Intelligent agent, emergency communication intelligent scheduling method, electronic equipment and readable medium

Abstract

The invention provides an intelligent agent, an emergency communication intelligent scheduling method, electronic equipment and a readable medium, and belongs to the technical field of communication. The intelligent agent is configured with models corresponding to basic functions such as intention recognition, content generation, information perception, data analysis, resource scheduling and interaction management; the intelligent agent can dynamically arrange the model to realize corresponding service functions, such as preprocessing of collected information, resource allocation and decision support, personnel scheduling and task allocation, real-time feedback and adjustment and the like. In an emergency communication scene, the intelligent agent can automatically combine collected information to carry out analysis of emergency association, demands and the like, dynamic distribution and real-time adjustment of the whole process of personnel and resources are realized, the scheduling time is shortened on the basis of ensuring accuracy and stability, the scheduling efficiency in the emergency communication scene is improved, and the labor cost investment is reduced.

Description

Technical Field

[0001] This disclosure belongs to the field of communication technology, specifically relating to intelligent agents, emergency communication intelligent dispatch methods, electronic devices, and computer-readable media. Background Technology

[0002] Emergency communications are used to maintain smooth and stable communication during natural disasters and emergencies, and can also ensure the timely and accurate dissemination of emergency information within a specific scope.

[0003] Currently, emergency communications typically require a large number of on-duty personnel, and based on this, a deployment is made using monitoring and early warning systems and resource planning to generate command and dispatch schemes.

[0004] In the existing emergency communication and dispatch system, on the one hand, a large number of on-duty personnel are required, and on the other hand, the accuracy and efficiency of emergency information extraction and editing, as well as the generation of command and dispatch plans, are unstable, which affects the implementation effect of emergency communication. Summary of the Invention

[0005] The purpose of this disclosure is to provide an intelligent agent, an emergency communication intelligent scheduling method, an electronic device, and a computer-readable medium that can shorten scheduling time, improve efficiency, and reduce labor costs in emergency communication scenarios while ensuring accuracy and stability.

[0006] To solve the above-mentioned technical problems, this disclosure is implemented as follows:

[0007] In a first aspect, this disclosure provides an intelligent agent configured with a model corresponding to at least one of the basic functions of intent recognition, content generation, information perception, data analysis, resource scheduling, and interaction management. The intelligent agent implements at least one service function through dynamic model orchestration. This service function may include: preprocessing of collected information, preprocessing collected information related to emergency communication scenarios, including at least one of filtering, verification, completion, expansion, multi-source fusion, and correlation analysis; resource allocation and decision support, generating support information for resource allocation and decision-making in emergency communication scenarios based on the collected information, including at least one of emergency communication resource demand reports and emergency communication resource allocation schemes; personnel scheduling and task allocation, performing at least one of personnel scheduling arrangements, emergency communication task allocation, and coordination based on the support information; and real-time feedback and adjustment, based on at least one of the basic functions of information perception, data analysis, content generation, resource scheduling, and interaction management, dynamically monitoring and evaluating collected information related to emergency communication scenarios, adjusting resource allocation, adjusting personnel scheduling, and adjusting task allocation.

[0008] Optionally, preprocessing includes: screening, where preprocessing of collected information includes filtering information related to emergency communication scenarios based on information perception and at least one of preset emergency event types and preset emergency keywords; verification, where preprocessing of collected information includes performing semantic analysis and verifying the authenticity of collected information based on data analysis; completion, where preprocessing of collected information includes completing missing content in collected information based on data analysis; expansion, where preprocessing of collected information includes interpretive expansion of collected information based on information perception and data analysis; multi-source fusion, where preprocessing of collected information includes integrating collected information from multiple data sources based on data analysis; and correlation analysis, where preprocessing of collected information includes performing correlation analysis and risk prediction in emergency communication scenarios based on data analysis of collected information from multiple data sources.

[0009] Optionally, the emergency communication resource demand report describes the emergency communication resource demand of each area in the emergency communication scenario; the emergency communication resource allocation scheme includes an allocation scheme for at least one available resource generated based on the emergency communication resource demand report and according to resource allocation factors, including at least one of resource availability, transportation time, and emergency communication priority.

[0010] Optionally, personnel scheduling includes scheduling target personnel to corresponding emergency communication tasks based on task parameters and personnel information; task parameters include at least one of task type, task complexity, and task priority; emergency communication task allocation and coordination includes decomposing emergency communication tasks into multiple sub-tasks according to task type and task complexity, and coordinating during the execution of multiple sub-tasks.

[0011] Optionally, dynamic monitoring and evaluation includes real-time monitoring and evaluation based on at least one of the following: emergency communication network status, emergency resource usage, and task execution progress status; resource allocation adjustment includes adjusting the emergency communication resource allocation plan based on real-time monitoring and evaluation; personnel scheduling adjustment includes adjusting personnel scheduling arrangements based on real-time monitoring and evaluation; and task allocation adjustment includes adjusting the allocation and coordination of emergency communication tasks based on real-time monitoring and evaluation.

[0012] Optionally, the information collected may include at least one of the following: environmental information, personnel information, equipment status information, resource inventory information, and task execution information.

[0013] Optionally, the agent uses historical information to train the model, enabling the model to perform the corresponding basic functions; the model includes a large model and a small model.

[0014] Secondly, this disclosure provides an intelligent scheduling method for emergency communication. The method is implemented through an intelligent agent as described in the first aspect. The method may include: performing intent recognition in response to emergency communication demand information to obtain at least one intent result in the emergency communication scenario; dynamically orchestrating the model according to the intent result; and implementing the service function corresponding to each intent result based on basic functions.

[0015] Thirdly, this disclosure provides an electronic device including a processor, a memory, and a program or instructions stored in the memory and executable on the processor, wherein the program or instructions, when executed by the processor, implement the steps of the emergency communication intelligent dispatch method of the second aspect.

[0016] Fourthly, this disclosure provides a computer-readable medium on which a program or instructions are stored, which, when executed by a processor, implement the steps of the emergency communication intelligent scheduling method of the second aspect.

[0017] Fifthly, this disclosure provides a chip including a processor and a communication interface coupled to the processor, the processor being used to run programs or instructions to implement the steps of the emergency communication intelligent scheduling method as described in the second aspect.

[0018] In a sixth aspect, this disclosure provides a computer program product containing instructions that, when run on a computer, cause the computer to perform steps such as those for implementing the emergency communication intelligent dispatch method as described in the second aspect.

