Technologies

The platform allows the deployment of a sensor network with peripheral nodes spread on the crop fields or on the environment for the monitoring of crop parameters/environmental parameters. The network architecture integrated LoRa peripheral nodes for short-medium range communication and star-center NB-IoT based for long range communication. It includes a web server and MySQL database for data storage and visualization. The network architecture is scalable to adapt to the area to monitor.

We developed an hybrid organic-inorganic composite consisting of a 2D perovskite and a copolymer. At room temperature the composite is highly transparent in the visible region with transmittance > 90%. At higher temperatures, the movement of the polymer chains releases the precursors, allowing the perovskite formation, which results in a colored film. The color changes according to the ‘n’ value of the PVK. PVK with n=1 starts coloring at 70°C, achieving a ∆T_max = 91.5% at 510 nm.

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.

The technology refers to a system for the safety and control of the mobility of vehicles, pedestrians, and mass transport users, in conventional and advanced contexts and is suitable for use as an infrastructure for the production/sharing of information and data, aimed at monitoring and intervention in critical areas by offering specific functions concerning the detection of potentially dangerous situations or the optimization of resources.

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.