211 results about "Alarm management" patented technology

The invention relates to the technical field of fault monitoring, in particular to a power transmission line fault monitoring and positioning method, system and device and a medium. The method comprises the following steps: firstly, performing digital conversion on an original current signal to obtain time sequence data, and then identifying and classifying fault events through threshold detection and a feature extraction algorithm to obtain classification labels of fault types; then, based on the classification label, establishing a traveling wave propagation model and carrying out time difference calculation, carrying out clustering analysis on a plurality of wave head data in a preset time window, and judging whether the fault is a single-point fault or a multi-point fault through a clustering result; and finally, a positioning result is transmitted to the central server for comprehensive verification and alarm management, and a final fault response is formed. By introducing a time series data analysis and clustering judgment mechanism, the fault type can be accurately identified, single-point and multi-point fault conditions can be effectively distinguished, and meanwhile, the reliability of a positioning result is improved through comprehensive verification of the central server.

The invention relates to the technical field of large model agent application, and discloses a hierarchical management alarm analysis and prediction implementation method based on a large model agent, and the method comprises the steps: obtaining historical alarm logs and real-time operation parameters of a target system, and constructing a hierarchical management feature library; designing an alarm grading evaluation framework and determining a multi-source data acquisition scheme; collecting multi-dimensional alarm data, and carrying out alarm grade judgment and abnormal mode recognition through a large model agent; and transmitting an analysis and prediction result to a management decision module to optimize a grading strategy. According to the invention, through multi-modal data fusion, dynamic weight distribution and intelligent analysis, the problems of single data processing and rigid grade division in traditional alarm management are solved, accurate classification and prediction of alarms are realized, and the operation and maintenance efficiency and reliability of the system are improved.

The invention discloses a standard video-in-channel monitoring early warning model method and terminal, and the method specifically comprises the steps: creating a universal video access platform, and configuring an early warning model, specifically, the configuration of the early warning model comprises the steps: analyzing a video stream frame by frame, judging whether an image is abnormal or not, and immediately giving out an early warning by a system once the abnormality is detected, real-time playback or storage of related frames is triggered; the video corresponds to a static wide angle, video analysis is carried out through static background comparison and sound analysis, whether a change occurs is judged, and a change result is recorded; a video middle station realizes deep understanding and alarm management of video contents through an intelligent analysis technology and in combination with multi-dimensional information, an algorithm model is trained and optimized by constructing a positive sample set and an error sample set, configuration is adjusted through a visual interface, and the alarm accuracy and efficiency are improved; dynamic video electronic fence early warning is established, and through real-time monitoring and intelligent analysis, abnormity identification is realized, so that an alarm mechanism is triggered.

The invention relates to the technical field of data management, in particular to a data center abnormal behavior analysis system based on artificial intelligence, and the system comprises the steps: obtaining an operation efficiency index of each monitoring node in a data center environment; constructing a comprehensive evaluation and analysis architecture to analyze the operation efficiency indexes, wherein the comprehensive evaluation and analysis architecture comprises a deviation mode recognition model and an influence weight evaluation model; the deviation mode recognition model analyzes the operation efficiency index to obtain an operation deviation mode; the influence weight evaluation model analyzes the operation efficiency index and generates a deviation mode influence weight; constructing a risk probability calculation model to analyze an operation deviation mode and a deviation mode influence weight, generating a potential risk probability score, and determining an association influence confidence coefficient; and when the potential risk probability score and / or the association influence confidence coefficient meet a preset management attention triggering threshold value, obtaining a business influence description of the risk event, generating a management response strategy of an alarm, and further generating an operation risk management notification.

The invention relates to the technical field of fire alarm systems, in particular to a distributed intelligent smoke monitoring and alarm management system, which comprises a data acquisition and trend analysis module for analyzing a smoke concentration change trend and generating a preliminary early warning signal based on real-time data acquired by a smoke sensor; the method specifically comprises the steps that the smoke concentration value Cs (t) of a smoke sensor in the time sequence is obtained, the average value Cmean and the standard deviation Std of the smoke concentration values in the current period are calculated, the upper limit threshold value and the lower limit threshold value of the smoke concentration are determined according to the formulas that Threshold High = Cmean + K1 * Std and Threshold Low = Cmean-K2 * Std, K1 and K2 are adjustment coefficients and are used for weighing sensitivity, when Cs (t) exceeds Threshold High or is lower than Threshold Low, preliminary early warning is triggered, and when Cs (t) is larger than Threshold Low, the smoke concentration is not subjected to early warning. The system analyzes the smoke concentration trend in real time, filters interference, links environment variables to adjust threshold values, performs multi-stage filtering, performs self-learning optimization, performs intelligent hierarchical scheduling, and efficiently prevents and controls fire disasters.

