Technologies

B-ME developed the first thermoplastic composite electrode film based on bio-derived and biodegradable polyesters and carbon nano-fibers. It is metal-free, highly electrically conductive and possess good thermo-mechanical properties, a challenging combination of three features in a single product. This is the first-of-its-kind product, as, to the best of our knowledge, no thermoplastic biobased electrode film has been effectively produced and used so far.

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 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.

We offer integrated tools for the acquisition, analysis, modelling and optimization of visitor flows in museums characterized by frequent congestion and/or complex geometries. Our intervention is divided into 4 phases:

1) Data acquisition related to the paths followed by visitors in the museum, number of visitors in the rooms, time of permanence, ... The acquisition is performed via a specific IoT system, smartphone app or manual counting.

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.

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.