Verizon Communications has patented a method using machine learning to optimize travel times for drivers by analyzing schedules, traffic data, and historical information. The device calculates estimated arrival times for appointments and adjusts its models based on accuracy. GlobalData’s report on Verizon Communications gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on Verizon Communications, Network traffic analysis was a key innovation area identified from patents. Verizon Communications's grant share as of February 2024 was 81%. Grant share is based on the ratio of number of grants to total number of patents.
Predicting estimated arrival times for vehicle appointments using machine learning
A recently granted patent (Publication Number: US11922530B2) outlines a method and device for optimizing appointment schedules for drivers of vehicles based on real-time traffic data. The method involves receiving schedule data, location data, and traffic data, and using a status estimate model to determine estimated statuses of appointments. The device then trains an isochrone model using historical data to generate polygons representing travel time to destinations. By inputting schedule, location, and traffic data into the model, the device can identify the smallest polygon containing a vehicle's current location and calculate estimated arrival times for subsequent appointments. The accuracy of these estimates is continuously refined using machine learning, allowing for adjustments to the isochrone model.
Furthermore, the patent includes additional features such as updating schedule data based on estimated arrival times, providing estimated arrival data to drivers and customers, reassigning appointments based on these estimates, and updating status data based on input status information. The device's processors are configured to define geofences around destinations, track vehicle movements, and adjust appointment statuses accordingly. The device can also compress the generated polygons for efficient storage and processing. Overall, the patented method and device offer a comprehensive solution for optimizing appointment schedules in real-time, leveraging machine learning and historical data to improve accuracy and efficiency in managing driver appointments and travel times.
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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.
