PSAP Publish-Subscribe Call Routing for Real-Time Transcript Sharing
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Solution Overview
Problem
Call data from public safety answering points (PSAPs) remains localized and is not shared externally, limiting access to valuable information for other systems and entities interested in emergency calls.
Innovation Solution
Implementing a publish/subscribe architecture that records and converts audio files from PSAPs into text, allowing external entities to subscribe to topics of interest and receive relevant call transcripts or notifications automatically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If call data is managed locally at the PSAP, then system complexity is reduced and ease of operation is improved, but information accessibility and utility for external entities deteriorates
Solution Approach 1:
The patent introduces a message broker as an intermediary component that sits between the PSAP call data and external subscribers. The broker receives call data from the PSAP, processes it through topic modeling and keyword extraction, and distributes it to appropriate subscribers. This intermediary architecture enables external information accessibility without requiring direct integration between PSAP systems and external entities, thus maintaining PSAP operational simplicity while enabling broad information distribution.
Solution Approach 2:
The system segments call data processing into distinct functional modules: data collection from PSAP, topic modeling analysis, keyword extraction, message routing, and subscriber notification. Each module operates independently with defined interfaces, allowing the system to handle information accessibility requirements without increasing PSAP operational complexity. The segmentation enables parallel processing and independent optimization of each function.
2Productivity
If automated topic detection and distribution is implemented, then productivity and information utility are improved, but device complexity and processing requirements increase
Solution Approach 1:
The system implements automated topic modeling and keyword extraction algorithms that self-adjust and optimize without human intervention. The topic modeling component automatically identifies recurring themes in call data, and the keyword extraction system autonomously determines relevant search terms. This self-service automation improves information distribution productivity by eliminating manual data processing while the modular architecture keeps processing complexity manageable through standardized interfaces and independent module operation.
3Loss of information
If call transcripts are converted and distributed in real-time, then information accessibility is improved, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary processing of call data by pre-computing topic models and extracting keywords while the call data is being collected and before distribution is required. The topic modeling and keyword extraction operations are initiated immediately upon data receipt, allowing processing to occur in parallel with data transmission and subscriber notification. This preliminary action reduces the critical path time for information delivery while maintaining real-time accessibility.
Data Source
AI summary
An example operation may include one or more of receiving an audio file from a public safety answering point (PSAP), the audio file comprising a recording of a telephone call, converting the audio file into a text file that comprises a transcript of the telephone call, identifying a keyword within the text file that is associated with a topic, and transmitting a portion of the text file of the telephone call to one or more subscribers that have registered with the topic.