Next Article in Journal
Nucleic Acid-based Detection of Bacterial Pathogens Using Integrated Microfluidic Platform Systems
Next Article in Special Issue
Dynamic Hierarchical Sleep Scheduling for Wireless Ad-Hoc Sensor Networks
Previous Article in Journal
Vehicle Based Laser Range Finding in Crops
Previous Article in Special Issue
Monitoring Animal Behaviour and Environmental Interactions Using Wireless Sensor Networks, GPS Collars and Satellite Remote Sensing
Article Menu

Export Article

Open AccessArticle
Sensors 2009, 9(5), 3695-3712;

A Hybrid Stochastic Approach for Self-Location of Wireless Sensors in Indoor Environments

Departamento de Comunicaciones, Universidad Politécnica de Valencia. Camino Vera s/n, 46022, Valencia, Spain
Author to whom correspondence should be addressed.
Received: 2 April 2009 / Revised: 4 May 2009 / Accepted: 14 May 2009 / Published: 15 May 2009
(This article belongs to the Special Issue Wireless Sensor Technologies and Applications)
Full-Text   |   PDF [468 KB, uploaded 21 June 2014]


Indoor location systems, especially those using wireless sensor networks, are used in many application areas. While the need for these systems is widely proven, there is a clear lack of accuracy. Many of the implemented applications have high errors in their location estimation because of the issues arising in the indoor environment. Two different approaches had been proposed using WLAN location systems: on the one hand, the so-called deductive methods take into account the physical properties of signal propagation. These systems require a propagation model, an environment map, and the position of the radio-stations. On the other hand, the so-called inductive methods require a previous training phase where the system learns the received signal strength (RSS) in each location. This phase can be very time consuming. This paper proposes a new stochastic approach which is based on a combination of deductive and inductive methods whereby wireless sensors could determine their positions using WLAN technology inside a floor of a building. Our goal is to reduce the training phase in an indoor environment, but, without an loss of precision. Finally, we compare the measurements taken using our proposed method in a real environment with the measurements taken by other developed systems. Comparisons between the proposed system and other hybrid methods are also provided. View Full-Text
Keywords: indoor location system; positioning system; WLANs indoor location system; positioning system; WLANs
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

Share & Cite This Article

MDPI and ACS Style

Lloret, J.; Tomas, J.; Garcia, M.; Canovas, A. A Hybrid Stochastic Approach for Self-Location of Wireless Sensors in Indoor Environments. Sensors 2009, 9, 3695-3712.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top