1749 results about "Emergency treatment" patented technology

The invention relates to the technical field of river channel environment monitoring, and discloses a river channel monitoring system based on the Internet of Things. The system comprises a multi-mode sensing module, an environment feature analysis module, a space-time coupling modeling module, a self-adaptive resource scheduling module and an intelligent cooperative control module. The multi-modal sensing module collects multi-source heterogeneous data, the environment feature analysis module extracts various feature vectors, the space-time coupling modeling module generates a coupling space-time feature matrix, and the self-adaptive resource scheduling module constructs a double-layer optimization library and stores related rule strategies. And the intelligent cooperative control module generates a real-time pollution early warning instruction and a hydrological regulation and control decision through a multi-target reinforcement learning framework based on the results. In addition, the system can carry out anomaly detection and emergency treatment on the floating objects and predict sudden change of water quality. According to the system, comprehensive monitoring, intelligent analysis and accurate regulation and control of the river environment are realized, and the efficiency and scientificity of river management are improved.

The invention discloses an intelligent emergency pre-examination triage system based on big data, and relates to the technical field of data analysis, the emergency pre-examination triage system comprises a data acquisition module, an evaluation index extraction module, an intelligent analysis module, a triage evaluation module, a triage decision module, a feedback interaction module and a patient information management module, all the modules are connected through electric signals. According to the intelligent emergency treatment pre-examination triage system based on the big data, the comprehensive evaluation model and the triage evaluation coefficient are integrated, and the symptoms of the patient are evaluated quickly and accurately, so that the triage level and the recommended treatment department are quickly determined, the emergency treatment efficiency is remarkably improved, the waiting time of the patient is shortened, and the patient experience is improved. According to the method, medical resources are configured more reasonably, meanwhile, more comprehensive patient portraits can be provided for medical staff according to multi-dimensional information such as medical history and examination results of patients, and making of more accurate diagnosis and treatment decisions is facilitated.

The invention relates to the technical field of power distribution network recovery, in particular to an urban power distribution network toughness recovery management system under extreme weather, which comprises the steps of acquiring voltage, current, temperature, humidity and wind speed in real time, cleaning, formatting and standardizing data, identifying abnormal conditions influencing the stability of a power grid, evaluating the performance of the power grid under the extreme weather, and managing the toughness of the power distribution network under the extreme weather. An optimization suggestion is provided, various extreme weather scenes are simulated, feedback data are generated, comprehensive risk assessment is carried out, a coping strategy is generated, a fault point needing emergency processing is identified, recovery resources are dispatched, and a result is analyzed in real time to dynamically optimize an operation strategy of a power grid; according to the invention, by introducing the scene simulation and virtual training module, complex dynamic scene simulation is carried out, and coping strategies are verified and optimized. Feedback data generated by the system in simulation is used for further optimizing strategies in the toughness evaluation and decision support module, and adaptability and effectiveness of the strategies in actual extreme weather events are ensured.

The invention relates to the technical field of medical big data intelligent analysis, and discloses a medical big data intelligent analysis method and system based on deep learning, and the method comprises the steps: obtaining patient image data, case text data and wearable equipment monitoring data, carrying out the preprocessing, and carrying out the standardized coding of each modal data; and calculating the dynamic weight of each modal data, and synthesizing a multi-level fusion weight. And in combination with the fusion weight and the clinical state parameters of the patient, constructing a modal value-clinical urgency degree two-factor resource decision model to obtain a priority score. According to the priority scores, the patients are divided into different emergency treatment levels, and different treatment strategies are provided. The model provided by the invention can maintain efficient prediction capability in various clinical scenes, improves the accuracy of clinical decisions, and enables the resource allocation of hospitals to be more scientific and reasonable. In an emergency treatment environment, the real-time priority evaluation of the patient can significantly improve the efficiency of emergency treatment, reduce the waiting time, and improve the survival rate and the treatment effect of the patient.

