3401 results about "Alarm message" patented technology

The invention discloses an old people tumble alarm system and method based on multiple sensors, and relates to the technical field of intelligent monitoring, and the system collects the body data of old people through an intelligent bracelet and a sensor group, transmits the body data to a cloud platform through a wireless network, carries out the processing, and generates a state data group. The acceleration modulus length, the angular velocity modulus length, the gait cycle and the posture angle of the old people are calculated, so that the motion state and the falling risk are accurately judged, a falling risk assessment coefficient is calculated based on the data, old people falling assessment is performed according to the falling risk assessment coefficient and a preset falling risk threshold value, and an alarm is triggered and a guardian is notified when the risk exceeds the standard. The heart rate variability index and the blood oxygen content are analyzed, a comprehensive health index is obtained through calculation, possible body injury after falling is evaluated, and injury alarm information is generated. The system can accurately monitor the health state of the old people in real time, timely send out early warning and alarm information, and provide comprehensive fall prevention and health monitoring guarantee.

The invention discloses a railway freight train data acquisition method and system based on multi-sensor fusion, and relates to the technical field of railway transportation, and the method comprises the steps: detecting the operation state and position of a train in real time through wireless communication, and carrying out the self-inspection of each sensor when the train is detected to be about to enter a monitoring region; constructing a three-dimensional health state model of the train through three-dimensional reconstruction and synchronous positioning according to the comprehensive state data of the train; in combination with a three-dimensional health state model and a side cloud collaborative architecture, layered processing and dynamic optimization of train comprehensive state data are accelerated by using a quantum algorithm, and abnormal features are identified in real time; the abnormal features are analyzed through deep learning and a time sequence analysis algorithm, and alarm information is generated and fed back to the edge computing terminal; according to the method, the running state of the train and the cargo state data are deeply fused through the convolution operation of the three-dimensional health state model and the space-time diagram, so that the global perception capability of the data is improved.

The invention provides a substation operation risk analysis method, and relates to the technical field of information, and the method comprises the steps: recognizing whether a person correctly wears a protection device or not in real time through a radio frequency identification reader on the protection device, triggering an alarm if the person does not wear the protection device, and synchronizing the alarm information to a block chain node; the block chain is used for carrying out whole-process recording on the operation behavior of personnel, the operation state of equipment and the disposal condition of a security event to form auditing evidence of security operation, and meanwhile, according to the behavior of the personnel and the state of the equipment, a block chain node dynamically optimizes a security management strategy and an emergency plan to form closed-loop management, so that the security accident is effectively prevented, and the security management efficiency is improved. And the overall safety management level of the transformer substation is improved.

The invention relates to the technical field of fault detection, and discloses a remote electric energy meter fault detection and identification system and method, and the system comprises a data collection module, a data integration module, a data inspection module, a feature extraction module, a fault analysis module, and a fault alarm module. According to the method, multiple electric energy meter target data are collected and integrated into a corresponding data set, and a complete and ordered data basis is provided for analysis; abnormal values are recognized and replaced by calculating the average value and the standard deviation, the data quality is improved, and the accurate analysis result is guaranteed; key parameters covering multiple aspects are accurately extracted from a data set, and a powerful basis is provided for fault analysis; from metering, hardware and communication fault dimensions, according to comparison of extracted parameters and threshold values, fault types and positions are accurately judged in multiple directions; the fault alarm module remotely transmits an analysis result to a monitoring center, and generates an alarm message containing detailed information such as an electric energy meter number, a fault type, a parameter value, a threshold value and the like when a fault occurs, thereby facilitating timely maintenance by maintenance personnel.

The invention relates to the technical field of hydrological monitoring, and discloses a river flow monitoring method and system fusing multi-source data, and the method comprises the steps: collecting river flow data and river water level data through employing a high-precision sensor group, and collecting river image data through employing an unmanned plane; filtering the river flow data and the river water level data by adopting a Kalman filtering method to obtain filtered river flow data and filtered river water level data; performing edge detection on the riverway image data by adopting a Canny edge detection method to obtain riverway boundary information; on the basis of the riverway boundary information, a cubic spline interpolation method is adopted for interpolation, a smooth first boundary line and a smooth second boundary line are obtained, and the actual flow of the riverway is calculated on the basis of the filtered riverway water level data and the riverway flow velocity data; judging whether the actual flow of the riverway is greater than a riverway flow preset value, and if yes, sending alarm information; the actual flow of the river channel is calculated by fusing the multi-source data, and the accuracy of monitoring the flow of the river channel is improved.

