On the Pedestrian Flow Analysis through Passive WiFi Sensing

Huang, Baoqi; Li, Xiangyu; Mao, Guoqiang; Jia, Bing; Li, Wuyungerile

doi:10.1109/globecom38437.2019.9013812

Cited by 5 publications

(4 citation statements)

References 20 publications

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“…The utilization of Wi-Fi-based systems for monitoring public transit ridership has been showcased in two notable studies [43] [44]. These works provide valuable insights into accurately assessing passenger flow within the transportation system.…”

Section: A Privacy Concerns In Mac-address Based People Tracking and ...mentioning

confidence: 99%

A Tutorial on Privacy, RCM and Its Implications in WLAN

Ficara,

Garroppo,

Henry

2024

IEEE Commun. Surv. Tutorials

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The proliferation of Wi-Fi devices has led to the rise of privacy concerns related to MAC Address-based systems used for people tracking and localization across various applications, such as smart cities, intelligent transportation systems, and marketing. These systems have highlighted the necessity for mobile device manufacturers to implement Randomized And Changing MAC address (RCM) techniques as a countermeasure for device identification. In response to the challenges posed by diverse RCM implementations, the IEEE has taken steps to standardize RCM operations through the 802.11aq Task Group (TG). However, while RCM implementation addresses some concerns, it can disrupt services that span both Layer 2 and upper-layers, which were originally designed assuming static MAC addresses. To address these challenges, the IEEE has established the 802.11bh TG, focusing on defining new device identification methods, particularly for Layer 2 services that require pre-association identification. Simultaneously, the IETF launched the MAC Address Device Identification for Network and Application Services (MADINAS) Working Group to investigate the repercussions of RCM on upper-layer services, including the Dynamic Host Configuration Protocol (DHCP).Concurrently, derandomization techniques have emerged to counteract RCM defense mechanisms. The exploration of these techniques has suggested the need for a broader privacy enhancement framework for WLANs that goes beyond simple MAC address randomization. These findings have prompted the inception of the 802.11bi TG, which aims to compile an exhaustive list of potential privacy vulnerabilities and prerequisites for a more private IEEE 802.11 standard.In this context, this tutorial aims to provide insights into the motivations behind RCM, its implementation, and its evolution over the years. It elucidates the influence of RCM on network processes and services. Furthermore, the tutorial delves into the recent progress made within the domains of 802.11bh, 802.11bi, and MADINAS. It offers a thorough analysis of the initial work undertaken by these groups, along with an overview of the relevant research challenges. The tutorial objective is to inspire the research community to explore innovative approaches and solutions that contribute to the ongoing efforts to enhance WLAN privacy through standardization initiatives.

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Section: A Privacy Concerns In Mac-address Based People Tracking and ...mentioning

confidence: 99%

A Tutorial on Privacy, RCM and Its Implications in WLAN

Ficara,

Garroppo,

Henry

2024

IEEE Commun. Surv. Tutorials

View full text Add to dashboard Cite

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“…However, OFDM is mainly manifested in the CSI signal as introduced in Subsection 2. SoundSense [73] BodyScope [74] EarSense [75] HearFit [76] Liang and Thomaz [77] DopLink [79] Dolphin [80] SoundWrite [83] LLAP [84] VSkin [81] Vernier [82] UltraGesture [85] RobuCIR [86] Acousticcardiogram [89] Localization and Navigation…”

Section: Orthogonal Frequency Division Multiplexing (Ofdm)mentioning

confidence: 99%

“…SoundWrite [122] and Sound-Write II [83] describe handwritten features using amplitude spectral density and some other acoustic features, such as MFCC, and use KNN to match the captured features with labeled features in the database. Using the ZC sequence, a periodic pulse signal, as the acoustic signal for sensing gestures, VSkin [81] enables touch gesture sensing on all surfaces of the mobile device, not just the touch screen area, by measuring the amplitude and phase, which use structure-borne sound (that is, the sound that travels through the structure of the device) and air-borne sound (that is, the sound that travels through air) to sense finger taps and movements, enabling finegrained gestures on the back of the mobile devices based on induced acoustic signals. Wang et al [123] proposed a dynamic speed warping (DSW) algorithm, based on the observation that the gesture type is determined by the trajectory of the hand component rather than the movement speed, by dynamically scaling the velocity distribution and tracking the movement distance of the trajectory.…”

Section: ) Acoustic: Gesture and Hand Motion Recognition Based On Aco...mentioning

confidence: 99%

“…After obtaining the WiFi or acoustic signal, the next step is to characterize it using various sensing techniques. Similar to WiFi sensing, typical applications based on acoustic sensing include daily actions monitoring [73][74][75][76][77][78] , gesture and hand movements recognition [79][80][81][82][83][84][85][86][87] , health caring [88][89][90][91][92] , localization and navigation [93][94][95][96][97][98] and privacy and security [99][100][101][102][103][104][105][106][107][108][109][110][111] . In the following, we will also introduce the basic content of signals and other characterization methods.…”

Section: Introductionmentioning

confidence: 99%

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Ubiquitous WiFi and Acoustic Sensing: Principles, Technologies, and Applications

Huang

Wang

Zou

et al. 2023

J. Comput. Sci. Technol.

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With the increasing pervasiveness of mobile devices such as smartphones, smart TVs, and wearables, smart sensing, transforming the physical world into digital information based on various sensing medias, has drawn researchers' great attention. Among different sensing medias, WiFi and acoustic signals stand out due to their ubiquity and zero hardware cost. Based on different basic principles, researchers have proposed different technologies for sensing applications with WiFi and acoustic signals covering human activity recognition, motion tracking, indoor localization, health monitoring, and the like. To enable readers to get a comprehensive understanding of ubiquitous wireless sensing, we conduct a survey of existing work to introduce their underlying principles, proposed technologies, and practical applications. Besides we also discuss some open issues of this research area. Our survey reals that as a promising research direction, WiFi and acoustic sensing technologies can bring about fancy applications, but still have limitations in hardware restriction, robustness, and applicability.

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Fusing Directional and Omnidirectional Wi-Fi Antennas for Accurate Indoor Localization

Zhu

Liu

et al. 2021

Wireless Algorithms, Systems, and Applications

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On the Pedestrian Flow Analysis through Passive WiFi Sensing

Cited by 5 publications

References 20 publications

A Tutorial on Privacy, RCM and Its Implications in WLAN

A Tutorial on Privacy, RCM and Its Implications in WLAN

Ubiquitous WiFi and Acoustic Sensing: Principles, Technologies, and Applications

Fusing Directional and Omnidirectional Wi-Fi Antennas for Accurate Indoor Localization

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