Context-Based Call Participant Highlighting for Dispatch Video Prioritization
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Solution Overview
Problem
Public safety dispatchers face challenges in efficiently identifying and communicating with relevant first responders during incidents due to issues like radio signal strength, volume, and video stream management, leading to increased communication and data traffic, which can slow down the network and hinder effective incident response.
Innovation Solution
A system that automatically extracts context information from talkgroup voice communications, highlights relevant participants in video streams, and prioritizes these streams for display on a dispatch console, reducing the need for manual checks and improving network efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If dispatchers manually monitor and identify relevant first responders during incidents, then communication effectiveness can be maintained, but time consumption and operational complexity increase significantly
Solution Approach 1:
The system enables automatic identification of relevant first responders through contextual analysis of video streams and voice communications. The electronic processor autonomously extracts context information, identifies relevant participants, and highlights them in video feeds without requiring manual dispatcher intervention, thus maintaining communication effectiveness while eliminating time-consuming manual monitoring
Solution Approach 2:
The patent replaces the mechanical manual monitoring process with an automated electronic system that processes video streams and voice communications. The electronic processor automatically analyzes context information from multiple sources, identifies relevant first responders, and presents highlighted video feeds, substituting human manual effort with automated computational processing
2Loss of information
If multiple video streams from various first responders are transmitted simultaneously, then comprehensive situational awareness is achieved, but network data traffic increases and slows down communication
Solution Approach 1:
The system extracts and processes only the essential information needed for situational awareness. Instead of transmitting all video streams equally, the electronic processor analyzes context information from voice communications and video streams, identifies only the relevant first responders, and highlights them in selected video feeds. This extraction of essential information maintains comprehensive situational awareness while reducing unnecessary data traffic
Solution Approach 2:
The patent applies different quality levels to different video streams based on their relevance. Rather than uniformly processing all video feeds, the system provides enhanced processing and highlighting only for video streams containing relevant first responders identified through contextual analysis. This localized quality approach ensures critical information is prioritized while reducing overall network burden
3Measurement precision
If dispatchers perform frequent manual checks to identify relevant first responders, then response accuracy improves, but device complexity and operational burden increase
Solution Approach 1:
The system performs automatic identification of relevant first responders through contextual analysis of video streams and voice communications. The electronic processor autonomously extracts context information, identifies relevant participants, and highlights them in video feeds without requiring manual dispatcher intervention, thus maintaining response accuracy while eliminating the need for complex manual checking procedures
Data Source
AI summary
Systems and methods for indicating call status for relevant dispatch call participants. One example method includes receiving a voice communication associated with a talkgroup having a plurality of participants, determining context information for the participants from the voice communication, and selecting a relevant participant based on the context information. The method includes receiving a plurality of video streams, at least one of which includes an image of one of the participants. The method includes, for each of the video streams, when the video stream includes an image of the relevant participant, augmenting the video stream to include a highlighted image of the relevant participant, and assigning a priority based on the highlighted image and the context information. The method includes selecting a video stream including the highlighted image of the relevant participant based on the priorities assigned to the video streams and presenting the video stream on a display.