Emergency Call Prioritization via Cloud Health Data
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Solution Overview
Problem
Existing emergency call systems do not prioritize calls based on health data stored in cloud servers, which can lead to delays in responding to life-threatening incidents.
Innovation Solution
A method and system that utilize smart devices and cloud databases to automatically prioritize emergency calls by retrieving health status data from cloud servers and assigning a prioritization value based on abnormal health readings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If emergency calls are handled using traditional IVR systems without health data integration, then the system complexity remains low, but the response time for serious injuries increases
Solution Approach 1:
The system performs preliminary actions by automatically retrieving health status data from cloud servers before the emergency call is answered. Health data is fetched in advance based on the caller's location and the type of emergency, allowing the dispatch center to assess the situation severity before initiating the call handling process.
Solution Approach 2:
A cloud server acts as an intermediary component that stores and provides health status data. This intermediary enables the dispatch center to access critical health information without integrating complex monitoring capabilities directly into the emergency call system, thus reducing overall system complexity while improving response time.
2Measurement precision
If health status data is retrieved from cloud servers for all emergency calls, then the prioritization accuracy improves, but the data processing time increases
Solution Approach 1:
The system applies local quality by retrieving health data selectively based on the specific emergency type and location. Not all emergency calls trigger a full health data retrieval; instead, the system determines the appropriate data scope and depth based on the call characteristics, balancing accuracy needs with processing time constraints.
Solution Approach 2:
The system performs partial action by retrieving only the necessary health data fields relevant to the emergency situation rather than all available data. This selective retrieval approach maintains sufficient prioritization accuracy while minimizing data processing time and avoiding unnecessary data transmission.
3Productivity
If automatic prioritization based on health data is implemented, then the emergency response efficiency improves, but the system requires integration with cloud databases and smart devices
Solution Approach 1:
The cloud server serves multiple functions: it stores health status data from smart devices, processes emergency call requests, and provides prioritization decisions. This multi-functional approach reduces the need for separate dedicated components, thereby improving productivity while managing integration complexity through a universal platform.
Solution Approach 2:
The system enables self-service by automatically retrieving and processing health data without requiring manual intervention from dispatch center operators. The automated health data retrieval and prioritization processes handle routine assessments independently, improving response efficiency while reducing the operational burden on human operators.
Data Source
AI summary
A method and a system can automatically prioritize emergency calls based on health data. Such prioritization can be provided even when the call is placed by a person who has no idea of what has happened in the incident and cannot give many details about the health status of the parties involved.