Name
Abstract | ||
|---|---|---|
Inevitably, there will be a huge number of sensor devices within the internet of things (IoT) - but how can we possibly manage to optimise each and every one of them? Our answer is to treat them as autonomous units, much like robots. To this end we have been experimenting with different approaches to find out how constrained devices can benefit from machine learning, so that they can operate optimally. |
Year | Venue | Field |
|---|---|---|
2017 | ERCIM NEWS | Computer science,Internet of Things,Artificial intelligence,Machine learning,Adaptive sensing |
DocType | Volume | Issue |
Journal | 2017 | SP110 |
ISSN | Citations | PageRank |
0926-4981 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Frank Alexander Kraemer | 1 | 262 | 21.13 |
| Nattachart Tamkittikhun | 2 | 24 | 2.10 |
| Anders Eivind Braten | 3 | 27 | 3.87 |