**2.3 AI in the monitoring of urban waste**

The monitoring of discharges assumes particular importance in the context of water management, both because it is allowed to obtain useful information along the pipeline in order to evaluate the presence of any illegal connections and illegal discharges and both because it allows modulating the management of the plant's purification as a function of the monitored polluting load and other ancillary parameters. The monitoring of the hydraulic efficiency of the drainage system,

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

the chemical and physical parameters and the functionality of wastewater treatment plants is an important prerequisite for ensuring the smooth operation on environmental, health, a city economic and social.

In this field too, the main applications of AI derive from the presence of sensors and the progress of research. Engineers and chemists have made it possible to develop devices capable of evaluating pollutants present in water such as oils, hydrocarbons and/or derivatives from a qualitative and quantitative point of view (**Figure 2**) [15].

In particular, starting from the acquisition of detailed information on the quality and quantity of wastewater that passes through a sewer section, it is possible to obtain useful data referring to events that characterize the functioning of a wastewater collection system (variations in flow rates and load, anomalous discharges, exceptional meteorological events). On the basis of the data collected from chemical/physical monitoring, with the help of AI, it is possible to develop useful knowledge to build a complete picture on the composition of wastewater, also identifying the presence of inter-correlation between the different parameters and users (private, artisanal or industrial) that contribute to the composition of the wastewater. Elements of innovations and which contribute to confer added value to Artificial Intelligence applications mainly relate to:


The monitoring of sewage discharges and the intelligent management of data with the consequent construction of scenarios, also allows the optimization of biological purification processes also for the purpose of subsequent reuse of the effluent of the purification plants. For example in the agricultural sector, within a broader framework of guaranteeing food safety (ensuring quality agricultural production), reducing hydrological stress in the summer (characterized by scarcity of irrigation water of natural origin), reducing pollution of surface and groundwater (reducing the excess of nutritional elements that flow into the surface water network and decreasing the pollution of the groundwater by nitrates).

The possibility that non-authorized industrial and/or artisanal discharges occur in the sewerage network, with high concentrations of chemical substances, represents a criticality that often occurs and that can affect subsequent purification processes but also of circular economy (both with reference to waters than mud).

In relation to the type, to the masses and concentrations of quests and chemicals, in fact, such recovery processes may be more or less efficient or even be inhibited. The identification and subsequent elimination of unauthorized discharges are therefore essential for the success of nutrient recovery processes and can be carried out through the combination of modeling and qualitative-quantitative monitoring of the sewer network. It should be noted that these discharges have the characteristic of being intermittent and irregular over time and can also occur in points other than those of the production activities that generated them. Their identification is therefore complex and is difficult to detect through ordinary sampling and analysis methods. However, the availability of smart sensors interfaced with AI systems can gradually refine their localization and therefore selectively organize and improve the control activity (also by modifying the location of the sensors) until the exact identification (even in flagrant) of the unloading operations.

Further monitoring element concerns the sediments into the sewer, which is a very important problem because of the considerable hydraulic and environmental uncertainties associated with the deposits. The accumulation of sediments in the sewer can, in fact, cause considerable hydraulic problems connected to the reduction of the flow capacity of the canals and, consequently, to the increase in the risk of flooding in urban areas; it can also be the cause of significant environmental and health problems, due for example to the resuspension from the bottom of the channels of solids and associated pollutants with consequent discharge through the overflow devices during the most intense meteoric events. In addition, phenomena of anaerobic transformation may occur, linked to the establishment of septic conditions within the accumulations of solid material, with the development of corrosive phenomena, but also with the formation and release of toxic substances and bad smells. Furthermore, the development of management methods of sewage sediments that guarantee a regular solid flow to the treatment allows to optimize the management of purification processes and, at the same time, to act on some of the criticalities that are typically induced by the provision of rainwater on the functionality of urban purification plants. Even with reference to these critical issues, AI support can be strategic.
