**2. Materials and methods**

#### **2.1 Artificial Intelligence and integrated management of the water cycle**

Water, as a primary source of life and as a natural, cultural, economic and political resource, requires *intelligent management* and the same artificial intelligence can assist in the involvement of the collective intelligence dispersed in citizenship, now evolved into a true *Smart Communities*, to ensure the protection, conservation and rational and optimal use in an *Adaptive Water Management* regime.

The management of water resources requires the formulation of new paradigms capable of combining, on the one hand, the protection of water resources, through new systems and intelligent technologies, capable of increasing the efficiency in the use of resources and the performances of networks and treatment plants present in the territory and on the other hand the development of new monitoring systems distributed and easy to access for widespread control of the quality status. In both cases, the AI plays an extraordinarily important role, especially in the presence of massive amounts of data: an increasingly recurring situation due to the strengthening of water and environmental monitoring systems. The development of interoperable technologies capable of promoting the dissemination and exchange of large volumes of information between decision-makers, managers and citizens, can lead to the creation of *widespread knowledge* capable of feeding artificial intelligence systems and aimed at supporting better environmental protection, ending with a direct impact on the educational and behavioral side. In this direction, the *ubiquity of water*, in every declination of social and productive life, constitutes a natural element to channel information and to consolidate a new culture that can combine the expressions of AI favoring growth, the sharing of structured expert knowledge and not and increasing the sense of belonging to one's territory and to the natural resources it expresses. The recognition of water, as a human right, passes through the acceptance of the sense of widespread (public) ownership and responsibility that must guide both the small daily choices and the big planning, management, political and administrative decisions.

In line with the definitions of the Water Framework Directive 2000/60/EC and the updates in progress, and in general with the articulated Community, national and regional regulatory framework, it is necessary to pursue the objectives of safeguarding, protecting and improving the environmental quality of water bodies, as well as the prudent and rational use of natural resources based on management that is not only sustainable but adaptable to the circumstances that arise also as a result of global changes: all elements of high complexity that find in AI an indispensable ally. In this vision, participatory processes that can also be activated through AI are crucial for triggering paths that lead to the construction of the economic and social vocation of smart cities.

#### *IoT Applications Computing*

The keyword underlying the concept of AI is "*integration*" to be achieved at various levels of knowledge: both in the management of the entire " *water supply chain* " but also with the active involvement of citizens, management bodies, research bodies and universities, companies, supervisory authorities, to achieve management of water resources capable of facing complexities, in line with the needs of environmental sustainability and reduction of impacts.

A correct understanding of the management of water resources can certainly not be limited to the simple government of only one of the components such as, procurement, distribution networks, purification, etc., but it requires a broader perspective that allows the analysis and definition of coordinated and integrated strategies that affect the entire water cycle (**Figure 1**).

Furthermore, even the potentially most efficient strategies have no chance of success if they are not supported by an "awareness" of citizens who must be directly involved as actors within a system that cannot ignore virtuous behavior at the macro level and micro-communities.

It must be emphasized that the constantly growing demographic evolutions, the consequent increased use of the intensification of crops, the effects of climate change with the increase in the frequency of extreme events, determine an extreme urgency in implementing every possible solution (including technological and "intelligent") that can make the resource management system as a whole more efficient, both in quantitative and qualitative terms.

In this context, the research activities on AI that envisage water management in the implementation of environmental policies, in close connection with the Europe 2020 strategy which has identified smart growth, sustainable growth and inclusive growth, as engines of the relaunch of the economy.

#### **Figure 1.**

*Water cycle and pressure factors and areas of application of AI [7]. Legend: 1) climatic change, 2) pollution, 3) physical alterations, 4) over exploitation.*

*Artificial Intelligence and Water Cycle Management DOI: http://dx.doi.org/10.5772/intechopen.97385*

The applications of AI in the water management sector, operating on huge amounts of data, concern the monitoring and management of extreme events also interface with the "*Territory security*" area, while others concern the collection and storage of data, their dissemination and their interoperable using interfaces with the "*Home automation and Smart Grids*" area, in particular concerning aspects relating to the improvement of the quality of life in domestic environments, the reduction of management costs and the transmission of information through *Power Line Communication* (PLC) and their storage using Cloud technology [8].

By way of example, a monitoring system based on AI technologies makes it possible to more effectively target control actions on diffused loads generated as a result of an overflow of the network and on production ones, in order to reduce the presence of metal contaminants and organic and maximize nutrient recovery. The AI itself, combined with innovative devices for controlling the efficiency of urban sewers, allows immediate intervention, reducing the risk of contamination of the unsaturated and groundwater [9]. Precisely for these reasons, these technologies are particularly functional for achieving *good ecological and chemical status* in water bodies, envisaged by the European Directive 2000/60/EC. In response to what is strongly desired by administrators, managers and citizens, the AI itself uses *early warning indicators* that make it possible to identify and suggest mitigation strategies on a local scale of extreme events attributable to natural factors (e.g. climate change and consequent changes in the regime rainfall) or anthropogenic (eg illicit disposal or accidental spills).

AI can be decisive in identifying and managing adaptation guidelines in relation to the climate changes underway. In particular, it can be useful for:

	- **control of leaks,** orienting measurement strategies and priorities and the most effective types of intervention to reduce water dispersion;
	- the definition of **investments in water networks and infrastructures**, supporting a holistic water policy that takes into account an extremely large number of technical, managerial, social and economic variables;
	- the promotion of the **natural conservation of water** by orienting the areas in which to favor it both for employment opportunities and for the reduction of hydraulic risk;
	- **the aggregation** of fragmented **surveillance activities** between the different management and control bodies, also in order to improve the quality and use of information;
	- support **capacities in adapting to extreme climatic events**, in particular as regards the control of floods and drought;
	- **the efficiency of water use in all sectors** and guaranteeing sustainable withdrawal and supply of freshwater also to reduce conflicts of use and to address water scarcity in the short, medium and long term;

As better specified below, in urban and semi-urban areas, AI can also intervene effectively in the urban wastewater purification sector, orienting technological applications to improve the efficiency and versatility of plants and favoring low environmental impact technologies, in terms of occupied surfaces, production of sludge and odor emissions, aimed at maximizing energy recovery and the recovery of raw materials and in particular nutrients and biofuels [10].
