"Nowadays most of the EU countries treat practically the totality of the volume of urban waste water (WW) generated. However, a deep look at the performance of most of the existing wastewater treatment facilities (WWTP) evidences that significant steps forward can still be given in terms of effluent quality, process robustness and operational costs.
One of the main technical limitations for optimizing plant operation some years ago was the lack of reliable measuring devices. At present, new and more reliable on-line sensors are available and the main limitation for the optimal operation of WWTPs is, clearly, the great difficulty to properly manage all the heterogeneous, incomplete and, sometimes inconsistent data of the WWTPs. WWTPs daily manage thousands of data from all points of the plant. The likelihood that data errors and/or faults occur has consequently highly increased. Also, unexpected situations occurring in the plants make sensors not fully reliable yet sending incorrect data to the data management systems. Using these data for real-time operation and control activities could lead to a drastic deterioration of the wastewater treatment efficiency.
The appropriate processing and management of the data available in a WWTP nowadays exceed the capacity of the staff of the WWTP, limiting the use of the information available for diagnosis and operation tasks. Advanced on-line data fault detection and monitoring tools could alert operators from sensors showing unrealistic or incorrect data whereas, real-time data processing and adequation tools could make data more reliable.
Project DIAMOND aims to achieve a model of excellence in the management of wastewater treatment systems by addressing the design, development, implementation and validation of new advanced data management, monitoring and control algorithms and tools for supporting the optimum operation of WWTPs. This objective is of great interest for the scientific and industrial communities related to WWTPs."
Fields of science
- natural sciencescomputer and information sciencesdata sciencedata processing
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensors
- engineering and technologyenvironmental engineeringwater treatment processeswastewater treatment processes
Call for proposal
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