The invention relates to the technical field of submarine cable fault positioning, in particular to a submarine cable fault positioning system based on underwater beacons. The method comprises the steps that an underwater acoustic beacon array unit monitors and collects submarine cable fault sound wave signals in real time based on underwater acoustic beacons; the fault signal processing analysis unit extracts submarine cable fault sound wave signal parameters based on a non-point source space sound source waveform analysis model, and generates multi-parameter fault sound source feature vectors; the sound source positioning analysis algorithm unit performs three-dimensional inversion positioning based on the multi-parameter fault sound source feature vector and the arrival time difference of the submarine cable fault sound wave signal to the underwater acoustic beacon, and obtains the spatial position information of the submarine cable fault point; and the data communication alarm management unit sends the spatial position information of the submarine cable fault point to a shore-based operation and maintenance system. The submarine cable fault positioning method is used for realizing a submarine cable fault positioning technology for quickly and accurately positioning and identifying spatial extension characteristics in a complex submarine environment.

The invention discloses a monitoring video information intelligent processing system based on cloud computing, which relates to the technical field of monitoring video information processing and comprises a monitoring information processing platform. The monitoring information processing platform is in communication connection with a video data acquisition module, a data transmission module, a cloud data storage module, a data stream processing module, a target analysis module, an anomaly detection module and an intelligent alarm management module. Through training the deep neural network model and learning the features of normal and abnormal behaviors, the method achieves the precise recognition and tracking of a target object in a video, detects a dynamic target in the video, extracts the motion and appearance features of the dynamic target, recognizes the abnormal behaviors through behavior analysis, calculates an abnormal score, and generates alarm information in time. The accuracy of the monitoring system is improved, the situations of false alarm and missing alarm are reduced, and safety monitoring is more efficient and reliable.

The present invention discloses a standardized alarm process method, system, electronic device and storage medium, including obtaining alarm data indicators in alarm information; converting alarm data indicators into normalized indicators through a normalization algorithm; fusing normalized indicators with semi-structured data in corresponding alarm information to form a standardized alarm data structure; designing business tags based on systems or businesses, designing response tags based on notification methods and upgrade strategies, and adding business tags and response tags to standardized alarm data structures; receiving alarm event streams; filling business templates with data in alarm event streams based on tag matching rules; generating contextualized alarm data streams based on business templates. The present invention realizes a standardized alarm process method and system through multi-dimensional tool integration in multi-cloud and hybrid environments, and drives the deepening of alarm capabilities based on multi-algorithms, thereby improving the uniformity, efficiency and response speed of alarm management.

The invention discloses a unified management system and method for a virtual controller, and the system comprises a controller registration module which is used for initializing a controller registration array, checking whether the number of network IO registration reaches an upper limit or not, traversing the controller registration array, searching vacancies, and recording new instance information; the instance mapping module is used for mapping the successfully registered controller indexes into a controller information array and updating the registration number; the multi-thread security module is used for realizing concurrent security access in a registration process through a mutual exclusion lock; and the communication management module is used for creating a read management module, a write management module and an alarm management module, processing different types of data and carrying out heartbeat monitoring and data forwarding through a port. The technical problems that when a plurality of virtual controllers work cooperatively, control tasks of the virtual controllers are difficult to coordinate efficiently, so that the system performance is reduced, and even control conflicts or data loss may occur are solved.

The invention discloses an electrical fire alarm management method and system under multi-modal information fusion, and relates to the technical field of electrical fire alarm, and the method comprises the steps: carrying out the multi-modal information collection of electrical equipment and lines in a production region, and obtaining multi-modal heterogeneous data; carrying out real-time monitoring on the multi-mode heterogeneous data of each electrical device and line, and judging whether an electrical fire alarm signal is generated or not according to a monitoring result; performing dynamic association analysis on different types of electrical fire alarm signals generated by each electrical device and line in a plurality of historical acquisition periods to obtain a dynamic association network corresponding to each type of electrical fire alarm signal; according to the dynamic association network corresponding to each type of electrical fire alarm signals, an electrical fire early warning model is constructed, and real-time early warning monitoring is performed on electrical equipment and lines which do not generate the electrical fire alarm signals, so that the comprehensiveness and accuracy of electrical fire alarm are remarkably improved.

