AIS aim is a robotized inclinometer measurement in standard inclinometer boreholes. The deep measurements have multiple applications, including: evaluating the rate of deep-seated ground deformation in landslide areas, evaluating the volume of deep-seated landslides and assessing landslide hazards. The AIS is composed by an electronic control manager, an inclinometer probe and an electric motor equipped with a high precision encoder for handling and continuous control of the probe in the borehole.
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
An interoperable and modular Digital Geospatial Ecosystem (DGE) is proposed, designed, implemented and tested in order to: collect in real time, manage and share geographic data; make usable tools and functionalities to support actions to prevent, monitor and mitigate impacts from extreme events as well as to prepare for and respond to emergency situations. The DGE is composed of the following modules:
The invention concerns an apparatus for measuring the three-dimensional (3-D) sea surface elevation from moving and floating platforms. In particular, the invention consists of two or more synchronized digital video-cameras that frame, from distinct and remote points of view, a common portion of the sea surface. A triangulation process makes it possible to obtain a three-dimensional reconstruction of the sea surface from these images. The invention is particularly suitable for measuring sea waves.
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.