Context-Aware Body Temperature Alert Generation System
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Solution Overview
Problem
Conventional technologies fail to effectively present alert information based on the environment or situation of a user, particularly in the context of body temperature monitoring, as they do not consider regional virus spread situations or individual circumstances when determining alert levels.
Innovation Solution
An information processing method that acquires body temperature information, user information, and alert criteria from a database to generate and output alert information, taking into account factors like regional virus spread situations, contact persons, and individual health conditions, thereby tailoring alert presentation to the user's environment and situation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional body temperature monitoring systems display only basic temperature data, then the system is simple and easy to operate, but it fails to provide context-aware health alerts that consider user environment and situation
Solution Approach 1:
The system segments information processing by separating basic temperature monitoring functions from advanced alert generation functions. It divides user information into multiple categories (basic info, health conditions, environmental factors) and processes them through distinct modules, allowing the system to provide comprehensive context-aware alerts while maintaining operational simplicity through modular architecture.
Solution Approach 2:
The system introduces an intermediary alert information generation unit that acts as a mediator between raw temperature data and user notifications. This intermediary component synthesizes temperature readings with user information from the database, applies alert criteria, and generates contextualized alert information, thereby enriching the output without requiring direct complexity in the user interface.
2Adaptability or versatility
If the system acquires and processes multiple types of user information and alert criteria, then it can provide personalized and context-aware alerts, but the information processing complexity increases
Solution Approach 1:
The system implements a universal alert criteria database that stores multiple types of user information (basic information, health conditions, environmental factors) and alert criteria in a standardized format. This multi-functional database structure allows the same processing framework to handle diverse information types uniformly, enabling personalized alerts without proportionally increasing processing complexity through standardization.
Solution Approach 2:
The system performs preliminary actions by pre-storing user information and alert criteria in the database before actual temperature monitoring occurs. User profiles, health conditions, and environmental factors are registered in advance, and alert criteria are predefined, allowing the processing unit to quickly match incoming temperature data against pre-prepared criteria without performing complex real-time analysis.
3Reliability
If the system stores detailed user information and alert criteria in a database, then it can retrieve personalized alert thresholds, but the data management complexity increases
Solution Approach 1:
The system applies local quality by organizing database content according to specific user needs and contexts. Different user information (basic info, health conditions, environmental factors) and alert criteria are stored in dedicated database sections with appropriate structures, allowing the retrieval unit to efficiently access only relevant data for each user's specific situation, thereby ensuring alert accuracy while managing data complexity through structured organization.
4Loss of information
If the system generates alert information based on multiple criteria including regional virus spread and contact persons, then the health alerts become more relevant and actionable, but the processing requirements increase
Solution Approach 1:
The system implements partial action by selectively applying different sets of alert criteria based on user profiles and situations. Not all users require evaluation against all criteria (e.g., regional virus spread, contact persons, health conditions). The retrieval unit and generation unit dynamically determine which criteria subsets to apply for each user, providing contextualized alerts with appropriate detail levels without uniformly processing all possible factors for every user.
Data Source
AI summary
A body temperature management server executes: acquiring body temperature information indicating a body temperature of a user and associated with a user ID specifying the user; acquiring user information about the user associated with the user ID; acquiring an alert criterion in accordance with the user information; determining whether the body temperature information satisfies the alert criterion; generating alert information for issuing an alert about a health state of the user in association with the user ID when the body temperature information is determined to satisfy the alert criterion; and outputting the alert information.