**1. Introduction**

When we talk about Artificial Intelligence, we immediately think of cuttingedge technologies, robots capable of understanding and deciding the actions to be taken and a futuristic world in which machines and humans coexist. In fact, Artificial Intelligence and its use are much more real than one might imagine and are now used in various areas of daily life. In this chapter, we want to discuss the state of the art of the application of artificial intelligence for the management of water resources.

The "White Paper on Artificial Intelligence - A European Approach to Excellence and Trust", COM (2020) 65, highlights how digital technology has improved our lives allowing easier access to knowledge and content. Nowadays, Europe is called to make two transformations (green and digital) which, in the water management sector, could have common objectives: the first requires to take actions towards more sustainable solutions, the second consists in directing the social transformations in such a way that every citizen can take full and maximum benefit. In line with these objectives, the applications of artificial intelligence can contribute to preserving the environment and first of all the most precious resource: water.

Digital and AI are an engine of change that can allow companies to expand and consolidate their competitive positions in international markets in the name of sustainability [1]. The challenges faced in recent months and the Commission's guidelines [2] aim to promote a series of initiatives, both legislative and development programs, to guide our society towards a more modern, equitable model that can exploit better the power of data and AI. One focus will be on extracting hidden information from available data.

The full exploitation of the significant potential of AI in the water sector to process important amounts of data and analyze relationships allows supporting technical and political choices especially during the planning stage. The management of water resources is particularly important also for the protection of the natural biodiversity which expresses a profound complexity, which is reflected in the extraordinary numbers of animal and plant biodiversity and the environmental parameters that our territory records [3]; but also natural and anthropogenic threats touch different levels of scale and complexity, causing alterations and changes in the stability of ecosystems, reducing functionality and resilience. Mathematical and geostatistical tools for the study of environmental complexity represent a fundamental tool for understanding the complexity of processes that can impact on the quality of life, but many times they are not sufficient [4]. Understanding and analyzing the complex and often imperceptible relationships between the environment and health are fully part of the issues that require a joint scientific commitment which, starting from the in-depth examination of each environmental and anthropic component in its complexity numerical, leads to an indispensable multidisciplinary collaboration often difficult to achieve [5]. A multitude of algorithms defined by different expertise and formalized in Artificial Intelligence systems can contribute to overcoming these criticalities [6]. We collectively need integrated analysis strategies of environmental information, which take us beyond the short-term horizon of specific sectoral knowledge, albeit specialized, aiming at the harmony of knowledge to face the challenges of protecting the water resources that impact not positively on the conservation of the environment and the preservation of health. The numbers involved allow us to understand the indispensability of *Big Data* analysis with AI systems: from the 1.000 billion bacterial species that populate the planet and/or our body to the 100.000 chemical compounds that we disperse into the environment and that they reach our organs, to the complexities that each of these elements brings with it individually and in their interaction.

The aforementioned complexity makes the creation of an ecosystem of excellence based on AI extremely positive, capable of introducing scientific innovation that can be transferred to the sector of Public Administration and Companies.

The hope is that the economic support for research can stimulate and reward the excellences present in the territories, determining a distribution growth of the communities on AI. I believe it is appropriate to encourage the use of technologies based on AI in relation to the resolution of application problems in sectors based on regional strategies designed for innovation areas such as "Human health and the environment", as well as "Sustainable manufacturing" with particular attention reference to water management in production processes.

In particular, concerning the theme of "*Human and environmental health"*, Artificial Intelligence can make a decisive contribution in terms of territorial control through automatic image classification systems (*CBIR - Content-Based Image Retrieval System*) that allow using mathematical models, computer implementations of the content of an image, to simulate the principles of the human visual system and to interpret the scenes with a semantics capable of recognizing predefined situations. Such AI applications allow to protect the privacy (as the videos are, in the first instance, analyzed by machines) and to recognize illegal acts such as *spills of wastewater, disposal of waste solids or liquids, picking activities unfair contract* 

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

*and infringements environmental of any kind* that can hurt the environment and in particular on water resources. Similar paths can be used with AI approaches through the application of *semi-automatic Change detection algorithms* functional to the evaluation of territorial transformations, enhancing the significant availability of satellite images acquired by the numerous sensors onboard satellite platforms. In this sense, the environmental and territorial applications affecting the water sector refer to the following areas: illicit disposal, illegal building, land-use change, forest fragmentation, urban growth, loss of agricultural land, availability of resources water supply in lakes and reservoirs, melting of glaciers, the evolution of watercourses, etc.
