Fire-fighting alarm receiving auxiliary method and device and storage medium

Abstract

The invention discloses a fire-fighting alarm receiving auxiliary method and device and a storage medium, and relates to the technical field of artificial intelligence, and discloses a fire-fighting alarm receiving auxiliary method, which comprises the following steps: acquiring voice call content between an alarm person and an alarm receiver in real time, and converting the voice call content into a corresponding dialogue text; inputting the dialogue text into an alarm auxiliary agent, extracting alarm key information from the dialogue text by the alarm auxiliary agent, and identifying an emotional state of the alarm person; generating alarm receiving guide information based on the alarm condition key information and / or the emotional state; and displaying the alarm receiving guide information to an alarm receiving page of the alarm receiver so as to assist the alarm receiver to complete alarm receiving operation. According to the invention, by constructing the intelligent alarm receiving auxiliary system, automatic extraction and analysis of the alarm information are realized, and the accuracy and response efficiency of the alarm receiving process are effectively improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of artificial intelligence, in particular to a fire alarm receiving assisting method and device and a storage medium. BACKGROUND

[0002] In the process of handling an alarm call, the alarm information mainly depends on the alarm receiver to obtain it through voice call, and the collection process of the alarm information is limited by the efficiency and accuracy of human operation. The operation of judging the alarm situation and completing the key elements needs to be completed by the alarm receiver based on experience, and it is difficult to quickly extract the key elements such as the event location, disaster type and trapped personnel information from unstructured dialogue in real time and accurately. Moreover, it is impossible to give corresponding auxiliary strategies in time according to the emotional state of the alarm person and the on-site danger, which is easy to lead to the omission of key information and the lag of response decision.

[0003] The above content is only used to assist in understanding the technical solutions of the present application, and does not represent the acknowledgement of the above content as prior art. SUMMARY

[0004] The main purpose of the present application is to provide a fire alarm receiving assisting method, device and storage medium, which aims to solve the technical problems of lacking means to generate effective alarm receiving guidance based on real-time alarm situation information in the process of receiving an alarm, and low accuracy of alarm information and low efficiency of alarm response.

[0005] To achieve the above purpose, the fire alarm receiving assisting method provided by the embodiments of the present application comprises: real-time acquisition of voice call content of an alarm person and an alarm receiver, and conversion of the voice call content into corresponding dialogue text; inputting the dialogue text into an alarm assisting agent, extracting alarm key information from the dialogue text by the alarm assisting agent, and identifying the emotional state of the alarm person at the same time; generating alarm receiving guidance information based on the alarm key information and / or the emotional state; displaying the alarm receiving guidance information to an alarm receiving page of the alarm receiver to assist the alarm receiver to complete the alarm receiving operation.

[0006] In an embodiment, the step of inputting the dialogue text into an alarm assisting agent, extracting alarm key information from the dialogue text by the alarm assisting agent, and identifying the emotional state of the alarm person at the same time comprises: inputting the dialogue text into an alarm assisting agent constructed based on the cooperation of a large model and an Agent process engine; calling, by the alarm auxiliary intelligent agent, an alarm case recognition model to extract the alarm case key information from the dialogue text, the alarm case key information including an alarm case occurrence location, an alarm case occurrence time, an alarm case type, trapped personnel information, and a field danger source; Meanwhile, the alarm auxiliary intelligent agent calls an emotion judgment model to determine the emotional state of the alarm person according to the emotional keywords in the dialogue text and / or the acoustic characteristics in the voice call content.

[0007] In an embodiment, the alarm receiving guidance information includes supplementary inquiry guidance, and the step of generating alarm receiving guidance information based on the alarm case key information and / or the emotional state includes: determining a corresponding alarm case element standard list according to the alarm case type in the alarm case key information; comparing the alarm case key information with the alarm case element standard list to identify missing alarm case elements; generating targeted inquiry scripts based on the missing alarm case elements as the supplementary inquiry guidance.

[0008] In an embodiment, the alarm receiving guidance information includes emotional pacification guidance, and the step of generating alarm receiving guidance information based on the alarm case key information and / or the emotional state includes: obtaining the alarm case type in the alarm case key information; According to the emotional state and the alarm case type, matching the corresponding pacifying speech from the pacifying script library as the emotional pacification guidance.

[0009] In an embodiment, the alarm receiving guidance information includes escape and self-rescue guidance, and the step of generating alarm receiving guidance information based on the alarm case key information and / or the emotional state includes: When it is identified from the alarm case key information that there are trapped personnel, determining a corresponding emergency treatment knowledge base according to the alarm case type in the alarm case key information; extracting the building type corresponding to the alarm case occurrence location, the trapped personnel information, and the field danger source from the alarm case key information to construct a retrieval query vector; According to the retrieval query vector, performing semantic matching in the emergency treatment knowledge base, and screening a preset number of self-rescue plans in descending order of matching degree; inputting the self-rescue plan into a large language model to generate the escape and self-rescue guidance conforming to the natural language expression habit through a preset prompt word.

[0010] In an embodiment, the alarm receiving guidance information includes a repeated alarm recognition result, and the step of generating alarm receiving guidance information based on the alarm case key information and / or the emotional state includes: The alarm key information of the current alarm is compared with historical alarm records in a preset time range for similarity; Based on the similarity comparison result, it is determined whether the current alarm belongs to repeated alarm, and a repeated alarm recognition result is generated.

[0011] In an embodiment, after the step of displaying the alarm guidance information to the alarm page of the alarm officer to assist the alarm officer to complete the alarm operation, the fire alarm assistance method further comprises: According to the alarm occurrence location in the alarm key information, combined with city traffic information, the road traffic state between the alarm occurrence location and the current alarm fire rescue station is obtained; Based on the road traffic state and path planning algorithm, the recommended driving route of the fire rescue station to the alarm occurrence location is calculated; The recommended driving route is associated and matched with the alarm key information, an alarm path guide containing route navigation data and alarm notice is generated, and is pushed to the alarm terminal corresponding to the fire rescue station.