[0019] The intelligent agent, emergency communication intelligent dispatch method, electronic device, and computer-readable medium disclosed herein are configured with models corresponding to basic functions such as intent recognition, content generation, information perception, data analysis, resource scheduling, and interaction management. The intelligent agent can dynamically orchestrate the models to achieve corresponding service functions, such as preprocessing of collected information, resource allocation and decision support, personnel scheduling and task assignment, and real-time feedback and adjustment. In emergency communication scenarios, this intelligent agent can automatically combine collected information to perform emergency correlation and demand analysis, achieving dynamic allocation and real-time adjustment of personnel and resources throughout the entire process. While ensuring accuracy and stability, it shortens dispatch time, improves dispatch efficiency in emergency communication scenarios, and reduces labor costs. Attached Figure Description

[0020] Figure 1 This is one of the schematic diagrams of the intelligent agent architecture provided in the embodiments of this disclosure;

[0021] Figure 2 This is a second schematic diagram of the intelligent agent architecture provided in the embodiments of this disclosure;

[0022] Figure 3A flowchart illustrating the steps of the intelligent emergency communication dispatch method provided in this embodiment of the disclosure;

[0023] Figure 4 A flowchart illustrating the agent-based intelligent dispatching method for emergency communication provided in this embodiment of the disclosure;

[0024] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present disclosure;

[0025] Figure 6 This is a hardware schematic diagram of an electronic device provided in an embodiment of the present disclosure. Detailed Implementation

[0026] The technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this disclosure. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.

[0027] The terms "first," "second," etc., used in this disclosure and in the claims are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that embodiments of this disclosure can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0028] Figure 1 This is one of the schematic diagrams of the intelligent agent 100 architecture provided in an embodiment of this disclosure. For example... Figure 1 As shown, the intelligent agent 100 can be divided into basic functions 110 and service functions 120 based on its functional implementation.

[0029] At the level of basic function 110, the intelligent agent 100 is configured with models corresponding to one or more basic functions, such as intent recognition 111, content generation 112, information perception 113, data analysis 114, resource scheduling 115, and interaction management 116. Each basic function 110 can be implemented by one model or by multiple models. Each model can support one basic function 110 or multiple basic functions 110.

[0030] In an optional embodiment of this disclosure, intent recognition 111 can be a basic function 110 for recognizing the intent of emergency communication personnel. Based on intent recognition 111, it supports the subsequent execution of related basic functions based on the recognition results. Emergency communication personnel can be on-duty personnel, on-site workers, etc. An existing intent recognition model in a specific field can be configured to support intent recognition 111, or the intent recognition model can be fine-tuned and configured to support intent recognition 111. Alternatively, multiple intent recognition models can be configured to fuse the recognition results to support intent recognition. The object of intent recognition 111 can be text descriptions, voice descriptions, captured images, etc., submitted by emergency communication personnel; this disclosure does not impose specific limitations on this.

[0031] In an optional embodiment of this disclosure, content generation 112 may be based on intent recognition 111, and output content according to corresponding templates, formats or other requirements.

[0032] In an optional embodiment of this disclosure, information perception 113 may be used to perceive and acquire information related to the internal acquisition terminal, the external network terminal and the emergency communication scenario in an emergency communication scenario, so as to support the model training of the intelligent agent 100 and the execution of functions based on model orchestration.

[0033] In an optional embodiment of this disclosure, data analysis 114 may be based on intent recognition 111, and based on the analysis requirements pointed to by the intent, analyze the information related to the emergency communication scenario obtained by information perception 113, such as analysis of different aspects such as scenario relevance, information accuracy, and information relevance.

[0034] In an optional embodiment of this disclosure, resource scheduling 115 may be based on intent recognition 111, and based on the operational requirements pointed to by the intent, according to the information related to the emergency communication scenario obtained by information perception 113, and according to the analysis results of data analysis 114, to command and schedule the actual operation in the emergency communication scenario, which may include tasks, personnel, resources, etc.; and may also be dynamically adjusted according to feedback information from the operation site.

[0035] In an optional embodiment of this disclosure, the interaction management 116 can be based on resource scheduling 115, managing internal instruction issuance, feedback reception, and external system interface specifications, processes, and quality during actual operation. Instruction issuance can be based on resource scheduling 115, accurately and promptly sending scheduling information to emergency communication personnel. Feedback reception can be the timely and accurate reception of on-site environmental information, personnel feedback, etc. Additionally, auxiliary information can be obtained from external interface systems, and internal information of the intelligent agent 100 can be fed back to external systems to achieve internal and external information sharing and collaborative work.

[0036] In this embodiment of the disclosure, the basic function 110 described above is only an example. Those skilled in the art can construct examples of some or all of the basic functions 110 according to actual needs, and can also extend other basic functions 110 based on some or all of the basic function 110 examples. This embodiment of the disclosure does not impose specific limitations in this regard.

[0037] At the service function 120 level, the intelligent agent 100 can implement at least one service function 120 through a dynamic orchestration model. Through the dynamic orchestration model, the basic functions corresponding to the model can be flexibly combined according to application scenarios and business needs, thereby achieving more targeted and complex service functions 120. Specifically, service functions 120 can be orchestrated in real-time, or based on historical application scenarios and business needs, they can invoke historical orchestration combinations, and basic functions can be added, deleted, or changed based on historical orchestration combinations. For example, service function 120 may include preprocessing of collected information 121, resource allocation and decision support 122, personnel scheduling and task allocation 123, and real-time feedback and adjustment 124.

[0038] In an optional embodiment of this disclosure, the preprocessing 121 of the collected information preprocesses the collected information related to the emergency communication scenario. The preprocessing includes at least one of screening, verification, completion, expansion, multi-source fusion, and correlation analysis.

[0039] In this embodiment of the disclosure, the collected information may be related to emergency communication scenarios. Preprocessing of the collected information 121 refers to preprocessing the collected information by arranging the basic functions 110. For example, the collected information can be obtained by information perception 113 based on the collection intent identified by intent recognition 111, or information perception 113 can also perform filtering according to preset collection requirements; the collected information can be analyzed by data analysis 114 based on the analysis intent identified by intent recognition 111 to obtain correlation characteristics between the collected information, or data analysis 114 can also perform correlation analysis according to preset analysis requirements; verification, completion, expansion, and multi-source fusion of the collected information can be performed similarly. In practical applications, other basic functions 110 may also be involved, and this embodiment of the disclosure does not impose specific limitations on them.

[0040] In an optional embodiment of this disclosure, the resource allocation and decision support 122 generates support information for resource allocation and decision-making in emergency communication scenarios based on the collected information. The support information includes at least one of an emergency communication resource demand report and an emergency communication resource allocation scheme.

[0041] In this embodiment, resource allocation and decision support 122 refers to generating support information for resource allocation and decision-making in emergency communication scenarios by arranging the basic functions 110 based on the collected information. Resources can include communication equipment, rescue supplies, and personnel; the support information for resource allocation and decision-making can be analysis information on resource needs and available resources, thereby supporting allocation decisions regarding resource origin and destination. For example, based on the analysis intent identified by intent recognition 111, data analysis 114 can analyze the emergency situation and disaster conditions, or data analysis 114 can analyze according to preset analysis requirements to obtain an emergency communication resource demand report; alternatively, based on the analysis intent identified by intent recognition 111, data analysis 114 can allocate available resources based on the analysis and evaluation of resource needs, or data analysis 114 can analyze according to preset analysis requirements to obtain an emergency communication resource allocation plan. In practical applications, other basic functions 110 may also be involved, and this embodiment does not impose specific limitations on them.

