EconPapers    
Economics at your fingertips  
 

An improved searching algorithm for indoor trajectory reconstruction

Min Li, Jingjing Fu, Yanfang Zhang, Zhujun Zhang, Siye Wang, Huafeng Kong and Rui Mao

International Journal of Distributed Sensor Networks, 2017, vol. 13, issue 11, 1550147717743697

Abstract: Trajectory reconstruction of mobile targets in large-scale infrastructure enables events in a range of applications, such as regional security, tourism, and healthcare, to be visualized. However, indoor environmental factors complicate the reconstruction process, usually resulting in reduced efficiency. In this article, we propose a searching algorithm that aims at a reasonable trajectory reconstruction scheme. The algorithm is developed based on the branch-and-bound method, which incorporates both depth-first search and breadth-first search so that a fast trajectory reconstruction on a topological map becomes viable. Experimental results demonstrated that the considered strategies are effective in accelerating reconstruction through a performance evaluation against current approaches for trajectory reconstruction.

Keywords: Algorithm; brand-and-bound method; depth-first search and breadth-first search; indoor trajectory; Internet of things; topological map (search for similar items in EconPapers)
Date: 2017
References: Add references at CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/1550147717743697 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:13:y:2017:i:11:p:1550147717743697

DOI: 10.1177/1550147717743697

Access Statistics for this article

More articles in International Journal of Distributed Sensor Networks
Bibliographic data for series maintained by SAGE Publications ().

 
Page updated 2025-03-19
Handle: RePEc:sae:intdis:v:13:y:2017:i:11:p:1550147717743697