DoorDash had two patents in metaverse during Q2 2024. DoorDash Inc’s patent filed in Q2 2024 describes a system that uses machine learning to analyze images and location data from agent devices to determine a consensus location for a delivery location. This consensus location is then stored as mapping information associated with the delivery location. GlobalData’s report on DoorDash gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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DoorDash had no grants in metaverse as a theme in Q2 2024.
Recent Patents
Application: Generating mapping information based on image locations (Patent ID: US20240203120A1)
The patent filed by DoorDash Inc. describes a system that receives images and location data from agent devices associated with delivery locations. These images are input into a machine-learning model to determine if they contain enough information. Based on this determination, the system calculates a consensus location for the delivery location by averaging or clustering the location information from the images. This consensus location is then stored as mapping information for the delivery location. The system can also handle requests for items to be delivered to these locations, generate maps for agents, and adjust location data based on feedback received.
Additionally, the system can train the machine learning model using images from past deliveries to densely populated areas, ensuring accuracy in determining delivery locations. The threshold amount of information required in the images includes details like the delivered item, entrance portion, door portion, or unit number. The system can also prompt agents to capture additional images if the initial ones do not meet the information threshold, ensuring precise mapping information for each delivery location. Overall, the system streamlines the process of determining accurate delivery locations based on images and associated location data, improving efficiency and accuracy in the delivery process.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
