A voice-controlled intelligent ambulance system and operation method

Abstract

The present invention discloses an intelligent ambulance system and operation method based on voice control. The system includes: a determination module that collects voice signals from medical personnel and determines whether they are voice commands. If so, it analyzes the command attributes of the voice commands and determines the travel destination requirements and operation project requirements based on the command attributes; a reminder module that plans a movement path based on the travel destination requirements and displays the navigation route, monitors the position parameters of the ambulance during travel, and issues destination arrival reminders based on the position parameters; a recording module that determines first aid equipment and first aid medicines based on the operation project requirements and records the operation time parameters and operation process parameters of the medical personnel for the first aid equipment and first aid medicines; and a generation module that uploads the operation time parameters and operation process parameters to a medical information system and performs an inventory of the first aid equipment and first aid medicines to generate a replenishment list and upload it to the logistics system. This ensures accurate recognition of multiple types of voice commands.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent control of emergency vehicles, and in particular to an intelligent emergency vehicle system based on voice control and an operating method thereof. Background Art

[0002] With the acceleration of urbanization and the frequent occurrence of public health emergencies, the limitations of traditional ambulance systems in terms of response speed, operational coordination, and intelligent decision-making capabilities are becoming increasingly prominent. The fragmented design of internal equipment control, information exchange, and rescue processes in ambulances has become a core bottleneck restricting emergency response efficiency. Specific technical deficiencies include: Due to the single nature of voice commands, the system only supports simple commands (such as "start navigation"), making it impossible to adjust complex parameters or implement cross-device linkage operations. Furthermore, manual recording of the emergency process is required, reducing work efficiency and stability. Summary of the Invention

[0003] In response to the above problems, the present invention provides a voice-controlled intelligent ambulance system and operation method to solve the problem mentioned in the background art that due to the single voice command, the system only supports simple commands, cannot realize complex parameter adjustment or cross-device linkage operation, and requires manual recording of the emergency process, which reduces work efficiency and stability.

[0004] An intelligent ambulance system based on voice control, the system comprising:

[0005] A determination module is used to collect the voice signal of the medical staff and determine whether it is a voice command. If so, it analyzes the command attributes of the voice command and determines the travel destination requirements and operation item requirements based on the command attributes;

[0006] The reminder module is used to plan the movement path based on the travel destination requirements and display the navigation route, monitor the location parameters of the ambulance during the driving process and issue destination arrival reminders based on the location parameters;

[0007] The recording module is used to determine the emergency equipment and emergency medicines according to the operation project requirements and record the operation time parameters and operation process parameters of the emergency equipment and emergency medicines by medical staff;

[0008] The generation module is used to upload the operation time parameters and operation process parameters to the medical information system and conduct an inventory count of first aid equipment and first aid medicines to generate a replenishment list and upload it to the logistics system.

[0009] Preferably, the determining module includes:

[0010] An acquisition submodule, configured to acquire voice signals of medical staff using a high-sensitivity microphone array and pre-process the voice signals;

[0011] The judgment submodule is used to perform voice energy detection and wake-up word detection on the preprocessed voice signal, and determine whether it is a voice command based on the detection results;

[0012] The recognition submodule is used to perform speech recognition on voice commands based on the Transformer model, and identify the intent and entity of the voice commands based on the recognition results and combined with natural language processing technology;

[0013] an extraction submodule, configured to parse instruction attributes of the voice instruction according to the intent and entity of the voice instruction, and extract keywords and information related to travel and operation according to the instruction attributes;

[0014] The first determination submodule is configured to determine a travel destination requirement and an operation item requirement based on the keywords and information.

[0015] Preferably, the judgment submodule performs speech energy detection and wake-up word detection on the preprocessed speech signal, including:

[0016] The pre-processed speech signal is divided into frames according to a preset time interval, and the energy value of each frame is calculated according to the energy calculation formula;

[0017] Determining a speech activity segment based on the energy value and in combination with a preset energy threshold, and performing speech energy detection of the speech signal based on the speech activity segment;

[0018] Obtain a preset number of wake-up word speech data and annotate the word attributes and word categories, and perform feature extraction on the annotated speech data based on the Mel spectrum;

[0019] A wake-up word template is constructed based on the extracted voice data features, and the similarity between the input voice and the wake-up word template is determined using a dynamic time warping algorithm.

[0020] Wake-up word detection of the voice signal is implemented according to the similarity.

[0021] Preferably, the reminder module includes:

[0022] A planning submodule, configured to plan a moving path according to the travel destination requirements based on a path planning algorithm and real-time traffic information, and display the moving path based on a navigation system;

[0023] A first acquisition submodule is configured to acquire the location information of the ambulance in real time based on the Beidou positioning system and in combination with the displayed route, and to acquire the speed and travel direction of the ambulance based on the location information of the ambulance;

[0024] The reminder submodule is used to draw the driving trajectory of the ambulance according to the speed and driving direction of the ambulance, estimate the time to reach the destination according to the driving trajectory, and remind the driver and medical staff through a reminder mechanism.

