Sentaur: Sensor Observable Data Model for Smart Spaces
| dc.contributor.author | Gupta, Peeyush | |
| dc.contributor.author | Mehrotra, Sharad | |
| dc.contributor.author | Mehrotra, Sharad | |
| dc.contributor.author | Yus, Roberto | |
| dc.contributor.author | Venkatasubramanian, Nalini | |
| dc.date.accessioned | 2022-11-10T17:24:31Z | |
| dc.date.available | 2022-11-10T17:24:31Z | |
| dc.date.issued | 2022-10-17 | |
| dc.description | CIKM '22: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, October 2022 | en |
| dc.description.abstract | This paper presents Sentaur, a middleware designed, built, and deployed to support sensor-based smart space analytical applications. Sentaur supports a powerful data model that decouples semantic data (about the application domain) from sensor data (using which the semantic data is derived). By supporting mechanisms to map/translate data, concepts, and queries between the two levels, Sentaur relieves application developers from having to know or reason about either capabilities of sensors or write sensor specific code. This paper describes Sentaur’s data model, its translation strategy, and highlights its benefits through real-world case studies | en |
| dc.description.sponsorship | This work was partially funded by the research sponsored by DARPA under agreement number FA8750-16-2-0021, NSF Grants 1952247, 2133391, 2032525, and 2008993, and UC Office of the President Grant LFR-20-653572 | en |
| dc.description.uri | https://dl.acm.org/doi/abs/10.1145/3511808.3557147 | en |
| dc.format.extent | 10 pages | en |
| dc.genre | conference papers and proceedings | en |
| dc.identifier | doi:10.13016/m27lj0-vcow | |
| dc.identifier.citation | Gupta, Peevish et al. “Sentaur: Sensor Observable Data Model for Smart Spaces.” In Proceedings of the 31st ACM International Conference on Information & Knowledge Management (CIKM ’22) (17 October 2022): 3131–3140. https://doi.org/10.1145/3511808.3557147 | en |
| dc.identifier.uri | https://doi.org/10.1145/3511808.3557147 | |
| dc.identifier.uri | http://hdl.handle.net/11603/26289 | |
| dc.language.iso | en | en |
| dc.publisher | ACM | en |
| dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
| dc.relation.ispartof | UMBC Computer Science and Electrical Engineering Department Collection | |
| dc.relation.ispartof | UMBC Faculty Collection | |
| dc.rights | Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) | * |
| dc.rights | This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author. | en |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc/4.0/ | * |
| dc.subject | UMBC Ebiquity Research Group | |
| dc.title | Sentaur: Sensor Observable Data Model for Smart Spaces | en |
| dc.type | Text | en |
| dcterms.creator | https://orcid.org/0000-0002-9311-954X | en |