| CPC G06Q 50/265 (2013.01) [G06Q 10/06311 (2013.01)] | 24 Claims |
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1. A method for dispatching emergency responders, the method comprising
obtaining, by one or more processors, responder profiling data comprising attributes of a plurality of responders, the attributes comprising respective locations of the responders;
obtaining, by the one or more processors from one or more monitoring devices, real-time incident data derived from monitoring a target environment, the real-time incident data comprising an indication of a current condition of the target environment;
obtaining, by the one or more processors, historical incident data comprising an indication of at least one warning condition of the target environment, the warning condition being a past condition at which a past incident event occurred;
identifying, by the one or more processors, a current incident event in the real-time incident data using a machine learning model, the machine learning model correlating the current condition with the warning condition of the target environment;
identifying, by the one or more processors in response to the current condition correlating with the warning condition, a location of the current incident event based on receiving a unique identifier from an addressable panel arranged in the target environment and comparing the unique identifier to a plurality of unique identifiers in a database comprising locations of addressable panels and associated unique identifiers;
extracting, by the one or more processors, current incident data comprising information about the current incident event from the real-time incident data using the machine learning model, the machine learning model filtering out irrelevant data from the real-time incident data;
assigning, by the one or more processors, according to the responder profiling data, the location of the current incident event, and the current incident data, a responder to the current incident event using the machine learning model based on the location of the current incident event and the respective locations of the responders, the machine learning model matching the information about the current incident event with the attributes of the responders;
generating, by the one or more processors, according to the current incident data, a response plan comprising a workflow model for the assigned responder using the machine learning model, the workflow model comprising a sequence of one or more tasks and one or more resources for the assigned responder;
obtaining, by the one or more processors from the one or more monitoring devices, feedback from the assigned responder as the responder is addressing the current incident event at the target environment; and
updating, by the one or more processors, according to the feedback, the assigned responder and the response plan using the machine learning model.
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