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公开(公告)号：US20230252800A1
公开(公告)日：2023-08-10
申请号：US18302979
申请日：2023-04-19
Applicant: Verizon Connect Development Limited
Inventor： Douglas COIMBRA DE ANDRADE , Andrea BENERICETTI , Aurel PJETRI , Leonardo TACCARI , Francesco SAMBO , Alex Quintero GARCIA , Luca BRAVI
CPC classification number: G06V20/59 , G06T7/10 , B60W40/09 , G06N20/00 , B60W50/14 , G06V20/40 , G06V40/172 , G06T2207/20081 , B60W2540/229 , G06T2207/20132 , G06T2207/30201
Abstract: A device may process the video data, with a first machine learning model, to identify a driver of a vehicle and may process the video data associated with the driver, with a second machine learning model, to detect behavior data identifying a behavior of the driver. The device may process the behavior data, with a third machine learning model, to determine distraction data identifying whether the behavior is classified as a distracted behavior. The device may process the behavior data, with a fourth machine learning model, to determine policy compliance data identifying whether the behavior satisfies one or more policies. The device may calculate a distraction score based on the distraction data and the video data, and may calculate a policy compliance score based on the policy compliance data and vehicle data. The device may perform one or more actions based on the distraction score and the policy compliance score.
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公开(公告)号：US20220402505A1
公开(公告)日：2022-12-22
申请号：US17820633
申请日：2022-08-18
Applicant: Verizon Connect Development Limited
Inventor： Matteo SIMONCINI , Douglas COIMBRA DE ANDRADE , Samuele SALTI , Leonardo TACCARI , Fabio SCHOEN , Francesco SAMBO , Leonardo SARTI
Abstract: A maneuver classification platform may obtain video data and telematic data that are associated with a driving event involving a vehicle. The maneuver classification platform may analyze the video data to identify a path of the vehicle along a roadway during the driving event, and based on markings of a plurality of roadways. The maneuver classification platform may analyze the video data to determine a type of a vehicle maneuver performed by the vehicle during the driving event. The maneuver classification platform may determine a maneuver score of the driving event based on the type of the vehicle maneuver, the path of the vehicle, and the telematic data. The maneuver classification platform may send a message associated with the maneuver score and a vehicle identifier of the vehicle to a client device to permit the client device to use the maneuver score.
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公开(公告)号：US20240221358A1
公开(公告)日：2024-07-04
申请号：US18411527
申请日：2024-01-12
Applicant: Verizon Connect Development Limited
Inventor： Luca BRAVI , Luca KUBIN , Leonardo TACCARI , Francesco SAMBO , Matteo SIMONCINI , Douglas COIMBRA DE ANDRADE , Stefano CAPRASECCA
IPC: G06V10/764 , B60Q9/00 , G06F18/21 , G06F18/24 , G06N7/01 , G06N20/00 , G06T7/70 , G06V20/58 , G08G1/052 , B60R11/04 , G05D1/227
CPC classification number: G06V10/764 , B60Q9/00 , G06F18/21 , G06F18/24 , G06N7/01 , G06N20/00 , G06T7/70 , G06V20/582 , G08G1/052 , B60R11/04 , G05D1/227 , G06T2207/20084 , G06T2207/30252
Abstract: A system may determine, for each frame of a plurality of frames of image data associated with a vehicle, a probability that each frame of the plurality of frames that includes an image of a stop sign is relevant to the vehicle. The system may determine a longest sequence of consecutive frames of the plurality of frames for which the probability satisfies a probability threshold. The system may determine a maximum probability associated with a frame included in the longest sequence of consecutive frames. The system may determine a time window based on a time associated with the frame associated with the maximum probability. The system may determine location data and sensor data for the vehicle based on the time window. The system may determine an occurrence of a stop sign violation based on the location data and the sensor data.
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公开(公告)号：US20220067485A1
公开(公告)日：2022-03-03
申请号：US17008398
申请日：2020-08-31
Applicant: Verizon Connect Development Limited
Inventor： Douglas COIMBRA DE ANDRADE , Leonardo TACCARI
Abstract: A device may receive an image. The device may utilize an episodic memory to determine a first classification associated with the image. The device may utilize a semantic memory to determine a second classification associated with the image. The device may determine an accuracy associated with utilizing the semantic memory to determine the second classification. The device may determine that the image is associated with the first classification when the accuracy fails to satisfy a threshold accuracy. The device may determine that the image is associated with the second classification when the accuracy satisfies the threshold accuracy.
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公开(公告)号：US20210365700A1
公开(公告)日：2021-11-25
申请号：US17001161
申请日：2020-08-24
Applicant: Verizon Connect Development Limited
Inventor： Luca BRAVI , Luca KUBIN , Leonardo TACCARI , Francesco SAMBO , Matteo SIMONCINI , Douglas COIMBRA DE ANDRADE , Stefano CAPRASECCA
Abstract: A violation detection platform may obtain image data, location data, and sensor data associated with a vehicle. The violation detection platform may determine a probability that a frame of the image data includes an image of a stop sign. The violation detection platform may determine that the probability satisfies a probability threshold. The violation detection platform may identify location data and sensor data associated with the frame of the image data based on the probability satisfying the probability threshold. The violation detection platform may determine an occurrence of a type of a stop sign violation based on the probability, the location data, and the sensor data. The violation detection platform may perform one or more actions based on determining the occurrence of the type of the stop sign violation.
