PSAP 911 Outage Detection Using Call and Query Analytics
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Solution Overview
Problem
Existing 911 call center systems fail to detect service outages, leading to fear-inducing experiences for callers and frustration for 911 call centers, as neither the public nor the centers are aware of service disruptions, which can be life-threatening.
Innovation Solution
An emergency management system (EMS) is developed to detect 911 service outages by analyzing call metrics such as call volume, redial volume, and query volume, and provides notifications to PSAPs and other personnel using a 911 outage confidence system that integrates with social media and other external sources to validate outage likelihood.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If 911 service systems operate without monitoring mechanisms, then system simplicity is maintained, but service reliability deteriorates due to undetected outages
Solution Approach 1:
The 911 service system performs self-diagnosis by automatically monitoring its own operational status through the analytics engine, which analyzes call data, location data, and system logs to detect outages without requiring external monitoring infrastructure
Solution Approach 2:
The system implements feedback mechanisms where the analytics engine continuously monitors system performance metrics and provides real-time status information back to the PSAP, enabling automatic detection and notification of service outages
2Loss of information
If traditional 911 call routing systems are used, then ease of operation is maintained, but information completeness deteriorates as callers cannot be informed of service status
Solution Approach 1:
The system performs preliminary analysis of call data and system status before the caller completes their call, pre-determining whether an outage condition exists and preparing notification information in advance
Solution Approach 2:
The analytics engine acts as an intermediary between the 911 call routing system and the PSAP, analyzing call data and system logs to detect outages and providing this information to both the caller and the PSAP without disrupting the existing call flow
3Productivity
If manual outage detection methods are used, then measurement precision can be maintained, but productivity deteriorates due to delayed outage awareness
Solution Approach 1:
The analytics engine continuously analyzes call data, location data, and system logs in real-time without interruption, ensuring that service outages are detected immediately when they occur rather than through periodic manual checks
Solution Approach 2:
The system replaces manual monitoring methods with automated electronic analysis of call data and system logs, using computer-based algorithms to detect outages faster and more reliably than human operators could
Data Source
AI summary
An emergency management system (EMS) generates a likelihood of a 911 service outage for a public safety access point (PSAP). The EMS receives supplemental call data for mobile devices that initiated 911 calls to a public safety answering point (PSAP). The EMS generates a 911 call volume metric for the 911 calls. The EMS receives a number of queries from the PSAP for a portion of the supplemental call data that corresponds to the 911 call volume metric. The EMS tracks the number of queries received from the PSAP. The EMS determines the likelihood of a 911 service outage for the PSAP based on the 911 call volume metric and the number of queries received. The EMS notifies the PSAP of the likelihood of the 911 service outage (e.g., with an outage score).