The invention discloses a power distribution network switching station on-line comprehensive monitoring method based on the Internet of Things, and aims to solve the problems that a traditional switching station is poor in monitoring real-time performance, insufficient in fault early warning capability and the like. The method is realized based on an intelligent monitoring and coping system of an Internet of Things architecture, and through cooperation of multiple modules of equipment operation state monitoring, environment monitoring, security monitoring, intelligent linkage control, alarm management, historical data analysis and the like, an alarm linkage intelligent control closed-loop cooperation algorithm and a time sequence analysis algorithm are combined. And comprehensive perception and intelligent analysis of the operation state, environmental parameters and the like of the switching station equipment are realized. The system can monitor key parameters such as cable head temperature and partial discharge in real time, supports intelligent linkage processing of abnormal scenes such as harmful gas exceeding and water immersion, and predicts the equipment trend through historical data mining. The technology improves the equipment operation safety and operation and maintenance efficiency, reduces the line loss, enhances the power supply reliability, lays a foundation for constructing a novel power system, and promotes the digital transformation of a power distribution network.

The invention discloses a fault alarm management method and device. The method comprises the following steps: acquiring a plurality of pieces of alarm data in a target time period, and determining feature vectors related to space and fault professional dimensions and corresponding to each piece of alarm data; calculating a first text similarity emphasizing on a spatial dimension and a second text similarity emphasizing on a fault professional dimension between every two pieces of alarm data according to the feature vectors; clustering all the alarm data based on the first text similarity to obtain a plurality of clusters, determining the cluster with the number of the alarm data exceeding a first threshold as a first target cluster, and generating regional large-scale alarm prompt information; and clustering the alarm data in the first target cluster based on the second text similarity to obtain a plurality of clusters, determining the cluster with the number of the alarm data exceeding a second threshold as a second target cluster, and generating single-specialty large-scale alarm prompt information. According to the invention, the technical problems that a related alarm processing scheme is difficult to accurately identify and merge large-scale alarm events and the processing efficiency is low are solved.

The invention discloses a coal loading and unloading equipment operation detection system based on visual identification, and relates to the technical field of visual identification. The system comprises a hardware architecture and a software architecture, the hardware architecture comprises an image acquisition unit, a data processing unit and a control feedback unit; the software architecture comprises an image processing layer, an intelligent analysis layer and a decision application layer; the image processing layer comprises an image acquisition subsystem, a preprocessing algorithm library and a feature extraction module; the intelligent analysis layer comprises a target detection and identification module, a three-dimensional reconstruction module and an abnormal behavior identification module; and the decision application layer comprises a rule engine, an alarm management subsystem and a data visualization platform. By deploying sensor equipment such as a multi-angle industrial camera and a laser radar and combining a deep learning algorithm and a computer vision technology, various illegal operations and abnormal conditions in the loading and unloading process are automatically identified, total-factor digital monitoring of the loading and unloading process is realized, the detection efficiency is improved, and the loading and unloading risk is reduced.

Systems, methods and apparatus for automatic alarm management in a radio-frequency (RF) environment are disclosed. An apparatus calculates a power distribution by frequency of the RF environment in real time or near real time, including a first derivative and a second derivative of FFT data of the RF environment. The apparatus then creates a baseline based on the power distribution by frequency of the RF environment in a period of time, identifies at least one alarm situation based on a multiplicity of alarm triggering conditions by comparing the power distribution in real time or near real time to the baseline of the RF environment, identifies at least one signal based on the first derivative and the second derivative of FFT data in the at least one alarm situation, and sends at least one alarm comprising details of the at least one signal identified in the at least one alarm situation.

The invention belongs to the field of intelligent monitoring systems, and particularly relates to a catering employee multi-mode behavior specification intelligent monitoring system based on deep learning, which comprises an active video inspection module, an image preprocessing module, an employee target element detection module, a multi-mode abnormal behavior analysis module and an abnormal information alarm management module. According to the invention, the video inspection management platform, the data processing platform, the target detection model and the modeled behavior analysis algorithm are fused, and the capability of detecting the abnormal behaviors of the store employees under the conditions of poor network environment, poor hardware facilities, poor monitoring environment and complex scenes is greatly improved. And intelligent identification of nonstandard abnormal behaviors of catering store employees in various scenes and different modes is realized with low computing power cost. And the operation efficiency and the management level of the store are further improved, a solid foundation is laid for intelligent transformation of the catering industry, and the method has relatively high technical replicability and generalization performance.

