multifunctional hardware-software complex that includes open interfaces, the original source code and licenses for the free diffusion of the software. The goal is to carry out a long-term observation of the energy parameters together with the production data, in order to arrive at an evaluation of the energy consumption as well. In addition to the monitoring types just described, there is structural monitoring which, in particular, is the one that has the most significant impact on the protection of human life. It is known in scientific literature by the acronym SHM, which stands for Structural Health Monitoring. It is a central theme because, with a well performed SHM, it is possible not only to monitor, but even \"take care\" of any structure or infrastructure and, indirectly, of those who use it. In general, SHM is implemented through a system composed of a series of nodes containing one or more sensors, a data processing system and a health evaluation system [5]. Ideally, this system should be versatile, timely in information transfer, reliable, capable of extremely accurate readings, easy to manage, capable of easily archiving large amounts of data, very cheap and characterized by a non-destructive approach [6; 7; 8; 9]. However, there is an objective difficulty in developing a system that has all these characteristics. The difficulty lies in the fact that the structures and infrastructures that surround us are extremely heterogeneous both from the point of view of the construction period (dating back to the past centuries or brand new and futuristic) and from the point of view of construction technology (stone walls, masonry in concrete blocks, reinforced concrete, wood, steel) and, therefore, of the particular type and extent of stresses undergone [10]. Obviously, if we wanted to take all these aspects into account in time, we would have to develop an \"ad-hoc\" system for practically each structure. It is therefore necessary to reach a fair compromise, which from time to time responds to the particular contingent needs, which are extremely heterogeneous. For example, on the one hand, it is necessary to respond to the need to implement continuous monitoring over time, to monitor the natural obsolescence of a given structure. The monitoring system, on the other hand, must be able to intervene even suddenly, downstream of an extreme and sudden event (such as an earthquake or a landslide), to determine if there has been damage and to what extent [11]. From what has been said so far, it is clear enough why SHM has become an extremely multidisciplinary topic over the years, and how complex it is to take into account all the variables involved [10]. For example, in [12] a wireless monitoring system of SHM for real-time data acquisition is presented. However, the system has limitations in the ability to synchronize samples but also in the number of sensors itself, which decreases as the sampling rate increases (only 12 sensors for a 100 Hz sampling rate). In [13], however, a wireless monitoring system integrated into the Zhengdian highway bridge is presented. Analog accelerometers are used. Their weakness, however, is the drift of the output due to temperature. Compensation loops are, therefore, needed. Also, results are limited due to noise interference from analog circuits and transmission data losses. In [14], instead, a low-cost WSN for SHM is proposed. The purpose of the system is the identification of the modal frequency. The problem with this system, however, is the synchronization of the samples. In [15], a WSN is presented to monitor wind excitation from a wind turbine tower. The limits of this system are the maximum sampling frequencies (31 Hz) and the maximum nodes (three). Also, synchronization is a critical issue here as well. As for wired SHM systems, on the other hand, [16] presents a wired monitoring system with 64 samples per second without synchronization from each node communicating data through an ethernet connection.