The invention belongs to the technical field of hospital triage systems, and provides an outpatient and emergency triage system, comprising: an information collection module collecting basic information and symptoms of a patient as original data, and preprocessing the data; the intelligent triage module classifies and predicts symptom data input by a patient through a medical knowledge graph and a machine learning algorithm; the triage result output module allocates departments to the patients according to the classification and prediction results of the intelligent triage module, and predicts the waiting time of the patients based on historical data; the interaction module displays and informs the patient according to the distribution information of the triage result output module and the predicted waiting time; through the intelligent triage module, the severity of the illness state of a patient can be rapidly judged, critical patients can be processed preferentially, so that distribution of medical resources is optimized, the waiting time of the patient in a hospital can be shortened through prediction and scheduling of waiting time of the patient, and the treatment efficiency is improved.

The invention discloses a multi-model coupling water quality optimization method, system and equipment based on digital twinning, and belongs to the technical field of urban water pollution simulation. An existing water quality optimization scheme is mainly applied to a single system and lacks comprehensive consideration of a multi-system synergistic effect in a complex urban environment, and pollutant diffusion prediction and layout scheme optimization cannot be carried out on an urban underground pipe network. According to the multi-model coupling water quality optimization method based on digital twinning, sudden pollution diffusion information is obtained by simulating a hydrological process and carrying out sudden pollution diffusion simulation calculation; meanwhile, based on a digital twinning mechanism and sudden pollution diffusion information, a hydraulic structure operation optimization scheme is obtained, so that full-process simulation and optimization scheduling can be performed on urban sudden pollution diffusion, timely control over the sudden pollution diffusion is realized, manual intervention and hysteresis of decision can be greatly reduced, and the working efficiency is improved. The scheduling response time is obviously shortened, and the emergency processing efficiency is improved.

The invention relates to the technical field of electronic commerce dynamic management, and particularly discloses an electronic commerce management system and method based on big data, and the method comprises the steps: collecting the data of each commercial operation node of an electronic commerce platform, and carrying out the real-time collection and time serialization processing of the data; the transmission quantity, the flow direction and the interaction frequency of the collected data are analyzed, interaction modes among different operation nodes are monitored, and potential abnormal interaction nodes are identified; based on the abnormal interaction node, calculating a failure node coefficient for judging whether the node has a failure risk; for non-failure nodes, constructing a multi-dimensional risk assessment model, predicting future risks of the nodes by adopting a random forest algorithm, and calculating risk coefficients; through comprehensive analysis of the node abnormal coefficient, the failure node coefficient and the risk coefficient, priority early warning and emergency processing are performed on the high-risk node, so that the operation risk is effectively prevented, and the stability and the response capability of the platform are improved.

The invention specifically discloses a triage training system and method based on a large language model and a knowledge graph, and relates to the technical field of medical training. The system comprises a multi-modal data sensing and processing module which is used for accessing and processing diversified training data sources; the dynamic time sequence knowledge graph construction and updating module comprises an entity relationship extraction unit, a multi-modal alignment unit and a knowledge fusion and conflict resolution unit; the multi-agent collaborative service module is composed of large language model agents which are special in function and work cooperatively, and comprises an extraction agent, a construction agent, a reasoning agent and a teaching agent; and the immersive interactive training and feedback module comprises a virtual case generation unit, a multi-modal interactive interface and a deep feedback system. According to the invention, the authenticity, accuracy and effectiveness of training are significantly improved, it is ensured that the learned knowledge and skills can efficiently adapt to a real emergency treatment scene, and the accuracy and efficiency of triage classification in emergency treatment are improved.

The invention provides a double-machine lifting dynamic balance control method based on real-time load feedback, which comprises the following steps of: after a system is initialized, synchronously acquiring load, height, attitude, position, motion and environment data of two machines, and fusing and filtering; load, height, angle, position and motion coordination multiple deviations are calculated, and balance and safety are evaluated; generating a speed, position, attitude and safety comprehensive control strategy by using multi-objective optimization according to an evaluation result, and setting a priority and a look-ahead mechanism; executing instructions in a distributed manner and monitoring the instructions in real time; self-adaptive parameter adjustment and machine learning continuous optimization are carried out based on a feedback closed loop; and multi-stage safety monitoring and emergency processing are synchronized. According to the invention, the precision, safety and efficiency of hoisting operation can be improved, the operation difficulty and energy consumption are reduced, and the adaptability and reliability of the system in a complex environment are enhanced.