[0025] Preferably, the recording module includes:

[0026] A second determination submodule is configured to obtain an operation type according to an operation item requirement, determine a risk level of the operation item according to the operation type, and identify a possible emergency situation according to the risk level;

[0027] A third determining submodule is configured to determine first aid equipment and first aid medicines according to the possible emergency situation;

[0028] The second acquisition submodule is used to obtain the operation time parameters of the first aid equipment and first aid medicines according to the equipment use automatic recording system and the medicine cabinet intelligent access recording system;

[0029] The capture submodule is used to monitor the operating status of emergency equipment in real time based on the status sensor, and to obtain the hand motion data of medical staff using emergency equipment and emergency medicines based on the hand motion capture system;

[0030] The fourth determining submodule is used to determine the operating process parameters of the first aid equipment and first aid medicines according to the operating status and hand motion data.

[0031] Preferably, the operating status of the emergency equipment is monitored in real time using a status sensor, including:

[0032] Collecting the operating data of the equipment in real time according to the status sensor and preprocessing the operating data;

[0033] Decompose and separate the vibration signal based on the preprocessing results and in combination with empirical mode analysis and independent component analysis, and obtain the characteristic signal of the emergency equipment during operation based on the processing results;

[0034] Constructing a convolutional neural network model and extracting key features of characteristic signals during the operation of the emergency equipment;

[0035] The operating status of emergency equipment is monitored in real time based on the extracted key features.

[0036] Preferably, the generating module includes:

[0037] a processing submodule, configured to perform parameter preprocessing and formatting on the operation duration parameter and the operation process parameter to obtain data in a data format compatible with a medical information system;

[0038] The import submodule is used to import data in a data format compatible with the medical information system according to the API interface of the medical information system;

[0039] The third acquisition submodule is used to count the emergency equipment and emergency medicines according to the imported results, and obtain the usage and inventory levels of the emergency equipment and emergency medicines according to the counting results;

[0040] The generation submodule is used to generate a replenishment list based on usage and inventory levels and upload it to the logistics system.

[0041] Preferably, after planning the moving path based on the path planning algorithm and real-time traffic information according to the travel destination requirements, the system is further configured to:

[0042] Count the number of turning points and multiple lane types of the intelligent emergency vehicle based on its moving path;

[0043] Based on the number of turning points, the information of the surrounding buildings of each turning point is obtained, the crowd gathering attributes are determined based on the building group information, and the influence weight of the turning decision is determined based on the crowd gathering attributes;

[0044] Determine the turning time cost index when the smart emergency vehicle passes each turning point based on the turning decision influence weight, and determine the recommendation degree of each turning point based on the turning time cost index;

[0045] Select qualified turning points and unqualified turning points based on the recommendation degree of each turning point, and determine an alternative road for each unqualified turning point;

[0046] The moving path is adjusted based on the replacement road to obtain a first moving path, and a road-level path is determined according to a statistical number parameter of multiple types of lanes;

[0047] Convert the road-level path into a lane-level path, determine the lane-change convenience of the intelligent emergency vehicle based on the lane-level path, and determine the eligibility of multiple lane ratios based on the lane-change convenience;

[0048] Determine the heading offset parameter of the intelligent emergency vehicle based on the eligibility of multiple lane ratios and preset planning time parameters, and determine the offset compensation coefficient based on the heading offset parameter and the preset lane offset suppression factor;

[0049] Substituting the offset compensation coefficient into a preset offset compensation function to determine a theoretical offset direction within a preset planning duration;

[0050] Determine multiple lane distribution parameters in a theoretical offset direction, and generate a lane layer information model and a road layer information model based on the multiple lane distribution parameters;

[0051] According to the lane layer information model and the road layer information model, a multi-lane trajectory is planned through a target search algorithm;

[0052] The first moving path is adjusted according to the multi-lane travel trajectories to obtain a second moving path, and the second moving path is confirmed as the final moving path of the intelligent ambulance.

[0053] Preferably, the system is further used for:

[0054] Determine the station number of each emergency station to which each intelligent emergency vehicle belongs, and determine the dynamic emergency response factor of each emergency station through the emergency station database based on the station number;

[0055] The emergency status benefit index of each first aid station is determined based on the dynamic emergency response factors, and the dispatch recommendation coefficient of each first aid station is determined based on the emergency status benefit index:

[0056]

[0057] Among them, S i Expressed as the dispatch recommendation coefficient of the i-th emergency station, p i is the first aid status benefit index of the i-th first aid station, Ni is the number of first aid adaptation targets of the i-th first aid station, j is the first aid adaptation target, d j It is expressed as the decision variable complexity of the emergency vehicle dispatch strategy corresponding to the j-th emergency adaptation goal, e is expressed as a natural constant with a value of 2.72, Q i Expressed as the influence weight of the dispatch interference factor of the kth emergency adaptation target, F i Expressed as the multi-emergency synchronization factor of the i-th emergency station, θ i It is represented as the emergency vehicle dispatch task response index of the i-th emergency station;

[0058] Select the target emergency station with the highest dispatch recommendation index, determine the idle smart emergency vehicles in the target emergency station, and generate a dispatch plan for the idle smart emergency vehicles;

[0059] Comprehensively dispatch idle ambulances based on the dispatch plan.