[0012] In an embodiment, the step of displaying the alarm guidance information to the alarm page of the alarm officer to assist the alarm officer to complete the alarm operation comprises: Obtain the type and priority of the alarm guidance information, the type includes supplementary inquiry guidance, emotion pacification guidance, escape self-help guidance and repeated alarm recognition result; Sort the alarm guidance information of each type based on the priority, and display the sorted alarm guidance information in an interactive card layout on the alarm page.

[0013] The embodiments of the present application also provide a fire alarm assistance device, which comprises a memory, a processor and a computer program stored on the memory and executable on the processor, the computer program is configured to implement the steps of the fire alarm assistance method as described above.

[0014] The embodiments of the present application also provide a storage medium, which is a computer readable storage medium, and the storage medium stores a computer program, the computer program is executed by a processor to implement the steps of the fire alarm assistance method as described above.

[0015] The one or more technical solutions proposed in the present application have at least the following technical effects: The application realizes digital collection of police information by real-time acquisition of voice call content of the alarm person and the police officer and conversion of the voice call content into dialogue text, and effectively solves the information omission problem caused by manual listening and recording in the traditional police receiving mode. By inputting the dialogue text into the alarm auxiliary intelligent agent, the alarm auxiliary intelligent agent automatically extracts key information of the police and synchronously identifies the emotional state of the alarm person, which not only improves the accuracy and efficiency of information extraction, but also realizes real-time perception of the psychological state of the alarm person, effectively avoids police receiving delay caused by information omission or improper communication mode, reduces invalid communication time, and improves the overall response efficiency of the police receiving process. Further, based on the extracted key information of the police and the identified emotional state, corresponding police receiving guidance information is automatically generated, which can actively provide supplementary inquiry, emotional soothing and other auxiliary suggestions to help the police officer quickly grasp the information gap and make targeted response. Finally, the generated police receiving guidance information is displayed to the police receiving page in real time, and decision support is provided for the police officer in a clear and intuitive visual manner, which significantly improves the information integration ability and emergency response efficiency of the police receiving process. BRIEF DESCRIPTION OF DRAWINGS

[0016] Figure 1 A flowchart of a first embodiment of a fire-fighting police receiving auxiliary method related to an embodiment scheme of the application is shown. Figure 2 A flowchart of a second embodiment of a fire-fighting police receiving auxiliary method related to an embodiment scheme of the application is shown. Figure 3 A flowchart of a third embodiment of a fire-fighting police receiving auxiliary method related to an embodiment scheme of the application is shown. Figure 4 A flowchart of a fourth embodiment of a fire-fighting police receiving auxiliary method related to an embodiment scheme of the application is shown. Figure 5 A flowchart of a fifth embodiment of a fire-fighting police receiving auxiliary method related to an embodiment scheme of the application is shown. Figure 6 A flowchart of a sixth embodiment of a fire-fighting police receiving auxiliary method related to an embodiment scheme of the application is shown. Figure 7 A structural diagram of a fire-fighting police receiving auxiliary device related to an embodiment scheme of the application is shown.

[0017] The purpose realization, functional characteristics and advantages of the application will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0018] It should be understood that the specific embodiments described herein are only used to explain the application and not to limit the application.

[0019] For better understanding of the technical solutions of the present application, the following will be described in detail in combination with the drawings of the specification and specific embodiments.

[0020] In the process of handling the alarm call, the alarm information mainly depends on the voice call of the alarm receiving staff to obtain manually, and the collection process of the alarm information is limited by the efficiency and accuracy of manual operation. The judgment of the alarm situation and the completion of the key elements need to be completed by the alarm receiving staff based on experience, and it is difficult to extract the key elements such as the event location, disaster type and trapped personnel information from unstructured dialogue in real time and accurately. Moreover, it is impossible to give corresponding auxiliary strategies in time according to the emotional state of the alarm person and the on-site danger, which may easily lead to the omission of key information and the lag of response decision.

[0021] In view of the above problems, the present application proposes a fire alarm receiving auxiliary method, which obtains the voice call content of the alarm person and the alarm receiving staff in real time, and converts the voice call content into corresponding dialogue text; inputs the dialogue text into an alarm auxiliary agent, extracts the alarm situation key information from the dialogue text by the alarm auxiliary agent, and identifies the emotional state of the alarm person; generates alarm receiving guidance information based on the alarm situation key information and / or the emotional state; and displays the alarm receiving guidance information to the alarm receiving page of the alarm receiving staff to assist the alarm receiving staff to complete the alarm receiving operation.

[0022] The present application provides a solution, which realizes the digital collection of alarm information by obtaining the voice call content of the alarm person and the alarm receiving staff in real time and converting it into dialogue text, effectively solving the information omission problem caused by relying on manual listening and recording in the traditional alarm receiving mode. By inputting the dialogue text into an alarm auxiliary agent, the alarm auxiliary agent automatically extracts the alarm situation key information and synchronously identifies the emotional state of the alarm person, which not only improves the accuracy and efficiency of information extraction, but also realizes the real-time perception of the psychological state of the alarm person, effectively avoids the delay of alarm receiving caused by information omission or improper communication method, reduces the invalid communication time, and improves the overall response efficiency of the alarm receiving process. Further, based on the extracted alarm situation key information and the identified emotional state, the corresponding alarm receiving guidance information is automatically generated, which can actively provide supplementary inquiry, emotional soothing and other auxiliary suggestions to help the alarm receiving staff quickly grasp the information gap and make targeted response. Finally, the generated alarm receiving guidance information is displayed to the alarm receiving page in real time, providing decision support for the alarm receiving staff in a clear and intuitive visual way, which significantly improves the information integration ability and emergency response efficiency of the alarm receiving process.

[0023] It should be noted that the execution subject of the embodiment can be a computing service device with data processing, network communication and program running functions, such as a fire alarm auxiliary system or a cloud computing platform, or an electronic device, an alarm terminal device or a fire alarm auxiliary device capable of realizing the above functions. The fire alarm auxiliary system is taken as an example to illustrate the embodiment and the following embodiments.

