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Decision Theory Based Localization Algorithm in Smart Park

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Abstract

The rapid development of the Internet facilitates the transformation to the smart park from the traditional one. The positioning function of the wireless sensor network—one of the solution of the smart park—is facing challenges on the region where a wide variety of environments mix up. And in order to deal with this problem, the paper proposes the localization algorithm based on the decision theory. We process the positional relationship among nodes through the interval type-2 fuzzy theory, use cooperative game theory for reference, and adaptively confirm the degree of importance of each anchor node’s participation in decision-making. Also, underpinned by the constructed knowledge, we rank those reference points and choose the optimum value in the light of the credibility theory. With the simulation experiment on typical application scenes in the smart park, the result shows that the localization algorithm built on the decision theory has quite strong adaptability in different environments.

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Acknowledgements

This work was supported by the Beijing Natural Science Foundation (4142049).

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Authors and Affiliations

  1. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources (North China Electric Power University), Beijing, China

    Yuan He, Liang-rui Tang, Xiang-jun Liu & Shi-yu Ji

Authors
  1. Yuan He
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  2. Liang-rui Tang
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  3. Xiang-jun Liu
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  4. Shi-yu Ji
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Correspondence to Yuan He.

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He, Y., Tang, Lr., Liu, Xj. et al. Decision Theory Based Localization Algorithm in Smart Park. Wireless Pers Commun 100, 1023–1046 (2018). https://doi.org/10.1007/s11277-018-5498-7

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