Name
Title | ||
|---|---|---|
Improving Temperature Control in Smart Buildings Based in IoT Network Slicing Technique |
Abstract | ||
|---|---|---|
In smart buildings there are many different types of IoT devices that collect measurements of the environment. These sensors can vary in their characteristics and can also influence the topology of the smart building. For this reason, IoT devices collect heterogeneous measurements. Using complex network and clustering techniques we have designed a new technique that allows to transform heterogeneous data into homogeneous data, this technique is called IoT slicing. This technique consists of creating a graph with the measurements of the IoT network, and virtualizing layers based on the clustering of the graph. To validate the efficiency of this new technique we present the results of a case study using a smart building temperature control algorithm. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/GLOBECOM38437.2019.9013263 | 2019 IEEE Global Communications Conference (GLOBECOM) |
Keywords | Field | DocType |
clustering techniques,complex network,heterogeneous measurements,IoT devices,IoT network slicing technique,smart building temperature control algorithm,IoT slicing,heterogeneous data | Computer science,Internet of Things,Slicing,Temperature control,Real-time computing,Building automation,Embedded system | Conference |
ISSN | ISBN | Citations |
1930-529X | 978-1-7281-0963-3 | 0 |
PageRank | References | Authors |
0.34 | 5 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Roberto Casado-Vara | 1 | 1 | 2.04 |
| Fernando De la Prieta | 2 | 263 | 41.90 |
| Javier Prieto | 3 | 127 | 19.53 |
| J. M. Corchado | 4 | 283 | 14.15 |