[0024] The fire alarm auxiliary method of the first embodiment of the present application is described with reference to Figure 1 , which comprises steps S10-S40: Step S10: Real-time acquisition of the voice call content of the alarm person and the alarm officer, and conversion of the voice call content into corresponding dialogue text.

[0025] In the fire alarm process, the two-way voice stream data between the alarm person and the alarm officer after the alarm person dials the alarm phone is captured in real time through the digital relay gateway or directly accessing the media stream of the IP voice communication system, ensuring that information collection starts at the same time as the call is made, avoiding missing key information due to delay. After acquiring the voice call content, the Paraformer speech recognition model deployed in the cloud or locally can be called through the MRCP (Media Resource Control Protocol) gateway to convert the real-time voice call content between the alarm person and the alarm officer into corresponding dialogue text. The dialogue text will be used as input data for the alarm assistance agent arranged based on the large model and the Agent process engine, so that the alarm assistance agent can extract information such as the location of the alarm, the floor, and the trapped personnel information in real time and record them in the cache of the current dialogue.

[0026] Optionally, before inputting the dialogue text into the alarm assistance agent, the dialogue text is preprocessed to remove irrelevant information or interfering information, improving the accuracy and efficiency of subsequent alarm information extraction. Specifically, first, according to the role marking information in the dialogue text, the mixed dialogue text is separated according to the alarm person voice channel and the alarm officer voice channel, and the text data corresponding to the alarm person voice channel is extracted; then, based on the alarm person text data, common mood words and repeated fillers are filtered through regular expression and keyword matching, so as to obtain effective text segments with complete semantics and high information density as the main input content of the alarm assistance agent. The processed effective text segments are written into the cache of the current session in real time, and the alarm assistance agent is triggered to perform the information extraction task.

[0027] Optionally, a minimum semantic unit length threshold can also be set, and after obtaining the effective text segments, short text units with a character number less than the preset length threshold are further discarded to avoid irrelevant information entering the alarm assistance agent.

[0028] Optionally, during the preprocessing of the dialogue text, the text data corresponding to the operator's voice channel is acquired simultaneously. Based on the operator's text data and the operator's response feature library, valid questions from the operator are identified and retained. Specifically, an operator's response feature library is pre-constructed, including standard responses (such as "Hello, 119 emergency center"), procedural confirmation statements (such as "You mean there's a fire on the 6th floor?"), common guiding questions (such as "Is anyone trapped?"), and emotional reassurance statements (such as "Don't worry, speak slowly"). Through string matching or semantic vector-based similarity comparison, the operator's text data is classified and identified to confirm the statement type corresponding to each statement in the operator's response feature library. Then, based on the statement type, non-information-gathering statements (such as standard responses and emotional reassurance statements) in the operator's text data are filtered out, while valid questions related to information gathering, such as procedural confirmation statements and guiding questions, are retained. Ultimately, the effective questions asked by the dispatcher and the effective text fragments of the caller's statement are input into the alarm assistance agent. This allows the agent to reference complete contextual information when extracting key information about the incident. For example, when the dispatcher asks, "Is anyone trapped?", this statement is recognized as a valid question and retained. Subsequently, the caller answers, "Three people are trapped on the second floor." Therefore, when extracting "people trapped information," the alarm assistance agent combines the intent of the preceding question to enhance its understanding and accuracy of the context of the answer. In this way, the alarm assistance agent can refer to the dispatcher's questions when analyzing the caller's response, improving the semantic accuracy of extracting key information about the incident.

[0029] Step S20: Input the dialogue text into the alarm assisting agent, which extracts key alarm information from the dialogue text and identifies the emotional state of the person making the alarm.

[0030] It should be noted that the alarm-assisting intelligent agent is a multi-task collaborative agent system built on a large model and an agent process engine. The agent process engine orchestrates multiple functional modules for parallel scheduling. Specifically, the alarm-assisting intelligent agent includes a named entity recognition model for extracting key alarm information, a relationship extraction model for building element associations, an emotion discrimination model for assessing the emotional state of the person reporting the alarm, an alarm information difference model for detecting the completeness of key alarm information, an escape RAG engine for generating rescue guidance, and an alarm receiving MCP service for alarm verification.

[0031] Optionally, step S20 includes steps S210 to S213: Step S210: Input the dialogue text into the alarm assistance intelligent agent that is collaboratively constructed based on the large model and the Agent process engine.

[0032] Step S211: The alarm-assisting intelligent agent calls the alarm identification model to extract the key alarm information from the dialogue text. The key alarm information includes the location of the alarm, the time of occurrence, the type of alarm, information on trapped personnel, and the on-site hazard sources.

[0033] Step S212: Simultaneously, the alarm-assisting intelligent agent invokes the emotion discrimination model to determine the emotional state of the person making the alarm based on the emotion keywords in the dialogue text and / or the acoustic features in the voice call content.

[0034] In this embodiment, after receiving the dialogue text (or a pre-processed valid text fragment), the alarm-assisting intelligent agent extracts key alarm information from the dialogue text by calling a pre-trained named entity recognition model and a relation extraction model in the fire protection field. The named entity recognition model is responsible for locating entity information in the text, including but not limited to the location of the alarm (including street address, building unit, floor, and surrounding landmarks), the time of occurrence, the type of alarm (such as fire, gas leak, hazardous chemical explosion, trapped personnel), the scale of the fire (such as the size of the open flame, the spread range, the type of combustible material, and whether there is an explosion risk), information on trapped personnel (such as the number, age characteristics, whether there are any injuries, and their specific location), the on-site hazard sources, and the contact information of the person who reported the alarm. The relation extraction model constructs the relationships between entities (such as the locational relationship between "Building 3 in Community A" and "5th Floor East Unit"), and stores the extracted information in a structured manner, forming a set of alarm elements in key-value pair format. Undefined key alarm information items are marked with a "to be supplemented" label.

