English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The reliability of location information still maintains a crucial impact on restricting the development of location based services in indoor environment. However, in wireless local area network, received signal strength indicator (RSSI) is prone to be interfered by indoor complex environment, resulting in low accuracy and instability of real-time positioning. Here, the new self-adaptive dynamic ranging model-based real-time hybrid algorithm was proposed to realize accurate and undisturbed localization in indoor scenes. A self-adaptive dynamic ranging model was initially constructed to update the environmental parameters and correct the ranging values of mobile terminals in real time. Based on this model, a hybrid KNN algorithm and a hybrid Bayesian algorithm were severally presented. Location fingerprint database and real-time RSSI data of test points were then obtained through data acquisition. Finally, the acquired data was further used to verify the two hybrid algorithms proposed, and compared with the results of several conventional algorithms. As a result, the stability and accuracy of dual hybrid algorithms were better than those of the traditional ones. The range of average location error of both hybrid algorithms maintained 1.26-1.38 m, which was significantly lower than the error level of 2-5 m under the current WLAN environment. This newly proposed hybrid algorithm could effectively improve the stability and accuracy of indoor localization with real-time positioning algorithm, providing a promising solution for RSSI-based indoor positioning system.

Self-Adaptive Dynamic Ranging Model-Based Real-Time Hybrid Algorithm for Accurate Indoor Localization