Server Aggregating Time-Series Vital Data
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Solution Overview
Problem
Existing systems for collecting and providing vital data are limited in their ability to aggregate and share data from multiple subjects and do not effectively handle a variety of vital data types.
Innovation Solution
A server system that collects time-series vital data from multiple subjects, clusters the data based on attribute information, and provides the data to other users upon request, while also handling different data formats and types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If vital data is collected from multiple subjects and aggregated in a centralized database, then data accessibility and sharing capability are improved, but data security risks and privacy protection requirements increase
Solution Approach 1:
The patent introduces a server as an intermediary between data collection systems and users. The server receives vital data from multiple collection systems, stores it in a centralized database, and provides controlled access to authorized users. This intermediary architecture enables data aggregation and sharing while centralizing security management and access control mechanisms.
Solution Approach 2:
The patent implements authentication mechanisms where users provide authentication information to the server before accessing vital data. The server verifies authentication credentials and controls data access based on user authorization. This feedback loop ensures that only authenticated users can access data, mitigating security risks while maintaining data sharing capability.
2Quantity of substance
If vital data from multiple sources is aggregated, then the quantity and diversity of available data increase, but the complexity of data handling and integration increases
Solution Approach 1:
The patent designs the server to handle multiple types of vital data from various collection systems through a unified architecture. The server can receive different types of vital data (e.g., physiological parameters, behavioral data) and store them in the same database structure, providing universal data handling capability that reduces system complexity despite data diversity.
Solution Approach 2:
The patent segments the data management function by separating data collection, storage, and access control into distinct functional components. The server acts as a dedicated intermediary that handles data aggregation and management independently from collection systems and user interfaces, reducing the complexity burden on individual components.
3Productivity
If attribute data is associated with vital data records, then data organization and retrieval efficiency are improved, but data storage requirements and processing complexity increase
Solution Approach 1:
The patent merges attribute data with vital data records in the database structure. Attribute information (such as subject characteristics, data collection metadata) is stored alongside corresponding vital data records, enabling efficient joint retrieval and analysis. This merging approach improves data organization and retrieval efficiency while managing storage requirements through structured data relationships.
Data Source
AI summary
A server receives a first type of time-series vital data from a first system that collects the first type of time-series vital data from a first group of subjects, and receives a second type of time-series vital data from a second system that collects a second type of time-series vital data from a second group of subjects. Provided are a storage unit for storing a plurality of types of time-series vital data including the first type and the second type, a receiving unit for receiving a request for provision of the time-series vital data from an external device that specifies at least a part of the time-series vital data stored in a vital data database, and a transmitting means for transmitting to the external device the time-series vital data selected in accordance with a request for provision from among the time-series vital data stored in the vital data database.