[0035] Simultaneously, the alarm-assisting agent invokes an emotion discrimination model based on the Transformer architecture. This model analyzes emotional keywords, sentence intensity (e.g., frequency of exclamations, density of short sentences), and logical coherence (e.g., semantic breaks, repetitions) in the dialogue text, and / or acoustic features preserved during speech-to-text conversion (e.g., speech rate parameters, intonation fluctuations, pause duration) to construct an emotion discrimination feature vector. After inputting this feature vector into the emotion discrimination model, the model outputs an emotion recognition result containing the emotion category (e.g., calm, tense, anxious, panic) and its corresponding confidence score. The emotion category with the highest confidence score is selected from the recognition results as the current emotional state of the person making the alarm. Finally, the determined emotional state and corresponding key alarm information are synchronously stored in the cache of the current session, establishing a mapping relationship between the emotional state and the key alarm information to provide data support for the subsequent generation of alarm guidance information.

[0036] Optionally, emotion discrimination can be performed based solely on text features (emotional keywords, sentence tone intensity, and logical coherence) or acoustic features; alternatively, a combination of text and acoustic features can be used to construct an emotion discrimination feature vector by fusing the two types of features, thereby improving the accuracy of emotion recognition.

[0037] It's important to note that relation extraction models are used to construct relationships between entities. This involves using algorithms to identify the logical connections between different information entities in a dialogue text, allowing fragmented information to form a meaningful whole. For example, in an alarm dialogue text, there might be a statement like, "I'm in Building 3 of Community A, and there's a fire on the 5th floor, east unit." Therefore, a named entity recognition model would first extract independent entities like "Building 3 of Community A," "5th floor, east unit," and "fire," but these entities are isolated. The role of the relation extraction model is to identify a "locational dependency" relationship between "5th floor, east unit" and "Building 3 of Community A" (i.e., "5th floor, east unit" is a specific location within "Building 3 of Community A"), and simultaneously identify an "event-location" relationship between "fire" and "5th floor, east unit," meaning the event of "fire" occurred in "5th floor, east unit."

[0038] Step S30: Generate alarm guidance information based on the key information of the alarm and / or the emotional state.

[0039] It should be noted that the alarm guidance information is an auxiliary prompt generated by the alarm assistance agent based on the extracted key information of the alarm and the identified emotional state, through the collaboration of a rule engine and a generative model. It is used to guide the alarm dispatcher to complete the alarm inquiry efficiently and accurately.

[0040] In this embodiment, after acquiring key information about the emergency and the caller's current emotional state, the alarm-assisting intelligent agent further invokes an emergency information difference model to analyze the completeness of the extracted key information. If key information is missing (e.g., the type of burning material is unclear, the risk of explosion is unconfirmed, or the number of trapped people is unknown), targeted supplementary questions are automatically generated (e.g., "What is the burning material? Is there a risk of explosion?" "How many people are trapped at the scene?"). Simultaneously, based on the caller's current emotional state, emotional reassurance guidance is generated (e.g., "Please remain calm. We have dispatched rescue personnel. Please cooperate by providing key information."). Finally, the generated alarm guidance information (such as supplementary question guidance and emotional reassurance guidance) is pushed to the alarm receiving page in real time and displayed in the auxiliary prompt area as a pop-up window or sidebar list to prompt the dispatcher to follow up with questions or provide emotional support, thereby improving the efficiency and accuracy of alarm receiving.

[0041] Furthermore, after acquiring key information about the emergency, if the alarm-assisting intelligent agent identifies that the person reporting the incident is trapped, it automatically triggers the escape RAG engine. Based on the known key information about the emergency (such as the type of emergency, building type, and contextual information such as the current location of the person reporting the incident), it retrieves matching emergency escape guidance from the emergency response knowledge base, generates corresponding rescue guidance scripts (such as "Please cover your mouth and nose with a wet towel and evacuate along the stairs in a low posture"), and pushes the rescue guidance scripts to the alarm receiving page for the dispatcher to guide the person reporting the incident in self-rescue.

[0042] In addition, after obtaining supplementary key information about the alarm, the alarm-assisting intelligent agent calls the alarm receiving MCP service to compare the key information of the current alarm with historical alarm records within a preset time range to help determine whether there are duplicate alarms. If duplicate alarms exist, the duplicate alarm identification results (including duplicate alarm records corresponding to the current alarm) are displayed on the alarm receiving page to help the alarm receiver quickly decide whether to merge and process them.

[0043] Step S40: Display the alarm receiving guidance information on the alarm receiver's alarm receiving page to assist the alarm receiver in completing the alarm receiving operation.

[0044] It should be noted that the alarm receiving page refers to the terminal interface used by the dispatcher when handling alarms, used to display incoming call information, record alarm details, and allocate resources. Displaying the alarm receiving page means presenting the generated alarm receiving guidance information in a visually appealing and prominent manner in a designated area of ​​the alarm receiving page, serving as an auxiliary tool for the dispatcher to help them communicate more efficiently and accurately with the caller, improve alarm information, and enhance the efficiency and quality of alarm handling.

[0045] Optionally, step S40 includes steps S410-S411: Step S410: Obtain the type and priority of the alarm guidance information, wherein the type includes supplementary inquiry guidance, emotional reassurance guidance, escape and self-rescue guidance, and repeated alarm identification results.

[0046] It should be noted that the types of alarm guidance information are divided according to their functional positioning. For example, supplementary inquiry guidance is used to guide the alarm receiver to obtain missing alarm information, emotional reassurance guidance is used to help alleviate the negative emotions of the alarm caller, escape and self-rescue guidance is used to provide trapped personnel with actionable self-rescue plans, and duplicate alarm identification results are used to help determine whether the current alarm is a duplicate report of a historical alarm, avoid duplicate resource allocation, and improve the response speed of alarms.

[0047] Step S411: Sort the alarm guidance information of each type according to the priority, and display the sorted alarm guidance information in an interactive card layout on the alarm receiving page.

