I-WKNN: Fast-speed and high-accuracy WIFI positioning for intelligent sports stadiums

Zhangzhi Zhao*, Zhengying Lou, Ruibo Wang, Qingyao Li, Xing Xu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Scopus citations


Based on various existing wireless fingerprint location algorithms in intelligent sports venues, a high-precision and fast indoor location algorithm improved weighted k-nearest neighbor (I-WKNN) is proposed. In order to meet the complex environment of sports venues and the demand of high-speed sampling, this paper proposes an AP selection algorithm for offline and online stages. Based on the characteristics of the signal intensity distribution in intelligent venues, an asymmetric Gaussian filter algorithm is proposed. This paper introduces the application of the positioning algorithm in the intelligent stadium system, and completes the data acquisition and real-time positioning of the stadium. Compared with traditional WKNN and KNN algorithms, the I-WKNN algorithm has advantages in fingerprint positioning database processing, environmental noise adaptability, real-time positioning accuracy and positioning speed, etc. The experimental results show that the I-WKNN algorithm has obvious advantages in positioning accuracy and positioning time in a complex noise environment and has obvious application potential in a smart stadium.

Original languageEnglish (US)
Article number107619
JournalComputers and Electrical Engineering
StatePublished - Mar 2022

Bibliographical note

Publisher Copyright:
© 2021 Elsevier Ltd


  • AP selection
  • Asymmetric Gaussian filtering
  • I-WKNN algorithm
  • Intelligent stadium
  • WIFI fingerprint positioning

ASJC Scopus subject areas

  • Control and Systems Engineering
  • General Computer Science
  • Electrical and Electronic Engineering


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