Virtual tagging of vehicles
AssigneeCambridge Mobile Telematics Inc.
InventorsYuting Qi, Sanujit Sahoo, Burak Erem
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Abstract
Techniques are disclosed for virtual tagging of vehicles that include generating an association between a user of a mobile device and the mobile device. The techniques include receiving a first set of measurements from one or more sensors of the mobile device while the mobile device is positioned in a first vehicle during a trip and training a machine-learning model using the first set of measurements. The techniques further include receiving a second set of measurements from the one or more sensors of the mobile device and determining, by executing the machine-learning model using the third set of measurements, that the mobile device is positioned in the first vehicle or a second vehicle.
Claims20
A method comprising:
- generating an association between a user of a mobile device and the mobile device;
- receiving a first set of measurements from one or more sensors of the mobile device while the mobile device is positioned in a first vehicle;
- training a machine-learning model using the first set of measurements;
- receiving a second set of measurements from the one or more sensors of the mobile device;
- and
- determining, by executing the machine-learning model on the second set of measurements, that the mobile device is not positioned in the first vehicle.
A system comprising:
- one or more processors;
- and
- a non-transitory computer-readable medium storing instructions which, when executed by the one or more processors, configure the system to:
- generate an association between a user of a mobile device and the mobile device;
- receive a first set of measurements from one or more sensors of the mobile device while the mobile device is positioned in a first vehicle;
- train a machine-learning model using the first set of measurements;
- receive a second set of measurements from the one or more sensors of the mobile device;
- and
- determine, by executing the machine-learning model on the second set of measurements, that the mobile device is not positioned in the first vehicle.
A method comprising:
- receiving a first set of measurements from one or more sensors of a mobile device while the mobile device is positioned in a first vehicle;
- and
- determining, by executing a machine-learning model on the first set of measurements, that the mobile device is positioned in the first vehicle, wherein the machine-learning model was trained using a previous set of measurements collected while the mobile device was positioned in the first vehicle.
Dependencies are inferred from the claim text.