Next Article in Journal
Governing GMOs: The (Counter) Movement for Mandatory and Voluntary Non-GMO Labels
Previous Article in Journal
Teaching Interdisciplinary Sustainability Science Teamwork Skills to Graduate Students Using In-Person and Web-Based Interactions
Article Menu

Export Article

Open AccessArticle
Sustainability 2014, 6(12), 9441-9455; doi:10.3390/su6129441

Enhancing the Sustainability of a Location-Aware Service through Optimization

1
Department of Information Technology, Lingtung University, No. 1, Lingtung Rd, Taichung City 408, Taiwan
2
Department of Industrial Engineering and Systems Management, Feng Chia University, No. 100, Wenhua Rd, Taichung City 407, Taiwan
*
Author to whom correspondence should be addressed.
Received: 26 August 2014 / Revised: 9 December 2014 / Accepted: 15 December 2014 / Published: 18 December 2014
View Full-Text   |   Download PDF [723 KB, uploaded 24 February 2015]   |  

Abstract

A location-aware service (LAS) is an imperative topic in ambient intelligence; an LAS recommends suitable utilities to a user based on the user’s location and context. However, current LASs have several problems, and most of these services do not last. This study proposes an optimization-based approach for enhancing the sustainability of an LAS. In this paper, problems related to optimizing a LAS system are presented. The distinct nature of a LAS optimization problem in comparison with traditional optimization problems is subsequently described. Existing methods applicable to solving a LAS optimization problem are also reviewed. The advantages and disadvantages of each method are then discussed as a motive for combining multiple optimization methods in this study, as illustrated by an example. Finally, opportunities and challenges faced by researchers in this field are presented. View Full-Text
Keywords: location-aware service (LAS); optimization; sustainability; ambient intelligence location-aware service (LAS); optimization; sustainability; ambient intelligence
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Tsai, H.-R.; Chen, T. Enhancing the Sustainability of a Location-Aware Service through Optimization. Sustainability 2014, 6, 9441-9455.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sustainability EISSN 2071-1050 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top