In some aspects, the techniques described herein relate to a method including: receiving, at an alarm management service, a plurality of alarms, wherein each of the plurality of alarms includes respective alarm data; clustering the plurality of alarms into an alarm cluster group; generating a plurality of binary time sequences, wherein each of the plurality of binary time sequences corresponds to one of the plurality of alarms; generating an initial alarm graph based on the alarm cluster group and the plurality of binary time sequences; providing, as input to a causal inference process, the initial alarm graph and the plurality of binary time sequences; and generating, by the causal inference process, a causal alarm graph, wherein the causal alarm graph is a partially connected and directed graph.

The invention provides a data monitoring method and platform, computing equipment and a computer readable storage medium. The method comprises the following steps: for a target application program accessed to the data monitoring platform, acquiring service data of the target application program by using a data acquisition service; wherein the service data comprises data of service indexes, data of service logs and link tracking data; based on a data monitoring demand corresponding to the target application program, processing the service data; displaying a processing result of the service data in a chart form by using a data display service; and when determining that the service data satisfies a target alarm condition based on the processing result, sending alarm information in an information notification mode corresponding to the target alarm condition by using an alarm management service. The method can improve the data monitoring effect.

The invention relates to the technical field of marine transportation safety, and discloses an AI video-based cabin smoke and open fire identification alarm system, which comprises a shipborne system and a shore-based system, the shipborne system comprises an information acquisition unit used for acquiring video, temperature difference, audio and other information of a control area; the smoke open fire and temperature difference identification unit is used for identifying smoke open fire and temperature difference appearing in the control and management area; the fire development situation evaluation unit is used for evaluating the fire development situation of the control and management area based on a fire situation development evaluation model; the shore-based system and the information acquisition unit are used for training a ship smoke open fire identification standard model and a ship fire situation development evaluation standard model; and alarm management: generating a coping decision based on the shipborne fire asking-for-help information. The defect that an existing smoke and fire sensor is low in sensitivity can be overcome, fire hazards can be found as soon as possible without dead angles, ship-shore linkage scientific rescue can be carried out in time, and ship fire prevention and shore-based rescue efficiency is improved.

The invention provides a lithium iron phosphate battery monitoring system, and relates to the technical field of lithium iron phosphate battery monitoring. Comprising a battery management system, a data acquisition and processing subsystem, a communication and remote control subsystem, a temperature monitoring and control subsystem, a voltage monitoring and protection subsystem, a current monitoring and protection subsystem, a power monitoring subsystem, a test and diagnosis subsystem, an alarm management subsystem, a visual interface subsystem and an enhancement subsystem, the enhancement subsystem comprises an SOC estimation subsystem, a health state evaluation subsystem, a temperature distribution monitoring subsystem, an external environment monitoring subsystem, an intelligent control and optimization subsystem and a predictive maintenance subsystem, and the SOC estimation subsystem is arranged, so that the residual capacity of a battery pack can be estimated in real time, accurate battery charge and discharge state information is provided, and the battery charge and discharge state of the battery pack is improved. A user is helped to reasonably use the battery pack capacity, overcharge or discharge is avoided, and the battery life is prolonged.

The invention discloses a dynamic alarm knowledge base creation method based on alarm management, which comprises the following steps: S1, carrying out alarm-to-knowledge point data conversion on the basis of experience of an engineer in processing alarm items to form an engineer knowledge base which is used for forming think tank management under unified management and control; s2, based on alarm data acquisition and processing of various heterogeneous monitoring systems, heterogeneous monitoring devices and heterogeneous monitoring servers, information corresponding to alarm data is created into an alarm fault knowledge base; and S3, the engineer knowledge base and the alarm fault knowledge base are subjected to association and information integration, so that a dynamic alarm knowledge base is formed, and the dynamic alarm knowledge base is used for providing guidance and support for fault processing. And an engineer is assisted to quickly position and solve one or more problems in various heterogeneous monitoring systems, heterogeneous monitoring equipment and heterogeneous monitoring servers. The invention also discloses a corresponding system, electronic equipment and a readable storage medium.

