. In this paper, a new approach will be presented based on the combination of pattern technique and Bayesian network to predict the next location of the user. This approach was tested on real data set, our model was able to achieve 89% of the next location prediction accuracy.

Authors and Affiliations

Wael Ali Alosaimi, Ahmed Binmahfoudh, Roobaea Alroobaea, Atef Zaguia

Keywords

Related Articles

Using the Facebook Iframe as an Effective Tool for Collaborative Learning in Higher Education

Facebook is increasingly becoming a popular senvironment for online learning. Despite the popularity of using Facebook as an e-learning tool, there is a limitation when it comes to presenting content: another platform is...

 Clustering and Bayesian network for image of faces classification

  In a content based image classification system, target images are sorted by feature similarities with respect to the query (CBIR). In this paper, we propose to use new approach combining distance tangent, k-m...

Advanced Personnel Vetting Techniques in Critical Multi-Tennant Hosted Computing Environments

The emergence of cloud computing presents a strategic direction for critical infrastructures and promises to have far-reaching effects on their systems and networks to deliver better outcomes to the nations at a lower co...

An Improved Image Steganography Method Based on LSB Technique with Random Pixel Selection

With the rapid advance in digital network, information technology, digital libraries, and particularly World Wide Web services, many kinds of information could be retrieved any time. Thus, the security issue has become o...

Comparison of Hash Function Algorithms Against Attacks: A Review

Hash functions are considered key components of nearly all cryptographic protocols, as well as of many security applications such as message authentication codes, data integrity, password storage, and random number gener...

Download PDF file
  • EP ID EP498560
  • DOI 10.14569/IJACSA.2019.0100334
  • Views 101
  • Downloads 0

How To Cite

Wael Ali Alosaimi, Ahmed Binmahfoudh, Roobaea Alroobaea, Atef Zaguia (2019). Location Prediction in a Smart Environment. International Journal of Advanced Computer Science & Applications, 10(3), 264-269. https://europub.co.uk/articles/-A-498560