[0060] A method for operating an intelligent emergency vehicle based on voice control, comprising the following steps:

[0061] Collect the medical staff's voice signal and determine whether it is a voice command. If so, analyze the command attributes of the voice command and determine the travel destination requirements and operation item requirements based on the command attributes;

[0062] Plan the movement path based on the travel destination and display the navigation route, monitor the location parameters of the ambulance during the driving process and provide destination arrival reminders based on the location parameters;

[0063] Determine first aid equipment and first aid medicines according to the requirements of the operation project and record the operation time parameters and operation process parameters of the first aid equipment and first aid medicines by medical staff;

[0064] Upload the operation time parameters and operation process parameters to the medical information system and conduct an inventory count of first aid equipment and first aid medicines to generate a replenishment list and upload it to the logistics system.

[0065] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0066] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention.

[0068] Figure 1 This is a schematic diagram of the structure of a voice-controlled intelligent ambulance system provided by the present invention;

[0069] Figure 2 This is a structural diagram of a determination module in a voice-controlled intelligent ambulance system provided by the present invention;

[0070] Figure 3 This is a structural diagram of a generation module in a voice-controlled intelligent ambulance system provided by the present invention;

[0071] Figure 4 This is a workflow diagram of a voice-controlled intelligent ambulance operation method provided by the present invention. DETAILED DESCRIPTION

[0072] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all possible embodiments consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.

[0073] At present, with the acceleration of urbanization and the frequent occurrence of public health emergencies, the limitations of traditional ambulance systems in terms of response speed, operational coordination and intelligent decision-making capabilities are becoming increasingly prominent. In the existing technology, the fragmented design of internal equipment control, information interaction and rescue processes in ambulances has become a core bottleneck restricting the efficiency of first aid. The specific technical defects are as follows: Due to the singleness of voice commands, the system only supports simple commands (such as "start navigation"), and cannot realize complex parameter adjustment or cross-device linkage operations, and manual recording of the first aid process is required, which reduces work efficiency and stability. In order to solve the above problems, this embodiment discloses an intelligent ambulance system based on voice control.

[0074] An intelligent emergency vehicle system based on voice control, such as Figure 1 As shown, the system includes:

[0075] The determination module 101 is used to collect the voice signal of the medical staff and determine whether it is a voice command. If so, it analyzes the command attributes of the voice command and determines the travel destination requirements and operation item requirements based on the command attributes;

[0076] The reminder module 102 is used to plan the movement path based on the travel destination requirements and display the navigation route, monitor the location parameters of the emergency vehicle during the travel process and issue a destination arrival reminder based on the location parameters;

[0077] The recording module 103 is used to determine the emergency equipment and emergency medicine according to the operation project requirements and record the operation time parameters and operation process parameters of the emergency equipment and emergency medicine by the medical staff;

[0078] The generating module 104 is used to upload the operation duration parameters and the operation process parameters to the medical information system and to perform an inventory count of the first aid equipment and first aid medicines to generate a replenishment list and upload it to the logistics system.

[0079] The working principle of the above technical solution is: first, the voice signal of the medical staff is collected through the determination module and it is determined whether it is a voice command. If so, the command attributes of the voice command are analyzed, and the travel destination requirements and operation item requirements are determined according to the command attributes; secondly, the reminder module is used to plan the movement path based on the travel destination requirements and display the navigation route, monitor the position parameters of the ambulance during the driving process and provide destination arrival reminders based on the position parameters; then, based on the recording module, the first aid equipment and first aid medicines are determined according to the operation item requirements and the operation time parameters and operation process parameters of the medical staff for the first aid equipment and first aid medicines are recorded; finally, the generation module is used to upload the operation time parameters and operation process parameters to the medical information system and perform an inventory of the first aid equipment and first aid medicines to generate a replenishment list and upload it to the logistics system.

[0080] The beneficial effects of the above technical solution are: by intelligently analyzing the voice commands issued by medical staff to determine the operational requirements and movement requirements, various types of requirements of medical staff can be obtained in real time and accurately, ensuring the accurate recognition of multiple types of voice commands, improving practicality and reliability. Furthermore, by intelligently recording the parameters of drug and equipment usage during the first aid process and then performing statistics and inventory replenishment, the first aid process can be recorded by the machine, which improves work efficiency and stability, and solves the problem mentioned in the prior art that due to the single voice commands, the system only supports simple commands, cannot realize complex parameter adjustment or cross-device linkage operation, and requires manual recording of the first aid process, which reduces work efficiency and stability.