The invention discloses a water conservancy project construction management system and method based on three-dimensional visualization, and belongs to the technical field of water conservancy projects, and the method specifically comprises the steps: collecting related data of a water conservancy project construction region, carrying out the preprocessing, obtaining first monitoring data, building a three-dimensional digital model of a water conservancy project based on the first monitoring data, and carrying out the construction of the water conservancy project. On the basis of the hydraulic engineering three-dimensional digital model, hydraulic engineering construction risks are evaluated in combination with hydraulic engineering construction historical data, and risk grades are divided and hydraulic engineering construction is dynamically managed according to risk evaluation; on the basis of a three-dimensional visual model, all-around and real-time risk monitoring and evaluation can be carried out on a construction site, through real-time data collection and analysis, potential safety hazards such as geological changes, equipment faults and earthwork collapse can be found in time, early warning and emergency treatment are carried out in advance, and safety accidents are effectively avoided.

The invention relates to the technical field of treatment scheme optimization, and provides an emergency treatment critical patient first-aid path optimization method and system based on big data, and the method comprises the steps: building a standardized event sequence through extracting historical diagnosis and treatment data of a hospital information system, and analyzing the time sequence correlation between events through a graph structure mining technology, key diagnosis and treatment nodes and high and low frequency paths are identified, and a layered first-aid path state transition network is constructed based on the key diagnosis and treatment nodes and high and low frequency paths. When a real-time patient is processed, the system matches an electronic health record of the patient with a network core state, dynamically plans a subsequent standard transfer path, and avoids a low-frequency risk path marked as a taboo, so that an emergency path optimization scheme of risk avoidance and path dynamic optimization is realized, and the treatment efficiency of emergency critical patients is improved. The treatment effect is improved, and the bad prognosis risk is reduced.

The invention discloses an emergency processing method and device for an abnormal event, electronic equipment and a storage medium, and relates to the technical field of safety emergency management, and the emergency processing method for the abnormal event comprises the following steps: S10, constructing a BIM model of a target building by using BIM software, and constructing a CIM model in combination with the environment information of the target building and the BIM model, the monitoring equipment information is imported into the CIM model; s20, constructing a database in which emergency plans are stored; s30, analyzing data monitored by each monitoring device in the CIM model, and identifying an abnormal event; s40, judging whether a corresponding emergency plan exists in the database or not according to the detailed information of the abnormal event, if yes, calling and executing the emergency plan in the database, and if not, generating and executing a temporary emergency plan by utilizing a large language model; and S50, analyzing and summarizing an emergency plan or a temporary emergency plan, and upgrading and maintaining parameters of the emergency plan or the temporary emergency plan. The method has the beneficial effect that the emergency treatment efficiency and effect are optimized.

The invention provides a first-aid tourniquet pressure monitoring and automatic alarm system, and relates to the technical field of pressure monitoring. The system comprises a biological reaction monitoring module, a pressure adjustment analysis module, a real-time pressure adjustment module, a safety threshold detection module and an emergency response activation module. According to the invention, through real-time monitoring of biological reactions, changes of micro blood flow, skin electrical impedance and tissue morphology of a patient after the patient uses the tourniquet are captured, so that monitoring of individual reactions is more comprehensive, the safety and effect of pressure are evaluated in combination with the actual physiological state of the patient, monitoring is more dynamic and personalized, and the monitoring accuracy is improved. Through the combination of pressure real-time adjustment and emergency response, it is ensured that when the pressure exceeds a safety range, pressure adjustment is conducted rapidly, warning is given out through an alarm, secondary injury caused by improper pressure is avoided, the use safety and response speed of the tourniquet are improved, tissue injury of a patient can be more accurately prevented, and the patient can be more accurately protected. And the real-time effectiveness and safety in the emergency treatment process are ensured.

