Technologies

The proposed technology consists of a portable device for monitoring the freshness of fish, based on its smell. The device is based on a gas sensor and pattern recognition software to correlate the sensor signal to the freshness of the food. The technology is designed for its integration into domestic or industrial refrigerators.

Digital Eye is an innovative, rapid and high-precision intelligent computer vision system for the non-destructive and contactless evaluation of quality and shelf-life of whole or fresh-cut fruit and vegetables. It integrates advanced vision and artificial intelligence technologies to estimate parameters useful to evaluate the quality of fruit and vegetables, during both the harvesting phase and the cold chain.

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.

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 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 proposed technology is based on the concept of Power-Over-Fibre (PoF), which involves the transmission of data and power over an optical fiber. This technology is suitable for applications where traditional copper cabling is impractical or undesirable. This is the case with pantographs, where there is a large potential difference between the catenary and the earth, and therefore any electrical contact must be avoided for safety reasons. Furthermore, pantographs operate in an environment with very high electromagnetic interference (EMI).

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 platform allows acquisition of data from commercial and custom sensors. By now, the system has been embedded in a wearable wristband where elastomeric based strain gauge have been integrated to detect fine hand/wrist/arm movements. The platform integrates inertial sensors (accelerometers, gyroscopes) to acquire more details about the subject movements. A sensor-fusion algorithm enables advanced movement recognition (gesture, 3D orientation). A machine-learning algorithm is in development to increase the performance of the platform.

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.

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.

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.