[0081] In one embodiment, Figure 2 As shown, the determining module 101 includes:

[0082] The acquisition submodule 1011 is used to acquire the voice signals of medical staff using a high-sensitivity microphone array and pre-process the voice signals;

[0083] The judgment submodule 1012 is used to perform voice energy detection and wake-up word detection on the preprocessed voice signal, and determine whether it is a voice command based on the detection results;

[0084] Recognition submodule 1013, configured to perform speech recognition on the voice command based on the Transformer model, and identify the intent and entity of the voice command based on the recognition results and in combination with natural language processing technology;

[0085] The extraction submodule 1014 is used to parse the instruction attributes of the voice instruction according to the intention and entity of the voice instruction, extract keywords and information related to travel and operation according to the instruction attributes, and determine the travel destination requirements and operation item requirements based on the keywords and information.

[0086] In this embodiment, the high-sensitivity microphone array is a system composed of a plurality of high-sensitivity microphones arranged in a characteristic geometric arrangement, which can improve the signal-to-noise ratio and directionality.

[0087] In this embodiment, the instruction attribute includes: an operation instruction or a driving instruction.

[0088] In this embodiment, the keywords and information related to travel may be: go to ward 101, go to the operating room.

[0089] In this embodiment, the operation-related keywords and information may be: preparing surgical instruments, checking patient medical records.

[0090] The beneficial effects of the above technical solution are: recognizing the voice signals of medical staff, determining the intention and entity of voice commands, parsing the command attributes of voice commands, obtaining keywords and information related to movement and operation, and being able to quickly identify different needs, thereby making accurate decisions and improving the intelligence and safety of the emergency system.

[0091] In one embodiment, the judgment submodule performs speech energy detection and wake-up word detection on the preprocessed speech signal, including:

[0092] The pre-processed speech signal is divided into frames according to a preset time interval, and the energy value of each frame is calculated according to the energy calculation formula;

[0093] Determining a speech activity segment based on the energy value and in combination with a preset energy threshold, and performing speech energy detection of the speech signal based on the speech activity segment;

[0094] Obtain a preset number of wake-up word speech data and annotate the word attributes and word categories, and perform feature extraction on the annotated speech data based on the Mel spectrum;

[0095] A wake-up word template is constructed based on the extracted voice data features, and the similarity between the input voice and the wake-up word template is determined using a dynamic time warping algorithm.

[0096] Wake-up word detection of the voice signal is implemented according to the similarity.

[0097] In this embodiment, the energy value of each frame refers to the sum of squares of the signals in each frame after the audio signal is divided into several short time periods (frames), reflecting the strength or energy level of the frame signal.

[0098] In this embodiment, speech energy detection is used to determine whether there is speech activity in the speech signal and to distinguish between speech segments and non-speech segments.

[0099] In this embodiment, the word attributes of the wake-up word refer to the characteristics of the specific word or phrase used to wake up the device and start the voice interaction function, such as: easy pronunciation and syllable differences.

[0100] The beneficial effects of the above technical solution are: voice energy detection of voice signals is achieved by judging voice activity segments through energy values ​​and combined with preset energy thresholds, thereby improving voice processing efficiency, accurately locating voice segments, and reducing recognition errors. Furthermore, wake-up word detection of voice signals is achieved based on the similarity between the input voice and the wake-up word template, which can accurately wake up the intelligent ambulance system, improve recognition accuracy, and ensure the reliability of the ambulance system.

[0101] In one embodiment, the reminder module includes:

[0102] A planning submodule, configured to plan a moving path according to the travel destination requirements based on a path planning algorithm and real-time traffic information, and display the moving path based on a navigation system;

[0103] A first acquisition submodule is configured to acquire the location information of the ambulance in real time based on the Beidou positioning system and in combination with the displayed route, and to acquire the speed and travel direction of the ambulance based on the location information of the ambulance;

[0104] The reminder submodule is used to draw the driving trajectory of the ambulance according to the speed and driving direction of the ambulance, estimate the time to reach the destination according to the driving trajectory, and remind the driver and medical staff through a reminder mechanism.

[0105] In this embodiment, the reminder mechanism may be: voice or text.

[0106] The beneficial effects of the above technical solution are: planning the moving path according to the destination and path planning algorithm, obtaining the location information and driving direction of the ambulance, and estimating the time to arrive at the destination based on the driving trajectory of the ambulance, and issuing reminders, which can achieve seamless connection between pre-hospital emergency and in-hospital treatment and improve the success rate of patient treatment.

