Digital twins and AI: the future of efficiency and security in seawater desalination plantsWater scarcity remains one of the most urgent global ...
Published by Water Network Research, Official research team of The Water Network
Digital twins and AI: the future of efficiency and security in seawater desalination plants
Water scarcity remains one of the most urgent global challenges, with more than two billion people lacking access to safe drinking water. Seawater desalination, particularly reverse osmosis, has become an indispensable technology to address this crisis. However, desalination plants face two fundamental hurdles: the high energy demand, which can represent up to 70% of operating costs, and their vulnerability as critical infrastructure, making cybersecurity a pressing priority.
Tedagua’s digital twin initiative was designed to confront these challenges directly. The project integrates advanced technologies such as artificial intelligence, Internet of Things (IoT), cloud services, and edge computing to deliver smarter, more secure, and more efficient operations. At the core lies a digital twin enhanced with AI capabilities, capable of simulating, predicting, and optimising desalination processes continuously.
Tedagua’s digital twin initiative aimed to create a standardised technological ecosystem to optimise reverse osmosis desalination plants
Launched under the Red.es 2021 Call for Proposals for R&D projects in artificial intelligence and other digital technologies and their integration into value chains, and co-financed by NextGenerationEU funds, Tedagua’s Digital Twin Platform for Desalination Plants (2022–2024) has demonstrated that efficiency and security can advance hand in hand in critical water infrastructure.
Project objectives and scope
The overarching aim was to create a standardised technological ecosystem to optimise reverse osmosis desalination plants. This ecosystem integrates IoT devices, advanced data analysis tools, evaluation criteria, and operational protocols, ensuring improved efficiency while reinforcing cybersecurity. Real data from several Tedagua desalination plants was used for validation.
The general goal was supported by three interrelated specific objectives:
Advanced artificial intelligence application: Use of machine learning, deep learning, and neural networks for predictive analysis and real-time optimisation, supported by big data technologies, high-performance computing, cloud services, and natural language processing for technical documentation.
Identification of operational improvement points: Systematic detection of optimisation opportunities through detailed process analysis, with emphasis on environmental sustainability, particularly energy consumption, and enhancing cybersecurity.
Development of a continuous improvement philosophy: Establishment of a framework to guide ongoing process evolution across the plant lifecycle, based on identifying complex patterns emerging from continuous data analysis.
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Water scarcity remains one of the most urgent global challenges, with more than two billion people lacking access to safe drinking water. Seawater desalination, particularly reverse osmosis, has become an indispensable technology to address this crisis. However, desalination plants face two fundamental hurdles: the high energy demand, which can represent up to 70% of operating costs, and their vulnerability as critical infrastructure, making cybersecurity a pressing priority.
Tedagua’s digital twin initiative was designed to confront these challenges directly. The project integrates advanced technologies such as artificial intelligence, Internet of Things (IoT), cloud services, and edge computing to deliver smarter, more secure, and more efficient operations. At the core lies a digital twin enhanced with AI capabilities, capable of simulating, predicting, and optimising desalination processes continuously.
Tedagua’s digital twin initiative aimed to create a standardised technological ecosystem to optimise reverse osmosis desalination plants
Launched under the Red.es 2021 Call for Proposals for R&D projects in artificial intelligence and other digital technologies and their integration into value chains, and co-financed by NextGenerationEU funds, Tedagua’s Digital Twin Platform for Desalination Plants (2022–2024) has demonstrated that efficiency and security can advance hand in hand in critical water infrastructure.
Project objectives and scope
The overarching aim was to create a standardised technological ecosystem to optimise reverse osmosis desalination plants. This ecosystem integrates IoT devices, advanced data analysis tools, evaluation criteria, and operational protocols, ensuring improved efficiency while reinforcing cybersecurity. Real data from several Tedagua desalination plants was used for validation.
The general goal was supported by three interrelated specific objectives:
Advanced artificial intelligence application: Use of machine learning, deep learning, and neural networks for predictive analysis and real-time optimisation, supported by big data technologies, high-performance computing, cloud services, and natural language processing for technical documentation.
Identification of operational improvement points: Systematic detection of optimisation opportunities through detailed process analysis, with emphasis on environmental sustainability, particularly energy consumption, and enhancing cybersecurity.
Development of a continuous improvement philosophy: Establishment of a framework to guide ongoing process evolution across the plant lifecycle, based on identifying complex patterns emerging from continuous data analysis.
Anterior
Siguiente
Tags
- Desalination
- Thermal Desalination
- Sustainable Desalination
- Desalination plant operations coordinator
- artificial intelligence
- Digital Transformation