Technologies

4Ts Game was born in ITD in 2017 to indicate a board game for teacher training, which aims to develop skills in designing collaborative learning activities. The game was originally conceived as a 'tangible' game, consisting of a board and 4 decks of paper cards which contain inputs that guide the teachers/players' design process. Subsequently the game evolved and was developed in its digital version. In this version, developed in Unity and with an underlying knowledge base in Prolog, the game is able to provide feedback to teachers regarding the design/game choices made.

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.

The dramatic global health emergency due to the SARS-CoV-2 pandemic requires new diagnostic devices capable of identifying the presence of virus particles in patient biological samples. In this direction, the development of an innovative low-cost test, which provides the result within a few minutes, which is reproducible and which can reveal the direct presence of even a few viral particles, would be of fundamental importance for the monitoring and containment of the pandemic.

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.

Detection devices for the presence of molecules of interest (analytes) enjoyed a renewed burst with the introduction of biological components (biosensors). Their high specificity is often used in various fields, from environmental monitoring and biomedicine to the protection and promotion of agri-food products. However, the high cost of production and the lack of compatibility with mass sampling (high-throughput) sometimes limit their use.

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 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 proposed technology deals with the development of active SERS (Surface Enhanced Raman Scattering) substrates ad hoc designed for diagnostics of cultural heritage. The substrates are prepared starting from common commercial 'polishing film' sheets (lapping optical fibers) showing an intrinsic roughness (48- 1000 nm) that favors the SERS effect. A pattern of silver or gold nanoparticles are deposited on these films through Pulsed Laser Deposition (PLD).

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 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.