[0048] Optionally, the card-based layout supports interactive operations by dispatchers, with each guidance card having a "processed" status marker control. Once the dispatcher confirms the processing of a guidance message, they can click the marker button to update the status of the guidance card to "processed." The system then visually fades the guidance card and automatically hides it after a delay. Simultaneously, the system records the specific adoption status and processing timestamp of each guidance message in the card for subsequent guidance effect analysis and algorithm optimization.

[0049] In this implementation, by acquiring the voice conversation between the caller and the dispatcher in real time and converting it into dialogue text, instant collection and digital processing of alarm information are achieved, ensuring that key information can be captured during the call. Furthermore, by inputting the dialogue text into an alarm-assisting intelligent agent built on a large model and agent process engine, the agent automatically extracts key alarm information and identifies the caller's emotional state, accurately extracting core alarm elements such as the location, floor, and information on trapped individuals, effectively reducing the risk of omissions during manual recording. Simultaneously, by identifying the caller's emotional state (tension, anxiety, or panic), crucial information is provided for generating targeted emotional reassurance guidance and dispatch strategies. Based on this, corresponding dispatch guidance information is generated according to the acquired key alarm information and emotional state, enabling dispatchers to quickly grasp key information gaps in emergency dispatch scenarios and respond swiftly. Finally, by displaying the generated dispatch guidance information on the dispatch page in real time, it provides decision-making assistance to dispatchers in an intuitive and prominent manner, significantly improving the accuracy and efficiency of alarm handling.

[0050] Based on the above embodiments of this application, in the second embodiment of this application, the content that is the same as or similar to that in the first embodiment can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 2 In the fire alarm receiving assistance method, the alarm guidance information includes supplementary inquiry guidance, and step S30 includes steps S310~S312: Step S310: Determine the corresponding list of standard alarm elements based on the alarm type in the key alarm information.

[0051] It should be noted that the alarm element standard list refers to a set of key information fields predefined for different alarm types, used to standardize the alarm elements that must be collected during the alarm receiving process. For example, the standard list for fire includes the location of the incident, the part of the fire that started, the nature of the combustible material, the spread of the fire, the number and location of trapped people, and the type of building.

[0052] Optionally, a crime report classification template library can be pre-established, where each template corresponds to a specific crime report type. The template defines the set of crime report elements required for that type of crime report in the form of configurable fields. When the current crime report type is determined based on the key information of the crime report, the crime report classification template library is automatically retrieved and the corresponding template is called to obtain the list of crime report elements defined therein as a comparison standard.

[0053] Step S311: Compare the key information of the police incident with the standard list of police incident elements to identify the missing police incident elements.

[0054] A differential comparison algorithm is used to match the extracted key information of the police incident with the required elements in the corresponding standard list of police incident elements one by one, and the police incident elements that are not matched are marked as missing items.

[0055] Optionally, a context-aware mechanism is introduced during the comparison process to determine whether a certain alarm element has been confirmed in previous dialogues. Specifically, the dialogue text of the current alarm is obtained, and each alarm element in the alarm element standard list is converted into a corresponding semantic requirement. For example, the semantic requirement for "number of trapped people" is "to specify the exact number of trapped people." Then, each sentence in the dialogue text is traversed to determine whether there is an expression that can satisfy the semantic requirement. If a semantically matching sentence is found, such as "There are two people in the house, and they can't get out," then the number of trapped people is identified as 2, and it can be determined that the alarm element has been confirmed and is not marked as missing. If the dialogue text only contains expressions without a specific quantity, such as "someone is trapped" or "there are still people inside," and cannot meet the requirement of "specifying the exact number," or does not mention relevant content, then the alarm element is determined to be missing.

[0056] Optionally, when contradictory information appears in the dialogue text, such as first stating "2 people are trapped" and then stating "it seems to be 3 people", the statement that is more recent and clearer shall prevail; if the exact value corresponding to the alarm element cannot be determined, the alarm element shall be marked as "to be verified" and a corresponding inquiry script shall be generated in the supplementary inquiry guidance to prompt the dispatcher to confirm, thereby avoiding misjudgment due to scattered information or ambiguous expression.

[0057] Step S312: Based on the missing police incident elements, generate targeted questioning scripts as supplementary questioning guidance.

[0058] It should be noted that missing alarm elements refer to information items that are not covered or are vaguely described in the key information of the alarm, as determined by the comparison in step S311. These include blank items that have not yet been mentioned, as well as items that are mentioned but whose information is unclear and need to be verified.

[0059] Optionally, a mapping rule library between alarm incident elements and standard inquiry scripts can be pre-established, with each alarm incident element associated with several preset question templates. When a missing element is identified, the corresponding question template is automatically invoked and adapted based on the current dialogue context. For example, if the element of "number of trapped people" is missing, the script "How many people are trapped at the scene?" can be generated; for alarm incident elements that have been mentioned but are unclear, verification scripts such as "You just mentioned that people are trapped, can you confirm the specific number?" can be generated. In addition, the generated inquiry scripts can be sorted according to the priority of alarm incident elements and displayed in a categorized manner in the auxiliary prompt area of ​​the alarm receiving page, helping dispatchers quickly locate key issues and effectively improve dialogue efficiency.

[0060] Based on the above embodiments of this application, in the third embodiment of this application, the same or similar content as the above embodiments can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 3 In the fire alarm receiving assistance method, the alarm guidance information includes emotional calming and guidance, and step S30 includes steps S320~S321: Step S320: Obtain the type of police incident from the key information of the police incident.

[0061] In generating emergency response guidance information, the first step is to determine the current emergency type from the extracted key information. It's important to note that the emergency type is a clear classification of the nature of the event according to fire emergency response procedures, including common scenarios such as residential fires, commercial fires, hazardous chemical leaks, gas explosions, and people trapped. Different emergency types differ significantly in their urgency, risk level, and psychological impact on the caller. For example, hazardous chemical leaks, due to the potential for poisoning and explosions, are more likely to trigger panic in the caller; while in the case of a small residential fire, the caller's emotional state is relatively stable. Therefore, accurately identifying the emergency type is a crucial prerequisite for selecting appropriate reassurance strategies, ensuring that the generated reassurance messages align with the risk characteristics of the current emergency and the caller's psychological needs.

