Addressing the Challenges of COVID-19 Social Distancing Through Passive Wi-Fi and Ubiquitous Analytics: A Real-World Deployment
Journal
Proceedings of the International Conference on Human-Computer Interaction
Type
conference paper
Date Issued
2021-09-01
Author(s)
Abstract (De)
During the COVID-19 pandemic, social distancing measures were employed to contain its spread. This paper describes the deployment and testing of a passive Wi-Fi scanning system to help people keep track of crowded spaces, hence complying with social distancing measures. The system is based on passive Wi-Fi sensing to detect human presence in 93 locations around a medium-sized European Touristic Island. This data is then used in website plugins and a mobile application to inform citizens and tourists about the locations’ crowdedness with real-time and historical data. To understand how people react to this type of information, we deployed online questionnaires in situ to collect user insights regarding the usefulness, safety, and privacy concerns. Results show that users considered the occupancy data reported by the system as positively related to their perception. Furthermore, the public display of this data made them feel safer while traveling and planning their commute.
Language
English
Keywords
HCI
Computer Science
Passive Wi-Fi
Survey
Mobile Application
COVID-19
HSG Classification
contribution to scientific community
Publisher
Springer
Event Title
INTERACT International Conference on Human-Computer Interaction
Subject(s)
Division(s)
Eprints ID
265255
File(s)![Thumbnail Image]()
open.access
Name
interact21a-sub1082-cam-i7WithWatermark2_DRAFT.pdf
Size
4.2 MB
Format
Adobe PDF
Checksum (MD5)
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