Technologies

We propose an optical technique for the fast check of the presence, on the exposed surfaces of persons and objects, of explosives and their precursors, or drugs, or in general materials which are not allowed in restricted environments: airports, courts, places of worship, etc. The technique yields bi-dimensional pictures, with exposure time of < 1 sec, reporting the target substances, and their locations and quantities. The technique already provided laboratory preliminary results, to be completed, and fully validated for sensitivity and selectivity.

The development of new materials with near-infrared emission (NIR, 700 – 1000 nm) represent an important target in the technological progress of innovative active components for OLED devices (including flexible ones), surveillance systems, autonomous driving, night vision sensors, fiber optic telecommunications and medical systems. In all these fields it still lacks a commercial NIR-OLED technology.

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.

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 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.