The invention discloses a flocculation treatment device and method for removing high turbidity of a water sample. The method comprises the following steps: monitoring an inflow turbidity parameter in real time, continuously collecting original optical characteristic data of water through an optical sensor array, and calculating a turbidity fluctuation rate parameter after noise reduction treatment; carrying out graded rotational flow mixing treatment, forming a pressure gradient through three stages of tapered rotational flow pipes in sequence, activating an ultrasonic frequency field, and synchronously adding main and auxiliary flocculants; the method comprises the following steps: introducing a water sample into a multi-stage gradient flocculation reaction zone, and sequentially executing turbulent flow enhanced flocculation, slow stirring flocculation and pulsed electric field assisted flocculation to form a floc structure with different particle size distribution; running parameters of a sedimentation module are adjusted according to real-time effluent turbidity feedback, and the inclination angle of an inclined plate assembly and the opening degree of a mud discharging valve are dynamically adjusted; a parameter set is updated through a prediction model based on periodically collected system operation data, a closed-loop optimization control strategy is formed, the adaptability to extreme turbidity is enhanced, the solid-liquid separation efficiency is improved, the overall energy consumption is reduced, and the efficient and stable requirements of emergency treatment are met.

The invention discloses a road traffic information monitoring system and method, and the method comprises the steps: deploying a video monitor, a sensor, an unmanned plane and a satellite device to collect real-time road traffic data, and protecting the data safety through encryption transmission and multilayer identity authentication; the flow is monitored in real time by combining image recognition and sensor data, congestion is analyzed, traffic violation is recognized, and an alarm is given; future flow is predicted through machine learning and big data analysis, and the signal lamp period is intelligently adjusted; through combination of real-time and historical data, accident risk points are identified and early warning is carried out, and early warning is automatically issued and adjustment and control are carried out for severe weather. The AI technology automatically identifies accidents and notifies a management center, dispatches emergency resources, optimizes signal lamps and lane traffic, and dynamically adjusts surrounding flow; according to the road traffic information monitoring system and method, an automatic emergency processing system is established, accidents are automatically detected and alarms are triggered under the conditions of traffic accidents and emergencies, and emergency resources are quickly dispatched.

The invention discloses a transformer dynamic diagnosis and early warning system based on sulfide deposition characteristics, and the system comprises a monitoring unit which is used for monitoring the deposition state of sulfide in a transformer in real time, and obtaining sulfide deposition characteristic parameters during the operation period of the transformer; the first diagnosis unit is used for judging whether the current sulfide deposition characteristic parameter affects the insulation system or not and obtaining a first diagnosis result; the second diagnosis unit is used for acquiring a second diagnosis result according to the propagation and attenuation characteristics of the electric signals, the thermal signals and the vibration signals under different turn-to-turn discharge positions, types and intensities; the fault diagnosis unit is used for judging whether the insulation defect and the turn-to-turn discharge phenomenon in the transformer reach the early warning level or not according to the first diagnosis result and the second diagnosis result; and the early warning unit is used for generating corresponding fault early warning information according to the current early warning level, and reminding a user or operation and maintenance personnel to take preventive maintenance or emergency treatment measures in real time.

The embodiment of the invention provides an emergency data quality control analysis method and device based on big data. Wherein a microcirculation dynamic mapping model with time-space correlation is constructed and integrated through a nanofiber sensing array of the flexible electronic skin device. And performing time reference synchronous compensation and space coordinate transformation mapping on the model and spatio-temporal data of emergency treatment monitoring equipment to form a fusion data field, thereby realizing joint feature distribution of microcirculation parameters and emergency treatment parameters. The fused data field is subjected to mode coupling verification with a microcirculation compensation track map in a shock compensation mode feature library through a dynamic quality control engine, and when it is detected that mode mismatching exists between a parameter evolution path and a historical track, space-time signal fragments are reconstructed based on phase features and space distortion features; and generating a quality control report associated with the abnormal skin perfusion gradient node. According to the technical scheme provided by the embodiment of the invention, the quality control effect of the emergency data of the shock patient is improved.