[0042] In an optional embodiment of this disclosure, personnel scheduling and task allocation 123 involves at least one of personnel scheduling arrangements, emergency communication task allocation and coordination based on supporting information.

[0043] In this embodiment, personnel scheduling and task allocation 123 refers to the scheduling and decision-making of on-site operations by arranging basic functions 110 based on obtained support information. This mainly includes the scheduling of personnel and the allocation of specific emergency communication tasks. Personnel scheduling can be based on static and dynamic attributes such as age, gender, profession, and historical experience, and dynamic attributes such as real-time location and real-time physical condition, using data analysis 114 and resource scheduling 115. The execution order and method of different emergency communication tasks can be allocated based on the type, region, and personnel corresponding to the emergency communication task, and multiple emergency communication tasks can be combined or split. The above process can be triggered based on the intent identified by intent recognition 111 or by preset scheduling and allocation requirements. In practical applications, other basic functions 110 may also be involved, and this embodiment does not impose specific limitations on them.

[0044] In an optional embodiment of this disclosure, the real-time feedback and adjustment 124 performs at least one of the following: dynamic monitoring and evaluation of collected information related to emergency communication scenarios, resource allocation adjustment, personnel scheduling adjustment, and task allocation adjustment.

[0045] In this embodiment, real-time feedback and adjustment 124 refers to the real-time feedback and adjustment of on-site operation scheduling and decision-making through the arrangement of basic functions 110 during on-site operations, based on personnel scheduling, emergency communication task allocation and coordination. This can be achieved by dynamically monitoring and evaluating relevant information at the work site based on information perception 113, data analysis 114, etc., and by adjusting resource allocation, personnel scheduling, and task allocation based on the results of dynamic monitoring and evaluation based on data analysis 114, resource scheduling 115, etc. These processes can be triggered based on the intent identified by intent recognition 111, or by preset feedback and adjustment requirements. In practical applications, other basic functions 110 may also be involved, and this embodiment does not impose specific limitations on them.

[0046] In this embodiment of the disclosure, the above-mentioned service function 120 is only used as an example. Those skilled in the art can construct examples of some or all of the service functions 120 according to actual needs, and can also extend other service functions 120 based on the examples of some or all of the service functions 120. This embodiment of the disclosure does not impose specific limitations in this regard.

[0047] Figure 2 This is a second schematic diagram of the intelligent agent 200 architecture provided in an embodiment of this disclosure. For example... Figure 2 As shown, the intelligent agent 200 can be divided into basic functions 210 and service functions 220 based on functional implementation.

[0048] At the level of basic function 210, the intelligent agent 200 is configured with one or more models corresponding to basic functions such as intent recognition 211, content generation 212, information perception 213, data analysis 214, resource scheduling 215, and interaction management 216.

[0049] In this embodiment of the disclosure, the aforementioned basic function 210 can be referred to in the preceding description. Figure 1 The basic functions of 110 are described below to avoid repetition.

[0050] In an optional embodiment of this disclosure, the agent 200 uses historical information to train the model, enabling the model to perform corresponding basic functions; the model includes a large model and a small model.

[0051] In this embodiment, the basic functions 210 required for the intelligent agent 200 to achieve the desired functionality can be obtained by configuring corresponding models or by training each model specifically using collected historical information, thereby realizing the expected basic functions of the subsequent service functions 220. Furthermore, the intelligent agent 200 supports multi-turn dialogue, enabling a more accurate understanding of the intentions of emergency communication personnel. Simultaneously, the intelligent agent 200 possesses dynamic orchestration capabilities, allowing it to dynamically orchestrate the basic functions 210 based on models according to changing needs, encapsulating them into corresponding service functions 220. For example, for emergency drill requirements in emergency communication scenarios, it can intelligently orchestrate basic functions 210 such as information perception 213, content generation 212, and resource scheduling 215 to formulate emergency drill plans that meet the needs of emergency drills.

[0052] In this embodiment, the model may include a large model and a small model. The difference between the large and small models typically lies in the number of parameters, inference performance, and computational resource consumption. Basic functions 210 can be implemented using different large and small models; for example, intent recognition 211 and content generation 212 can be implemented using a large model, while information perception 213, data analysis 214, resource scheduling 215, and interaction management 216 can be implemented based on a small model. Alternatively, basic functions 210 can also be implemented collaboratively using large and small models; for example, data analysis 214 can be based on a large language model and machine learning algorithms to jointly analyze the collected information. The agent 200 can fine-tune the large model using historical information or train the small model to achieve the corresponding basic functions 210. Depending on the expected basic functions 210, the collected information may include emergency communication drill methods, historical resource scheduling work orders, emergency material and equipment management methods, emergency material reserve management methods, emergency communication support response methods, etc. In an optional embodiment of this disclosure, the quality of the collected information can also be improved through knowledge retrieval enhancement technology.

[0053] For example, taking intent recognition 211 as an example, the intelligent agent 200 can identify the intent of emergency communication personnel through a large model, and then execute related capabilities. For instance, for on-duty personnel in emergency communication scenarios, dialogue intent recognition can be performed. The identified intent result can be to analyze the accuracy of the collected information, revise the collected information as required, initiate an emergency response to generate a resource allocation plan for emergency support deployment, revise or improve the resource allocation plan for emergency support deployment as required, and assign task work orders to relevant emergency communication personnel or teams based on the resource allocation plan for emergency support deployment. Based on the above intent result, basic function 210 can be further invoked to realize the corresponding intent.

[0054] For example, taking content generation 212 as an example, the intelligent agent 200 can generate content in corresponding templates and formats based on different intent results. For instance, in an emergency communication scenario of a natural disaster, when the intent result is to report the disaster situation, the corresponding content generation 212 model can be called to output a disaster situation feedback summary based on the collected information and the accuracy analysis results of the collected information, including the basic situation of the disaster, the scope of the disaster impact, the scope of emergency communication terminals, and the damage to communication facilities. Furthermore, when the intent result is to generate an emergency support and rescue deployment plan, the corresponding content generation 212 model can be called to generate an emergency support and rescue deployment plan including personnel and material dispatch based on the disaster situation feedback summary and the emergency support response measures.

[0055] For example, taking information perception 213 as an example, the intelligent agent 200 can adjust the collection method for different objects through the model to obtain collected information. For example, for web pages, dynamic keywords and dynamic monitoring range can be set through web crawlers to obtain collection information related to emergency communication scenarios. The crawler method can also be dynamically adjusted according to the web page structure and content update mechanism, such as using a crawler that simulates browser behavior to collect information for dynamically loaded web pages. Dynamic keywords may include emergency communication equipment models that change according to deployment area and version iteration, communication base station status that changes according to disaster situation, and geographical information of disaster-stricken areas that changes according to disaster situation; dynamic monitoring range may include social media platforms, communication operator websites, meteorological department websites, etc. In an optional embodiment of this disclosure, the intelligent agent 200 can also clean, deduplicate, and format the collected information according to preset standardization rules.

