Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
CONTROLLED ACCESS GATE
A controlled access entrance gate, comprising a frame or structure (11) that defines an entry area (I1), an exit area (I2) and a transit area (P) of a user (U), a actuation unit (13), which allows the passage of one or more subjects (U), an electronic control unit (14) and a plurality of sensors or cameras (15, 16). The sensors or cameras (15, 16), which can also be used as an independent kit and can be associated with any type of passage or area to be controlled, are suitable for detecting the data relating to the distance (DT) between each sensor (15, 16) and each subject (U) present in the entry area (11) or in the exit area (I2) or in the passage area (P) and the speed, trajectory and tracking parameters of the subject (U). An electronic control unit (14) receives and processes data through interpolation processes and machine-learning and/or deep-learning algorithms, so as to autonomously learn the characteristics of the passage and predict the forms and probabilistic directions of each subject (U) inside the volume corresponding to the entry (I1) and exit (I2) areas and to the transit area (P) of the passage.
CONTROLLED ACCESS GATE
A controlled access entrance gate, comprising a frame or structure (11) that defines an entry area (I1), an exit area (I2) and a transit area (P) of a user (U), a actuation unit (13), which allows the passage of one or more subjects (U), an electronic control unit (14) and a plurality of sensors or cameras (15, 16). The sensors or cameras (15, 16), which can also be used as an independent kit and can be associated with any type of passage or area to be controlled, are suitable for detecting the data relating to the distance (DT) between each sensor (15, 16) and each subject (U) present in the entry area (11) or in the exit area (I2) or in the passage area (P) and the speed, trajectory and tracking parameters of the subject (U). An electronic control unit (14) receives and processes data through interpolation processes and machine-learning and/or deep-learning algorithms, so as to autonomously learn the characteristics of the passage and predict the forms and probabilistic directions of each subject (U) inside the volume corresponding to the entry (I1) and exit (I2) areas and to the transit area (P) of the passage.
CONTROLLED ACCESS GATE
TISO MARCO (Autor:in) / GAMBATO ELISA (Autor:in)
21.07.2022
Patent
Elektronische Ressource
Englisch
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