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

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. • This paper puts forward the application scheme of WIFI location in the sports field. • The scheme of AP signal selection is established. • This paper proposes a new algorithm I-WKNN to improve the positioning accuracy and speed. • The performance of the algorithm is analyzed and compared from the perspective of delay and positioning accuracy. [ABSTRACT FROM AUTHOR]