The invention relates to an AI analysis alarm platform and method for video monitoring, and relates to the related technical field of video analysis alarm, and the platform comprises a priori threshold determination module which is used for constructing a negative space based on absolute normal data as a preposed priori threshold according to a region operation and maintenance rule for a target monitoring region; the abnormal alarm management module is used for accessing monitoring stream data, triggering a preposed prior threshold, executing data entropy change judgment by taking a negative space as a baseline, and performing abnormal alarm management; comprising a direct alarm response sub-module; a directional alarm response sub-module; wherein the preposed prior threshold and depth discriminator is an embedded plug-in of the AI analysis alarm platform. The technical problem that in the prior art, abnormal recognition model training depends on positive samples and annotation data and is difficult to adapt to dynamic complex scenes, so that video analysis alarm accuracy and timeliness are poor is solved, and the technical effect of improving video monitoring analysis alarm accuracy and timeliness is achieved.

The invention belongs to the field of electric power, and discloses an electric power dual-mode carrier communication network management method and a related device, and the method comprises the steps: issuing a communication channel management instruction and an alarm management instruction to a central coordinator of each electric power dual-mode carrier communication network, receiving and storing a carrier station communication channel quality index value fed back by the central coordinator based on the communication channel management instruction and communication module alarm information fed back by the central coordinator based on the alarm management instruction; receiving and storing the communication performance monitoring index value of the communication module of each power dual-mode carrier communication network, which is periodically fed back by the central coordinator of each power dual-mode carrier communication network; and obtaining network fault information and a network optimization strategy of each power dual-mode carrier communication network. The communication module of the power dual-mode carrier communication network is innovatively used as an independent network management unit for management, so that the service terminal and the communication module are separately managed and controlled, and the problem of fault misjudgment is effectively solved.

The invention relates to the technical field of magnesium metal precision manufacturing workshop production management, in particular to a magnesium die casting identification tracing and tracking system and method based on MES, and the system comprises a real-time monitoring module, a report management module, a log management module, an alarm management module, an equipment management module, a system management module and an interface management module. The main function of the real-time monitoring module is to carry out real-time monitoring on hardware equipment of the identification tracing and tracking system, such as an ink-jet printer, a two-dimensional code / bar code identification device, a sensor, an RFID data acquisition device and a marking press, the whole production tracking process of the magnesium die casting is dynamically displayed, and the product information of the magnesium die casting and the like are reflected together. According to the magnesium precision machining workshop system, interconnection and intercommunication among the automatic code spraying equipment, the automatic code scanning identification equipment, the RFID data acquisition equipment and the automatic engraving equipment are achieved, code spraying, code scanning identification and tracking of on-site die castings are dispatched in a coordinated mode, efficient operation and stable operation of the whole magnesium precision machining workshop are achieved, and the magnesium metal feeding and discharging efficiency is improved.

The invention discloses a method and a device for repairing a fault node of a container arrangement system, and a storage medium. Relates to the field of cloud computing, and the method comprises the steps: obtaining a monitoring index of a container arrangement system for a target node in a cluster, the monitoring index being measurement data used for describing an operation index of the target node; under the condition that the target node is determined to be a fault node according to the monitoring index and a predefined alarm rule, generating first alarm information according to the monitoring index and the alarm rule; generating target alarm information according to the first alarm information through the alarm manager, and sending the target alarm information to an event callback mechanism; and under the condition that the event callback mechanism receives the target alarm information, calling an automatic operation and maintenance tool to repair the fault node. Through application of the method and the device, the problem of low repair efficiency due to dependence on manual repair when the node in the container arrangement system cluster has a fault in the prior art is solved.

The invention discloses a network security operation and maintenance management system and method, and belongs to the field of network security operation and maintenance, and the system comprises a data collection module which is used for collecting equipment logs, analyzing flow data, and deploying a distributed performance probe to collect transaction response time and throughput indexes; the real-time processing module is used for executing streaming window association calculation through an Flink engine, matching an attack mode sequence in combination with a CEP rule engine, and storing performance baseline data; the AI analysis module is used for detecting abnormal behaviors, constructing an equipment access relation graph through GNN, fusing log text and traffic image features, and combining historical performance data to train a load prediction model; the alarm management module is used for generating hierarchical alarms according to knowledge graph reasoning and explaining alarm root causes through an SHAP algorithm; and the test management module is used for drawing a transaction response time distribution diagram and generating a pressure test report. According to the invention, the attack pattern recognition accuracy can be improved.

