Rakuten Group had 65 patents in artificial intelligence during Q1 2024. The Rakuten Group Inc patents filed in Q1 2024 cover a range of technologies including optimizing energy usage based on traffic patterns, controlling zero trust remote access to a network system, processing information from social platforms to trigger actions, and a live distribution system that evaluates viewer comments for appropriateness. These patents showcase innovative methods and systems for improving network efficiency, security, and user engagement. GlobalData’s report on Rakuten Group gives a 360-degree view of the company including its patenting strategy. Buy the report here.
Rakuten Group grant share with artificial intelligence as a theme is 27% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Method and system for optimizing energy using traffic patterns (Patent ID: US20240107565A1)
The patent filed by Rakuten Group Inc. discloses a method and system for optimizing energy within a network by analyzing traffic patterns. The method involves receiving identification data related to user devices and cell sites, applying a threshold criterion to the data, and generating a probability of network traffic for each cell site based on the received data. The system aims to efficiently allocate network resources and manage operational times of servers based on the traffic patterns identified.
The claims associated with the patent detail the steps involved in optimizing energy within a network using traffic patterns. These steps include grouping identification data based on time, generating probabilities of network traffic for cell sites, utilizing neural network embeddings, determining travel paths for user devices, and clustering cell sites based on traffic probabilities. The apparatus described in the patent includes a processor and memory storage to execute the computer-executable instructions for optimizing energy within the network. Overall, the patent focuses on leveraging traffic patterns to enhance energy efficiency and resource allocation in a network environment.
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