Forecasting crowd counts with Wi-Fi systems: Univariate, non-seasonal models

JF Determe, U Singh, F Horlin… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Recently, event organizers and researchers have advocated the development of novel
technologies supporting crowd control, notably for public events. This paper presents a …

Enhancing crowd monitoring system functionality through data fusion: Estimating flow rate from wi-fi traces and automated counting system data

DC Duives, T van Oijen, SP Hoogendoorn - Sensors, 2020 - mdpi.com
Crowd monitoring systems (CMSs) provide a state-of-the-art solution to manage crowds
objectively. Most crowd monitoring systems feature one type of sensor, which severely limits …

Crowd forecasting based on wifi sensors and lstm neural networks

U Singh, JF Determe, F Horlin… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
To ensure effective management and security in large-scale public events, it is imperative for
the event organizers to be aware of potentially critical crowd densities. This article, therefore …

A people-counting and speed-estimation system using Wi-Fi signals

L Tian, L Chen, Z Xu, Z Chen - Sensors, 2021 - mdpi.com
Counting the number of people and estimating their walking speeds are essential in crowd
control and flow. In this work, we propose a system that uses prevalent Wi-Fi signals to …

CountMeIn: Adaptive crowd estimation with Wi-Fi in smart cities

G Solmaz, P Baranwal, F Cirillo - 2022 IEEE International …, 2022 - ieeexplore.ieee.org
The widespread use of pervasive sensing technologies such as wireless sensors and street
cameras allows the deployment of crowd estimation solutions in smart cities. However …

Indoor crowd density estimation through mobile smartphone wi-fi probes

X Tang, B Xiao, K Li - IEEE transactions on systems, man, and …, 2018 - ieeexplore.ieee.org
Crowd density estimation is one of the critical issues in social activities. The traditional
solution to this problem is to leverage video surveillance to monitor a crowd. However, this is …

FCCF: Forecasting citywide crowd flows based on big data

MX Hoang, Y Zheng, AK Singh - Proceedings of the 24th ACM …, 2016 - dl.acm.org
Predicting the movement of crowds in a city is strategically important for traffic management,
risk assessment, and public safety. In this paper, we propose predicting two types of flows of …

Comparing deep learning and statistical methods in forecasting crowd distribution from aggregated mobile phone data

A Cecaj, M Lippi, M Mamei, F Zambonelli - Applied Sciences, 2020 - mdpi.com
Accurately forecasting how crowds of people are distributed in urban areas during daily
activities is of key importance for the smart city vision and related applications. In this work …

Towards exploiting Wi-Fi signals from low density infrastructure for crowd estimation

L Tonetto, M Untersperger, J Ott - Proceedings of the 14th Workshop on …, 2019 - dl.acm.org
The ubiquity of wireless devices such as smartphones, tablets and laptops, has enabled
sensing large crowds. This was made possible with numerous methods available that mostly …

Indoor crowd estimation scheme using the number of wi-fi probe requests under mac address randomization

Y Furuya, H Asahina, M Yoshida… - … on Information and …, 2021 - search.ieice.org
As smartphones have become widespread in the past decade, Wi-Fi signal-based crowd
estimation schemes are receiving increased attention. These estimation schemes count the …