People Crowd Density Estimation System using Deep Learning for Radio Wave Sensing of Cellular Communication

In recent years, research and development of a people flow observation system is attracting attention in various fields (e.g., city area, shopping district) because the directional information of people flow is very useful for various objective (e.g., navigation, evacuation). However, existing studies of the observation system have mainly been utilizing cameras and image analysis techniques for specifying people flow, but the use of cameras is not preferable in actual fields because of the privacy issues.Therefore, in this study, we propose a new people crowd density observation system for people flow observation. In order to avoid privacy issues, the proposed system dmeasures only signal strength of radio waves of the cellular communication. Furthermore, the measurement results are analyzed by utilizing several machine learning techniques so as to estimate crowd density of many people who have a mobile phone or a smartphone.

• Publication year

  2019

• Venue

  Digital Signal Processing and Signal Processing Education Workshop

• Publication date

  2019-02-01

• Fields of study

  Computer Science, Engineering, Environmental Science

• Identifiers
  DOI 10.1109/ICAIIC.2019.8669071
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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