[0062] Step S321: Based on the emotional state and the type of alarm, match the corresponding reassuring phrases from the reassuring phrase library as guidance for emotional reassurance.

[0063] After obtaining the caller's emotional state and the current emergency type, these are used as joint matching conditions to retrieve the most suitable reassurance statements from a pre-set reassurance script database. This database stores content according to two dimensions: emergency type and emotional state, ensuring that the generated reassurance statements not only respond to the caller's psychological state but also fit the risk characteristics of the specific emergency type. For example, when the caller's emotion is "panic" and the emergency type is "high-rise building fire," the matched output is "Please try to remain calm. The fire truck is on its way. Let's first confirm whether your location is safe." When the emotion is "anxious" and the emergency type is "elevator entrapment," the generated output is "Please don't panic. We have already notified maintenance personnel to arrive. The rescue will take a few minutes. Please check if the trapped person is unwell."

[0064] Optionally, script matching can be achieved through rule mapping, that is, pre-setting recommended scripts for different combinations of emotional states and emergency types. When the conditions of the emotional state and emergency type combination match, the corresponding preset statement is directly invoked and generated. Alternatively, dynamic generation based on semantic models can be adopted, using natural language processing technology to construct reassuring scripts that conform to the current context in real time.

[0065] In this embodiment, the generated emotional reassurance guidance will be pushed to the alarm receiving page simultaneously with other alarm receiving guidance information. It will be visually presented in the auxiliary prompt area according to the priority of different alarm receiving guidance information, which will help the dispatcher respond quickly and accurately during the alarm receiving process, improve communication efficiency and the cooperation of the alarm caller.

[0066] Based on the above embodiments of this application, in the fourth embodiment of this application, the same or similar content as the above embodiments can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 4 In the aforementioned fire alarm receiving assistance method, the alarm guidance information includes escape and self-rescue guidance, and step S30 includes steps S330~S333: Step S330: When it is identified from the key information of the alarm that someone is trapped, determine the corresponding emergency response knowledge base according to the type of alarm in the key information of the alarm.

[0067] It should be noted that the emergency response knowledge base is a collection of professional rescue knowledge categorized by type of emergency, including emergency response plans for different scenarios such as building fires, hazardous chemical leaks, and earthquakes.

[0068] When the caller is confirmed to be trapped in the key information of the emergency, such as the phrase "I am trapped inside" appearing in the dialogue text, the escape RAG engine is automatically triggered. Then, based on the type of emergency identified in the key information, the corresponding emergency response knowledge base is dynamically matched and invoked.

[0069] Step S331: Extract the building type, trapped personnel information and on-site hazard sources corresponding to the location of the incident from the key information of the incident, and construct a retrieval query vector.

[0070] Step S332: Based on the retrieval query vector, perform semantic matching in the emergency response knowledge base, and filter out a preset number of self-rescue plans according to the matching degree from high to low.

[0071] In this embodiment, a deep learning-based semantic encoding model is used to convert key information about the emergency, such as building type, characteristics of trapped personnel, and hazard source information, into semantic vectors, thereby obtaining the retrieval query vector. Specifically, a pre-trained BERT model is used to uniformly encode various features, generating vector representations with rich semantic information. Then, in the retrieval stage, the cosine similarity between the retrieval query vector and the self-rescue plan vectors in the emergency response knowledge base is calculated. Based on the similarity score, the matched self-rescue plans are ranked, and the top preset number of self-rescue plans with the highest scores are retained to form a candidate plan set.

[0072] Step S333: Input the self-rescue plan into the large language model, and generate the escape and self-rescue guidance that conforms to the natural language expression habits through preset prompt words.

[0073] In this embodiment, the preset number of self-rescue plans (i.e., the candidate plan set) selected in step S332 are integrated into the input text, and the large language model is optimized for expression by combining preset prompts. The preset prompts explicitly require that the output content should be easy-to-understand, conversational guidance statements, avoiding the use of professional terminology or complex sentence structures, to ensure that the alarm caller can quickly understand and execute them. At the same time, key information about the emergency is introduced into the preset prompts as contextual constraints, enabling the large language model to generate personalized guidance based on specific circumstances. For example, when information such as "there are children" or "people with mobility difficulties" is identified as trapped persons, targeted suggestions such as "take good care of the children to prevent them from getting lost" or "try to stay close to the door or window to wait for rescue" are automatically added. Finally, the generated escape and self-rescue guidance will be pushed to the alarm receiving page simultaneously with other alarm guidance information, providing the alarm receiver with a professional self-rescue plan that can be relayed immediately, effectively improving the remote guidance effect for trapped persons, helping them quickly master self-rescue methods, buying time for rescue, and increasing the success rate of self-rescue.

[0074] For example, the structured self-rescue plan "advance in a low posture, cover your mouth and nose with a wet towel, and evacuate down the evacuation stairs" can be transformed into "bend over, cover your mouth and nose with a wet towel or wet clothes, run down the stairs, and never take the elevator."

[0075] Based on the above embodiments of this application, in the fifth embodiment of this application, the same or similar content as the above embodiments can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to...Figure 5 In the fire alarm receiving assistance method, the alarm guidance information includes the result of repeated alarm identification, and step S30 includes steps S340~S341: Step S340: Compare the key information of the current alarm with the historical alarm records within a preset time range.

[0076] Step S341: Based on the similarity comparison results, determine whether the current alarm is a duplicate alarm and generate a duplicate alarm identification result.