[0056] For example, taking data analysis 214 as an example, intelligent agent 200 can use models to perform targeted analysis on the collected information for different needs. For instance, for the need to analyze the authenticity and accuracy of information, semantic analysis can be performed on the collected information to make judgments, and descriptions of communication interruptions from different sources in the same disaster area can be compared to identify potentially exaggerated or misleading content. For the need to analyze the urgency and priority of information, priority rules in emergency communication scenarios can be used to rank the importance of collected information according to factors such as the degree of disaster and the urgency of rescue missions to support subsequent command and dispatch. For the need to analyze the correlation of information, the correlation between collected information can be analyzed and predicted. For example, by combining meteorological data and communication base station location information, it can predict the disaster areas where heavy rain may cause communication base stations to be flooded, and it can also analyze the evacuation routes of disaster victims and the communication coverage along the routes to predict the possible location and range of communication blind spots, supporting subsequent resource scheduling and allocation.

[0057] For example, taking resource scheduling 215 as an example, the intelligent agent 200 can use a model to schedule and allocate personnel, materials, and equipment based on collected information and the analysis results of the collected information, as well as to command and adjust the allocation of personnel, materials, and equipment during the operation. For example, regarding resource allocation, based on the analysis results provided by data analysis 214, such as resource transportation time and rescue work priority, and comprehensively considering the resource availability information provided by information perception 213, an operations research algorithm can be used to obtain a resource allocation demand plan. When multiple disaster-stricken areas need to allocate emergency communication equipment, the specific type and quantity of emergency communication equipment to be allocated to each area can be determined. Among them, resource availability can include the fuel level of emergency communication vehicles, the battery level of satellite phones, and the number of satellite phones, etc. Resource transportation time can be calculated based on traffic conditions and the speed of transportation vehicles. On this basis, it can also match the corresponding personnel from the emergency communication personnel data and assign tasks according to the type and complexity of emergency communication tasks, such as base station repair type and temporary communication network construction type; and coordinate the workflow between different rescue teams during the operation, such as fire rescue teams and medical rescue teams, to ensure efficient collaboration between emergency communication support work and other rescue operations. Furthermore, real-time scheduling adjustments can be made during operations, such as real-time monitoring of base station signal strength changes, the operational status of emergency communication equipment, determining the communication network status, and monitoring resource usage such as the remaining fuel level of emergency communication vehicles and the frequency of satellite phone use. In the event of sudden situations such as new communication failure points or rapid resource depletion, the scheduling plan can be reassessed based on the real-time information collected by information perception 213 and the real-time analysis results of data analysis 214, allowing for timely adjustments to resource allocation and personnel task assignments. For example, if an emergency communication vehicle in a disaster-stricken area is unable to continue its mission due to a malfunction, the system can dynamically plan the transfer route for the emergency equipment carried by that vehicle or allocate other vehicles to fill the gap.

[0058] This disclosure presents an exemplary dynamic programming-based emergency communication resource allocation algorithm. This algorithm considers factors such as emergency communication resource availability, transportation time, and rescue work priorities. The algorithm can allocate emergency communication resources to multiple emergency communication tasks to reasonably support their efficient completion while also satisfying resource availability and transportation time constraints. In dynamic programming, emergency communication tasks can be decomposed into multiple stages, and the optimal solution can be found through recursive relationships. The task allocation process can be viewed as multiple stages, with each stage corresponding to a task allocation decision.

[0059] I. Parameter Definition

[0060] T: Set of emergency communication tasks, T = {1, 2, ..., n};

[0061] R: Set of emergency communication resources, R = {1,2,...,m}, where emergency communication resource types include emergency communication vehicles, satellite phones, backpack base stations, etc.

[0062] a r The number of available emergency communication resources r;

[0063] d t : The priority of emergency communication task t, the larger the value, the higher the priority;

[0064] t tr The time required to transport emergency communication resources (r) to the emergency communication task (t);

[0065] x tr : Decision variable, representing whether emergency communication resources r are allocated to emergency communication task t, where x tr =1 indicates allocation, x tr =0 indicates no allocation.

[0066] II. State Definition

[0067] Define state S k This represents the resource allocation for the first k emergency communication tasks, where k represents the task number; the state can be represented by a vector, recording the remaining available quantity of each type of emergency communication resource.

[0068] III. Decision Variables

[0069] At each stage k, the decision variable x kr This indicates whether to allocate emergency communication resources r to emergency communication task k.

[0070] IV. Stage Division

[0071] The task number k is used as the stage, and the allocation decision is made sequentially from emergency communication task 1 to emergency communication task n.

[0072] V. State Transition Equations

[0073] Assume the current state is S k , representing the resource allocation for the first k emergency communication tasks. In stage k, after allocating emergency communication resource r to emergency communication task k, the state transitions to S. k+1 The state transition equation is shown in formula (1) below:

[0074] S k+1 =S k -e r #(1)

[0075] Among them, e r It is a unit vector representing a decrease of 1 in the number of emergency communication resources r.

[0076] VI. Objective Function

[0077] The goal of dynamic programming is to maximize the priority-weighted sum, and the value function V is defined. K (S K If the optimal allocation value is to be derived from emergency communication task k to emergency communication task n, then the recursive relationship is shown in the following formula (2):

[0078] V K (S K ) = max r∈R {d k ·x kr +V K+1 (S K -e r )}#(2)

[0079] Where, x kr =1 indicates that emergency communication resources r are allocated to emergency communication task k; otherwise, x kr =0.

[0080] Based on this, the boundary condition should also be met. When k = n + 1, that is, when all emergency communication tasks have been assigned, the value function is as shown in the following formula (3):

[0081] V n+1 (S n+1 )=0#(3)

[0082] For example, taking interactive management 216 as an example, agent 200 can manage the interaction between personnel, teams, and internal and external systems by connecting to, coordinating, and maintaining different information transmission channels through model docking. For instance, regarding information release and feedback reception during operations, the model can dynamically select appropriate release channels based on communication requirements to ensure that dispatch information is accurately sent to operators and relevant teams. Release channels can include satellite communication, 4G networks, 5G networks, walkie-talkies, etc., and receive feedback information from operators and relevant teams. For example, it can send dispatch information including target location, transportation route, and estimated arrival time to the emergency communication vehicle driver, and receive real-time location information of the emergency communication vehicle and road traffic conditions reported by the driver. On this basis, it can also dock with external systems such as third-party emergency command platforms and communication operator operation and maintenance systems, managing docking standards, communication protocols, and information security, thereby obtaining auxiliary information provided by external systems, such as the latest disaster updates released by third parties and base station maintenance plans provided by communication operators. It can also feed back the command and dispatch decisions and emergency communication support status of agent 200 to external systems, realizing internal and external information sharing and collaboration.

[0083] At the service function 220 level, the agent 200 can implement at least one service function 220 through a dynamic orchestration model. For example, the service function 220 may include preprocessing of collected information 221, resource allocation and decision support 222, personnel scheduling and task allocation 223, and real-time feedback and adjustment 224.

[0084] In this embodiment of the disclosure, the aforementioned service function 220 can be referred to in the corresponding manner described above. Figure 1 The relevant descriptions of service function 220 are omitted here to avoid duplication.