The invention discloses a vital sign and sleep monitoring method and system based on a millimeter-wave radar, the method utilizes the millimeter-wave radar to realize non-contact sleep monitoring, and the millimeter-wave radar is firstly used to collect radar echo signals obtained by vibration of a chest wall in a sleep state; determining the position of a monitored object and extracting a vital sign signal of the target; then accurately detecting a first amplitude body movement and a second amplitude body movement of the target; whether an apnea event happens to the target is detected in real time, and alarm information is prompted under the condition that the event happens for a long time; three sleeping postures of supine, side-lying and prostrate are detected; and finally, sleep state monitoring is formed, a user sleep quality analysis report is formed in combination with the monitored information, and health suggestions are given. The method is simple, convenient, accurate, economical and efficient, is suitable for various application scenes such as families, hospitals and nursing homes, and provides all-weather health monitoring services for users.

The invention relates to the technical field of power grids, in particular to a metering box remote monitoring method, system and device based on artificial intelligence and a medium. Acquiring electrical parameter data and environmental data of the metering box; performing time domain and frequency domain feature extraction on the data to obtain key features; inputting the processed data into a preset abnormal state detection model; identifying an abnormal state of the metering box based on a model output result; and when the abnormity is identified, alarm information is generated and sent to a monitoring terminal through a remote communication network. Multi-dimensional monitoring data are collected in real time through multiple sensors, feature extraction and anomaly detection are performed by applying an artificial intelligence technology, a model is continuously optimized in combination with an online learning mechanism, and comprehensive sensing of the running state of the metering box and accurate recognition of the abnormal state are achieved. Compared with a traditional monitoring system, the method improves the detection accuracy, reduces the false alarm rate and the missing report rate, improves the fault processing efficiency through the automatic generation of the maintenance suggestions, and provides a powerful guarantee for the operation of a power system.

The invention relates to an electric energy quality detection device abnormity early warning method and system and an intelligent terminal, and relates to the technical field of electric energy detection, and the method comprises the steps: obtaining image detection information; when the image detection information is consistent with the reference image information, acquiring an electric energy detection parameter; when the electric energy detection parameter is inconsistent with the reference electric energy parameter, calculating a difference between the electric energy detection parameter and the reference electric energy parameter and taking the difference as an electric energy deviation value; when the electric energy deviation value does not fall into the reference deviation range, determining a wire loosening position according to the electric energy detection parameter and the phase parameter; according to the wire loosening position, traction is carried out through a traction method, and a wire rebound value and a wire specification are obtained; determining a reference rebound value according to the specification of the electric wire; if the wire rebound value is not less than the reference rebound value, continuing to obtain the electric energy detection parameter; and when the wire rebound value is smaller than the reference rebound value, outputting alarm information. The method and the device have the effect of improving the exception handling efficiency of the electric energy quality detection device.

The invention discloses a bulk cargo supply chain data transmission method and system based on an intelligent transportation box, and relates to the technical field of logistics data transmission, and the method comprises the steps: collecting multi-modal sensing data in real time through a multi-source data collection interface of the intelligent transportation box; the intelligent transportation box edge calculation module performs cleaning, compression aggregation and key event intelligent identification on the data; a transmission strategy is adaptively selected according to the data type and the network state, a key event alarm message is immediately sent, data are locally cached when the network is interrupted, and subsequent transmission is recovered; transmitting the data to a cloud by adopting a secure communication protocol; the cloud receives management data and provides remote configuration, alarm notification and data visualization functions, the system comprises an intelligent transportation box terminal unit and a cloud service platform unit, data transmission reliability and efficiency are improved, bandwidth and cloud cost are reduced, cargo transportation safety is guaranteed, and the system is suitable for bulk cargo cross-regional transportation scenes.

The invention discloses a gate control method and system based on an intelligent valve positioner, and relates to the technical field of gate dynamic control, and the method comprises the steps: setting parameters based on the intelligent valve positioner, dividing a valve into a plurality of intervals according to the parameters, and setting an independent PID parameter for each interval; the PID parameter is substituted into the optimized PID controller to generate a control signal; performing dead-zone compensation on the control signal, and generating a final control signal by combining the control signal; and valve control is conducted according to the final control signal. The two-way communication capability of the HART protocol is fully utilized, so that an operator can accurately adjust various parameters of the valve in a remote control room, and the parameters comprise key indexes such as flow characteristics, split-range control setting and stroke range. The remote control not only improves the convenience of operation, but also enables a control room to master the working state, operation parameters and alarm information of on-site electrical equipment at any time through a real-time data transmission function.

