**2.2 Smart devices in the home: data source for AI applications**

The availability of sensors in the home, interfaced via Wi-Fi network to routers or smartphones and computers, allows to acquire important amounts of data that can be used both for the benefit of the individual user, but also and above all for the benefit of the manager, allowing responsible management of consumption, maintenance of the plants and networks as well as the operating pressures in the different time bands.

In addition, the *intelligent* management of water distribution systems allows ample space for the introduction of innovations in the name of water-saving and environmental sustainability, obtaining useful advantages in terms of monitoring and optimization of resources.

Technologies based on microelectronic applications make it possible to create multiple systems of specialized micro and nanosensors, capable of monitoring in realtime the main physic-chemical parameters that establish the characteristics of the water.

Among the many types of sensors available or in advanced development we remember in particular:


The dimensions of these sensors, all of the order of more than a few millimeters, allow them to be installed in smart meters and, in perspective, directly in the flow limiters of the taps according to advantages (water conservation, energy saving) and disadvantages (initial investments, reflective surfaces and extremely bright colors for infrared sensors) [11] also from the point of view of the loss of transmission signals [12].

For data collection, industrial research has already developed numerous types of computational models [13], which, however, are susceptible to important innovations related to the measurement of consumption with quantitative assessments. Sensors installed in the same meters have to transmit data wirelessly to second-level data collection systems, similar to the cells of the cellular telephone network, in turn, connected directly to the data collection and processing network of the water network operator. Similarly, techniques borrowed from artificial intelligence are mature that can allow data to be collected from smart meters to transmit them (after appropriate processing) directly to the network manager, transparently using the decentralized network made up of the smartphones of users who are nearby. This could avoid the implementation of second-level data collection systems, with significant benefits at the level of complexity and overall cost of the system. Such projects, but on a much smaller scale, have already been developed and implemented both in the Netherlands and in Singapore. A Dutch water distributor, has implemented a "*smart grid*" of sensors for real-time monitoring of water quality at a chemical and bacteriological level, considering, in particular, the presence of pesticides, hormones and pharmaceutical products. The sensors are developed are mounted in flow cells crossed by the distribution water. But research continues with the development of increasingly innovative technological solutions and increasingly providing useful information to artificial intelligence systems [14].

The chemical-bacteriological characteristics are monitored in real-time by measuring the change in the refractive index of the water using a laser beam and comparing it with the seasonal reference values for pure water. All this makes it possible to build an "*early warning*" system capable of dealing with water contamination events in real-time within the macroscopic grid made up of the installed sensors. The system incorporates wireless transmission modules that allow to automatically transmit the measured data to the operator. In Singapore, the local water manager, the Public Utility Board (PUB), has also implemented a similar *smart grid* using the same sensors [14].

#### *IoT Applications Computing*

Ultimately, these low-cost *smart devices* make it possible [12] to achieve significant water savings through the active involvement of citizens. These devices, suitably miniaturized and customized, allow total integration with the innovative information transmission systems as well as capturing the energy necessary for self-supply.

These low-cost sensors are born with the aim of connecting element between the *Smart Communities* and the *intelligent government of resources*, allowing each citizen to be an active part in the acquisition of distributed information can be used both directly (through specific *apps*) and both with the mediation of interoperable Artificial Intelligence systems that make it possible to return the information with high added value to managers and citizens.

The implementation of low-cost sensors that can be marketed through distribution channels of simple access, allows reaching citizens in a widespread manner, supporting mechanisms for acquiring information useful both to users/ citizens and to public decision-makers. In this direction, AI systems capable of reading and interpreting large amounts of data from individual users allows *for precision water management* that can be commensurate with each individual user or even aggregated by the district.

The AI System, acquiring information from individual users on a daily basis, is able to identify any anomalies in real-time, signaling possible malfunctions and providing alarm signals. In this direction, AI can be profitably aimed at implementing efficient systems for controlling and reducing water losses both in distribution networks and in the home, favoring technological convergences between the scientific fields of electronics and hydraulics.
