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.
Kort titelMachine Learning in The Water Sector
Effektiv start/slut dato01/01/201931/12/2021


  • 1 Igangværende

ASIR: Automated Sewer Inspection Robot

Moeslund, T. B., Haurum, J. B., Bahnsen, C. H. & Hansen, B. D.


Projekter: ProjektForskning


  • 1 Konferenceartikel i proceeding

General Sewer Deterioration Model Using Random Forest

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 s.

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review