[0085] In an optional embodiment of this disclosure, the preprocessing 221 of the collected information preprocesses the collected information related to the emergency communication scenario. The preprocessing includes at least one of screening, verification, completion, expansion, multi-source fusion, and correlation analysis.

[0086] In this embodiment of the disclosure, the preprocessing 221 of the aforementioned collected information can be referred to in the preceding description. Figure 1 The relevant description of the preprocessing of the collected information 221 will not be repeated here to avoid repetition.

[0087] In an optional embodiment of this disclosure, the preprocessing is screening. The preprocessing of the collected information includes screening the collected information related to the emergency communication scenario based on information perception and according to at least one of preset emergency event types and preset emergency keywords.

[0088] In this embodiment of the disclosure, the intelligent agent 200 can identify relevant and key collected information based on information perception 213, such as filtering preset emergency event types and preset emergency keywords through a model, and extracting collected information related to emergency communication scenarios, thereby avoiding the inefficiency and tediousness of manual screening one by one.

[0089] In an optional embodiment of this disclosure, the preprocessing is verification, and the preprocessing of the collected information includes semantic analysis of the collected information based on data analysis, and verification of the authenticity of the collected information.

[0090] In this embodiment, the intelligent agent 200 can perform language understanding based on data analysis 214 supported by a large model, and analyze the authenticity of collected information based on a large knowledge reserve, thereby identifying false information in the collected information and avoiding the impact of false information on rescue and communication restoration work. For example, data analysis 214 can compare multiple information sources, analyze the logical coherence of collected information, and refer to the information released by trusted entities to determine the authenticity of messages related to emergency communication, thereby providing reliable support for emergency decision-making.

[0091] In an optional embodiment of this disclosure, the preprocessing is completion, and the preprocessing of the collected information includes completing the missing content of the collected information based on data analysis.

[0092] In this embodiment of the disclosure, the intelligent agent 200 can analyze the completeness of the collected information based on data analysis 214. When it is confirmed that there is missing information, it can further supplement the information reasonably based on existing knowledge and information. For example, if there is missing information in the emergency communication equipment allocation information, the intelligent agent 200 can infer the type and quantity of equipment that may need to be supplemented based on factors such as the emergency communication equipment allocation plan of similar historical events, equipment inventory, and the geographical scope of the disaster area, so as to supplement the emergency communication equipment allocation information.

[0093] In an optional embodiment of this disclosure, the preprocessing is an extension, and the preprocessing of the collected information includes interpretive extension of the collected information based on information perception and data analysis.

[0094] In this embodiment, the intelligent agent 200 can expand upon the collected information, such as by providing easily understandable explanations for highly specialized or domain-specific emergency communication technology information, or by supplementing auxiliary information based on existing collected information. For example, when a new emergency communication technology standard is obtained through information perception 213, the intelligent agent 200 can obtain simple operational requirements corresponding to complex technical clauses through data analysis 214, and further expand upon the specific application methods of the new emergency communication technology standard for different types of emergency communication scenarios through information perception 213.

[0095] In an optional embodiment of this disclosure, the preprocessing is multi-source fusion, and the preprocessing of the collected information includes integrating the collected information from multiple data sources based on data analysis.

[0096] In this embodiment of the disclosure, the intelligent agent 200 can integrate information collected from multiple data sources of different platforms and types. For example, in an emergency communication scenario of a forest fire, the intelligent agent 200 can align and fuse information collected from multiple sources, such as wind direction and force information released by the meteorological department, fire spread reports from the fire department, base station operation status data from communication operators, and on-site descriptions published on social media, based on data analysis 214.

[0097] In an optional embodiment of this disclosure, the preprocessing is correlation analysis. The preprocessing of the collected information includes correlation analysis and risk prediction in emergency communication scenarios based on data analysis of collected information from multiple data sources.

[0098] In this embodiment of the disclosure, the intelligent agent 200 can discover potential connections between collected information based on data analysis 214. For example, in an emergency communication scenario during a flood disaster, the intelligent agent 200 can analyze the potential connection between the rate of water level rise and the risk of flooding of communication base stations, as well as the potential connection between evacuation routes of affected people and communication coverage along those routes. Based on correlation analysis, the occurrence of communication problems can be predicted in advance, such as predicting disaster-stricken areas that may lose communication signals due to flooding, thereby supporting communication support operations.

[0099] In an optional embodiment of this disclosure, the resource allocation and decision support 222 generates support information for resource allocation and decision-making in emergency communication scenarios based on the collected information. The support information includes at least one of an emergency communication resource demand report and an emergency communication resource allocation scheme.

[0100] In this embodiment of the disclosure, the aforementioned resource allocation and decision support 222 can be referred to in the corresponding manner described above. Figure 1 The relevant descriptions of resource allocation and decision support 222 are omitted here to avoid repetition.

[0101] In an optional embodiment of this disclosure, the emergency communication resource requirement report describes the emergency communication resource requirements of each area in the emergency communication scenario.

[0102] In this embodiment, the intelligent agent 200 acquires collected information based on information perception 213, such as the extent of damage to communication equipment in the disaster area, the density of the affected population, and the location of rescue teams. Based on data analysis 214, it assesses the emergency communication resource needs of different disaster areas, such as the need for emergency communication vehicles, satellite phones, and temporary base stations. Based on content generation 212, it obtains an emergency communication resource demand report. For example, in an earthquake-stricken area, by collecting and analyzing location information and distress calls posted by affected people on social media, as well as network failure reports provided by communication operators, the intelligent agent 200 can identify the disaster areas with the most severe communication disruptions and the largest number of affected people, thus supporting the rational allocation of communication resources.

[0103] In an optional embodiment of this disclosure, the emergency communication resource allocation scheme includes generating an allocation scheme for at least one available resource based on an emergency communication resource demand report and according to resource allocation factors, including at least one of resource availability, transportation time, and emergency communication priority.

[0104] In this embodiment of the disclosure, based on the emergency communication resource needs of various regions in the emergency communication scenario as reported by the emergency communication resource demand report, the intelligent agent 200 can determine resource allocation factors based on data analysis 214 and generate an allocation scheme for at least one available resource based on content generation 212. The resource allocation factors may include resource availability, transportation time, and emergency communication priority. For example, in an emergency communication scenario during a flood disaster, the intelligent agent 200 can comprehensively consider the inventory location of emergency communication equipment, road conditions determined by real-time traffic information obtained from transportation departments, and the urgency of communication needs on affected islands to generate a reasonable number of equipment to be allocated and transportation routes, so that communication resources can be delivered to the disaster area as quickly as possible.

[0105] In an optional embodiment of this disclosure, personnel scheduling and task allocation 223 involves at least one of personnel scheduling arrangements, emergency communication task allocation and coordination based on supporting information.

[0106] In this embodiment of the disclosure, the aforementioned personnel scheduling and task allocation 223 can be referred to in the preceding description. Figure 1 The relevant descriptions of personnel scheduling and task allocation 223 will not be repeated here to avoid duplication.

