Design and Implementation of a Real-Time Crowd Monitoring System Based on Public Wi-Fi Infrastructure: A Case Study on the Sri Chiang Mai Smart City
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Published:2023-03-17
Issue:2
Volume:6
Page:987-1008
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ISSN:2624-6511
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Container-title:Smart Cities
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language:en
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Short-container-title:Smart Cities
Author:
Wiangwiset Thalerngsak1ORCID, Surawanitkun Chayada1ORCID, Wongsinlatam Wullapa1ORCID, Remsungnen Tawun1ORCID, Siritaratiwat Apirat2, Srichan Chavis3, Thepparat Prachya4, Bunsuk Weerasak4, Kaewchan Aekkaphan4, Namvong Ariya1ORCID
Affiliation:
1. Center of Multidisciplinary Innovation Network Talent (MINT Center), Department of Technology and Engineering, Faculty of Interdisciplinary Studies, Nong Khai Campus, Khon Kaen University, Nong Khai 43000, Thailand 2. Department of Electrical Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen 40002, Thailand 3. Department of Computer Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen 40002, Thailand 4. Central Maintenance Sector, National Telecom Public Company Limited, Khon Kaen 40000, Thailand
Abstract
The COVID-19 pandemic has caused significant changes in many aspects of daily life, including learning, working, and communicating. As countries aim to recover their economies, there is an increasing need for smart city solutions, such as crowd monitoring systems, to ensure public safety both during and after the pandemic. This paper presents the design and implementation of a real-time crowd monitoring system using existing public Wi-Fi infrastructure. The proposed system employs a three-tiered architecture, including the sensing domain for data acquisition, the communication domain for data transfer, and the computing domain for data processing, visualization, and analysis. Wi-Fi access points were used as sensors that continuously monitored the crowd and uploaded data to the server. To protect the privacy of the data, encryption algorithms were employed during data transmission. The system was implemented in the Sri Chiang Mai Smart City, where nine Wi-Fi access points were installed in nine different locations along the Mekong River. The system provides real-time crowd density visualizations. Historical data were also collected for the analysis and understanding of urban behaviors. A quantitative evaluation was not feasible due to the uncontrolled environment in public open spaces, but the system was visually evaluated in real-world conditions to assess crowd density, rather than represent the entire population. Overall, the study demonstrates the potential of leveraging existing public Wi-Fi infrastructure for crowd monitoring in uncontrolled, real-world environments. The monitoring system is readily accessible and does not require additional hardware investment or maintenance. The collected dataset is also available for download. In addition to COVID-19 pandemic management, this technology can also assist government policymakers in optimizing the use of public space and urban planning. Real-time crowd density data provided by the system can assist route planners or recommend points of interest, while information on the popularity of tourist destinations enables targeted marketing.
Subject
Electrical and Electronic Engineering,Artificial Intelligence,Urban Studies
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