Technologies

The prototype uses soil moisture sensors which, through a measurement of dielectric permittivity, estimate the soil moisture based on which irrigation is started through relay-controlled solenoid valve. The system was developed using Open Source technologies. Specifically, for the hardware components, a small sized board computer Raspberry PI 3B + was used together with a 4G LTE Wi-Fi router and a Modbus rs485 / USB converter.

The Q-PLL is a nonlinear circuit which can maintain a locked state when forced by two incommensurate frequencies.

The locked state is a third frequency parametrically selected among those prescribed by the theory of three-frequency resonances in dynamical systems.

In particular, the locked frequency forms a three-frequency resonance with the frequencies of the quasi- periodic input and is closely related to the pitch perception of complex sound in humans.

AIS aim is a robotized inclinometer measurement in standard inclinometer boreholes. The deep measurements have multiple applications, including: evaluating the rate of deep-seated ground deformation in landslide areas, evaluating the volume of deep-seated landslides and assessing landslide hazards. The AIS is composed by an electronic control manager, an inclinometer probe and an electric motor equipped with a high precision encoder for handling and continuous control of the probe in the borehole.

Network structures that require the use of a common database are affected by the risk of processing identification data that are necessary for sharing information and updating and processing data with equal access level between the network nodes. However, this sharing could lead risks of vulnerability when identification data are exchanged between the nodes of the network. The proposed information system involves the exchange of information by encrypting the identification data with an MD5 Hashing procedure (RFC1321).

Spark anemometry based on the analysis of an electrical discharge can be implemented in the automotive sector through measurements of the secondary circuit voltage. Actual applicability of this method is quite limited, given that it requires additional hardware that is not compatible with space requirements specific for production engines (e.g. fueled with gasoline, LPG or methane); furthermore, applying high voltage measurements is complex and entails increased cost.

This technology is based on an algorithm able to provide the probability of being asthmatic with high accuracy. This probability is based on the evaluation of respiratory function and, specifically, of forced expiratory vital capacity in the first second (FEV₁), in resting conditions, and 20 minutes after administration of a bronchodilator drug.

IMM has developed tactile sensors for the detection of objects and surface and for the handling of objects with humanoid robots (e-skin). These devices can be integrated on ultra-flexible and high conformable substrates and they can be used for multiple applications: 1) for a correct interaction with objects distributed in complex environment; 2) for a safe short-range interaction between humanoid robot and humans; 3) for fabricating smart wearables for the detection of biometric parameters (e.g. heartbeat); 4) for remotely control rovers with wearable gadgets.

uManager is a management game designed to foster the development of young students' entrepreneurial skills and abilities. The game offers the opportunity to manage a tourist village, stimulating the skills of decision making and problem-solving in a simulated scenario adhering to the real one. uManager is suitable for use in the classroom or at a distance, in formal and informal contexts.

This form describes a programmable, autonomous and stand-alone imaging system for the acquisition and processing of images containing subjects whose size is larger than 1cm (e.g. gelatinous zooplankton, fishes, litter, manufacts), form the seafloor or along the water column, in shallow or deep waters. It is capable to recognize and classify the image content through pattern recognition algorithms that combine computer vision and artificial intelligence methodologies.

Environmental monitoring is a rapidly growing field, both in academia and industry. The use of wearables for environmental monitoring is a promising technique, as it allows data to be collected continuously and comprehensively. The main problem with using wearables for environmental monitoring is the size and weight of the system, as well as the high degree of specialization required to develop a fully functional device.