公开(公告)号：US20240295458A1

公开(公告)日：2024-09-05

申请号：US18178477

申请日：2023-03-03

Applicant: Metropolis Technologies, Inc.

Inventor： Barry James O'Brien ,  Leah Sardone ,  Zachary James Thompson ,  Kyle Bradley Kufalk ,  Luis Felipe Rodriguez Herrera ,  Antonio Ortega ,  Alexander David Israel

IPC: G01M5/00 ,  G06N5/022

CPC classification number: G01M5/0025 ,  G01M5/0033 ,  G01M5/0066 ,  G06N5/022

Abstract: An edge device receives sensor data from a sensor affixed to a moveable gate. The edge device determines the positional state of the moveable gate based on the sensor data by inputting the received data into a machine learning model or by comparing the sensor data to values associated with a positional state through a calibration process. The edge device stores a log that associates the positional state and sensor data. The edge device determines the health state of the moveable gate using a machine learning model that is trained to predict, based on input of a new log, the health state of the gate. Responsive to determining that the health state of the gate is unhealthy, the edge device triggers a remedial action.

公开(公告)号：US20250003827A1

公开(公告)日：2025-01-02

申请号：US18824741

申请日：2024-09-04

Applicant: Metropolis Technologies, Inc.

Inventor： Barry James O'Brien ,  Leah Sardone ,  Zachary James Thompson ,  Kyle Bradley Kufalk ,  Luis Felipe Rodriguez Herrera ,  Antonio Ortega ,  Alexander David Israel

IPC: G01M5/00 ,  G06N5/022

Abstract: An edge device receives sensor data from a sensor affixed to a moveable gate. The edge device determines the positional state of the moveable gate based on the sensor data by inputting the received data into a machine learning model or by comparing the sensor data to values associated with a positional state through a calibration process. The edge device stores a log that associates the positional state and sensor data. The edge device determines the health state of the moveable gate using a machine learning model that is trained to predict, based on input of a new log, the health state of the gate. Responsive to determining that the health state of the gate is unhealthy, the edge device triggers a remedial action.

公开(公告)号：US20240185566A1

公开(公告)日：2024-06-06

申请号：US18076227

申请日：2022-12-06

Applicant: Metropolis Technologies, Inc.

Inventor： Edwin Thomas ,  June Guo ,  Ji Sung Hwang ,  Anil Kumar Nayak ,  Todd Merle Shipway ,  Barry James O'Brien ,  Alexander David Israel

IPC: G06V10/764

CPC classification number: G06V10/764 ,  G06V2201/08

Abstract: A device captures a series of images over time in association with a gate, each image having a timestamp. The device determines, for a vehicle approaching the entry side, from a subset of images of the series of images featuring the vehicle, a first data set comprising a plurality of parameters that describe attributes of the vehicle by inputting the subset of images into a first machine learning model and a vehicle identifier of the vehicle by inputting images of the subset featuring a depiction of a license plate of the vehicle into a second machine learning model. The device stores the data set in association with one or more timestamps with the subset of images, determines a second data set for a second vehicle approaching the exit side, and responsive to determining that the first data set and the second data set match, instructs the gate to move.

公开(公告)号：US20240185569A1

公开(公告)日：2024-06-06

申请号：US18431738

申请日：2024-02-02

Applicant: Metropolis Technologies, Inc.

Inventor： Edwin Thomas ,  June Guo ,  Ji Sung Hwang ,  Anil Kumar Nayak ,  Todd Merle Shipway ,  Barry James O'Brien ,  Alexander David Israel

IPC: G06V10/764

CPC classification number: G06V10/764 ,  G06V2201/08

Abstract: A device captures a series of images over time in association with a gate, each image having a timestamp. The device determines, for a vehicle approaching the entry side, from a subset of images of the series of images featuring the vehicle, a first data set comprising a plurality of parameters that describe attributes of the vehicle by inputting the subset of images into a first machine learning model and a vehicle identifier of the vehicle by inputting images of the subset featuring a depiction of a license plate of the vehicle into a second machine learning model. The device stores the data set in association with one or more timestamps with the subset of images, determines a second data set for a second vehicle approaching the exit side, and responsive to determining that the first data set and the second data set match, instructs the gate to move.