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Domingo-Perez F, Lazaro-Galilea JL, Bravo I, et al. Optimization of the Coverage and Accuracy of an Indoor Positioning System with a Variable Number of Sensors. Sensors (Basel). 2016;16(6)doi: 10.3390/s16060934.
Domingo-Perez, F., Lazaro-Galilea, J. L., Bravo, I., Gardel, A., & Rodriguez, D. (2016). Optimization of the Coverage and Accuracy of an Indoor Positioning System with a Variable Number of Sensors. Sensors (Basel, Switzerland), 16(6), . https://doi.org/10.3390/s16060934
Domingo-Perez, Francisco, et al. "Optimization of the Coverage and Accuracy of an Indoor Positioning System with a Variable Number of Sensors." Sensors (Basel, Switzerland) vol. 16,6 (2016). doi: https://doi.org/10.3390/s16060934
Domingo-Perez F, Lazaro-Galilea JL, Bravo I, Gardel A, Rodriguez D. Optimization of the Coverage and Accuracy of an Indoor Positioning System with a Variable Number of Sensors. Sensors (Basel). 2016 Jun 22;16(6). doi: 10.3390/s16060934. PMID: 27338414; PMCID: PMC4934359.
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Sensors (Basel). 2016 Jun 22;16(6). doi: 10.3390/s16060934.

Optimization of the Coverage and Accuracy of an Indoor Positioning System with a Variable Number of Sensors.

Sensors (Basel, Switzerland)

Francisco Domingo-Perez, Jose Luis Lazaro-Galilea, Ignacio Bravo, Alfredo Gardel, David Rodriguez

Affiliations

  1. Department of Electronics, University of Alcalá, Alcalá de Henares E-28806, Spain. [email protected].
  2. Department of Electronics, University of Alcalá, Alcalá de Henares E-28806, Spain. [email protected].
  3. Department of Electronics, University of Alcalá, Alcalá de Henares E-28806, Spain. [email protected].
  4. Department of Electronics, University of Alcalá, Alcalá de Henares E-28806, Spain. [email protected].
  5. Department of Electronics, University of Alcalá, Alcalá de Henares E-28806, Spain. [email protected].

PMID: 27338414 PMCID: PMC4934359 DOI: 10.3390/s16060934

Abstract

This paper focuses on optimal sensor deployment for indoor localization with a multi-objective evolutionary algorithm. Our goal is to obtain an algorithm to deploy sensors taking the number of sensors, accuracy and coverage into account. Contrary to most works in the literature, we consider the presence of obstacles in the region of interest (ROI) that can cause occlusions between the target and some sensors. In addition, we aim to obtain all of the Pareto optimal solutions regarding the number of sensors, coverage and accuracy. To deal with a variable number of sensors, we add speciation and structural mutations to the well-known non-dominated sorting genetic algorithm (NSGA-II). Speciation allows one to keep the evolution of sensor sets under control and to apply genetic operators to them so that they compete with other sets of the same size. We show some case studies of the sensor placement of an infrared range-difference indoor positioning system with a fairly complex model of the error of the measurements. The results obtained by our algorithm are compared to sensor placement patterns obtained with random deployment to highlight the relevance of using such a deployment algorithm.

Keywords: evolutionary optimization; indoor positioning; multi-objective optimization; range-difference; sensor placement

References

  1. Sensors (Basel). 2011;11(5):5416-38 - PubMed
  2. Sensors (Basel). 2013 Aug 16;13(8):10674-710 - PubMed
  3. Sensors (Basel). 2015 Jul 20;15(7):17572-620 - PubMed

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