Mammadova, Chinara ; Ben Hmida, Helmi ; Braun, Andreas ; Kuijper, Arjan (2017)
New Approach for Optimizing the Usage of Situation Recognition Algorithms Within IoT Domains.
AmI 2017 - 13th European Conference on Ambient Intelligence. Malaga, Spain (26.04.2017-28.04.2017)
doi: 10.1007/978-3-319-56997-0_15
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
The growth of the Internet of Things (IoT) over the past few years enabled a lot of application domains. Due to the increasing number of IoT connected devices, the amount of generated data is increasing too. Processing huge amounts of data is complex due to the continuously running situation recognition algorithms. To overcome these problems, this paper proposes an approach for optimizing the usage of situation recognition algorithms in Internet of Things domains. The key idea of our approach is to select important data, based on situation recognition purposes, and to execute the situation recognition algorithms after all relevant data have been collected. The main advantage of our approach is that situation recognition algorithms will not be executed each time new data is received, thus allowing the reduction of the situation recognition algorithms execution frequency and saving computational resources.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2017 |
| Autor(en): | Mammadova, Chinara ; Ben Hmida, Helmi ; Braun, Andreas ; Kuijper, Arjan |
| Art des Eintrags: | Bibliographie |
| Titel: | New Approach for Optimizing the Usage of Situation Recognition Algorithms Within IoT Domains |
| Sprache: | Englisch |
| Publikationsjahr: | 2017 |
| Veranstaltungstitel: | AmI 2017 - 13th European Conference on Ambient Intelligence |
| Veranstaltungsort: | Malaga, Spain |
| Veranstaltungsdatum: | 26.04.2017-28.04.2017 |
| DOI: | 10.1007/978-3-319-56997-0_15 |
| URL / URN: | https://link.springer.com/chapter/10.1007%2F978-3-319-56997-... |
| Kurzbeschreibung (Abstract): | The growth of the Internet of Things (IoT) over the past few years enabled a lot of application domains. Due to the increasing number of IoT connected devices, the amount of generated data is increasing too. Processing huge amounts of data is complex due to the continuously running situation recognition algorithms. To overcome these problems, this paper proposes an approach for optimizing the usage of situation recognition algorithms in Internet of Things domains. The key idea of our approach is to select important data, based on situation recognition purposes, and to execute the situation recognition algorithms after all relevant data have been collected. The main advantage of our approach is that situation recognition algorithms will not be executed each time new data is received, thus allowing the reduction of the situation recognition algorithms execution frequency and saving computational resources. |
| Freie Schlagworte: | Internet of things (IoT), Ambient assisted living (AAL), Smart home, Situation analysis, Situation aware assistance, Smart living |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Mathematisches und angewandtes Visual Computing |
| Hinterlegungsdatum: | 04 Mai 2020 12:46 |
| Letzte Änderung: | 04 Mai 2020 12:46 |
| PPN: | |
| Export: | |
| Suche nach Titel in: | TUfind oder in Google |
 |
Frage zum Eintrag |
Optionen (nur für Redakteure)
 |
Redaktionelle Details anzeigen |
Drucken
Impressum