Technologies

We propose a compact innovative spectroscopy system operating in the UV range. In the actual version, designed for gas, it exhibits: an aluminium tubular optical chamber (length can be adjusted; currently is 20 cm); a cheap commercial UV LED; a SiC visible blind UV detector designed and manufactured at the CNR-IMM facilities. The team developed also the electronic chain for wireless remote real time read out; while able to deal with pA current levels, it uses very cheap components and construction technology.

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.

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 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.