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公开(公告)号：US20250157267A1
公开(公告)日：2025-05-15
申请号：US18815371
申请日：2024-08-26
Applicant: Geotab Inc.
Inventor： Giordano Aldo Arezza , Giuliano Roberto Barrella Garcia , Gagandeep Bedi , Young Seok Shin , Nadia Sophia Stefopulos
Abstract: Systems, methods, devices, and models determining fuel level in vehicles are described. Raw fuel sensor data tends to be noisy and of low quality. Herein, operational data is collected, which is used to determine times when motion of the vehicle is stable. Raw fuel sensor data for these times is collected in a data subset, which is used to determine fuel level. Quality fuel sensor data is thus obtained. Fuel data can be combined over different time periods to provide a prompt initial fuel level, and an intermittent fuel level during a trip.
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Patent Agency Ranking
公开(公告)号：US20250157266A1
公开(公告)日：2025-05-15
申请号：US18815344
申请日：2024-08-26
Applicant: Geotab Inc.
Inventor： Giordano Aldo Arezza , Gagandeep Bedi , Daniel J. Lewis , Ivan Li , Young Seok Shin , Evan Klinger Takefman
IPC: G07C5/04
Abstract: Systems, methods, devices, and models determining fuel level in vehicles are described. Raw fuel sensor data tends to be noisy and of low quality. Herein, operational data is collected, which is used to determine times when motion of the vehicle is stable. Raw fuel sensor data for these times is collected in a data subset, which is used to determine fuel level. Quality fuel sensor data is thus obtained. Fuel data can be combined over different time periods to provide a prompt initial fuel level, and an intermittent fuel level during a trip.
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公开(公告)号：US12077019B1
公开(公告)日：2024-09-03
申请号：US18413179
申请日：2024-01-16
Applicant: Geotab Inc.
IPC: B60C23/04 , G06F18/243
CPC classification number: B60C23/0479 , G06F18/24323
Abstract: Systems and methods for detecting and removing erroneous tire pressure values are provided. The method involves operating at least one processor to: receive tire pressure data comprising a time series of tire pressure values; simplify the tire pressure data by removing at least some of the tire pressure values that satisfy a predetermined interpolation error threshold; detect, using a trained machine learning classifier, at least one erroneous tire pressure value in the tire pressure data, each erroneous tire pressure value being detected based on the erroneous tire pressure value and a plurality of lagging tire pressure values consecutively trailing the erroneous tire pressure value; clean the tire pressure data by removing the at least one erroneous tire pressure value; and transmit the tire pressure data to a fleet management system, whereby the at least one erroneous tire pressure value is not transmitted to the fleet management system.
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公开(公告)号：US20250104494A1
公开(公告)日：2025-03-27
申请号：US18894639
申请日：2024-09-24
Applicant: Geotab Inc.
Inventor： Lourd Arun Raj , Giordano Aldo Arezza , Daniel J. Lewis , Michael Angelo David Santorelli , James Spencer
Abstract: Disclosed herein are systems and methods for estimating remaining useful life of vehicle engine oil. Such methods may comprise operating at least one processor to: receive telematics data originating from a plurality of vehicles, the telematics data comprising odometer data and engine oil quality data associated with each of the plurality of vehicles; determine, for one or more of the plurality of vehicles, a start point of a current oil cycle based on when an oil cycle event previously occurred by identifying within the engine oil quality data: a first series of engine oil quality datapoints, and a second series of engine oil quality datapoints immediately following the first series, a difference between a final datapoint of the first series and an initial datapoint of the second series being greater than a predetermined threshold; synchronize the odometer data and the engine oil quality data by associating odometer datapoints and engine oil quality datapoints reported within a same time period; determine a remaining useful vehicle engine oil distance by applying to synchronized odometer and engine oil quality data reported during the current oil cycle a regression model; and determine a remaining useful vehicle engine oil time by converting the remaining useful vehicle engine oil distance thereto based on an average difference in odometer datapoints reported during a selected time period, whereby the remaining useful life of vehicle engine oil is estimated based on vehicle operational factors associated with the current oil cycle, and independently from those of a previous oil cycle.
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公开(公告)号：US20240326524A1
公开(公告)日：2024-10-03
申请号：US18733174
申请日：2024-06-04
Applicant: Geotab Inc.
IPC: B60C23/04 , G06F18/243
CPC classification number: B60C23/0479 , G06F18/24323
Abstract: Systems and methods for detecting and removing erroneous tire pressure values are provided. The method involves operating at least one processor to: receive tire pressure data comprising a time series of tire pressure values; simplify the tire pressure data by removing at least some of the tire pressure values that satisfy a predetermined interpolation error threshold; detect, using a trained machine learning classifier, at least one erroneous tire pressure value in the tire pressure data, each erroneous tire pressure value being detected based on the erroneous tire pressure value and a plurality of lagging tire pressure values consecutively trailing the erroneous tire pressure value; clean the tire pressure data by removing the at least one erroneous tire pressure value; and transmit the tire pressure data to a fleet management system, whereby the at least one erroneous tire pressure value is not transmitted to the fleet management system.
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公开(公告)号：US20240270031A1
公开(公告)日：2024-08-15
申请号：US18413179
申请日：2024-01-16
Applicant: Geotab Inc.
IPC: B60C23/04 , G06F18/243
CPC classification number: B60C23/0479 , G06F18/24323
Abstract: Systems and methods for detecting and removing erroneous tire pressure values are provided. The method involves operating at least one processor to: receive tire pressure data comprising a time series of tire pressure values; simplify the tire pressure data by removing at least some of the tire pressure values that satisfy a predetermined interpolation error threshold; detect, using a trained machine learning classifier, at least one erroneous tire pressure value in the tire pressure data, each erroneous tire pressure value being detected based on the erroneous tire pressure value and a plurality of lagging tire pressure values consecutively trailing the erroneous tire pressure value; clean the tire pressure data by removing the at least one erroneous tire pressure value; and transmit the tire pressure data to a fleet management system, whereby the at least one erroneous tire pressure value is not transmitted to the fleet management system.
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