Abstract: Methods, systems, and devices for integrating priority keywords into an emergency incident queue for emergency communications centers are described. In some implementations, a server may provide a user interface of an emergency management application operable by a computing system of one of multiple emergency communications centers. The server may receive emergency call data, including a call location and live call audio data associated with an emergency call, and may analyze the live call audio data to detect one or more keywords. The server may associate the detected keywords with the emergency call data and may display an incident queue of emergency incidents in the user interface. The server may update at least one of the emergency incidents in the queue to display the detected keywords, which may visually indicate a priority of the emergency call data associated with the emergency call to improve dispatcher efficiency and response prioritization.

Abstract: A client-side emergency data processing system may provide low-latency and/or locally generated user interface (UI) updates to facilitate emergency response management. The system may include executing an emergency management application from a web browser operating on a call-taker computing system of an ECC, global security operations center (GSOC), and/or alarm/emergency monitoring agency. The system may include transmitting, with the web browser, at least part of the incident data from the emergency management application to a client-side application. The client-side application may determine a potential intent of a user of the emergency management application and may generate emergency response insights based on the potential intent. The insights may include an emergency management suggestion, an emergency management action, or an emergency management notification. The client-side application may use a local large language model (LLM) to generate the insights.

Abstract: Disclosed herein is an emergency response data platform that facilitates communications between private security systems, monitoring center systems, and emergency service providers. In various embodiments, the emergency response data platform provides automated flows for sharing emergency data and facilitating voice-based communication sessions between private security systems, monitoring center systems, and emergency service providers.

Abstract: A disclosed method includes: receiving a satellite-initiated alert notification where the satellite-initiated alert is sent from a mobile device; pushing emergency data associated with the satellite-initiated alert to an emergency network entity comprising mobile device location data; displaying the satellite-initiated alert notification in an alarm queue of a cloud-application graphical user interface; monitoring the satellite-initiated alert notification at the cloud-application graphical user interface for an acceptance input indicating acceptance of the satellite-initiated alert notification; and initiating a call to the emergency network if no acceptance input is received within a timeout period.

Abstract: Methods, systems, and devices for adapting artificial intelligence voice interactions of a caller with an emergency communications center are described. In some implementations, a server may receive an incoming call to an emergency or non-emergency line of an emergency communications center and may initiate artificial intelligence voice agent interaction with the caller. The server may extract call metadata, including caller identification data and audio signals, to define a caller profile comprising parameters for voice characteristics and interaction pacing. Based on the caller profile, one or more artificial intelligence voice agents may generate audio output with tailored voice characteristics, interaction pacing, and conversational patterns. During the call, the artificial intelligence voice agents may evaluate interaction data to determine a disposition score, which may trigger either continued interaction by the artificial intelligence voice agents or escalation of the call to a human operator.

Abstract: 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).

Abstract: An emergency response data system (ERDS) provides artificial intelligence (AI)-based emergency notifications to field responders using radio-based dispatches from emergency communications centers (ECCs). The ERDS receives audio data of a radio-based dispatch of emergency responders of an emergency communication, provides the audio data to an AI model with a prompt to transcribe the audio data into a radio dispatch transcript, provides the radio dispatch transcript to the AI model with a further prompt to analyze the radio dispatch transcript to extract activation notification content from the transcript, and receives operating instructions for the plurality of field responders based on the activation notification content.

Abstract: Described herein are systems, devices, methods, and media for transmitting emergency alerts, emergency services requests, and emergency data associated with emergency alerts and emergency service requests to relevant parties, such monitoring centers and emergency service providers.

Abstract: An emergency response system is operable to provide artificial intelligence (AI)-based CAD interface (e.g., read/write/action), in accordance with aspects of the disclosure. The emergency response system includes an emergency response data system (ERDS) that hosts emergency management applications that are operable on ECC computing systems. Client-side components and/or back-end components work together in concert with agentic AI (e.g., an AI agent, one or more large language models (LLMs), machine learning (ML), etc.) to extract CAD data from a screenshot of a CAD user interface (UI) operating at an ECC. An AI agent and/or LLMs may be operable to condition (e.g., format) the data into, for example, a payload that may be used to: deliver the data to another CAD system, populate a protocol tool/form integrated into the emergency management application, and/or perform CAD dispatch operations from the emergency management application.

Abstract: An emergency response data system (ERDS) integrates an artificial intelligence (AI) system into an emergency management application to generate emergency response analytics to facilitate operational efficiency of one or more ECCs. The ERDS provides an emergency management application operable by an emergency communications center (ECC) computing system to display an emergency management user interface (UI) at one or more ECCs. The ERDS stores, in one or more data structures, historical emergency response analytics. The ERDS receives, with the emergency management UI, user instructions related to the historical emergency response analytics. The ERDS provides the user instructions to the AI system. The AI system provides a response to the user instructions. The ERDS displays, with the emergency management UI, one or more data windows to visual data based on the AI system response and based on the historical emergency response analytics.