[0107] In one embodiment, the recording module includes:

[0108] A second determination submodule is configured to obtain an operation type according to an operation item requirement, determine a risk level of the operation item according to the operation type, and identify a possible emergency situation according to the risk level;

[0109] A third determining submodule is configured to determine first aid equipment and first aid medicines according to the possible emergency situation;

[0110] The second acquisition submodule is used to obtain the operation time parameters of the first aid equipment and first aid medicines according to the equipment use automatic recording system and the medicine cabinet intelligent access recording system;

[0111] The capture submodule is used to monitor the operating status of emergency equipment in real time based on the status sensor, and to obtain the hand motion data of medical staff using emergency equipment and emergency medicines based on the hand motion capture system;

[0112] The fourth determining submodule is used to determine the operating process parameters of the first aid equipment and first aid medicines according to the operating status and hand motion data.

[0113] The beneficial effects of the above technical solution are: determining first aid equipment and first aid medicines according to the risk level, and determining the operation time parameters and operation process parameters of the equipment and medicines based on the equipment usage automatic recording system, the medicine cabinet intelligent access recording system and the status sensor. It can standardize the treatment process, avoid abnormal situations caused by improper operation or operation time, improve medical quality, and ensure the safe use of equipment and medicines.

[0114] In one embodiment, the operating status of the emergency equipment is monitored in real time using a status sensor, including:

[0115] Collecting the operating data of the equipment in real time according to the status sensor and preprocessing the operating data;

[0116] Decompose and separate the vibration signal based on the preprocessing results and in combination with empirical mode analysis and independent component analysis, and obtain the characteristic signal of the emergency equipment during operation based on the processing results;

[0117] Constructing a convolutional neural network model and extracting key features of characteristic signals during the operation of the emergency equipment;

[0118] The operating status of emergency equipment is monitored in real time based on the extracted key features.

[0119] The beneficial effects of the above technical solution are: by preprocessing the operating data of the first aid equipment, obtaining the characteristic signals during the operation of the first aid equipment and extracting the key features, the operating status of the first aid equipment can be monitored in real time, and the abnormal operating status of the equipment can be quickly discovered to ensure the reliability and safety of the equipment.

[0120] In one embodiment, Figure 3 As shown, the generating module 104 includes:

[0121] The processing submodule 1041 is used to perform parameter preprocessing and formatting on the operation duration parameter and the operation process parameter to obtain data in a data format compatible with the medical information system;

[0122] An import submodule 1042 is used to import data in a data format compatible with the medical information system according to the API interface of the medical information system;

[0123] The third acquisition submodule 1043 is used to count the emergency equipment and emergency medicines according to the imported results, and obtain the usage and inventory levels of the emergency equipment and emergency medicines according to the count results;

[0124] The generation submodule 1044 is used to generate a replenishment list based on usage and inventory levels and upload it to the logistics system.

[0125] The beneficial effects of the above technical solution are: by importing data in a data format compatible with the medical information system into the system, and determining the inventory results of first aid equipment and first aid medicines based on the import results, thereby generating a replenishment list, it is possible to timely and accurately understand the usage and inventory status of equipment and medicines, replenish stocks in time, and avoid medical accidents caused by insufficient inventory.

[0126] In one embodiment, after planning a moving route based on the travel destination requirements based on a route planning algorithm and real-time traffic information, the system is further configured to:

[0127] Count the number of turning points and multiple lane types of the intelligent emergency vehicle based on its moving path;

[0128] Based on the number of turning points, the information of the surrounding buildings of each turning point is obtained, the crowd gathering attributes are determined based on the building group information, and the influence weight of the turning decision is determined based on the crowd gathering attributes;

[0129] Determine the turning time cost index when the smart emergency vehicle passes each turning point based on the turning decision influence weight, and determine the recommendation degree of each turning point based on the turning time cost index;

[0130] Select qualified turning points and unqualified turning points based on the recommendation degree of each turning point, and determine an alternative road for each unqualified turning point;

[0131] The moving path is adjusted based on the replacement road to obtain a first moving path, and a road-level path is determined according to a statistical number parameter of multiple types of lanes;

[0132] Convert the road-level path into a lane-level path, determine the lane-change convenience of the intelligent emergency vehicle based on the lane-level path, and determine the eligibility of multiple lane ratios based on the lane-change convenience;

[0133] Determine the heading offset parameter of the intelligent emergency vehicle based on the eligibility of multiple lane ratios and preset planning time parameters, and determine the offset compensation coefficient based on the heading offset parameter and the preset lane offset suppression factor;

[0134] Substituting the offset compensation coefficient into a preset offset compensation function to determine a theoretical offset direction within a preset planning duration;

[0135] Determine multiple lane distribution parameters in a theoretical offset direction, and generate a lane layer information model and a road layer information model based on the multiple lane distribution parameters;

[0136] According to the lane layer information model and the road layer information model, a multi-lane trajectory is planned through a target search algorithm;

[0137] The first moving path is adjusted according to the multi-lane travel trajectories to obtain a second moving path, and the second moving path is confirmed as the final moving path of the intelligent ambulance.