The invention relates to an intelligent first-aid decision system based on multi-modal fusion, which comprises a main control unit, and the main control unit is connected with a display unit, a connection unit, an interaction unit and a cross-linking unit. When the main control unit judges whether the patient has potential health hazards or not according to the patient life monitoring data, if yes, the main control unit predicts possible diseases according to the patient life monitoring data and generates predicted first-aid content according to all predicted diseases; when the doctor judges that the patient has diseases and needs emergency treatment, the predicted emergency treatment content is called through the main control unit for reference of the doctor. According to the application, the time for the main control module to generate the content can be saved when the first-aid situation occurs by generating the predicted first-aid content in advance, in addition, the main control module records the first-aid content, the legal risk prevention and control effect is achieved, the time axis precision is high, and the digital signature and CA authentication meet the judicial expertise requirement.

The invention discloses a water area pollutant emergency treatment system and equipment in the technical field of water pollution treatment, and the system comprises a plurality of water quality monitoring modules which are used for collecting water quality factors of a covered area and generating real-time water quality data; the data collection module is used for acquiring, storing and forwarding real-time water quality data; the prediction module is used for analyzing and predicting the pollutant component evolution condition based on the real-time water quality data by using a big data model, and generating a pollutant component evolution condition graph of the water area; the emergency preprocessing scheme generation module is used for generating a corresponding preprocessing scheme and a preprocessing position based on the pollutant diffusion range diagram and the pollutant component evolution situation diagram; the biological filtration assemblies are used for being deployed at the pretreatment position and filtering and cleaning the water area. Plants aiming at specific pollutants are planted on the biological filtration assembly, and long-term ecological restoration can be achieved while water area pollutants are emergently treated.

The invention relates to the technical field of cast-in-place pile construction, in particular to a cast-in-place pile drilling device for a pump station and a construction technology, and the cast-in-place pile drilling device comprises a drilling mechanism, a slurry recycling mechanism, a supporting mechanism and a tamping mechanism. According to the device, when the sliding plate descends, the first one-way rotating plate is driven to descend together, clay between the sliding plate and the soil discharging shell can be scraped and pushed to the position below the drilling barrel through the first one-way rotating plate, when the clay is discharged into the bottom of a hole, external air can be discharged into the space between a drill bit and the bottom of the hole together, and therefore the negative pressure strength can be reduced; a sliding plate continues to press downwards, clay can be compacted layer by layer through a compacting plate, when the sliding plate ascends, blocking is conducted through a second one-way rotating plate, and therefore the situation that the soil is backfilled into a soil discharging shell can be prevented, clay backfilling and tamping can be conducted on the collapsed hole wall at the first time, the collapse area is prevented from being increased, and the construction efficiency is improved. Emergency treatment can be carried out when hole wall collapse and hole wall hole shrinkage occur through the tamping mechanism, and it is guaranteed that follow-up drilling construction is recovered as soon as possible.

The invention discloses a multi-source environment monitoring and intelligent alarm system and method based on a Palladium platform. The method comprises the following steps: S1, obtaining preprocessed environment monitoring data; s2, forming transmission environment monitoring data; s3, carrying out distributed aggregation and fusion on the transmission environment monitoring data on the central Palladium platform; s4, identifying abnormal fluctuation in the data; s5, generating adjusted alarm threshold data by using a self-learning mechanism; s6, according to the adjusted alarm threshold data, carrying out grading evaluation on the detected environment abnormal events, forming multi-grade risk determination, and generating corresponding intelligent alarm signals; and S7, transmitting the intelligent alarm signal to each edge computing node and a related monitoring terminal, issuing alarm information in a short message, mail, voice broadcast or system interface display mode, and starting a corresponding emergency processing plan. According to the invention, the transmission efficiency of the alarm information can be effectively improved, and the emergency response system can make proper response according to different risk levels.