[0077] After obtaining key information about the current emergency, the alarm receiving MCP service is invoked to extract core elements of the current emergency, including key fields such as the location of the emergency, the type of emergency, the time of occurrence, the building type, the description of the burning material, and the on-site hazard sources. Then, based on these core elements, historical alarm records are retrieved within a preset time window (e.g., the past 1 to 3 hours), and a multi-dimensional similarity calculation method that integrates semantics and rules is used for matching analysis. Specifically, the textual description information (e.g., "Fire in Building 3 of Community A," "Heavy smoke") is first converted into a semantic vector using a large model, and then its cosine similarity with each historical alarm record is calculated. Simultaneously, a rule engine can be further combined to perform precise or fuzzy matching of key fields, such as determining whether the geographical distance between the current emergency and the location of the alarm in historical alarm records is less than a preset distance threshold (e.g., 50 meters), and whether the emergency types are consistent. Finally, a comprehensive similarity score is generated by weighted fusion of semantic similarity and rule matching scores, serving as the basis for judgment.

[0078] If the overall similarity score exceeds the preset similarity threshold, the current alarm is identified as a duplicate alarm, and an identification result containing the matching historical alarm record number, the location of the alarm, the event, and the similarity score is generated; if it does not exceed the preset similarity threshold, it is identified as a new alarm.

[0079] The duplicate alarm identification result is also pushed to the alarm receiving page in real time and synchronously along with other alarm receiving guidance information, such as "Suspected duplicate alarm, matching record: J123456", to prompt and assist the alarm receiver to quickly determine whether to merge the alarms, avoid duplicate dispatch of rescue resources, and improve alarm receiving efficiency and the accuracy of handling decisions.

[0080] Based on the above embodiments of this application, in the sixth embodiment of this application, the same or similar content as the above embodiments can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 6 After step S40, the fire alarm receiving assistance method further includes steps S50 to S70: Step S50: Based on the location of the incident in the key information of the incident and combined with urban traffic information, obtain the road traffic status between the location of the incident and the fire and rescue station that received the alarm.

[0081] After extracting key information about the incident, the system automatically analyzes the geographical coordinates of the incident location. Then, by connecting to the city's traffic management system or a third-party map service platform, it obtains real-time traffic conditions for each road segment between the receiving rescue station and the incident location. This includes dynamic information such as road congestion, road construction, traffic light waiting times, traffic restrictions, and emergencies (such as traffic accidents or temporary road closures). This forms a complete road traffic situation map, providing accurate real-time road condition data for subsequent route planning.

[0082] Step S60: Based on the road traffic status and route planning algorithm, calculate the recommended route for the fire and rescue station to reach the location of the emergency.

[0083] In this embodiment, a shortest-time-first path planning algorithm (such as Dijkstra's algorithm or A* algorithm) is employed. This algorithm comprehensively considers road length, real-time congestion, and fire truck traffic characteristics (such as turning radius and avoidance of restricted areas) to calculate the optimal route from the fire station to the location of the emergency, ensuring that rescue vehicles can arrive at the scene in the shortest possible time. Furthermore, one or two backup routes can be generated during route calculation to handle unexpected traffic changes along the way.

[0084] Step S70: Associate and match the recommended driving route with the key information of the emergency, generate a dispatch route guide containing route navigation data and dispatch precautions, and push it to the dispatch terminal of the corresponding fire and rescue station.

[0085] In this embodiment, the calculated recommended driving route is integrated with the extracted key information of the emergency to generate a dispatch route guide. This guide includes navigation data (such as intersections, turn prompts, and estimated travel time) and dispatch precautions, such as "Fire in a high-rise residential building, please carry climbing and demolition equipment," "Gas leak at the scene, take precautions against explosions," and "Three people are trapped on the second floor, prioritize searching the east-facing rooms." Finally, the generated dispatch route guide is pushed in real-time to the vehicle-mounted terminals or mobile law enforcement equipment of the corresponding fire and rescue stations through the command and dispatch system, achieving seamless integration of alarm information and dispatch actions, and improving the speed of emergency response and the targeted nature of on-site handling.

[0086] This application provides a fire alarm receiving auxiliary device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the fire alarm receiving auxiliary method in the above embodiment 1.

[0087] The following is for reference. Figure 7 The diagram illustrates a structural schematic of a fire alarm receiving auxiliary device suitable for implementing embodiments of this application. The fire alarm receiving auxiliary device in the embodiments of this application may include various hardware and software components for implementing fire alarm receiving auxiliary methods. Figure 7 The fire alarm receiving auxiliary equipment shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0088] like Figure 7 As shown, the fire alarm receiving auxiliary equipment may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM) 1004. The RAM 1004 also stores various programs and data required for the operation of the fire alarm receiving auxiliary equipment. The processing unit 1001, the ROM 1002, and the RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, touchscreens, touchpads, keyboards, etc.; output devices 1008 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 1003 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1009. Communication device 1009 allows the fire alarm receiving auxiliary equipment to communicate wirelessly or wiredly with other equipment to exchange data. Although the figures show fire alarm receiving auxiliary equipment with various systems, it should be understood that implementation or possession of all the systems shown is not required. More or fewer systems may be implemented alternatively.

[0089] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from read-only memory 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0090] The fire alarm receiving auxiliary equipment provided in this application, employing the fire alarm receiving auxiliary method in the above embodiments, can solve the technical problems of lacking effective means to generate effective alarm receiving guidance based on real-time alarm information, and low accuracy of alarm information and low alarm response efficiency during the alarm receiving process. Compared with the prior art, the beneficial effects of the fire alarm receiving auxiliary equipment provided in this application are the same as those of the fire alarm receiving auxiliary method provided in the above embodiments, and other technical features in this fire alarm receiving auxiliary equipment are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0091] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0092] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0093] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, which are used to execute the fire alarm receiving assistance method in the above embodiments.

[0094] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, radio frequency (RF), etc., or any suitable combination thereof.

[0095] The aforementioned computer-readable storage medium may be included in the fire alarm receiving auxiliary equipment; or it may exist independently and not be assembled into the fire alarm receiving auxiliary equipment.

[0096] The aforementioned computer-readable storage medium carries one or more programs. When these programs are executed by the fire alarm receiving auxiliary equipment, the fire alarm receiving auxiliary equipment: acquires in real time the voice communication content between the alarm caller and the dispatcher, and converts the voice communication content into corresponding dialogue text; inputs the dialogue text into an alarm assistance intelligent agent, which extracts key alarm information from the dialogue text and simultaneously identifies the emotional state of the alarm caller; generates alarm receiving guidance information based on the key alarm information and / or the emotional state; and displays the alarm receiving guidance information on the dispatcher's alarm receiving page to assist the dispatcher in completing the alarm receiving operation.

