If you are a municipal operator dealing with high energy bills and frequent membrane replacements — this project developed a nanoscale sensor system that boosts energy savings by >10% and prolongs membrane lifespan up to 20%.
AI-Powered Nanoscale Sensors to Reduce Desalination Plant Operating Costs and Downtime
Imagine a filter that gets clogged with tiny invisible particles, making it work harder and cost more to run. Instead of guessing when to clean it, this technology acts like a high-definition microscope that watches the clog happen in real-time. It tells the operator exactly when to clean the system, preventing damage and saving energy.
What needed solving
Desalination plants rely on indirect measurements to detect membrane fouling, leading to aggressive cleaning cycles and high energy waste. This results in shortened membrane life and significant economic losses for operators.
What was built
A non-invasive nanoscale sensor system and AI-based software for real-time fouling detection, including a cybersecurity-compliant data acquisition system and user interface.
Who needs this
Who can put this to work
If you are a water producer dealing with expensive chemical cleaning and unplanned shutdowns — this project developed AI-based monitoring that reduces process downtimes up to 60% and decreases cleaning costs by 25%.
If you are a consultancy dealing with inefficient plant productivity for clients — this project developed a non-invasive sensor that surpasses existing sensitivity limits by three orders of magnitude to enable predictive monitoring.
Quick answers
How does this impact operational costs?
The system decreases cleaning costs by 25% and provides energy savings of more than 10%.
What is the industrial scale of the rollout?
The business model anticipates installation in over 666 desalination plants, producing an estimated 25 million m3/day of water by 2030.
Is the technology protected by intellectual property?
Yes, the Excalibur sensor system has a granted patent in the EU.
How does it integrate with existing plant software?
It uses proprietary AI-based software and professionalized data acquisition incorporating cybersecurity measures that follow industry standards.
What is the expected timeline for deployment?
Based on available project data, the project period is from 2025-01-01 to 2026-12-31, with a target market penetration by 2030.
Who built it
The project is led by a single Spanish SME, Ingenious Membranes S.L., which maintains 100% industry control. This lean structure suggests a fast-track commercial focus, as the coordinator is both the technology developer and the entity managing the B2B business model.
Contact Ingenious Membranes S.L. regarding their patented Excalibur sensor system.
Talk to the team behind this work.
Contact us to explore licensing or partnership opportunities with Ingenious Membranes S.L.