A Privacy-Enabled Platform for COVID-19 Applications

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dc.contributor.authorAugust, Michael
dc.contributor.authorDavison, Christopher
dc.contributor.authorDiallo, Mamadou H
dc.contributor.authorGhosh, Dhrubajyoti
dc.contributor.authorGupta, Peeyush
dc.contributor.authorGraves, Christopher
dc.contributor.authorHan, Shanshan
dc.contributor.authorHolstrom, Michael
dc.contributor.authorKhargonekar, Pramod P
dc.contributor.authorKline, Megan E M
dc.contributor.authorMehrotra, Sharad
dc.contributor.authorSharma, Shantanu
dc.contributor.authorVenkatasubramanian, Nalini
dc.contributor.authorWang, Guoxi
dc.contributor.authorYus, Roberto
dc.date.accessioned2022-06-07T20:16:52Z
dc.date.available2022-06-07T20:16:52Z
dc.date.issued2020-11-16
dc.description.abstractWe 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.en_US
dc.description.sponsorshipThis material is based on research sponsored by DARPA under Agreement No. FA8750-16-2-0021. The U.S. Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright notation thereon. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of DARPA or the U.S. Government. This work is partially supported by NSF Grants No. 1527536, 1545071, 2032525, and 2008993.en_US
dc.description.urihttps://dl.acm.org/doi/10.1145/3384419.3430594en_US
dc.description.urihttps://robertoyus.com/publication/sensys-demo-2020/
dc.description.urihttps://www.youtube.com/watch?v=bEXjw85rh-4&list=PL6jLuiS6wP5a5ugVZaZ2wNpH5e3jWyViU&index=6
dc.format.extent2 pagesen_US
dc.genreconference papers and proceedingsen_US
dc.genrevideorecordingsen_US
dc.identifierdoi:10.13016/m2klkk-jlfh
dc.identifier.citationMichael 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, and Roberto Yus. 2020. A privacy-enabled platform for COVID-19 applications: poster abstract. Proceedings of the 18th Conference on Embedded Networked Sensor Systems. Association for Computing Machinery, New York, NY, USA, 745–746. https://doi.org/10.1145/3384419.3430594en_US
dc.identifier.urihttps://doi.org/10.1145/3384419.3430594
dc.identifier.urihttp://hdl.handle.net/11603/24840
dc.language.isoen_USen_US
dc.publisherACMen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department Collection
dc.rightsThis work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.en_US
dc.rightsPublic Domain Mark 1.0*
dc.rights.urihttp://creativecommons.org/publicdomain/mark/1.0/*
dc.titleA Privacy-Enabled Platform for COVID-19 Applicationsen_US
dc.typeTexten_US
dcterms.creatorhttps://orcid.org/0000-0002-9311-954Xen_US

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