[0107] In an optional embodiment of this disclosure, personnel scheduling includes scheduling target personnel to corresponding emergency communication tasks based on task parameters and personnel information; the task parameters include at least one of task type, task complexity, and task priority.

[0108] In this embodiment, the intelligent agent 200, based on resource scheduling 215, can rationally allocate target personnel to different emergency communication tasks according to task parameters, personnel information, etc. Task parameters can include task type, task complexity, task priority, etc., while personnel information can include personnel skills, experience, or other information. Scheduling can be performed by dynamically matching task parameters with personnel information. For example, in an emergency communication scenario of a large-scale forest fire, if the task type is determined to be building a temporary communication network to assist firefighters in their firefighting operations by analyzing the communication needs at the fire site, the intelligent agent 200 can match and filter target personnel with relevant experience in setting up and maintaining field communication equipment from among the emergency communication personnel, and allocate these target personnel to the emergency communication task of building a temporary communication network. If the task type is a drone reconnaissance task, then target personnel with the "drone pilot's license" skill tag can be matched and filtered, and allocated to that drone reconnaissance task.

[0109] In an optional embodiment of this disclosure, emergency communication task allocation and coordination includes decomposing the emergency communication task into multiple sub-tasks according to the task type and task complexity, and coordinating the execution of multiple sub-tasks.

[0110] In this embodiment, the intelligent agent 200, based on data analysis 214 and resource scheduling 215, can decompose emergency communication tasks into multiple sub-tasks. These sub-tasks can collaborate during execution based on interactive management 216. The allocation of sub-tasks can refer to the aforementioned personnel scheduling and task allocation 223, and this embodiment does not impose specific limitations on this. Based on the sub-task allocation, the intelligent agent 200 can promote collaborative work among different rescue teams, such as fire fighting, medical, and communication teams. For example, in earthquake rescue, the intelligent agent 200 can assign the emergency communication task of restoring communication in the disaster area to the communication repair team, and the emergency communication task of using the restored communication network for rescue command to the rescue command center, coordinating the workflow between the two to ensure that communication can be immediately put into use after restoration.

[0111] In an optional embodiment of this disclosure, the real-time feedback and adjustment 224 performs at least one of the following: dynamic monitoring and evaluation of collected information related to emergency communication scenarios, resource allocation adjustment, personnel scheduling adjustment, and task allocation adjustment.

[0112] In this embodiment of the disclosure, the aforementioned real-time feedback and adjustment 224 can be referred to in the preceding description. Figure 1 The description of the real-time feedback and adjustment 224 is omitted here to avoid repetition.

[0113] In an optional embodiment of this disclosure, dynamic monitoring and evaluation includes real-time monitoring and evaluation based on at least one of the following: emergency communication network status, emergency resource usage, and task execution progress status.

[0114] In this embodiment, the intelligent agent 200 can continuously capture and collect information in real time through information sensing 213, such as base station signal strength, communication equipment power consumption, and communication equipment malfunction status. Based on data analysis 214, it can monitor and evaluate the emergency communication network status, emergency resource usage, and task execution progress in real time, thereby dynamically assessing the effectiveness of resources and task progress. For example, during the emergency communication vehicle's emergency communication mission, the intelligent agent 200 can receive real-time equipment operation data and surrounding environmental information transmitted back by the vehicle. When a gap is found in the communication coverage of the disaster area, it can analyze the cause in a timely manner to support the dynamic adjustment of resource allocation.

[0115] In an optional embodiment of this disclosure, resource allocation adjustment includes adjusting the emergency communication resource allocation scheme based on real-time monitoring and assessment.

[0116] In an optional embodiment of this disclosure, personnel scheduling adjustment includes adjusting personnel scheduling arrangements based on real-time monitoring and evaluation.

[0117] In an optional embodiment of this disclosure, task allocation adjustment includes adjusting emergency communication task allocation and coordination based on real-time monitoring and assessment.

[0118] In this embodiment of the disclosure, based on the aforementioned dynamic monitoring and evaluation, the intelligent agent 200 can flexibly adjust emergency communication resource allocation schemes, personnel scheduling arrangements, communication task allocation and coordination, etc., based on basic functions such as data analysis 214, content generation 212, resource scheduling 215, and interaction management 216. For example, if the dynamic monitoring and evaluation feedback indicates that the resource allocation scheme cannot be effectively implemented due to unforeseen circumstances, such as a road collapse preventing the emergency communication vehicle from reaching the predetermined location, the intelligent agent 200 can replan the route or adjust the resource allocation; if the dynamic monitoring and evaluation feedback indicates that target personnel are injured or the workload changes, the intelligent agent 200 can reassign communication tasks to reduce the impact on communication support work.

[0119] like Figure 2 As shown, the intelligent agent 200 can also be divided into a data layer 230 related to data acquisition, processing, and management. The data layer 230 is the foundation of the intelligent agent 200, and the information collected may include environmental information 231, personnel information 232, equipment status information 233, resource inventory information 234, and task execution information 235.

[0120] In an optional embodiment of this disclosure, environmental information 231 may include environmental detection information acquired by an internal acquisition terminal, such as road information collected by emergency communication vehicles and disaster information reported by workers, or information released by external systems, such as meteorological data and traffic data.

[0121] In an optional embodiment of this disclosure, personnel information 232 may include personnel skills, experience, and personnel status. Acquiring personnel status may include location tracking and task management to track personnel location changes and task execution progress in real time. For example, personnel location information is updated every 30 seconds, and an automatic reminder is sent if personnel location information has not been updated for more than 10 minutes.

[0122] In an optional embodiment of this disclosure, the device status information 233 may include basic device data, such as device identification and basic device information, including device number, device name and model, manufacturer, purchase date and service life; device technical parameters, such as communication frequency band, transmit power, receive sensitivity, modulation method, data transmission rate, antenna gain, etc.; device performance indicators, such as call quality, video transmission quality, data transmission stability, handover performance, etc.; device physical characteristics, such as size and weight, protection level, operating temperature range, etc.; device power parameters, such as power supply method, power consumption, battery life, etc.; and device network configuration information, such as IP address, subnet mask, gateway address, etc. The device status information 233 may also include real-time monitoring and update data, such as base station signal strength and real-time location of communication equipment, which can be monitored in real time through sensors and network interfaces and updated periodically.

[0123] Based on the aforementioned device status data 233, the intelligent agent 200 can perform device performance evaluation through data analysis 214, such as determining the performance status based on device operating data like CPU utilization, memory usage, and temperature. For example, if the CPU usage remains above 80% and the temperature exceeds 70°C for an extended period, the device may be in an overload state, thus supporting operational and maintenance decisions.

[0124] In an optional embodiment of this disclosure, the resource inventory information 234 may include the inventory location, quantity, and availability of emergency communication resources, such as emergency communication vehicles, satellite phones, and temporary base stations. The resource inventory information 234 changes dynamically with the severity of the disaster, task allocation, and execution progress. By recording the resource inventory information 234 for each type of emergency communication resource, the intelligent agent 200 can perform inventory management based on data analysis 214, such as triggering a replenishment reminder when the inventory of emergency communication resources falls below a threshold.

