Water treatment is crucial for a well-functioning and sustainable society. In spite of its importance, the water treatment sector is facing several and significant challenges related to increased requirements for quality, safety and the environment combined with increasing influent and large investment needs for existing facilities. Thus, there is a need for both knowledge-building and innovation to ensure more efficient and optimal operation so 1) the increasing demands can be met, 2) the existing facilities can be exploited to a maximal extent so investments and maintenance can be postponed and/or dispersed over a longer period of time, and 3) the use of chemicals and effluent discharge are minimized. The objective of Invapro is to move the Norwegian water treatment sector towards more optimal, efficient and environmentally friendly operation by exploiting machine learning (ML) and available operational data for increased process knowledge and control of these highly complex and non-linear processes. Previous activities among the project partners confirm that there is a large potential for knowledge and value creation in applying these methods to water treatment processes. Critical R&D challenges in Invapro include integration of existing domain knowledge with data-driven methods to ensure safe, robust and explainable application of data-driven models, and evaluation of benefits and business opportunities enabled by this technology. In particular, Invapro will establish methods, analyses and concrete measures for improved operations of water treatment processes that are of interest both to utility owners and the supplier industry. The project results are expected to improve the competence level in the field among the public sector partners and enhance operation for Norwegian water treatment industry through increased autonomy and knowledge.
Project leader: Hilde Johansen
Category: Øvrige offentlige
Institution: VESTFJORDEN AVLØPSSELSKAP (VEAS)