According to the transformer substation construction safety distance monitoring method, device and equipment and the storage medium provided by the embodiment of the invention, the three-dimensional target detection model is established through the obtained point cloud data of the transformer substation, and the first three-dimensional target detection is carried out based on the three-dimensional target detection model so as to detect whether the electrified equipment exists in the to-be-monitored area; and under the condition of determining that the electrified equipment exists in the to-be-monitored area, obtaining three-dimensional position information corresponding to the electrified equipment, dividing a risk area based on the three-dimensional position information, and then performing secondary three-dimensional target detection based on the three-dimensional target detection model so as to detect whether an invader exists in the risk area. When the condition that an invader exists in the risk area is determined, the type of the invader is further judged, namely whether the invader is an invader or a construction machine is judged, and finally the Euclidean distance between the electrified equipment and the invader is calculated based on the boundary information; and if the Euclidean distance exceeds a preset distance threshold, outputting alarm information based on the category information.

The invention discloses a multi-scene positioning and intelligent warning system and method for industrial equipment, and the system comprises a track analysis module which obtains the radar signal data of the industrial equipment, carries out the denoising, extracts a signal intensity change feature, and generates a human body dynamic track when the matching degree of the feature and a preset metal reflection model exceeds a threshold value; the abnormity judgment module is used for acquiring the vibration sensing data of the key position, generating a vibration frequency spectrum by applying wavelet decomposition, and generating abnormal vibration alarm information if the vibration frequency spectrum exceeds a range; the intrusion alarm module is used for acquiring node signal sources, performing weighted fusion to obtain an initial positioning coordinate group, inputting the initial positioning coordinate group into a three-dimensional map model, obtaining a final coordinate result through multi-source fusion, and sending out intrusion alarm information if the result falls into a dangerous fence boundary; and the safety evaluation module is used for performing time alignment and deep fusion on the human body dynamic track, the abnormal vibration alarm information and the intrusion alarm information to generate a safety evaluation report. According to the invention, omnibearing safety monitoring and management of industrial equipment are realized.

A multi-dimensional hydropower station control panel cabinet working condition abnormity monitoring method based on sound recognition is characterized in that a sound pickup, a mutual inductor, an infrared image monitor, a switch node sensor and the like are installed at different positions of a control panel cabinet to acquire multi-dimensional data including voiceprint, voltage, current, temperature, images and switch displacement signals; the voiceprint signals are subjected to pre-emphasis, framing, FFT transformation, Mel frequency filter bank application, MFCC feature extraction and the like, and feature vectors are extracted by using UBM, GMM and MAP algorithms. A PLDA algorithm is adopted for data analysis and fault judgment, multi-dimensional data comprehensive scoring is fused, the fault type is determined, alarm information and processing measures are output, and the system has the advantages of comprehensive multi-dimensional data acquisition, advanced signal processing technology, scientific and accurate fault judgment, high practicability and the like.

The invention discloses a sound acquisition and processing system based on cooperation of multiple microphone arrays. The system comprises a sound acquisition module, a multi-channel signal preprocessing module, a sound signal feature extraction module, an abnormal sound recognition module, a sound source positioning module and an alarm module. A multi-channel mixed data signal is collected through a circularly-arranged multi-microphone array formed by a plurality of microphones, after echo cancellation, wave beam domain noise reduction and multi-sound-source separation, a single-sound-source feature vector is extracted, according to the single-sound-source feature vector, abnormal sound including explosion, screaming or glass breakage is recognized through a BiLSTM and an attention mechanism model, and the abnormal sound is recognized through an attention mechanism model. And the GCC-PHAT and MDS-MUSIC algorithms are combined to position abnormal sound production, and alarm information is generated. According to the invention, accurate identification, positioning and alarm of the abnormal sound can be realized, and the real-time performance, the accuracy and the multi-target processing capability of abnormal sound monitoring in a complex environment can be obviously improved.

The invention discloses a safety early warning and alarming system based on a subway underground excavation construction environment, and relates to the technical field of early warning and alarming, the safety early warning and alarming system comprises a safety early warning platform, the safety early warning platform is in communication connection with a data acquisition module, a data transmission module, a data analysis module, an early warning analysis module, an alarm notification module and a visual report module, all the modules are connected through electric signals. By monitoring state information of key parts, performing data processing and analysis in time and capturing subtle changes which easily generate potential safety hazards in time, potential potential safety hazards can be quickly found, and once monitoring data exceed a preset alarm threshold value, the system can immediately trigger an alarm mechanism to give an alarm. Alarm information is sent to related personnel in various modes such as short messages, mails or system notifications, so that risk response time is greatly shortened, decision time is provided for managers, and occurrence risks of safety accidents are effectively reduced.

