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Smart cities and digitised critical infrastructures require efficient and secure ways to handle volumes of data while ensuring security and integrity of it. Data itself is not the final product but serves as an input for analysis, models, and AI. However, how do we know the datasets used to train the machine learning algorithms or the data forming the baseline for a new policy has not been accidentally or purposely modified?

Last month, we kicked off our NAIADES webinar series with our webinar #1 on IoT Technologies for Smart Water Systems. On the 16.11.2021 a small group of experts – both from the NAIADES project as well as externally – presented the current trends for Smart Water Systems as well as reflected and expressed their constructive point of views on these trends in a panel discussion.

The City Council of Alicante has just made public the Plan for the Smart City Strategy in the coming years, which includes the full-scale implementation of some of the tools developed within the NAIADES project.

The water sector is facing rapid development towards the smart digitalisation of resources, much motivated and supported by the UN’s global initiative for the Sustainable Development Goal 6. In that context, the efforts to address the specific challenges related to water management data and priorities multiply globally.

In the context of the NAIADES project, the Brăila pilot is currently working on robust optimisation. The main objective of this research is to formulate a methodology for the robust optimisation of the quantity and localization of pressure sensors for leak detection. For this, the hydraulic model of the study will be used (.inp format) and for the multiple simulations we will consider a pressure-driven analysis (the demands of the nodes will be a function of the system pressure).

Working on a research project at the European scale with teams spread all over the continent is not a trivial task per se. It is much less so in the COVID era, when physical travel becomes close to impossible and most countries have lockdowns in place. In such a complicated context, the advantages of rapid prototyping and 3d printing become an evidence.

In drinking water supplies systems, water from natural courses is fully treated before being supplied to a distribution system from where it will go to consumers. Water treatments consists in sequential units to eliminate pollutants and pathogens. It usually includes pretreatment; coagulation, flocculation and sedimentation; filtration and disinfection. Performance models can help in understanding and predicting treatments effectiveness, especially in stream events when abstraction water changes like during storms or droughts.

The water consumption prediction has an important place within the water economy. For example, Alicante water utility, in order to be able to distribute potable water to its residents, needs to fill its water tanks. Due to lower energy prices, Alicante water utility is refilling their water tanks over the night – every night. In order to prevent bacteria development in potable water, water needs to be consumed – or disposed (a loss).

The NAIADES project envisions the use of digital innovations for improved water management in three pilots in Europe, Alicante (Spain), Braila (Romania) and Carouge (Switzerland). An important step in the project is the identification of needs and the subsequent definition of use cases. This task, carried out by IHE in collaboration with all the partners in the project, promoted discussions among partners and stakeholders during the first half of the project, which complemented the findings of earlier visits made to the pilots of Alicante and Braila.

Smart Water and Water Treatment applications and services is a critical aspect of the NAIADES project. Towards that direction the adoption of various AI technologies is required for the development of a novel ICT network. Recent advancements in machine learning and deep learning (two main AI technologies) rendered machines capable of performing tasks in tech industry that typically required human intelligence until now.