[0138] The beneficial effect of the above technical solution is: by evaluating the turning points and multiple lanes on the moving path and then selecting a replacement lane, the traffic efficiency and stability of the smart ambulance at the destination can be effectively guaranteed, and the time utilization can be maximized to improve the efficiency of emergency rescue.

[0139] In one embodiment, the system is further configured to:

[0140] Determine the station number of the emergency station to which each smart emergency vehicle belongs, and determine the dynamic emergency response factor of each emergency station through the emergency station database based on the station number;

[0141] The emergency status benefit index of each first aid station is determined based on the dynamic emergency response factors, and the dispatch recommendation coefficient of each first aid station is determined based on the emergency status benefit index:

[0142]

[0143] Among them, S i Expressed as the dispatch recommendation coefficient of the i-th emergency station, p i is the first aid status benefit index of the i-th first aid station, Ni is the number of first aid adaptation targets of the i-th first aid station, j is the first aid adaptation target, d j It is expressed as the decision variable complexity of the emergency vehicle dispatch strategy corresponding to the j-th emergency adaptation goal, e is expressed as a natural constant with a value of 2.72, Q i Expressed as the weight of the dispatch interference factor affecting the kth emergency adaptation target, F i Expressed as the multi-emergency synchronization factor of the i-th emergency station, θ i It is represented as the emergency vehicle dispatch task response index of the i-th emergency station;

[0144] Select the target emergency station with the highest dispatch recommendation index, determine the idle smart emergency vehicles in the target emergency station, and generate a dispatch plan for the idle smart emergency vehicles;

[0145] Comprehensively dispatch idle ambulances based on the dispatch plan.

[0146] The beneficial effect of the above technical solution is: by calculating the dispatch recommendation coefficient of each first aid station and then selecting the target first aid station, the rapid response of each first aid battle to the first aid task and the dispatch of ambulances can be comprehensively evaluated based on the first aid target response parameters and synchronous first aid status parameters of each first aid station, thereby ensuring the dispatch efficiency of the ambulance.

[0147] In one embodiment, this embodiment also discloses a method for operating an intelligent emergency vehicle based on voice control, such as Figure 4 As shown, the following steps are included:

[0148] Step S401: Collect the voice signal of the medical staff and determine whether it is a voice command. If so, analyze the command attributes of the voice command and determine the travel destination requirements and operation item requirements based on the command attributes;

[0149] Step S402: planning a moving route based on the destination demand and displaying the navigation route, monitoring the location parameters of the ambulance during travel and providing a destination arrival reminder based on the location parameters;

[0150] Step S403: Determine first aid equipment and first aid medicines according to the operation project requirements and record the operation time parameters and operation process parameters of the first aid equipment and first aid medicines by the medical staff;

[0151] Step S404: Upload the operation duration parameters and operation process parameters to the medical information system and perform an inventory count of emergency equipment and emergency medicines to generate a replenishment list and upload it to the logistics system.

[0152] The working principle and beneficial effects of the above technical solution have been explained in the system embodiment and will not be repeated here.

[0153] Those skilled in the art should understand that the first and second in the present invention simply refer to different application stages.

[0154] Other embodiments of the present disclosure will readily occur to those skilled in the art after considering the specification and practicing the disclosure herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow from the general principles of the present disclosure and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered as exemplary only, with the true scope and spirit of the present disclosure being indicated by the following claims.