[0125] In an optional embodiment of this disclosure, the task execution information 235 may include task priority, task execution progress, etc. The intelligent agent 200 can dynamically assess the urgency of the emergency communication task based on data analysis 214, thereby distinguishing different task processing priorities, such as prioritizing repair tasks in communication interruption areas over routine equipment inspection tasks. During task execution, the intelligent agent 200 can obtain collected information through information sensing 213, and then monitor the task progress in real time based on data analysis 214, updating the task status through the task management system. For example, the emergency communication task status can be categorized as "pending execution," "in execution," or "completed," and updated according to the task execution information analyzed by the intelligent agent 200.

[0126] The intelligent agent disclosed herein is configured with models corresponding to basic functions such as intent recognition, content generation, information perception, data analysis, resource scheduling, and interaction management. The intelligent agent can dynamically orchestrate these models to achieve corresponding service functions, such as preprocessing of collected information, resource allocation and decision support, personnel scheduling and task assignment, and real-time feedback and adjustment. In emergency communication scenarios, this intelligent agent can automatically combine collected information to perform emergency correlation and demand analysis, enabling dynamic allocation and real-time adjustment of personnel and resources throughout the entire process. While ensuring accuracy and stability, it shortens scheduling time, improves scheduling efficiency in emergency communication scenarios, and reduces labor costs.

[0127] Figure 3 This is a flowchart illustrating the steps of an emergency communication intelligent dispatch method provided in an embodiment of the present disclosure. The method can be implemented through the aforementioned... Figure 1 , Figure 2 For any of the agent implementations shown, the method may include the following steps 301 to 302.

[0128] Step 301: Respond to emergency communication demand information to perform intent recognition and obtain at least one intent result in the emergency communication scenario.

[0129] In this embodiment of the disclosure, based on the foregoing Figure 1 , Figure 2 The intelligent agent shown, in the command and dispatch orchestration of emergency communication scenarios, can include responding to emergency communication request information to obtain the intended results in the emergency communication scenario. The emergency communication request information can be submitted by emergency communication personnel, such as emergency communication field operators and emergency communication duty personnel, or it can be automatically submitted based on data analysis of collected information; this disclosure does not impose specific limitations on this.

[0130] In this embodiment of the disclosure, intent recognition of emergency demand information can be performed by referring to the foregoing. Figure 1 , Figure 2 To avoid repetition, the relevant content regarding intent recognition in the shown agent will not be repeated here.

[0131] Step 302: Dynamically orchestrate the model based on the intent results, and implement the service functions corresponding to each intent result based on the basic functions.

[0132] In this embodiment of the disclosure, based on intent recognition, one or more intent results can be obtained. Based on this, the agent can dynamically orchestrate the model, combining basic functions into one or more corresponding service functions, thereby realizing the service function corresponding to the intent result. The specific details of the basic functions and service functions are as described above. Figure 1 , Figure 2To avoid repetition, the basic and service functions of the intelligent agent shown will not be described again here.

[0133] For example, Figure 4 A flowchart illustrating an example of an agent-based intelligent dispatching method for emergency communication is shown in an embodiment of this disclosure. Figure 4 As shown, taking the interaction between emergency communication duty personnel and intelligent agents in an earthquake scenario as an example, the process is as follows: steps 401 to 408.

[0134] Step 401: Emergency communication duty personnel submit emergency communication request information to the intelligent agent.

[0135] Step 402: The agent responds to the emergency communication demand information by performing intent recognition, and the intent results include information screening and filtering for the earthquake scenario, generation of emergency communication resource demand report, and generation of available resource allocation scheme.

[0136] Step 403: Based on basic functions such as information perception and data analysis, the intelligent agent filters, identifies, integrates, and analyzes multi-source data for earthquake scenarios, thereby achieving information screening and identification of collected information.

[0137] Step 404: The intelligent agent generates an emergency communication resource demand report based on the collected information using basic functions such as data analysis and content generation, and provides the emergency communication resource demand report to the emergency communication duty personnel.

[0138] Step 405: Emergency communication duty personnel report the revised and confirmed emergency communication resource requirements to the intelligent agent.

[0139] Step 406: In response to the confirmation of the emergency communication resource demand report, the intelligent agent generates an allocation plan for available resources based on basic functions such as content generation and resource scheduling, according to personnel information and resource inventory, and provides the allocation plan for available resources to the emergency communication duty personnel.

[0140] Step 407: Emergency communication duty personnel report the revised and confirmed allocation plan of available resources to the intelligent agent.

[0141] Step 408: In response to the confirmation of the allocation plan for available resources, the intelligent agent issues the allocation plan in the form of work orders to the target personnel or emergency communication support team based on basic functions such as interactive management. During the operation, it ensures that instructions are accurately issued and receives execution feedback information through multiple channels. Based on basic functions such as information perception, data analysis, and resource scheduling, it monitors the dynamics of personnel and materials in real time and adjusts the allocation plan flexibly in a timely manner. Based on basic functions such as interactive management, it connects with the third-party emergency command platform to obtain auxiliary information and feeds back the allocation plan for available resources and the emergency communication support status to the third party to achieve information sharing and collaborative work.

[0142] In this embodiment of the disclosure, the intent identification in step 402, and the feedback confirmation such as the emergency communication resource demand report and the allocation scheme of available resources in steps 405 and 407, can be achieved through multi-round sessions.

[0143] The earthquake scenario described above is for illustrative purposes only and can be extended to emergency communication scenarios such as extreme cold weather, flood control, and typhoon prevention. This disclosure does not impose any specific limitations on these scenarios.

[0144] The emergency communication intelligent dispatch method disclosed herein can be applied to the aforementioned intelligent agent, which is configured with models corresponding to basic functions such as intent recognition, content generation, information perception, data analysis, resource scheduling, and interaction management. The intelligent agent can dynamically orchestrate the models to achieve corresponding service functions, such as preprocessing of collected information, resource allocation and decision support, personnel scheduling and task assignment, and real-time feedback and adjustment. Based on this, the intelligent agent can perform intent recognition in response to emergency communication demand information to obtain intent results in the emergency communication scenario, and dynamically orchestrate the models according to the intent results, realizing the service functions corresponding to each intent result based on the basic functions. In emergency communication scenarios, this intelligent agent can automatically combine collected information to perform emergency correlation and demand analysis, realizing dynamic allocation and real-time adjustment of personnel and resources throughout the entire process. While ensuring accuracy and stability, it shortens dispatch time, improves dispatch efficiency in emergency communication scenarios, and reduces labor costs.

[0145] Figure 5 This is a schematic diagram of the structure of an electronic device 500 provided in an embodiment of the present disclosure, as shown below. Figure 5 As shown, the electronic device 500 may include a processor 501, a memory 502, and a program or instructions stored in the memory 502 and executable on the processor 501. When the program or instructions are executed by the processor 501, they implement the various processes of the above signaling interoperability embodiments and achieve the same technical effects. To avoid repetition, they will not be described again here.

[0146] It should be noted that, Figure 5The electronic device 500 shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments disclosed herein.