Abstract: A cloud-based emergency management system provides an instance of a cloud-based emergency response application to a first emergency dispatch center via a first graphical user interface (GUI) accessed using a web browser. The first GUI has an incident queue within a first panel showing incidents associated with respective emergency alerts. Each incident queue entry has an associated phone number from which an emergency call originated. An interactive map is positioned within a second panel and shows location markers for the incidents. Emergency data received has a device identifier and device-based hybrid location from a mobile device. The system shares an incident associated with the device identifier within the incident queue of the first emergency dispatch center with a second emergency dispatch center having a second GUI, and provides an incident location marker within the interactive map of the first GUI and the second GUI.

Abstract: Described herein are systems, devices, methods, and media for facilitating communications between emergency service providers and low acuity emergency service providers and managing low acuity responses to emergencies.

Abstract: An emergency response data system (ERDS) provides artificial intelligence (AI)-based emergency notifications to operations centers using radio-based dispatches from emergency communications center (ECC). The ERDS receives audio data of a radio-based dispatch of first responders to a location of an initiated emergency communication. The ERDS provides the audio data to an AI model with a prompt to transcribe the audio data into a radio dispatch transcript. The ERDS provides the radio dispatch transcript to the AI model with a prompt to analyze the radio dispatch transcript to extract a location of the initiated emergency communication from the radio dispatch transcript. The ERDS provides an AI-based emergency notification to an emergency response application that is operable to display the AI-based emergency notification on an operations center computing system. The AI-based emergency notification includes the location of the initiated emergency communication.

Abstract: A disclosed method implements: determining, by a cloud server, a geofence surrounding a section of a roadway at a crossing of train tracks, the geofence comprising geofence coordinates; monitoring, by the cloud server, railway sensor and telematics data related to trains running on the train tracks at the crossing; predicting that a train will approach the crossing at a predicted time; generating a warning message in response to predicting that a train will approach the crossing at a predicted time; and sending the warning message to a vehicle located within the geofence.

Abstract: A disclosed method of operating an emergency data management system includes: obtaining emergency data related to an emergency call to an emergency communication center (ECC) by a cloud server of the emergency data management system independent from the ECC; obtaining an address for the emergency call via a connectivity device located at the ECC, where the connectivity device is operatively coupled to the cloud server; matching the address to an ECC computer-aided-dispatch (CAD) system incident record address; and sending the emergency data to the ECC CAD system incident record corresponding to the matched CAD system incident record address.

Abstract: A disclosed data exchange cloud computer system includes a plurality of cloud servers. Each cloud server of the plurality of cloud-servers is operative to: provide an application programming interface operative to establish a plurality of links to a plurality of agency computer systems, where the links enable data exchange between the plurality of agency computer systems; and provide configurable state machines, operative to facilitate data exchange between the plurality of agency computer systems.

Abstract: Described herein are systems, devices, methods, and media for an emergency response data exchange system. The system provides an operations center emergency management application with a textual and/or graphical notification of emergency communications initiated on a premises managed by the operations center. The system exchanges operations center data (e.g., floorplans, video feeds, point of contact information, building access controls) with an emergency communications center (ECC) and/or with a first responder device to facilitate reducing emergency response times. The system selectively establishes communications (e.g., messaging windows) between the operations center, ECC, and/or first responder device to facilitate real-time information sharing between relevant parties of an emergency.

Abstract: A disclosed method implements sending emergency data from a cloud server to an emergency network entity, where the emergency data is received by the cloud server from a mobile device; performing a verification operation for an emergency responder device located in proximity to a location of the mobile device; sending a link to the emergency responder device in response to the emergency network entity receiving the emergency data, and the verification operation being successful; and establishing a data connection with the emergency responder device in response to selection input from the emergency responder device selecting the link.

Abstract: A disclosed method implements: receiving, by a cloud server, a plurality of video streams from a plurality of cameras located near an emergency scene; generating a combined video stream by performing graphics processing operations on the plurality of video streams; generating an overlay data layer for the combined video stream; and providing the combined video stream with the overlay data layer to an emergency communication center (ECC) via an instance of a cloud application executing on a computing device at the ECC, the cloud application provided by the cloud server.

Abstract: An emergency response data system (ERDS) integrates an AI agent network into an emergency management application to generate emergency response analytics to facilitate operational efficiency of one or more ECCs. The ERDS provides an emergency management application operable by an emergency communications center (ECC) computing system to display an emergency management user interface (UI) at one or more ECC. The ERDS stores, in one or more data structures, historical emergency response analytics. The ERDS receives, with the emergency management UI, user instructions related to the historical emergency response analytics. The ERDS provides the user instructions to the AI agent network. The ERDS generates, with the AI agent network, emergency response suggestions. The AI agent network includes a number of AI agents communicatively coupled together to analyze emergency response data and generate suggestions to facilitate operational efficiency of an ECC.