An infrastructure-based interpolation and propagation approach for IoT data analytics
| Autor(en): | Kuemper, D. Toenjes, R. Pulvermueller, E. |
Herausgeber: | Secci, S. Crespi, N. Manzalini, A. |
Stichwörter: | Geo-spatial data; Geospatial model; Infrastructure modeling; Interpolation; Inverse Distance Weighting; IoT; Kriging; OSM; Real-world; Shortest Path; Shortest path, Internet of things; Smart Cities; Smart city, Data analytics | Erscheinungsdatum: | 2017 | Herausgeber: | Institute of Electrical and Electronics Engineers Inc. | Journal: | Proceedings of the 2017 20th Conference on Innovations in Clouds, Internet and Networks, ICIN 2017 | Startseite: | 349 | Seitenende: | 354 | Zusammenfassung: | Interpolation of data in smart city architectures is an eminent task for the provision of reliable services. Furthermore, it is a key functionality for information validation between spatiotemporally related sensors. Nevertheless, many existing projects use a simplified geospatial model that does not take the infrastructure, which affects events and effects in the real world, into account. There are various available algorithms for interpolation and the calculation of routes on infrastructure based graphs and distances on geospatial data. This work proposes a combined approach by interconnecting detailed geospatial data whilst regarding the underlying infrastructure model. © 2017 IEEE. |
Beschreibung: | Conference of 20th Conference on Innovations in Clouds, Internet and Networks, ICIN 2017 ; Conference Date: 7 March 2017 Through 9 March 2017; Conference Code:127386 |
ISBN: | 9781509036721 | DOI: | 10.1109/ICIN.2017.7899439 | Externe URL: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85018900641&doi=10.1109%2fICIN.2017.7899439&partnerID=40&md5=cd8fb03896b67331c1002006d9deeef7 |
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