Projects per year
This project aims to identify and analyse the potential for value creation in the intersection between machine learning and the utility sector, with focus on the water supply sector. The specific areas targeted are: Sewers, drains, climate and streams, wastewater treatment plant, clean water, energy, and software and economy within the water sector.
|Short title||Machine Learning in The Water Sector|
|Effective start/end date||01/01/2019 → 31/12/2021|
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.
- 1 Article in proceeding
Hansen, B. D., Jensen, D. G., Rasmussen, S. H., Tamouk, J., Uggerby, M. & Moeslund, T. B., 2019, IEEE Symposium on Computational Intelligence for Engineering Solutions (IEEE CIES). IEEE, 8 p.
Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review