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Patent Agency Ranking
公开(公告)号：US20220084395A1
公开(公告)日：2022-03-17
申请号：US17456405
申请日：2021-11-24
Applicant: VERIZON CONNECT DEVELOPMENT LIMITED
Inventor： Samuele SALTI , Francesco SAMBO , Leonardo TACCARI , Luca BRAVI , Matteo SIMONCINI , Alessandro LORI
Abstract: A method and system for classifying a vehicle based on low frequency GPS tracks. The method and system comprise retrieving a low frequency GPS track having a sampling interval of at least 20 seconds; deriving additional data from the low frequency GPS track, the additional data including interval speed and instantaneous acceleration of the vehicle; extracting a plurality of data sets from the low frequency GPS track and the additional data; generating a plurality of features from the extracted data sets; and providing the plurality of generated features to a classifier that classifies the vehicle into a predetermined class.
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7.发明申请公开(公告)号：US20210366144A1
公开(公告)日：2021-11-25
申请号：US17001166
申请日：2020-08-24
Applicant: Verizon Connect Development Limited
Inventor： Simone MAGISTRI , Francesco SAMBO , Douglas COIMBRA DE ANDRADE , Fabio SCHOEN , Matteo SIMONCINI , Luca BRAVI , Stefano CAPRASECCA , Luca KUBIN , Leonardo TACCARI
Abstract: A device may receive a first image. The device may process the first image to identify an object in the first image and a location of the object within the first image. The device may extract a second image from the first image based on the location of the object within the first image. The device may process the second image to determine at least one of a coarse-grained viewpoint estimate or a fine-grained viewpoint estimate associated with the object. The device may determine an object viewpoint associated with the second vehicle based on the at least one of the coarse-grained viewpoint estimate or the fine-grained viewpoint estimate. The device may perform one or more actions based on the object viewpoint.
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公开(公告)号：US20210354704A1
公开(公告)日：2021-11-18
申请号：US16947918
申请日：2020-08-24
Applicant: Verizon Connect Development Limited
Inventor： Matteo SIMONCINI , Douglas COIMBRA DE ANDRADE , Samuele SALTI , Leonardo TACCARI , Fabio SCHOEN , Francesco SAMBO , Leonardo SARTI
Abstract: A maneuver classification platform may obtain video data and telematic data that are associated with a driving event involving a vehicle. The maneuver classification platform may analyze the video data to identify a path of the vehicle along a roadway during the driving event, and based on markings of a plurality of roadways. The maneuver classification platform may analyze the video data to determine a type of a vehicle maneuver performed by the vehicle during the driving event. The maneuver classification platform may determine a maneuver score of the driving event based on the type of the vehicle maneuver, the path of the vehicle, and the telematic data. The maneuver classification platform may send a message associated with the maneuver score and a vehicle identifier of the vehicle to a client device to permit the client device to use the maneuver score.
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9.发明申请公开(公告)号：US20230102113A1
公开(公告)日：2023-03-30
申请号：US18061124
申请日：2022-12-02
Applicant: Verizon Connect Development Limited
Inventor： Simone MAGISTRI , Francesco SAMBO , Douglas COIMBRA DE ANDRADE , Fabio SCHOEN , Matteo SIMONCINI , Luca BRAVI , Stefano CAPRASECCA , Luca KUBIN , Leonardo TACCARI
Abstract: A device may receive a first image. The device may process the first image to identify an object in the first image and a location of the object within the first image. The device may extract a second image from the first image based on the location of the object within the first image. The device may process the second image to determine at least one of a coarse-grained viewpoint estimate or a fine-grained viewpoint estimate associated with the object. The device may determine an object viewpoint associated with the second vehicle based on the at least one of the coarse-grained viewpoint estimate or the fine-grained viewpoint estimate. The device may perform one or more actions based on the object viewpoint.
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公开(公告)号：US20220245935A1
公开(公告)日：2022-08-04
申请号：US17659928
申请日：2022-04-20
Applicant: Verizon Connect Development Limited
Inventor： Leonardo TACCARI , Luca KUBIN , Tommaso BIANCONCINI , Andrea BENERICETTI , Leonardo SARTI , Tommaso INNOCENTI
Abstract: A device may receive sensor data and video data associated with a vehicle, and may process the sensor data, with a rule-based detector model, to determine whether a probability of a vehicle accident satisfies a first threshold. The device may preprocess acceleration data of the sensor data to generate calibrated acceleration data, and may process the calibrated acceleration data, with an anomaly detector model, to determine whether the calibrated acceleration data includes anomalies. The device may filter the sensor data to generate filtered sensor data, and may process the filtered sensor data and anomaly data, with a decision model, to determine whether the probability of the vehicle accident satisfies a second threshold. The device may process the filtered sensor data, the anomaly data, and the video data, with a machine learning model, to determine whether the vehicle accident has occurred, and may perform one or more actions.
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