Sensor-based layout generation
AssigneeSquare, Inc.
InventorsArjun Mahanti, Matthew T. Kursmark, Brian Stegall
Life of this patent
Estimating the term…
Abstract
This disclosure describes, in part, techniques for enabling merchant devices to interoperate with one another in a more robust manner, such that overall operation and efficiency within a merchant establishment is improved. For instance, the techniques described herein may enable the intelligent routing of requests between devices within the merchant establishment based on real-time locations of the devices, which devices are associated with which orders, and the like.
Claims20
A method comprising:
- generating image data of a physical establishment of a merchant using a camera of a merchant device;
- analyzing the image data to:
- (i) identify at least a first surface and a second surface within the physical establishment, and (ii) determine a first location associated with the first surface in the physical establishment and a second location associated with the second surface in the physical establishment;
- presenting, on a display of the merchant device, the image data overlaid with:
- (i) a first indication that the first surface has been identified, and (ii) a second indication that the second surface has been identified;
- receiving a selection of the first surface, the selection indicating that the first surface represents an available seating area in the physical establishment;
- generating, based at least in part on the selection, a first layout of available seating areas in the physical establishment, the layout of seating areas indicating that the first surface is an available seating at the first location;
- generating, by a trained machine-learning model and using the first layout, a second layout of available seating areas in the physical establishment;
- and
- presenting the second layout of the available seating areas on the display of the merchant device.
The method as recited in claim Error! Reference source not found., wherein the analyzing the image data comprises analyzing the image data using at least one trained machine-learning model to identify at least the first surface and the second surface within the physical establishment.
The method as recited in claim Error! Reference source not found., wherein the analyzing the image data comprises using LIDAR on the merchant device to identify at least the first surface and the second surface within the physical establishment.
A method comprising:
- receiving data from a device in an environment;
- analyzing the data to identify:
- (i) a first surface within the environment, and (ii) a first location associated with the first surface in the environment;
- generating a user interface (UI) indicating the first surface;
- sending the UI to the device;
- receiving, from the device, a selection of the first surface indicating that the first surface represents an available seating area in the environment;
- generating, based at least in part on the selection, a first layout of available seating areas in the environment, the layout of seating areas indicating that the first surface is an available seating at the first location;
- generating, by a trained machine-learning model and using the first layout, a second layout of available seating areas in the environment;
- and
- sending the second layout of the available seating areas to the device.
A system comprising:
- one or more processors;
- and
- one or more computer-readable media storing computer-executable instructions that, when executed, cause the one or more processors to perform acts comprising:
- receiving data from a device in an environment;
- analyzing the data to identify:
- (i) a first surface within the environment, and (ii) a first location associated with the first surface in the environment;
- generating a user interface (UI) indicating the first surface;
- sending the UI to the device;
- receiving, from the device, a selection of the first surface indicating that the first surface represents an available seating area in the environment;
- generating, based at least in part on the selection, a first layout of available seating areas in the environment, the layout of seating areas indicating that the first surface is an available seating at the first location;
- generating, by a trained machine-learning model and using the first layout, a second layout of available seating areas in the environment;
- and
- sending the second layout of the available seating areas to the device.
Dependencies are inferred from the claim text.