The invention relates to the technical field of energy storage lithium batteries, and discloses a remote monitoring operation and maintenance management device for energy storage lithium batteries, which is characterized in that a battery temperature acquisition module, a battery voltage acquisition module, a battery current acquisition module and an environment temperature acquisition module are respectively used for acquiring the surface temperature, voltage and current of a battery cell of an energy storage lithium battery group and the environment temperature of the battery; the state of charge calculation module calculates the state of charge (SOC) of the energy storage lithium battery group; the battery fault diagnosis module performs battery abnormity detection to identify a fault battery; and the early warning module generates alarm information when the SOC is not in a preset range and detects that a fault battery exists in the energy storage lithium battery group. According to the method, more data are collected through the intelligent sensor, multiple calculation modes are established to calculate the SOC of the battery, the calculation result can accurately reflect the actual working state of the energy storage power station, real-time fault detection is carried out on the energy storage lithium battery, and the use safety of the energy storage lithium battery is guaranteed.

The invention discloses an intelligent power grid fault deduction method and device based on a knowledge graph and electronic equipment, and relates to the technical field of power grid fault diagnosis, and the method comprises the steps: receiving protection action alarm information and circuit breaker tripping alarm information when a target intelligent power grid breaks down; based on the protection action alarm information and the circuit breaker tripping alarm information, performing hypothesis reasoning by using a preset power grid topology knowledge graph to obtain a suspected fault equipment set; performing deductive reasoning on each suspected fault device in the suspected fault device set by using a preset protection configuration knowledge graph based on the protection action alarm information and the circuit breaker tripping alarm information to obtain observation event confidence corresponding to each suspected fault device; and evidence fusion reasoning is carried out on each suspected fault device based on each expected observation event confidence, and actual fault information of the smart power grid is obtained. The method can improve the accuracy of the fault diagnosis result of the smart power grid.

According to the positive pressure air-tight sealing waterproof and dustproof structure of the five-axis rotary table, multiple layers of active and passive waterproof and dustproof structures are arranged, so that cutting fluid or chippings are prevented from entering the rotary table, and even if liquid enters the rotary table, the liquid can be discharged out of the rotary table through an internal circulation channel; the damage of expensive parts such as a bearing, a coil and an electric appliance caused by the blocking failure of the sealing ring is avoided, heavy property loss and production delay are avoided, and the service life of the sealing ring and the maintenance time of the rotary table are greatly prolonged due to the multi-layer waterproof and dustproof structure; the whole five-axis rotary table is provided with a positive pressure gas circuit, a humidity sensor and an alarm system, once leakage occurs, alarm information can be sent out on an operation panel of a numerical control machine tool, but the rotary table can still continuously work for a period of time, heavy loss caused by coil burning when liquid enters the rotary table is avoided, and the service life of the rotary table is prolonged. And the safety is improved.

The invention provides a cross-border logistics order management method and a cross-border logistics order management system, and the method comprises the steps: carrying out the similarity comparison of package feature data and historical package feature data, and obtaining a similarity comparison result; if the preset similarity threshold is not exceeded, determining that the to-be-sent parcel is a target parcel; inputting the parcel feature data of the target parcel into a pre-trained digital twinborn model to obtain a digital twinborn body; carrying out analog simulation on the digital twinborn body based on the digital twinborn model, and generating a standard logistics track and a standard transportation cost; after the target parcel is delivered, an actual logistics track, actual transportation cost and current logistics environment information are acquired; and when the logistics deviation value exceeds a logistics abnormal threshold value or the cost deviation value exceeds a cost abnormal threshold value, generating alarm information. In the mode, automatic identification of repeated delivery, logistics abnormity and transportation cost abnormity can be realized, so that the intelligent and precise level of cross-border logistics order management is improved.

