Predictedar
Design and development of an intelligent predictive maintenance system based on artificial intelligence tools for the critical components of urban wastewater treatment plants.
Project description: design and development of an intelligent system for the predictive maintenance of critical components of urban wastewater treatment plants based on artificial intelligence tools. PREDICTEDAR
Geographical area: Seville.
Duration: 1/Jan/2023 – 31/Oct/2024.
Investment: 254,860.00 €.
Co-financing CDTI (51,584.94 €) and ERDF (22,107.83 €).
Results: the circular economy and the sustainable use of resources have been boosted, increasing the valorisation of sludge as agricultural fertiliser by optimising the reliability and availability of the associated subsystem and leading to a reduction in energy consumption that improves the self-sufficiency ratios of a WWTP.
Slogan: EUROPA SE SIENTE
In addition, this project has received funding from the Andalusian Technological Corporation (CTA)
Resulting incentive: 142,937.79
Reimbursable credit (92,909.56 €) and non-refundable funds (50,028.23 €).
Innovation
Integral building system with seismic-resistant capacity, highly industrialised thanks to prefabricated concrete panels.
Innovation
New auscultation system by using virtual sensor technology in railway vehicles.
Innovation
Innovative construction project that uses materials from construction waste in road pavements.
Innovation
A new process for managing green spaces through sensors onboard Unmanned Aerial Vehicles (UAVs).
Innovation
An intelligent system for the automatic application of the BIM methodology in construction.
Innovation
Recovery of reclaim soils degraded by construction activities using sludge from sewage treatment plants and the use of cyanobacteria.
Innovation
Assessment and promotion of ecosystem services provided by urban trees.
Innovation
Application of Artificial Intelligence (AI) to detect pavement incidents for road maintenance.
Innovation
System for monitoring civil engineering infrastructures using SAR satellite images.
