Siemens had two patents in social media during Q1 2024. Siemens AG has developed a system for machine-to-machine (M2M) or machine-to-human (M2H) communication using hyperlink messages. These messages contain semantic metadata, content, and an executable specification field that instructs machines to perform tasks and post results on a machine social media platform. This allows for visible and collaborative communication between participating machines on the platform. GlobalData’s report on Siemens gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Siemens grant share with social media as a theme is 50% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Hyperlink messages for machine-to-machine communication on a machine social media platform (Patent ID: US20240015122A1)
The patent filed by Siemens AG describes a system for machine-to-machine (M2M) or machine-to-human (M2H) communication using a hyperlink message with semantic metadata, content, and an executable specification field. The system allows machines to perform tasks associated with machine-related data, post results to a machine social media platform, and engage in discussions with other participating machines. The technology involves artificial intelligence algorithms defining metadata tags and executable specifications, enabling machines to interact on the social media platform based on conditions set in the specifications.
The system includes a machine configured to construct, post, and interact with hyperlink messages on the machine social media platform. It utilizes AI algorithms to define metadata tags and executable specifications, allowing machines to perform tasks, post results, and engage in discussions. Additionally, the machine can read, schedule, and differentiate between posted messages based on unique specifications, subscribe to specific interests, filter content, and present trending topics based on activity levels. Overall, the technology enables efficient and structured communication between machines through a social media platform, enhancing collaboration and information sharing in M2M and M2H interactions.
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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.