The invention provides a multi-factor correction and real-time early warning method and system based on bridge deflection, and the method comprises the steps: deploying a high-precision deflection sensor at a key position of a bridge, and collecting the deflection data of the bridge under different load and temperature conditions in real time; establishing an initial finite element model of a vehicle load and a temperature effect on the basis of the collected data, and correcting and optimizing the model through methods of static and dynamic load tests, weighted moving average and the like so as to accurately reflect the actual stress state of the bridge; combining the design standard, the safety margin and the historical monitoring data of the bridge to calculate a reasonable threshold value of the deflection of the bridge; in the real-time monitoring process, when actual deflection data exceed a set threshold value, the system automatically triggers an alarm mechanism, and alarm information is sent to a manager through a preset alarm channel; the functions of intelligent monitoring and early warning of the deflection of the bridge are achieved, and the safety and reliability of the bridge structure are improved.

The invention discloses an intelligent tunnel construction safety monitoring and early warning system and method, and belongs to the technical field of tunnel engineering monitoring. The method comprises the steps that construction quality data and environment data in the tunnel construction process are collected; performing data preprocessing on the data, extracting key features from the preprocessed data for analysis, and generating a daily data analysis report; generating a dynamic threshold of the construction quality data based on a dynamic adaptive threshold optimization model DATOM; and adjusting an early warning trigger condition according to the real-time construction stage label, and sending alarm information to terminal equipment when the construction quality data and the environment data deviate from the threshold value and reach the early warning condition. According to the method, the requirements of different construction stages on dynamic change of the monitoring parameter threshold can be met, and the safety monitoring and early warning precision is relatively high.

The invention provides an intelligent inspection warning method and system based on panoramic video fusion, and relates to the technical field of intelligent inspection, and the method comprises the steps: obtaining equipment fault first-level warning information through a panoramic video monitoring assembly; according to the abnormal equipment bit number list, constructing an equipment fault relation tree based on the upstream and downstream topological information of the equipment; based on the equipment fault relation tree, extracting first fault equipment, a mother node fault equipment set of the first fault equipment and a child node fault equipment set of the first fault equipment; based on the instrument monitoring state list, performing fault traceability analysis on the first fault equipment and the parent node fault equipment set to generate fault source equipment; adding the fault source equipment into a fault source equipment group; and generating an intelligent inspection warning signal according to the fault source equipment group. The technical problem that in the prior art, accurate traceability of the fault equipment is difficult to achieve is solved, and the technical effects of accurately positioning the fault source equipment and improving the alarm reliability are achieved.

A method for the dynamic integrity monitoring of a container runtime environment executed on a host computer, in which environment at least one container is executed and is managed by an orchestration device, in the orchestration device, when a container instance is started in the container runtime environment by the orchestration device, creating an instance-specific integrity rule concerning at least one resource of the host computer adding the instance-specific integrity rule to form a host-computer-specific integrity standard which includes an instance-specific integrity rule for each container instance already executed in the container runtime environment transmitting the host-computer-specific integrity standard to the host computer; in the host computer, checking the resources on the host computer allocated by container instances against the host-computer-specific integrity standard, and outputting an alarm message if the check reveals a breach of the host-computer-specific integrity standard.

The invention relates to a subway station large passenger flow emergency command linkage method and device and a storage medium. The method comprises the steps that station passenger flow information is received in real time; the station passenger flow information is preprocessed and analyzed, and real-time passenger flow data are extracted; the historical passenger flow data and the real-time passenger flow data are utilized, the future passenger flow condition and the number of passengers getting off a train about to arrive are predicted through a machine learning algorithm, if it is predicted that the future passenger flow exceeds a station bearing capacity threshold value, the abnormal passenger flow condition is judged, and if it is judged that the abnormal passenger flow is generated, a large passenger flow alarm is generated; alarm information is automatically generated according to large passenger flow alarm, and is pushed to an operation control center for confirmation; and after the alarm information is confirmed, an emergency plan is started for station management and control. Compared with the prior art, real-time monitoring, early warning, evaluation and emergency command of the large passenger flow of the subway station are realized, and the emergency response speed and the disposal efficiency are improved.

The invention discloses a fire-fighting fireproof door alarm information transmission device and method based on the Internet of Things, and relates to the technical field of fire-fighting alarm, and the method comprises the following steps: carrying out the multi-band continuous scanning of a wireless communication environment of a fireproof door alarm device deployment region after a fire emergency mode is started, identifying a target communication protocol frequency band used by the fireproof door alarm device, and obtaining spectrum parameter information of each frequency band to form a to-be-analyzed communication frequency band set; and extracting a working frequency band used by the peripheral wireless equipment based on a pre-established environment wireless equipment frequency band database. Frequency spectrum mapping is constructed through frequency spectrum scanning and an environment database, intelligent interference prediction is realized in combination with a support vector machine, coding parameters are dynamically adjusted based on interference intensity, the transmission reliability of key alarm information in a high-interference environment is improved, feedforward recognition and closed-loop regulation and control capabilities are achieved, and the method is suitable for popularization and application. And the problems of slow response and unstable transmission of a traditional system are effectively solved.

