A privacy-enabled platform for COVID-19 applications: Poster abstract

Michael August, Christopher Davison, Mamadou Diallo, Dhrubajyoti Ghosh, Peeyush Gupta, Christopher Graves, Shanshan Han, Michael Holstrom, Pramod Khargonekar, Megan Kline, Sharad Mehrotra, Shantanu Sharma, Nalini Venkatasubramanian, Guoxi Wang, Roberto Yus

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

We present our experiences in adapting and deploying TIPPERS1, a novel privacy-enabled IoT data collection and management system for smart spaces, to facilitate the monitoring of adherence to COVID-19 regulations in a university campus and a military facility.

Original languageEnglish
Title of host publicationSenSys 2020 - Proceedings of the 2020 18th ACM Conference on Embedded Networked Sensor Systems
PublisherAssociation for Computing Machinery, Inc
Pages745-746
Number of pages2
ISBN (Electronic)9781450375900
DOIs
StatePublished - 16 Nov 2020
Externally publishedYes
Event18th ACM Conference on Embedded Networked Sensor Systems, SenSys 2020 - Virtual, Online, Japan
Duration: 16 Nov 202019 Nov 2020

Publication series

NameSenSys 2020 - Proceedings of the 2020 18th ACM Conference on Embedded Networked Sensor Systems

Conference

Conference18th ACM Conference on Embedded Networked Sensor Systems, SenSys 2020
Country/TerritoryJapan
CityVirtual, Online
Period16/11/2019/11/20

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Computer Networks and Communications

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