Skip to main navigation Skip to search Skip to main content

Wi2DMeasure: WiFi-based 2D Object Size Measurement

  • Xuanzhi Wang
  • , Junzhe Wang
  • , Kai Niu
  • , Jie Xiong
  • , Fusang Zhang
  • , Enze Yi
  • , Anlan Yu
  • , Zhiyun Yao
  • , Daqing Zhang
  • Tsinghua University
  • Beijing Xiaomi Mobile Software Company Ltd.
  • UMass Amherst
  • Institute of Software Chinese Academy of Sciences

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Citations (Scopus)

Abstract

While a large range of sensing applications such as activity sensing and vital sign monitoring have been realized with WiFi sensing, using commercial WiFi devices to obtain fine-grained size information of objects remains challenging due to the narrow bandwidth of WiFi. Very recent studies attempted to measure object sizes using WiFi signals. However, these systems are still far from practical with a lot of limitations including requiring multiple transceiver pairs and can only measure one-dimensional size, hindering their real-life adoption. Also, these systems rely on Channel State Information (CSI) to work, which is only available on few commercial WiFi cards. In this work, we propose to employ a new channel data, i.e., Beamforming Feedback Information (BFI), widely available on almost all new generation WiFi cards for fine-grained size measurement. Through thoroughly analyzing the mathematical relationship between BFI and CSI, we show how to use BFI to achieve fine-grained size measurement. We propose a novel method to accurately measure the two-dimensional size of an object using a single transceiver pair by identifying the positions of singularities when the object passes through the diffraction zone of the transceiver pair. Experiment results show that Wi2DMeasure can accurately measure the two-dimensional size of objects under various conditions, achieving a small median error of only 3.7 mm.

Original languageEnglish
Title of host publicationSenSys 2024 - Proceedings of the 2024 ACM Conference on Embedded Networked Sensor Systems
PublisherAssociation for Computing Machinery, Inc
Pages253-266
Number of pages14
ISBN (Electronic)9798400706974
DOIs
Publication statusPublished - 4 Nov 2024
Event22nd ACM Conference on Embedded Networked Sensor Systems, SenSys 2024 - Hangzhou, China
Duration: 4 Nov 20247 Nov 2024

Publication series

NameSenSys 2024 - Proceedings of the 2024 ACM Conference on Embedded Networked Sensor Systems

Conference

Conference22nd ACM Conference on Embedded Networked Sensor Systems, SenSys 2024
Country/TerritoryChina
CityHangzhou
Period4/11/247/11/24

Keywords

  • BFI
  • CSI
  • diffraction zone
  • size measurement
  • wifi sensing

Fingerprint

Dive into the research topics of 'Wi2DMeasure: WiFi-based 2D Object Size Measurement'. Together they form a unique fingerprint.

Cite this