[0097] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0098] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0099] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0100] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described fire alarm receiving assistance method. This solves the technical problems of lacking effective alarm receiving guidance based on real-time alarm information, and low accuracy of alarm information and low alarm response efficiency during the alarm receiving process. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the fire alarm receiving assistance method provided in the above embodiments, and will not be repeated here.

[0101] This application provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the fire alarm receiving assistance method described above.

[0102] The computer program product provided in this application can solve the technical problems of lacking effective alarm guidance based on real-time alarm information, and low accuracy of alarm information and low alarm response efficiency during the alarm receiving process. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as the beneficial effects of the fire alarm receiving assistance method provided in the above embodiments, and will not be repeated here.

[0103] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent scope of this application.

[0104] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0105] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method.

[0106] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A fire alarm receiving assistance method, characterized in that, The fire alarm receiving assistance method includes: The system acquires the voice conversation between the person making the alarm and the operator in real time, and converts the voice conversation into corresponding dialogue text. The dialogue text is input into the alarm assistance agent, which extracts key alarm information from the dialogue text and identifies the emotional state of the person making the alarm. Based on the key information of the incident and / or the emotional state, generate alarm guidance information; The alarm reception guidance information is displayed on the alarm receiver's alarm reception page to assist the alarm receiver in completing the alarm reception operation.

2. The fire alarm receiving assistance method as described in claim 1, characterized in that, The step of inputting the dialogue text into the alarm-assisting intelligent agent, and having the alarm-assisting intelligent agent extract key alarm information from the dialogue text and simultaneously identify the emotional state of the person making the alarm, includes: The dialogue text is input into an alarm-assisted intelligent agent that is collaboratively constructed based on a large model and an Agent process engine; The alarm-assisting intelligent agent invokes the alarm identification model to extract the key information of the alarm from the dialogue text. The key information of the alarm includes the location of the alarm, the time of the alarm, the type of alarm, information of the trapped personnel, and the sources of danger at the scene. Simultaneously, the alarm-assisting intelligent agent invokes an emotion discrimination model to determine the emotional state of the person making the alarm based on emotion keywords in the dialogue text and / or acoustic features in the voice call content.

3. The fire alarm receiving assistance method as described in claim 1, characterized in that, The alarm reception guidance information includes supplementary questioning guidance. The step of generating alarm reception guidance information based on the key information of the alarm and / or the emotional state includes: Based on the type of police incident in the key information of the police incident, determine the corresponding standard list of police incident elements; The key information of the police incident is compared with the standard list of police incident elements to identify the missing police incident elements; Based on the missing police incident elements, a targeted questioning script is generated as a guide for the supplementary inquiry.

4. The fire alarm receiving assistance method as described in claim 1, characterized in that, The alarm reception guidance information includes emotional reassurance guidance. The step of generating alarm reception guidance information based on the key alarm information and / or the emotional state includes: Obtain the type of police incident from the key information of the police incident; Based on the emotional state and the type of incident, corresponding reassuring phrases are matched from the reassuring phrase library as guidance for emotional reassurance.

5. The fire alarm receiving auxiliary method as described in claim 1, characterized in that, The alarm guidance information includes escape and self-rescue instructions. The step of generating the alarm guidance information based on the key alarm information and / or the emotional state includes: When it is identified from the key information of the alarm that people are trapped, the corresponding emergency response knowledge base is determined according to the type of alarm in the key information of the alarm; Extract the building type, trapped personnel information, and on-site hazards corresponding to the location of the incident from the key information of the incident, and construct a retrieval query vector; Based on the retrieval query vector, semantic matching is performed in the emergency response knowledge base, and a preset number of self-rescue plans are selected according to the matching degree from high to low. The self-rescue plan is input into a large language model, and the escape and self-rescue guidance that conforms to the natural language expression habits is generated through preset prompt words.

6. The fire alarm receiving assistance method as described in claim 1, characterized in that, The alarm guidance information includes the result of repeated alarm identification. The step of generating alarm guidance information based on the key alarm information and / or the emotional state includes: The key information of the current alarm is compared with the similarity of historical alarm records within a preset time range; Based on the similarity comparison results, it is determined whether the current alarm is a duplicate alarm, and a duplicate alarm identification result is generated.

7. The fire alarm receiving auxiliary method as described in claim 1, characterized in that, After the step of displaying the alarm guidance information to the alarm receiver's alarm receiving page to assist the alarm receiver in completing the alarm receiving operation, the fire alarm receiving assistance method further includes: Based on the location of the incident in the key information of the incident, and combined with urban traffic information, the road traffic status between the location of the incident and the fire and rescue station that received the alarm is obtained; Based on the road traffic conditions and route planning algorithm, calculate the recommended route for the fire and rescue station to reach the location of the emergency. The recommended driving route is associated and matched with the key information of the emergency, generating a dispatch route guide that includes route navigation data and dispatch precautions, and is pushed to the dispatch terminal of the corresponding fire and rescue station.

8. The fire alarm receiving assistance method as described in claim 1, characterized in that, The step of displaying the alarm guidance information to the alarm receiver's alarm receiving page to assist the alarm receiver in completing the alarm receiving operation includes: The type and priority of the alarm guidance information are obtained, and the type includes supplementary questioning guidance, emotional comfort guidance, escape and self-rescue guidance, and repeated alarm identification results; The alarm guidance information of each type is sorted according to the priority, and the sorted alarm guidance information is displayed in an interactive card layout on the alarm receiving page.

9. A fire alarm receiving auxiliary device, characterized in that, The fire alarm receiving auxiliary device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the fire alarm receiving auxiliary method as described in any one of claims 1 to 8.

10. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, it implements the steps of the fire alarm receiving assistance method as described in any one of claims 1 to 8.

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