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.).
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 - 6 of 6
Our innovative proposal involves an educational robotics training program, resulting from an experimental research that combines traditional educational approaches with the utilization of robotics. Specifically, the educational robot Thymio, developed by EPFL, serves as a facilitator in the learning process to enhance School Readiness.
The instrumentation is based on the electrical resistivity tomography (ERT) which is a non-invasive geophysical technology used to obtain information on anomalous bodies possibly present in the subsoil. The theoretical basis lies in the different electrical properties of the lithotypes present in the subsoil.
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).
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.