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A Compact Snake Optimization Algorithm in the Application of WKNN Fingerprint Localization.

Weimin Zheng1, Senyuan Pang1, Ning Liu1

  • 1College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China.

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|July 29, 2023
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Summary
This summary is machine-generated.

This study introduces compact snake optimization (cSO) to improve indoor positioning accuracy. Combining cSO with weighted K-nearest neighbor (WKNN) and RSSI positioning significantly reduces localization errors in challenging indoor environments.

Keywords:
RSSI localizationWKNNcompactsnake optimization

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Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Signal Processing

Background:

  • Indoor localization is crucial but challenging in confined spaces.
  • Weighted K-nearest neighbor (WKNN) enhances localization accuracy.
  • Metaheuristic algorithms offer efficient solutions for complex optimization problems.

Purpose of the Study:

  • To enhance indoor positioning accuracy using metaheuristic algorithms.
  • To introduce and evaluate a novel compact snake optimization (cSO) algorithm.
  • To validate the effectiveness of heuristic algorithms in indoor positioning.

Main Methods:

  • Developed a compact snake optimization (cSO) algorithm, a variant of snake optimization (SO).
  • Evaluated cSO on 28 CEC2013 test functions against other intelligent computing algorithms.
  • Integrated cSO with WKNN fingerprinting and RSSI-based indoor positioning.

Main Results:

  • cSO demonstrated superior performance compared to existing intelligent computing algorithms.
  • The integration of cSO with WKNN and RSSI significantly reduced indoor positioning errors.
  • cSO proved effective in improving localization accuracy in simulations.

Conclusions:

  • The novel cSO algorithm offers an efficient approach for metaheuristic optimization.
  • Combining cSO with WKNN and RSSI positioning is a viable strategy for accurate indoor localization.
  • cSO effectively addresses computational and memory constraints in resource-limited environments.