1074 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 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 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 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 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 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 relates to a disaster site injury condition identification device and a distributed disaster response processing system. The method comprises the following steps: acquiring disaster data, and constructing an entity recognition model for multi-disaster emergency processing according to the data; meanwhile, vital sign data of the wounded person on a disaster site are obtained and processed through an injury condition classification model obtained based on machine learning training to generate an injury condition result, an injury condition score is obtained according to the injury condition result and the evaluation index corresponding to each model, and then an injury condition identifier corresponding to the wounded person is generated. And then, based on the constructed entity identification model, identifying and analyzing the disaster data and the injury identification, and generating a disaster response plan. And finally, distributing the pre-arranged plan to each disaster site, and obtaining a scheduling strategy of the corresponding disaster site. The pertinence and the practicability of the disaster response plan are remarkably improved, reasonable allocation of rescue resources and scientific arrangement of the wounded are ensured, and the high efficiency and the intelligence of the disaster response process are improved.

The invention provides assembly type integrated sewage treatment equipment for environmental emergency treatment, which is applied to the field of sewage treatment, and comprises an assembly type stepped assembled wetland system, an in-situ filler regeneration system and an ecological filler regeneration system, the wetland system comprises a wetland box, a purification mechanism is arranged in the wetland box, the wetland box comprises an inner box, and an outer box is arranged in the inner box; a plurality of parallel and inclined filler columns are arranged in the inner box, each filler column comprises a columnar reticulated shell, filler and flexible spiral blades are arranged in the columnar reticulated shell, the purification mechanism further comprises a side plate, the assembly type assembly design is adopted, all the systems can be rapidly connected and installed, the deployment time in an emergency scene is greatly shortened, the design of the filler columns is convenient, and the service life of the system is prolonged. Impurities and pollutants in sewage can be effectively intercepted and filtered, the arrangement of a rotating structure of the filler column and the flexible spiral blades can promote the uniformity of filler biofilm formation, and the treatment efficiency is improved; meanwhile, the grid box, the aeration box, the settling box and the like work cooperatively, so that multi-stage treatment of the sewage is realized.

The invention discloses a construction method for repairing a shield tunnel, which comprises the following steps: S1, carrying out emergency treatment on tunnel collapse, and controlling the tunnel collapse and submerging range; s2, selecting a new tunnel line to avoid the original collapsed tunnel, and fitting a section tunnel flat and vertical section line; s3, an open cut vertical shaft is arranged in the tunnel collapse area, an open cut method is adopted for construction, excavation is conducted step by step, and a supporting structure is erected step by step; s4, the open cut vertical shaft is connected with the intact shield tunnel; s5, carrying out obstacle clearing processing on underground obstacles; s6, when the open cut vertical shaft is constructed, a shield tunneling machine is newly started at the receiving end of the tunnel, and construction is conducted according to a new line of the tunnel; and S7, after open cut shaft construction is completed, a new starting shield tunneling machine is received, and repairing of the whole shield tunnel is completed. According to the method, on the basis that the existing tunnel is fully utilized, ex-situ repair of the collapsed tunnel can be rapidly and economically achieved.

The invention discloses an abnormality monitoring method and system for a feed production control system, and relates to the technical field of abnormality monitoring. During operation of the system, safety data of raw materials, production processes and feed finished products are collected by deploying various high-precision sensors, analysis equipment and sensors; a first data set, a second data set and a third data set are obtained, the collected data are preprocessed and calculated to obtain a production safety index Slaq, the production safety index Slaq is compared with a preset first qualified threshold value M and a preset second qualified threshold value N, a grade strategy scheme is obtained, abnormal conditions in the production process are detected in real time, potential problems are recognized, and the production safety index Slaq is obtained. According to the abnormal condition identified by the abnormal detection module, preliminary emergency treatment measures are executed, including adjusting production parameters or starting an emergency plan, and when the abnormal detection module or the abnormal response module identifies an abnormal condition, the abnormal condition is fed back to an operator in time in a sound-light alarm or mobile terminal notification mode.

