The development of functional foods is often limited by industrial manufacturing processes, for example, for the production of baked foods, the use of high cooking temperatures causes denaturation of proteins, destruction of vitamins, alteration of fatty acids, etc. The protection of these components is essential in the production of gluten-free foods as they are generally poor in proteins and vitamins.
Technologies
In this section it is possible to view, also through targeted research, the technologies inserted in the PROMO-TT Database. For further information on the technologies and to contact the CNR Research Teams who developed them, it is necessary to contact the Project Manager (see the references at the bottom of each record card).
Displaying results 1 - 4 of 4
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.
We present a new concept of ultra-compact, configurable and implantable brain computer interface (BCI). The device can be applied to monitor or stimulate, with high temporal and spatial accuracy, neural activity of the brain. It allows implementation of closed-loop algorithms in real time applications. The system can be also used in vitro to monitor or induce cell growth or as tDCS tool. The system can be customized (microelectrodes materials and shapes) to guarantee the best solution for the specific application.
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.