The invention relates to the technical field of street lamps, and provides a solar street lamp fault self-inspection and cloud alarm system, which comprises a cloud control platform and a local module, and is characterized in that the local module comprises a wireless communication unit, a data processing unit with a built-in dynamic decision algorithm, a data acquisition unit and an execution unit; the method comprises the following steps: periodically collecting real-time operation data and real-time environment data of the solar street lamp; outputting a fault type code and an emergency disposal instruction through the fault classification decision tree model; sending alarm information to the cloud control platform; the execution unit executes the emergency disposal instruction. According to the method, the dynamic threshold value interval is generated through the dynamic threshold value adjustment algorithm, the influence of dynamic environment parameters such as illumination intensity and temperature on the running state of the solar street lamp is fully considered, misjudgment caused by fixed threshold value judgment is avoided, the system false alarm rate is greatly reduced, and unnecessary manual troubleshooting cost is reduced.

The invention provides a multi-source data fusion high-altitude falling object detection system and a high-altitude falling object detection method. The system comprises an acceleration sensor, a sound sensor, a processor and an alarm module. The acceleration sensor monitors the acceleration change of the target falling object and preliminarily judges an object falling event; when the sound sensor preliminarily judges that an object falling event occurs, a sound signal generated by a target falling object is monitored, and sound source positioning is achieved; the processor receives data of the sensor and verifies an object falling event again through a data fusion algorithm, so that misjudgment is avoided. In addition, the alarm module further generates alarm information including the falling time, the object type and the falling position to give an alarm. The system solves the problem that in the prior art, the accuracy of object falling detection through a single-type sensor is low.

The invention discloses a household intelligent alarm device based on the Internet, and relates to the technical field of intelligent security and protection, and the device comprises an alarm information generation module which carries out the fusion of multi-source feature data, calculates an alarm index through a weighted summation method, and generates alarm information; the control instruction module is used for encrypting the alarm information, generating an encrypted data packet, sending the encrypted data packet to a remote user side through the Internet and receiving a control instruction of the user side; and the alarm command module is used for dynamically adjusting the alarm strategy based on the control instruction of the user side and generating an alarm processing command. By dynamically distributing the weight of the multi-source sensor, the adaptability of the device is improved, and false alarms caused by environment changes in the daytime and at night are reduced; in combination with historical false alarm data analysis and a self-adaptive updating algorithm, an alarm threshold is continuously optimized, the alarm accuracy is improved, and the false alarm rate and the missing report rate are reduced.

The invention, which relates to the technical field of data management, discloses an Internet-of-Things intelligent security data system comprising a data acquisition module for acquiring field data based on a sensor and a camera; the data transmission module is used for transmitting the acquired data through a network; the data analysis module is used for identifying and pre-warning potential security threats based on a clustering analysis algorithm, and carrying out danger coefficient scoring on the potential security threats; the alarm level identification module is used for dynamically adjusting the alarm level based on the risk coefficient score; and the alarm information pushing module is used for automatically triggering linkage equipment according to different alarm levels and situations and pushing the alarm information. Through sensor data acquisition, edge calculation, clustering analysis, danger coefficient scoring and other technical means, the prediction capability, response speed and processing efficiency of the security event are effectively improved, and through automatic linkage equipment and an intelligent alarm mechanism, it is ensured that the security event is responded and processed in time.

The invention provides an elevator emergency rescue data intelligent analysis and early warning method and system, and relates to the technical field of data analysis, and the method comprises the steps: collecting operation parameter data, carrying out preprocessing, carrying out local calculation through an elevator safety evaluation model, outputting a safety evaluation score, determining a safety level, and judging whether to trigger an early warning mechanism or not. If triggered, early warning information is sent, early warning information classification and summarization are carried out, a historical early warning data sequence is obtained, feature learning is carried out, deep features are generated, fault probability distribution is predicted, key omen factors are identified, and an elevator fault early warning report and a preventive maintenance strategy are generated; whether an alarm mechanism is triggered or not is judged, if yes, alarm information is sent, correlation matching, representation learning and semantic label information extraction are carried out, a graph-based Markov decision process is modeled, a fault diagnosis report is obtained through solving, and a rescue action combination is selected to obtain an initial rescue scheme; and an optimal rescue scheme is obtained through optimization and sent to a safety management department.