International journal of advanced smart convergence

The Institute of Internet, Broadcasting and Communication (한국인터넷방송통신학회)
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Estimating Indoor Radio Environment Maps with Mobile Robots and Machine Learning

  • Taewoong, Hwang (Department of Electrical/Electronic and Computer Engineering, University of Ulsan) ;
  • Mario R. Camana, Acosta (Department of Electrical/Electronic and Computer Engineering, University of Ulsan) ;
  • Carla E. Garcia, Moreta (Department of Electrical/Electronic and Computer Engineering, University of Ulsan) ;
  • Insoo, Koo (Department of Electrical/Electronic and Computer Engineering, University of Ulsan)
  • Received : 2023.01.16
  • Accepted : 2023.01.22
  • Published : 2023.03.31
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Abstract

Wireless communication technology is becoming increasingly prevalent in smart factories, but the rise in the number of wireless devices can lead to interference in the ISM band and obstacles like metal blocks within the factory can weaken communication signals, creating radio shadow areas that impede information exchange. Consequently, accurately determining the radio communication coverage range is crucial. To address this issue, a Radio Environment Map (REM) can be used to provide information about the radio environment in a specific area. In this paper, a technique for estimating an indoor REM usinga mobile robot and machine learning methods is introduced. The mobile robot first collects and processes data, including the Received Signal Strength Indicator (RSSI) and location estimation. This data is then used to implement the REM through machine learning regression algorithms such as Extra Tree Regressor, Random Forest Regressor, and Decision Tree Regressor. Furthermore, the numerical and visual performance of REM for each model can be assessed in terms of R2 and Root Mean Square Error (RMSE).

Keywords

Acknowledgement

This work was supported in part by the ICT R&D innovation voucher conducted in 2022 with the support of the Institute of Information and Communications Technology Planning and Evaluation (IITP), funded by the government's Ministry of Science and ICT.(No. 2022-0-00805, Development of wired/wireless communication technology for installation safety communication network for workers in shaded areas of building ships). In addition, this result was supported by the "Regional Innovation Strategy (RIS)" through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (MOE) (2021RIS-003)

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