Wlan rss-based fingerprinting for indoor localization: a machine learning inspired bag-of-features approach

HIGHLIGHTS

  • who: Mostafa et al. from the Smart Systems Engineering Lab, College of Engineering, Prince Sultan University have published the article: WLAN RSS-Based Fingerprinting for Indoor Localization: A Machine Learning Inspired Bag-of-Features Approach, in the Journal: Sensors 2022, 22, 5236. of /2022/
  • what: The authors propose a novel machine learning framework consisting of Bag-of-Features and followed by a k-nearest neighbor classifier to categorize the final features into their respective geographical coordinate data. The authors focus on the robustness and distinctiveness of RSS fingerprint data with the support of pre-processing . . .

     

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