The invention relates to the field of clinical diagnostics, and discloses an elderly NSC emergency risk layering method and device and a medium, and the method comprises the steps: S1, obtaining multi-dimensional evaluation data of an elderly NSC patient; s2, adopting a preset risk mapping rule to convert the risk values into single risk values of a unified scale; s3, dividing the single risk value into a plurality of risk sub-models, and calculating a dimension risk score of each risk sub-model; s4, based on a preset fusion strategy, integrating the risk sub-model and the single risk value interaction effect, and calculating to obtain a total risk score of the patient; and S5, determining the risk level of the patient according to the total risk score, and outputting a clinical diagnosis and treatment suggestion. According to the method, multiple biomarkers and key clinical parameters are integrated, a multi-dimensional combined risk assessment model is constructed, and the potential pathological state of a patient can be reflected more comprehensively.

The invention discloses an electric power field operation management system, which relates to the technical field of electric power and comprises the following process modules: S1, planning; s1-1, an operation plan and task management module; s1-2, a power industry core combined scale block; s2, preparing; s2-1, a personnel and qualification management module; s2-2, a tool and material management module; s2-3, a risk assessment and scheme management module; s3, executing; s3-1, a field execution and monitoring module; s3-2, an emergency processing module; s4, checking and accepting; s4-1, an acceptance check and filing module; s4-2, a performance and data analysis module; s4-3, a system management module; and S5, summarizing. According to the electric power field operation management system, through systematicness and integrity of emergency plan management, a process covers full life cycle management of an emergency plan from formulation, auditing, issuing to updating, and meanwhile, links such as emergency response starting, disposal, resource management, information communication and recovery summarization are included; and a complete closed loop of prevention, preparation, response and recovery is formed.

The embodiment of the invention relates to the technical field of pile foundation construction, and particularly discloses a karst pile foundation slurry leakage prevention early warning method and system. According to the embodiment of the invention, the pile foundation construction area is determined, and geological radar detection, electrical exploration and drilling exploration are carried out on the pile foundation construction area to obtain geological detection data; monitoring deployment is carried out, real-time monitoring data is acquired, a three-dimensional monitoring model is established, and visual monitoring display is carried out; extracting a plurality of key feature data in the real-time monitoring data, and importing the key feature data into a preset slurry leakage model to obtain a slurry leakage prediction probability; and according to the slurry leakage prediction probability, determining a slurry leakage early warning grade, and according to the slurry leakage early warning grade, carrying out early warning alarm and emergency treatment. According to the method, a synergistic leaking stoppage mechanism of the pH sensitive pneumatic capsule and the geological bonding agent is innovatively designed, directional enrichment of nano materials is driven through the instantaneous negative pressure field effect, in-situ strengthening reaction based on rock mass mineral characteristics is triggered, and dependence of a traditional grouting process on the fracture form is broken through.

The invention discloses an all-directional monitoring and emergency treatment system for patients in the emergency department, which belongs to the technical field of diagnosis and monitoring of emergency surgery and comprises a data input and acquisition module, a data processing module, a data processing module, a data processing module, a data processing module and a data processing module, wherein the data input and acquisition module is used for acquiring emergency treatment features including external stimulation inducements and ages of a current patient before emergency treatment; the monitoring and evaluation module is used for acquiring an epilepsy risk evaluation value, a comprehensive evaluation value and a feedback adjustment value, and collecting all-dimensional monitoring characteristics of a current patient, including amygdalia activeness, a brain activity reference level, abnormal discharge intensity, heart rate, respiratory rate, systolic pressure value and diastolic pressure value, and the monitoring and evaluation module is used for acquiring and outputting the epilepsy risk evaluation value, the comprehensive evaluation value and the feedback adjustment value; the early warning module is responsible for carrying out early warning and inputting an adjusted first-aid strategy to the first-aid execution module when the epilepsy risk assessment value, the comprehensive assessment value and the feedback adjustment value are in a continuous monitoring rising trend on the visualization module, and comprehensive and real-time monitoring and accurate assessment of the illness state of a patient and timely adjustment of first-aid measures are achieved.