[0155] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes can be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. An intelligent emergency vehicle system based on voice control, characterized in that: The system includes: A determination module is used to collect the voice signal of the medical staff and determine whether it is a voice command. If so, it analyzes the command attributes of the voice command and determines the travel destination requirements and operation item requirements based on the command attributes; The reminder module is used to plan the movement path based on the travel destination requirements and display the navigation route, monitor the location parameters of the ambulance during the driving process and issue destination arrival reminders based on the location parameters; The recording module is used to determine the emergency equipment and emergency medicines according to the operation project requirements and record the operation time parameters and operation process parameters of the emergency equipment and emergency medicines by medical staff; A generation module is used to upload the operation time parameters and operation process parameters to the medical information system and to conduct an inventory count of emergency equipment and emergency medicines to generate a replenishment list and upload it to the logistics system; The reminder module includes: A planning submodule, configured to plan a moving path according to the travel destination requirements based on a path planning algorithm and real-time traffic information, and display the moving path based on a navigation system; A first acquisition submodule is configured to acquire the location information of the ambulance in real time based on the Beidou positioning system and in combination with the displayed route, and to acquire the speed and travel direction of the ambulance based on the location information of the ambulance; a reminder submodule, configured to draw a travel trajectory of the ambulance based on the speed and travel direction of the ambulance, estimate the time to arrive at the destination based on the travel trajectory, and remind the driver and medical staff through a reminder mechanism; After planning the moving path based on the path planning algorithm and real-time traffic information according to the travel destination requirements, the system is further configured to: Count the number of turning points and multiple lane types of the intelligent emergency vehicle based on its moving path; Based on the number of turning points, the information of the surrounding buildings of each turning point is obtained, the crowd gathering attributes are determined based on the building group information, and the influence weight of the turning decision is determined based on the crowd gathering attributes; Determine the turning time cost index when the smart emergency vehicle passes each turning point based on the turning decision influence weight, and determine the recommendation degree of each turning point based on the turning time cost index; Select qualified turning points and unqualified turning points based on the recommendation degree of each turning point, and determine an alternative road for each unqualified turning point; The moving path is adjusted based on the replacement road to obtain a first moving path, and a road-level path is determined according to a statistical number parameter of multiple types of lanes; Convert the road-level path into a lane-level path, determine the lane-change convenience of the intelligent emergency vehicle based on the lane-level path, and determine the eligibility of multiple lane ratios based on the lane-change convenience; Determine the heading offset parameter of the intelligent emergency vehicle based on the eligibility of multiple lane ratios and preset planning time parameters, and determine the offset compensation coefficient based on the heading offset parameter and the preset lane offset suppression factor; Substituting the offset compensation coefficient into a preset offset compensation function to determine a theoretical offset direction within a preset planning duration; Determine multiple lane distribution parameters in a theoretical offset direction, and generate a lane layer information model and a road layer information model based on the multiple lane distribution parameters; According to the lane layer information model and the road layer information model, a multi-lane trajectory is planned through a target search algorithm; The first moving path is adjusted according to the multi-lane travel trajectories to obtain a second moving path, and the second moving path is confirmed as the final moving path of the intelligent ambulance.

2. The intelligent emergency vehicle system based on voice control according to claim 1, characterized in that: The determining module includes: An acquisition submodule, configured to acquire voice signals of medical staff using a high-sensitivity microphone array and pre-process the voice signals; The judgment submodule is used to perform voice energy detection and wake-up word detection on the preprocessed voice signal, and determine whether it is a voice command based on the detection results; The recognition submodule is used to perform speech recognition on voice commands based on the Transformer model, and identify the intent and entity of the voice commands based on the recognition results and combined with natural language processing technology; an extraction submodule, configured to parse instruction attributes of the voice instruction according to the intent and entity of the voice instruction, and extract keywords and information related to travel and operation according to the instruction attributes; The first determination submodule is configured to determine a travel destination requirement and an operation item requirement based on the keywords and information.

3. The intelligent emergency vehicle system based on voice control according to claim 2, characterized in that: The judgment submodule performs speech energy detection and wake-up word detection on the preprocessed speech signal, including: The pre-processed speech signal is divided into frames according to a preset time interval, and the energy value of each frame is calculated according to the energy calculation formula; Determining a speech activity segment based on the energy value and in combination with a preset energy threshold, and performing speech energy detection of the speech signal based on the speech activity segment; Obtain a preset number of wake-up word speech data and annotate the word attributes and word categories, and perform feature extraction on the annotated speech data based on the Mel spectrum; A wake-up word template is constructed based on the extracted voice data features, and the similarity between the input voice and the wake-up word template is determined using a dynamic time warping algorithm. Wake-up word detection of the voice signal is implemented according to the similarity.

4. The intelligent emergency vehicle system based on voice control according to claim 1, characterized in that: The recording module includes: A second determination submodule is configured to obtain an operation type according to an operation item requirement, determine a risk level of the operation item according to the operation type, and identify a possible emergency situation according to the risk level; A third determining submodule is configured to determine first aid equipment and first aid medicines according to the possible emergency situation; The second acquisition submodule is used to obtain the operation time parameters of the first aid equipment and first aid medicines according to the equipment use automatic recording system and the medicine cabinet intelligent access recording system; The capture submodule is used to monitor the operating status of emergency equipment in real time based on the status sensor, and to obtain the hand motion data of medical staff using emergency equipment and emergency medicines based on the hand motion capture system; The fourth determining submodule is used to determine the operating process parameters of the first aid equipment and first aid medicines according to the operating status and hand motion data.

5. The intelligent ambulance system based on voice control according to claim 4 is characterized in that: Real-time monitoring of the operating status of emergency equipment based on status sensors, including: Collecting the operating data of the equipment in real time according to the status sensor and preprocessing the operating data; Decompose and separate the vibration signal based on the preprocessing results and in combination with empirical mode analysis and independent component analysis, and obtain the characteristic signal of the emergency equipment during operation based on the processing results; Constructing a convolutional neural network model and extracting key features of characteristic signals during the operation of the emergency equipment; The operating status of emergency equipment is monitored in real time based on the extracted key features.