According to one embodiment of the present invention, a method for correcting for loss of a chest compression depth of a patient includes a) setting a value of a chest compression start position of the patient to start chest compression of the patient with a lower end of a piston positioned above a chest of the patient, and then expanding or contracting the piston so that the lower end of the piston moves to the chest compression start position according to the value of the chest compression start position of the patient, by a control unit, b) applying a value of an initial chest compression depth which is a movement length value of the piston from the chest compression start position of the patient toward an upper side of a base plate supporting a back of the patient and a threshold value of the chest compression depth to expand and contract the piston so that chest compression is performed, and detecting a change in a shape of the chest of the patient during chest compression to update the chest compression start position of the patient, by the control unit, c) comparing and determining a value obtained by adding a separation distance between a cap fastened to the lower end of the piston and the chest of the patient and the value of the initial chest compression depth and the threshold value of the chest compression depth, by the control unit, and d) expanding and contracting the piston so that the cap reciprocates according to the value of the initial or updated chest compression depth to perform the chest compression by the cap.

The invention relates to the technical field of safety monitoring, in particular to an intelligent safety monitoring method and system for a coal yard of a thermal power plant, and the method comprises the steps: carrying out the multi-dimensional safety monitoring analysis based on a coal pile infrared thermogram, a coal yard monitoring image and environment monitoring data, and determining a multi-dimensional safety monitoring analysis result. When the multi-dimensional safety monitoring analysis result is abnormal, emergency processing analysis is carried out based on abnormal data, emergency measure information is determined, and the emergency measure information is sent to the corresponding linkage equipment, so that the linkage equipment is controlled to automatically execute emergency measures. In the process of carrying out safety monitoring on the coal yard of the thermal power plant, multi-dimensional monitoring analysis on the safety of the coal yard is realized by integrating multiple monitoring means and data resources, the limitation of a single monitoring mode in related technologies is solved, the discovery and processing efficiency of potential safety hazards is improved, and the safety of the coal yard is ensured. And powerful technical support is provided for safety management of the coal yard of the thermal power plant.

The invention belongs to the field of water pollution emergency treatment, and particularly relates to a deep water emergency treatment device which comprises a buoyancy platform, an electric lifting device, a purification device and a PLC, the center of the buoyancy platform is hollowed out, the electric lifting device is installed at the center of the buoyancy platform, and the purification device comprises a medicine storage bin, a pressure pump and a spraying module. The pesticide storage bin and the pressure pump are arranged on the surface of the buoyancy platform, the PLC is arranged on the pesticide storage bin, the spraying module is arranged on the electric lifting device, the spraying module is sequentially connected with the pressure pump and the pesticide storage bin through pipelines, and the electric lifting device and the pressure pump are electrically connected with the PLC. According to the invention, water pollution at different depths can be rapidly treated, the water pollution treatment efficiency is improved, and secondary pollution caused by excessive dosing is avoided.

The embodiment of the present application relates to the pile foundation construction technical field, specifically discloses a kind of karst pile foundation leak slurry early warning method and system.The embodiment of the present application is determined by pile foundation construction area, carries out geological radar detection, electrical prospecting and borehole exploration to pile foundation construction area, obtains geological detection data;Monitoring deployment is carried out, and real-time monitoring data is obtained, and three-dimensional monitoring model is established, and visual monitoring display is carried out;Extract multiple key feature data in real-time monitoring data, import into the preset slurry leakage preset model, obtain slurry leakage prediction probability;According to slurry leakage prediction probability, determine slurry leakage early warning level, according to slurry leakage early warning level, early warning and emergency treatment are carried out.The present application breaks through the dependence of traditional grouting process on crack morphology by innovative design of the synergistic plugging mechanism of pH-sensitive pneumatic capsules and geological bonding agents, using the instantaneous negative pressure field effect to drive the directional enrichment of nanomaterials, triggering in-situ strengthening reactions based on the mineral characteristics of rock mass.

The invention provides an edge calculation and AR collaborative intelligent first-aid method and system based on trauma grading, and relates to the technical field of trauma first-aid, and the method comprises the steps: collecting trauma field data through a multi-modal sensor, constructing a dynamic digital twinborn model, and calling a medical knowledge graph to carry out trauma grading evaluation. And generating multiple groups of emergency plans based on a biological plasticity calculation principle, performing parallel deduction to select an optimal plan, and continuously collecting, feeding back and optimizing the plan through the neural morphology adaptive sensing network. Accurate grading and intelligent decision making of the emergency treatment process are achieved, and the emergency treatment efficiency and accuracy are improved.