LTE-based passive device-free crowd density estimation

Domenico, Simone Di; Sanctis, Mauro De; Cianca, Ernestina; Colucci, Paolo; Bianchi, Giuseppe

doi:10.1109/icc.2017.7997194

Cited by 18 publications

(15 citation statements)

References 11 publications

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“…Most of the works in this field are based on features extracted from WiFi signals in different domains as time correlation and statistics, probability density function, Doppler spectrum, frequency analysis, etc [26]. As a matter of fact, very few scientific works have been focused on features extraction from LTE signals; in [13] the authors have demonstrated for the first time the use of features extracted from LTE signals for density estimation, obtaining very promising results. However, this feasibility study only considers signals with a bandwidth of 1.4 MHz and few people in the room (up to 5).…”

Section: Related Workmentioning

confidence: 99%

“…However, this feasibility study only considers signals with a bandwidth of 1.4 MHz and few people in the room (up to 5). The limited bandwidth that is considered in [13] does not motivate the use of features directly related to the CSI and to the frequency selectivity of the channel. As a matter of fact, in [13] the used features are related to the RSRP.…”

Section: Related Workmentioning

confidence: 99%

“…It is evident that when the number of people is low (e.g. 1-2), the curve is less steep, while when it is high (e.g., [4][5][6][7][8][9][10][11][12][13][14][15][16], the curve is steeper. Therefore, we propose to use as features metrics characterizing the trend of this curve.…”

Section: Feature Extraction From Csi Vector Differences and Svdmentioning

confidence: 99%

“…Authors of [13] have proved the feasibility of a crowd density estimation system based on LTE. In [13], the use of features extracted from the Reference Signal Received Power (RSRP) provides an accuracy of around 80% for a number of people up to 5 and by collecting data from LTE signals of 1.4 MHz of bandwidth. This paper aims to provide a significant step forward with respect to [13] in terms of performance.…”

Section: Introductionmentioning

confidence: 99%

“…In [13], the use of features extracted from the Reference Signal Received Power (RSRP) provides an accuracy of around 80% for a number of people up to 5 and by collecting data from LTE signals of 1.4 MHz of bandwidth. This paper aims to provide a significant step forward with respect to [13] in terms of performance. First of all, LTE signals with a bandwidth of one order of magnitude wider are considered (15 MHz instead of 1.4 MHz).…”

Section: Introductionmentioning

confidence: 99%

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LTE Signals for Device-Free Crowd Density Estimation Through CSI Secant Set and SVD

et al. 2019

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The rising need of crowd monitoring in public spaces, especially for safety purposes, pushes the research community to propose and experiment novel methods of crowd density estimation. This paper focuses on device-free RF sensing, which does not require the monitored people to carry any electronic device. In particular, the paper proposes and assesses the performance of a crowd density estimation system based on the analysis of the variations of Channel State Information (CSI) computed from unencrypted synchronization signals transmitted by a eNodeB and reflected/scattered by people located in the monitored area. The proposed method uses features extracted from the list of singular values of the CSI secant set. This approach allows to reduce the impact of CSI variations due to noise or HW instability, improving the sensitivity to CSI variations caused by human presence. The average accuracy achieved by the proposed approach is 84%, which is comparable with the accuracy achieved with WiFi based crowd density estimation systems.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Feature Extraction From Csi Vector Differences and Svdmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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LTE Signals for Device-Free Crowd Density Estimation Through CSI Secant Set and SVD

et al. 2019

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Indoor occupancy estimation using the LTE-CommSense system

Sardar

Mishra

Khan

2020

International Journal of Remote Sensing

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Retail operations strategy for improved customer experience: a better response to crises such as COVID-19 pandemic

C.V.

2024

JGOSS

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Purpose Discount grocery stores (DGSs) are attractive food supply chain (FSC) channels because many cost-conscious Indians use them for monthly needs. Despite capacity, DGSs must address customer concerns about store crowd densities and improve their COVID-19 preparedness. The purpose of this study is to learn how retail operations strategies can improve customer experience and how stores can benefit. Design/methodology/approach The study looked at a case study where retail operations are run more efficiently, and the customer experience is enhanced by standardizing and customizing customer transactions. The potential benefits that customers and retailers might anticipate are then statistically verified. Next, the potential benefits were examined to determine which ones from customers’ and retailers’ views should be prioritized to increase satisfaction. Findings The case situation analysis in the study demonstrates how DGSs can improve their retail operations to reduce customer wait times and provide greater convenience. The study also provides practitioners with potential benefits to pursue from the perspectives of retailers, customers and both retailers and customers. Research limitations/implications This study requires many past transactions and can be considered an extension of the current study, so it does not capture floor space and capacity improvements. Practical implications This research can help FSC retailers compete with upstream supply chain partners and customers in omnichannel retailing. By improving DGS retailer capacity and customer experience, this study can benefit all FSC stakeholders. Originality/value Although there are numerous potential benefits that practitioners can pursue, the current study suggests that practitioners focus on those that can improve retailer and customer satisfaction.

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LTE-based passive device-free crowd density estimation

Cited by 18 publications

References 11 publications

LTE Signals for Device-Free Crowd Density Estimation Through CSI Secant Set and SVD

LTE Signals for Device-Free Crowd Density Estimation Through CSI Secant Set and SVD

Indoor occupancy estimation using the LTE-CommSense system

Retail operations strategy for improved customer experience: a better response to crises such as COVID-19 pandemic

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