6. The intelligent emergency vehicle system based on voice control according to claim 1, characterized in that: The generation module includes: a processing submodule, configured to perform parameter preprocessing and formatting on the operation duration parameter and the operation process parameter to obtain data in a data format compatible with a medical information system; The import submodule is used to import data in a data format compatible with the medical information system according to the API interface of the medical information system; The third acquisition submodule is used to count the emergency equipment and emergency medicines according to the imported results, and obtain the usage and inventory levels of the emergency equipment and emergency medicines according to the counting results; The generation submodule is used to generate a replenishment list based on usage and inventory levels and upload it to the logistics system.

7. The intelligent emergency vehicle system based on voice control according to claim 1, characterized in that: The system is also used to: Determine the station number of each emergency station to which each intelligent emergency vehicle belongs, and determine the dynamic emergency response factor of each emergency station through the emergency station database based on the station number; The emergency status benefit index of each first aid station is determined based on the dynamic emergency response factors, and the dispatch recommendation coefficient of each first aid station is determined based on the emergency status benefit index: Among them, S i Expressed as the dispatch recommendation coefficient of the i-th emergency station, p i is the first aid status benefit index of the i-th first aid station, Ni is the number of first aid adaptation targets of the i-th first aid station, j is the first aid adaptation target, d j It is expressed as the decision variable complexity of the emergency vehicle dispatch strategy corresponding to the j-th emergency adaptation goal, e is expressed as a natural constant with a value of 2.72, Q j Expressed as the impact weight of the dispatch interference factor of the jth emergency adaptation target, F i Expressed as the multi-emergency synchronization factor of the i-th emergency station, θ i It is represented as the emergency vehicle dispatch task response index of the i-th emergency station; Select the target emergency station with the highest dispatch recommendation index, determine the idle smart emergency vehicles in the target emergency station, and generate a dispatch plan for the idle smart emergency vehicles; Comprehensively dispatch idle ambulances based on the dispatch plan.

8. A method for operating an intelligent emergency vehicle based on voice control, characterized in that: The following steps are involved: S1. Collect the medical staff's voice signal and determine whether it is a voice command. If so, analyze the command attributes of the voice command and determine the travel destination requirements and operation item requirements based on the command attributes; S2. Plan the movement path based on the destination and display the navigation route, monitor the location parameters of the ambulance during the driving process and provide destination arrival reminder based on the location parameters; S3. Determine the emergency equipment and emergency medicines according to the operation project requirements and record the operation time parameters and operation process parameters of the emergency equipment and emergency medicines by medical staff; S4. Upload the operation duration parameters and operation process parameters to the medical information system and conduct an inventory of emergency equipment and emergency medicines to generate a replenishment list and upload it to the logistics system; Wherein step S2 comprises: Planning a moving path based on the travel destination requirements based on a path planning algorithm and real-time traffic information, and displaying the moving path based on a navigation system; obtaining the location information of the ambulance in real time based on the Beidou positioning system and in combination with the displayed route, and obtaining the speed and direction of travel of the ambulance based on the location information of the ambulance; Draw a travel trajectory of the ambulance based on the speed and travel direction of the ambulance, estimate the time to arrive at the destination based on the travel trajectory, and alert the driver and medical staff through an alert mechanism; After planning the moving path based on the path planning algorithm and real-time traffic information according to the travel destination requirements, the method further includes: Count the number of turning points and multiple lane types of the intelligent emergency vehicle based on its moving path; Based on the number of turning points, the information of the surrounding buildings of each turning point is obtained, the crowd gathering attributes are determined based on the building group information, and the influence weight of the turning decision is determined based on the crowd gathering attributes; Determine the turning time cost index when the smart emergency vehicle passes each turning point based on the turning decision influence weight, and determine the recommendation degree of each turning point based on the turning time cost index; Select qualified turning points and unqualified turning points based on the recommendation degree of each turning point, and determine an alternative road for each unqualified turning point; The moving path is adjusted based on the replacement road to obtain a first moving path, and a road-level path is determined according to a statistical number parameter of multiple types of lanes; Convert the road-level path into a lane-level path, determine the lane-change convenience of the intelligent emergency vehicle based on the lane-level path, and determine the eligibility of multiple lane ratios based on the lane-change convenience; Determine the heading offset parameter of the intelligent emergency vehicle based on the eligibility of multiple lane ratios and preset planning time parameters, and determine the offset compensation coefficient based on the heading offset parameter and the preset lane offset suppression factor; Substituting the offset compensation coefficient into a preset offset compensation function to determine a theoretical offset direction within a preset planning duration; Determine multiple lane distribution parameters in a theoretical offset direction, and generate a lane layer information model and a road layer information model based on the multiple lane distribution parameters; According to the lane layer information model and the road layer information model, a multi-lane trajectory is planned through a target search algorithm; The first moving path is adjusted according to the multi-lane travel trajectories to obtain a second moving path, and the second moving path is confirmed as the final moving path of the intelligent ambulance.

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