The invention discloses a hospital emergency triage method in combination with medical history data, and belongs to the technical field of medical triage, and the method specifically comprises the steps: obtaining the actual illness state and historical treatment data of a current patient to form a pre-examination data set, inputting an illness state prediction model to obtain a pathological entity and the confidence probability thereof, and preferably evaluating a dominant illness in combination with a danger coefficient; obtaining a target department corresponding to the dominant disease, calculating the coverage overlap ratio of the non-dominant disease and the treatment capacity of the target department, if the overlap ratio is smaller than or equal to a preset threshold value, obtaining the department corresponding to the non-dominant disease, marking the department as a candidate department, and extracting the treatment data of the department to calculate a waiting pressure coefficient; calling cross-department cooperation data to calculate candidate department response efficiency coefficients; the comprehensive turnover efficiency scores corresponding to the candidate departments are calculated, and the candidate department with the highest score is selected as the first diagnosis department, so that the patient turnover link minimization and the medical resource utilization optimization are realized on the premise that the dominant threat is preferentially treated, and the emergency treatment efficiency is improved.

The invention is suitable for the technical field of active vehicle control, and particularly relates to an active vehicle control method and system based on driver state monitoring, and the method comprises the steps: constructing an active vehicle control scene, editing a driving evaluation rule, collecting the real-time driving data of a target vehicle in the active vehicle control scene, and comparing the real-time driving data with the driving evaluation rule. Identifying risk factors, creating adjustment suggestions in one-to-one correspondence with the risk factors, issuing the adjustment suggestions to a vehicle-mounted terminal of the target vehicle, and performing voice playing; after playing is completed, real-time driving data continues to be collected, whether the risk factors exist or not is judged, if yes, a multi-level vehicle control strategy is constructed, and the multi-level vehicle control strategy is composed of a mild strategy, a moderate strategy and a takeover strategy. According to the invention, by selecting the parking point and generating the advancing route, the vehicle can be ensured to be parked at the position with the minimum risk, the safety of emergency treatment is obviously improved, the influence on other traffic participants on the road is reduced, and the vehicle control experience and the road traffic safety are improved.

The invention provides an intelligent transfer and self-rescue guidance aid decision-making method and system based on federal learning, and relates to the technical field of intelligent medical treatment, and the method comprises the steps: obtaining emergency help information, constructing an emergency rescue knowledge graph, extracting physiological feature parameters to recognize diseases, and generating a self-rescue scheme; based on the disease and position of the user, medical resources are retrieved, and an ant colony algorithm is adopted to solve the multi-objective optimization function to obtain an optimal transfer path; and inputting the transfer path and the self-rescue scheme into a federal learning model to obtain a comprehensive decision. Accurate and efficient emergency rescue and self-rescue guidance are realized, and the medical resource allocation efficiency and the first-aid success rate are improved.

The invention discloses an automatic detection method and system for small-size pests, and relates to the technical field of automatic detection of pests, environmental condition data in a pest monitoring area are collected, and pest data are collected by a sensor network; identifying insect types and position information in the insect pest image by using the trained insect pest target detection model; the insect types are verified according to the insect pest characteristics of the small-size insects, the insect intensity in the area is calculated according to the position information of the target insect pests and the time nodes, when the insect intensity exceeds the expectation, the trained insect pest outbreak prediction model is used for predicting the number of the insect pests, and if the prediction result exceeds the expectation, an alarm value is constructed according to the alarm data. And when the warning value exceeds a warning threshold value, outputting an insect pest emergency treatment scheme by the small-size insect pest treatment knowledge graph. On the basis of mutual cooperation and verification of a plurality of different characteristics, the detection reliability is improved when small-size insects are detected and identified.

The invention relates to the technical field of emergency treatment of marine ecological disasters, and provides an algae remover for emergency treatment of red tide and a preparation method of the algae remover. The algae remover comprises the following raw materials in parts by weight: 70-90 parts of clay, 10-40 parts of an inorganic flocculant and 0.02-1 part of an organic flocculant. The organic flocculating agent comprises poly dimethyl diallyl ammonium chloride and polyvinyl alcohol; the mass ratio of the poly dimethyl diallyl ammonium chloride to the polyvinyl alcohol is 10: (1-8). According to the technical scheme, the problem of low red tide organism removal rate of an algae remover in related technologies is solved.