[0147] Figure 6 This is a hardware schematic diagram of an electronic device 600 provided in an embodiment of the present disclosure, as shown below. Figure 6 As shown, the electronic device 600 includes a Central Processing Unit (CPU) 601, which can perform various appropriate actions and processes based on programs stored in ROM (Read-Only Memory) 602 or programs loaded from storage section 608 into RAM (Random Access Memory) 603. RAM 603 also stores various programs and data required for system operation. The CPU 601, ROM 602, and RAM 603 are interconnected via bus 604. An I / O (Input / Output) interface 605 is also connected to bus 604.

[0148] The following components are connected to I / O interface 605: an input section 606 including a keyboard, mouse, etc.; an output section 607 including CRT (Cathode Ray Tube), LCD (Liquid Crystal Display), etc., and speakers, etc.; a storage section 608 including a hard disk, etc.; and a communication section 609 including a network interface card such as a LAN (Local Area Network) card, modem, etc. The communication section 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to I / O interface 605 as needed. A removable medium 611, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on drive 610 as needed so that computer programs read from it can be installed into storage section 608 as needed.

[0149] In particular, according to embodiments of this disclosure, the processes described below with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this disclosure 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 communication section 609, and / or installed from removable medium 611. When the computer program is executed by the central processing unit (CPU 601), it performs various functions defined in the system of this application.

[0150] This disclosure also transmits a computer-readable medium storing a program or instructions that, when executed by a processor, implement the various processes of the above signaling interoperability embodiments and achieve the same technical effects. To avoid repetition, these will not be described again here.

[0151] The processor is the processor in the electronic device described in the above embodiments. Computer-readable media includes computer-readable media such as ROM, RAM, magnetic disks, or optical disks.

[0152] This disclosure also discloses a chip, which includes a processor and a communication interface. The communication interface and the processor are coupled. The processor is used to run programs or instructions to implement the various processes of the above signaling interoperability embodiments and achieve the same technical effect. To avoid repetition, it will not be described again here.

[0153] It should be understood that the chip mentioned in the embodiments of this disclosure may also be referred to as a system-on-a-chip, system chip, chip system, or system-on-a-chip, etc.

[0154] This disclosure provides a computer program product containing instructions that, when run on a computer, causes the computer to perform the signaling interoperability steps described above and achieves the same technical effect. To avoid repetition, further details are omitted here.

[0155] 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 apparatus 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 apparatus. 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 apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this disclosure is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0156] 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. Based on this understanding, the technical solution of this disclosure, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes several instructions to cause a terminal (which may be a mobile phone, computer, electronic device, air conditioner, or network device, etc.) to execute the methods of the various embodiments of this disclosure.

[0157] The embodiments of this disclosure have been described above with reference to the accompanying drawings. However, this disclosure is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this disclosure without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this disclosure.

Claims

1. An intelligent agent, characterized in that, The intelligent agent is configured with models corresponding to at least one basic function among intent recognition, content generation, information perception, data analysis, resource scheduling, and interaction management. The intelligent agent implements at least one service function by dynamically orchestrating the models. The service functions include: Preprocessing of collected information: Preprocessing of collected information related to emergency communication scenarios, the preprocessing includes at least one of screening, verification, completion, expansion, multi-source fusion, and correlation analysis; Resource allocation and decision support: Based on the collected information, generate support information for resource allocation and decision-making in emergency communication scenarios. The support information includes at least one of an emergency communication resource demand report and an emergency communication resource allocation scheme. Personnel scheduling and task allocation, including at least one of personnel scheduling arrangements, emergency communication task allocation and coordination based on the supporting information; Real-time feedback and adjustment include at least one of the following: dynamic monitoring and evaluation of collected information related to the emergency communication scenario, resource allocation adjustment, personnel scheduling adjustment, and task allocation adjustment.

2. The intelligent agent according to claim 1, characterized in that, The preprocessing is filtering, and the preprocessing of the collected information includes filtering the collected information related to the emergency communication scenario based on the information perception and at least one of the preset emergency event type and preset emergency keywords. The preprocessing is verification, and the preprocessing of the collected information includes semantic analysis of the collected information based on the data analysis, and authenticity verification of the collected information. The preprocessing is completion, and the preprocessing of the collected information includes completing the missing content of the collected information based on the data analysis; The preprocessing is an extension, and the preprocessing of the collected information includes interpreting and extending the collected information based on the information perception and the data analysis; The preprocessing is multi-source fusion, and the preprocessing of the collected information includes integrating the collected information from multiple data sources based on the data analysis. The preprocessing is correlation analysis, which includes correlation analysis and risk prediction in emergency communication scenarios based on the data analysis of the collected information from multiple data sources.

3. The intelligent agent according to claim 1, characterized in that, The emergency communication resource requirement report describes the emergency communication resource requirements of each area in the emergency communication scenario; The emergency communication resource allocation scheme includes generating an allocation scheme for at least one available resource based on the emergency communication resource demand report and according to resource allocation factors, including at least one of resource availability, transportation time, and emergency communication priority.

4. The intelligent agent according to claim 1, characterized in that, The personnel scheduling arrangement includes scheduling target personnel to corresponding emergency communication tasks based on task parameters and personnel information; the task parameters include at least one of task type, task complexity, and task priority; The emergency communication task allocation and coordination includes decomposing the emergency communication task into multiple sub-tasks according to the task type and the task complexity, and coordinating the execution of the multiple sub-tasks.

5. The intelligent agent according to claim 1, characterized in that, The dynamic monitoring and evaluation includes real-time monitoring and evaluation based on at least one of the following: emergency communication network status, emergency resource usage, and task execution progress status. The resource allocation adjustment includes adjusting the emergency communication resource allocation scheme based on real-time monitoring and evaluation; The personnel scheduling adjustment includes adjusting the personnel scheduling arrangements based on real-time monitoring and evaluation; The task allocation adjustment includes adjusting the allocation and coordination of emergency communication tasks based on real-time monitoring and evaluation.

6. The intelligent agent according to any one of claims 1 to 5, characterized in that, The collected information includes at least one of the following: environmental information, personnel information, equipment status information, resource inventory information, and task execution information.

7. The intelligent agent according to any one of claims 1 to 5, characterized in that, The intelligent agent uses historical information to train the model, enabling the model to achieve the corresponding basic functions; the model includes a large model and a small model.

8. An intelligent dispatching method for emergency communication, characterized in that, The method is implemented by an intelligent agent according to any one of claims 1 to 7, and the method includes: In response to emergency communication needs, intent recognition is performed to obtain at least one intent result in the emergency communication scenario; The model is dynamically orchestrated based on the intent results, and the service function corresponding to each intent result is implemented based on the basic functions.

9. An electronic device, characterized in that, It includes a processor, a memory, and a program or instructions stored in the memory and executable on the processor, wherein the program or instructions, when executed by the processor, implement the emergency communication intelligent scheduling method as described in claim 8.

10. A computer-readable medium, characterized in that, The computer-readable medium stores a program or instructions that, when executed by a processor, implement the emergency communication intelligent scheduling method as described in claim 8.

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