CrowdMap: Spatiotemporal Visualization of Anonymous Occupancy Data for Pandemic Response
29th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, SIGSPATIAL 2021
; : 630-633, 2021.
Article
in English
| Scopus | ID: covidwho-1528580
ABSTRACT
CrowdMap is an anonymous occupancy monitoring system developed in response to the COVID-19 pandemic. CrowdMap collects, cleans, and visualizes occupancy data derived from connection logs generated by large arrays of Wi-Fi access points. Thus, CrowdMap is a passive digital tracking tool that can be used to reopen buildings safely, as it helps actively manage occupancy limits and identify utilization trends at scale. Occupancy monitoring is possible at various levels of resolution over large spatial (e.g., from individual rooms to entire buildings) and temporal (e.g., from hours to months) extents. The CrowdMap web-based front-end implements powerful spatiotemporal querying and visualization tools to quickly and effectively explore occupancy patterns throughout large campuses. We will demonstrate CrowdMap and its spatiotemporal GUI that was deployed for an entire university campus with data continuously being collected since summer 2020. © 2021 Owner/Author.
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
29th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, SIGSPATIAL 2021
Year:
2021
Document Type:
Article
Similar
MEDLINE
...
LILACS
LIS