WiFlowCount: Device-Free People Flow Counting by Exploiting Doppler Effect in Commodity WiFi

Zhou, Rui; Gong, Ziyuan; Lu, Xiang; Fu, Yang

doi:10.1109/jsyst.2019.2961735

Cited by 12 publications

(2 citation statements)

References 19 publications

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“…Wi-Fi people counting can also be performed through the use of crowd-sourced Wi-Fi smartphone data [26]; this approach circumvents reliance on 'exact location' sensor data and increases count accuracy with additional smartphone data in aggregate. A potential retrofit solution for existing Wi-Fi infrastructure is presented in [27] where Wi-Fi radio signal strength is modulated by the doppler effect; the perceived signal loss and passers-by can be processed by CNNs and interpreted as pedestrians walking past the sensor. Similarly, a device-free crowd counting approach is presented in [28] which also utilises the doppler effect on Wi-Fi signals.…”

Section: Wi-fi/ble Device Monitor 'Sniffer'mentioning

confidence: 99%

“…How often individuals visit a trail can be quantified and allows for analysis of returning visitors, and unique or new visitors can be differentiated. A potential retrofit solution for existing Wi-Fi infrastructure is presented in [27] where Wi-Fi radio signal strength is modulated by the doppler effect; the perceived signal loss and passers-by can be processed by CNNs and interpreted as pedestrians walking past the sensor. Similarly, a device-free crowd counting approach is presented in [28] which also utilises the doppler effect on Wi-Fi signals.…”

Section: Wi-fi/ble Device Monitor 'Sniffer'mentioning

confidence: 99%

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Trailgazers: A Scoping Study of Footfall Sensors to Aid Tourist Trail Management in Ireland and Other Atlantic Areas of Europe

Madden

Ramsey

Loane

et al. 2021

Sensors

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This paper examines the current state of the art of commercially available outdoor footfall sensor technologies and defines individually tailored solutions for the walking trails involved in an ongoing research project. Effective implementation of footfall sensors can facilitate quantitative analysis of user patterns, inform maintenance schedules and assist in achieving management objectives, such as identifying future user trends like cyclo-tourism. This paper is informed by primary research conducted for the EU funded project TrailGazersBid (hereafter referred to as TrailGazers), led by Donegal County Council, and has Sligo County Council and Causeway Coast and Glens Council (NI) among the 10 project partners. The project involves three trails in Ireland and five other trails from Europe for comparison. It incorporates the footfall capture and management experiences of trail management within the EU Atlantic area and desk-based research on current footfall technologies and data capture strategies. We have examined 6 individual types of sensor and discuss the advantages and disadvantages of each. We provide key learnings and insights that can help to inform trail managers on sensor options, along with a decision-making tool based on the key factors of the power source and mounting method. The research findings can also be applied to other outdoor footfall monitoring scenarios.

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Section: Wi-fi/ble Device Monitor 'Sniffer'mentioning

confidence: 99%

Section: Wi-fi/ble Device Monitor 'Sniffer'mentioning

confidence: 99%