The invention provides an electric power system monitoring data cloud unified access and resource intelligent prediction system and method based on cloud edge collaboration. The system is provided with a unified access module, an alarm rule configuration module, a real-time alarm module, a real-time monitoring display module and an intelligent trend prediction and health degree evaluation and maintenance module. According to the system and method, Java language development is adopted, the system and method serve as a central platform to receive and manage monitoring data from a plurality of lower-level power platforms in a unified mode, and standardized data unified access, real-time multi-dimensional monitoring, intelligent trend prediction, dynamic alarm management and system health degree evaluation and maintenance of a CPU, a memory, a hard disk, network resources and middleware services are achieved; the method is very suitable for a power system, can also be widely applied to other industries needing high reliability and real-time performance, and effectively solves the technical problems that monitoring data of multiple servers cannot be managed in a unified mode, the resource prediction precision is low, and system fault response lags behind.

The invention discloses a low-level alarm management method and device. The method comprises the following steps: receiving a low-level alarm, and respectively storing a first alarm caused by a network element fault, a second alarm caused by a user behavior and a third alarm caused by network management equipment upgrading into corresponding databases; detecting the alarm flow written into the first database in real time, and analyzing the alarm in the first database when the alarm flow meets a preset condition; periodically utilizing the time sequence prediction model to analyze the alarms in the second database, and analyzing the alarms in the second database when the predicted number of the second alarms is not matched with the actual number of the second alarms; analyzing alarms in a third database in response to the alarm analysis instruction; and corresponding early warning notifications are generated based on analysis results of different alarms. The technical problems that a related alarm management scheme focuses on responding to high-grade alarms, and the analysis and early warning capability on low-grade alarms is insufficient are solved.

A method comprises determining, by an alarm management system, that an alarm parameter exceeds a threshold value, transmitting, by the alarm management system, a throttle alarm to an incident reporting application in the communication network, in which the throttle alarm indicates that the second alarms describing the common incident will be throttled at the alarm management system for the throttle period, storing, by the throttle application, second alarms describing a common incident at a data store accessible by the alarm management system during a throttle period instead of forwarding the second alarms to a processing entity, transmitting, by the alarm management system, at pre-defined time intervals during the throttle period, an interval alarm report, and transmitting, by the incident management system to an incident reporting system, a throttled alarm report.

The invention discloses a load-based logistics vehicle overload alarm management method, relates to the technical field of logistics vehicle management, and aims to solve the problems of inaccurate vehicle load data acquisition and wrong overload judgment. According to the method, the instant change of the vehicle load can be quickly captured through the instant load judgment, the sliding window judgment reflects the long-term load trend of the vehicle by calculating the average load within a period of time, the overload judgment accuracy can be remarkably improved by combining the instant load judgment and the sliding window judgment, and the threshold value better conforms to the actual driving condition through dynamic adjustment; the adaptability is improved, the inertia force is compensated by adding an additional load compensation coefficient on the downhill road section, the overload risk caused by superposition of the self weight of the vehicle and the weight of goods during downhill can be prevented, and therefore the driving safety is improved.

The invention discloses an expressway code scanning alarm rescue management system and method, and relates to the technical field of expressway rescue management, an alarm starting module runs on a code scanning request terminal, a background server distributes a road section fault code scanning rescue signal, an alarm management verification platform verifies and feeds back the road section fault code scanning rescue signal, and the alarm management verification platform verifies the road section fault code scanning rescue signal. The alarm receiving rescue assistance platform obtains fault associated information according to the road section fault code scanning rescue signal, and the alarm receiving rescue management module generates a rescue navigation route and a rescue management scheme based on the road section fault code scanning rescue signal and the fault associated information. According to the system and the method provided by the invention, the accurate position and fault association condition can be automatically analyzed according to the alarm two-dimensional code information, the fault positioning efficiency is improved, the rescue efficiency is effectively improved, the alarm management and verification platform judges the authenticity of the alarm data, and the alarm receiving and rescue assistance platform supplementarily describes the alarm data, so that the alarm management and verification efficiency is improved. And the rescue efficiency can be improved.