Yulia Turchin, Avigdor Gal, et al.
DEBS 2009
This work addresses operational management optimization problems in wastewater treatment plants. We developed a novel technology that allows control of such plants, based on real-time sensor readings, with cloud computing at the front end and state-of-the-art operations research and data science algorithms at the back end. We used a constrained Markov decision process as the key optimization framework. We tested our technology in a one-year pilot at a plant in Lleida, Spain, operated by Aqualia, the world's third-largest water company. The results showed a dramatic 13.5 percent general reduction in the plant's electricity consumption, a 14 percent reduction in the amount of chemicals needed to remove phosphorus from the water, and a 17 percent reduction in sludge production. Moreover, results showed a significant improvement in total nitrogen removal, especially in low temperature conditions.
Yulia Turchin, Avigdor Gal, et al.
DEBS 2009
Takayuki Osogami, Segev Wasserkrug, et al.
IJCAI 2023
Ariel Landau, Segev Wasserkrug, et al.
WSC 2004
Sarel Aiber, Dagan Gilat, et al.
ICAC 2004