Huang Lin

Huang Lin

Machine Learning Engineer and Researcher working on model development, LLM evaluation, and data analysis.

Two-stage clustering for improved indoor positioning accuracy

Published in Automation in Construction, 2023

Two-stage clustering for improved indoor positioning accuracy preview
Published Automation in Construction

This paper proposes TSCA, a two-stage clustering-based indoor positioning method for complex indoor fingerprint datasets. It first uses the Group Matching Method to divide RSRP data into meaningful groups, then applies KNN-based positioning within the selected group to improve accuracy.

Indoor Localization Machine Learning Clustering KNN RSRP
Paper All Research

Citation

Lin, H., Purmehdi, H., Fei, X., Zhao, Y., Isac, A., Louafi, H., & Peng, W. (2023). Automation in Construction.