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.
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 - 9 of 9
The proposed technology is based on the micro-fabrication of electrodes in order to generate surface acoustic waves (SAW) with well-defined frequencies, on piezoelectric substrates. The operating principle of a surface acoustic wave sensor is linked to the variation of the characteristics of the acoustic wave that propagates on the device (e.g. wave velocity on the substrate, etc.) caused by the interaction with the environment (e.g. interaction of an analyte on the surface of the device, deformation of the substrate, etc.).
We propose a portable chemical analysis system capable of identifying chemical substances at trace concentrations (sub-ppm), even in case of a complex matrix of interfering species.
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 invention is about the development of a device and its methodology for measuring the active and reactive sound intensity from the impedance computation. The active intensity is calculated directly in the frequency domain multiplying the complex impedance and power spectrum of the air particle velocity. A second line of post-processing is applied to obtain the overall complex sound intensity.
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 technology refers to a system for the safety and control of the mobility of vehicles, pedestrians, and mass transport users, in conventional and advanced contexts and is suitable for use as an infrastructure for the production/sharing of information and data, aimed at monitoring and intervention in critical areas by offering specific functions concerning the detection of potentially dangerous situations or the optimization of resources.
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.