Intelligent Alerting in Public-Safety Communication Systems
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current public-safety communication systems lack an automatic and selective way to alert relevant individuals within a talkgroup about specific topics or incidents, leading to unnecessary notifications for all members, which can delay critical information dissemination during emergencies.
Innovation Solution
A method and apparatus that analyze prior conversations stored in an electronic database, comparing query terms and results to past group audio session records to identify relevant individuals and send targeted notifications, using a virtual partner server with natural language processing to determine relevance and send private alerts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If notification is sent to all talkgroup members about query results, then information dissemination is comprehensive, but unnecessary notifications are generated causing information overload
Solution Approach 1:
The system segments the talkgroup members into different categories based on their conversation history and relevance to the query topic. Instead of notifying all members uniformly, notifications are selectively sent only to those segments (individuals) who have demonstrated relevant interest or expertise in the query subject matter.
Solution Approach 2:
Different notification strategies are applied to different individuals within the talkgroup based on their local characteristics (conversation history, role, relevance). Each member receives notifications according to their specific relevance to the query, rather than applying a uniform notification policy to the entire group.
2Reliability
If manual channel switching is required to notify relevant individuals, then information accuracy is maintained, but time loss occurs during dialogue exchange
Solution Approach 1:
The system performs preliminary analysis of conversation history and participant relevance before the query results are finalized. By pre-identifying which individuals should be notified based on their past conversations and relevance to the query topic, the system eliminates the need for manual channel switching and dialogue exchange to determine who should be alerted.
Solution Approach 2:
The system automatically identifies and notifies relevant individuals without requiring manual intervention from the first responder. The automated relevance determination and notification dispatch eliminates the time-consuming manual process of switching channels and individually notifying personnel.
3Measurement precision
If selective notification based on conversation analysis is implemented, then notification precision is improved, but system complexity increases
Solution Approach 1:
The system introduces an intermediary component (the server with conversation analysis capabilities) that handles the complex task of analyzing conversation history and determining notification relevance. This intermediary processes the raw conversation data and query results to generate targeted notification lists, shielding the first responders from the complexity of the analysis process while maintaining high notification precision.
Data Source
Figure 1~2
Figure 3
AI summary
A method and apparatus for intelligently alerting individuals within a public-safety communication system is provided herein. During operation a query result is determined to have certain keywords. When this happens, prior conversations of individuals over various talkgroups are analyzed. The query terms and/or the query result are compared to the prior conversations, and a determination is made if any prior conversations are relevant to the query terms and/or the query results. If so, identities are determined for those individuals who were involved in the relevant prior conversations, and a notification of the results of the query are sent to electronic devices associated with the individuals who were involved in the relevant prior conversations.