Activities Data Modeling in Human Internet-of-Things Platforms

    公开(公告)号:US20210279382A1

    公开(公告)日:2021-09-09

    申请号:US17207604

    申请日:2021-03-20

    摘要: A platform models and correlates physical activities based on users' interactions with a simple grip-metaphor design, enabling multi-dimensions actionable information to improve the health, performance and well-being of connected grip users within like-minded communities. For example, the platform captures multi-dimensional datasets generated from activities of each of a plurality of users on the online human internet of thing platform, where the activities include physical interactions with connected grips systems connected to the online human internet of thing platform. The platform then filters the captured multi-dimensional datasets into a plurality of categories and scores the filtered multi-dimensional data by the human internet of thing platform. Finally, the platform generates a multi-dimensional information modeling for each user based on the scored multi-dimensional data.

    Activities data modeling in human internet-of-things platforms

    公开(公告)号:US11610035B2

    公开(公告)日:2023-03-21

    申请号:US17207604

    申请日:2021-03-20

    摘要: A platform models and correlates physical activities based on users' interactions with a simple grip-metaphor design, enabling multi-dimensions actionable information to improve the health, performance and well-being of connected grip users within like-minded communities. For example, the platform captures multi-dimensional datasets generated from activities of each of a plurality of users on the online human internet of thing platform, where the activities include physical interactions with connected grips systems connected to the online human internet of thing platform. The platform then filters the captured multi-dimensional datasets into a plurality of categories and scores the filtered multi-dimensional data by the human internet of thing platform. Finally, the platform generates a multi-dimensional information modeling for each user based on the scored multi-dimensional data.