How SophyAI® works (A.I. & Robotic Platform)
The SophyAI’s neural network can “classify and interpret” if properly trained, a scenario caught from a normal video surveillance camera.
The streaming video, coming from the cameras, are sent to the neural network that, through specific algorithms, identifies particular “objects” of the scene.
In addition to this, a specific geolocation module can identify the correct spatial position of the observed “objects” and transform it into geographic coordinates, representable on any map.
The third component of Cogito, the workflow module, takes care of implement predefined “actions” in relation to the behavior of the classified “objects”. This is a very important function of the system, in fact it allows SophyAI to relate to other systems providing information and commands
Quantity, direction, velocity, and state of “objects” are processed by the workflow module to send information and alerts to operators.
Cogito can also be interconnected with collaborative elements (IOT) present in the observed area, both to improve his understanding of the scene and send automatic commands as: close and open gates, activate fire-fighting systems, change traffic light timing, etc.
The street lighting analyzed by SophyAI®
Through Cameras It is possible to define the operating state of a city lamppost using the “smart” analysis of the light spots.
The neural network can identify if a lamp is working or not.
The localization module defines the spatial position of the lamp failure and places it on a map. The workflow module immediately sends an alert to the maintenance staff and the correct position of the out of order lamp.
This is very useful to know exactly where the failure is located (repairs are not always made immediately, and it is very convenient, for maintainers, know the exact geographic location of the fault, which can be even detected when the lighting network is off, as in daylight hours).
Based on its positioning, a single camera can keep under control different streetlights.
This solution is particularly suitable for those city areas where there are no light poles connected to the network, and where there are no sensors that can determine the lamps status. The SophyAI system allows to significantly reduce the infrastructural costs obtaining substantial advantages for maintainers and citizen.
If the street lampposts are connected to a network and they are equipped with dimmable lamps, they can become a “collaborative” objects (IOT) and the SophyAI’S workflow module can intervene in modulating the light intensity in according to the vehicles or pedestrians presence in the street. This can allow the municipality to substantially reduce the energy expenses for street lighting service.
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