1098 results about "Rollback" patented technology

The invention discloses a JDK8-based heterogeneous service large model dynamic adaptation and intelligent scheduling method and system, and belongs to the technical field of artificial intelligence service integration, and the method comprises a unified service module which provides standardized HTTP / WebSocket access for an application layer and shields the difference of multiple platforms at the bottom layer; the dynamic routing module is used for dynamically selecting service nodes based on service quality indexes and supporting weight calculation, fusing recovery and flow dyeing; the service execution module is used for loading a platform adapter through a dual-mode service factory, integrating a tool calling function and realizing protocol conversion and authentication injection; and the configuration management module supports dual-configuration source hot loading of the static file and the dynamic database and provides versioning rollback and consistency verification. According to the method, the problems of multi-platform protocol difference, service rigid expansion, tool calling coupling and the like can be solved, the complexity of multi-platform management is remarkably reduced, and the flexibility and maintainability of the system are improved.

The invention provides an intelligent analysis and execution method and system for database cascading operation, and relates to the technical field of database management.The intelligent analysis and execution method comprises the steps that a target table and an association table are extracted through a recursive query algorithm, field mapping analysis is carried out to generate a dependency weight matrix, cyclic dependency is recognized based on the matrix and decomposed into directed acyclic subgraphs, and the directed acyclic subgraphs are analyzed; node depth values and breadth values are calculated for topological sorting to generate an execution sequence; performing node classification on the execution sequence, organizing the execution sequence into a batch processing task group, calculating an optimal execution path through an adaptive path optimization algorithm, generating a distributed transaction control instruction, and allocating the task group to an execution thread pool for execution by using a consistent Hash algorithm; monitoring an execution process, dynamically adjusting thread pool resources according to a performance prediction value, executing cascade rollback when an exception occurs, and reconstructing a transaction execution path; according to the method, the execution efficiency and stability of the database cascade operation can be effectively improved, and the system resource consumption is reduced.

The invention discloses a cloud information system index collection method, system and device and a medium, and relates to the technical field of cloud information system operation and maintaining.The method comprises the steps that information collection interfaces of a cloud system are integrated, data flow information entropy is quantized, and an entropy value sequence is constructed; an interface calling serial number is traced based on a historical log, a calling chain is formed, a directed graph topological structure is established, an influence propagation path of an entropy mutation node is identified, and a collection regulation priority of an interface cluster is determined; an acquisition strategy is formulated in combination with entropy time sequence data and a load level, a state-strategy mapping relation matrix is optimized, and a time period driving type strategy adjustment parameter set is generated; and issuing the strategies in sequence, dynamically regulating and controlling the acquisition frequency, and if state transition or fitting degree abnormity occurs, triggering strategy rollback and optimizing the learning weight. According to the method, on the premise of guaranteeing the integrity of the monitoring data of the power equipment, the utilization rate of edge computing resources is remarkably optimized, and high-timeliness and high-fidelity data support is provided for safe and stable operation of a power grid.

The invention relates to the technical field of artificial intelligence, can be applied to business scenes such as financial science and technology and medical health, and discloses a processing environment switching and recovery method, device, equipment and medium. The method comprises the steps that multi-source heterogeneous data in a main processing environment and a standby processing environment are acquired, and the system fault probability is obtained through multi-model collaborative prediction; a dynamic threshold value is generated in combination with a historical service period mode and a real-time service load, when the fault probability exceeds the threshold value, a switching strategy is generated based on the fault scene knowledge base and the service priority, and flow scheduling between the main processing environment and the standby processing environment is executed; and monitoring the business index of the standby processing environment during the scheduling period, and triggering the fusing rollback when the business index is lower than the health standard. According to the method, the fault identification precision is improved through multi-source data fusion and multi-model prediction, adaptive scheduling is realized in combination with a dynamic threshold and a switching strategy, and fusing rollback is triggered to guarantee high availability and data consistency, so that the continuity and stability of key services are enhanced.

The invention provides a multi-transaction deadlock detection and processing method in resource-constrained equipment, which comprises the following steps of: in a transaction execution process, constructing a resource waiting graph which is used for recording a waiting relationship among transactions so as to reflect the occupation condition of shared resources by the transactions and a dependency relationship among the transactions; before a transaction is subjected to read-write operation each time, whether execution of the current transaction can cause a deadlock risk or not is judged in real time by detecting a dependency relationship between the current transaction and a target resource and combining a resource waiting graph; and when a deadlock risk is detected, deadlock avoidance strategies of priority processing, transaction rollback, transaction retry and exception processing are adopted to avoid deadlock. The deadlock problem occurring in the transaction parallel processing process can be effectively avoided or solved, and meanwhile the response efficiency of the application and the utilization rate of the storage space are guaranteed.

The invention provides an online document processing method and system based on a document processing model, and the method comprises the steps: obtaining an editing request of a user for a target data unit, generating a temporary locking identifier according to a user authority identifier and a request timestamp, limiting the modification operation of other users for the target data unit, and obtaining a conflict isolation result; constructing a data consistency module according to a conflict isolation result, extracting editing state information of the current data unit from the temporary locking identifier, and performing sequential recording on concurrent operation by adopting a distributed transaction processing technology; if it is detected that version conflicts exist in the sequenced records, a rollback mechanism is triggered, operation priorities are redistributed, and data versions after consistency verification are determined; and designing a hierarchical cache structure according to the data version after consistency verification, storing the high-frequency access data into a memory cache region, and storing the low-frequency access data into a disk cache region to obtain a hierarchical storage structure. The data consistency and security are good, and the storage and access efficiency is improved.

The invention relates to the technical field of retrieval enhancement generation, and discloses an reflection rollback type retrieval enhancement generation method and device, equipment and a storage medium. The method comprises the steps of generating a rewritten query statement based on a question input by a user and an answer candidate set; executing retrieval based on the rewritten query statement, and adding a retrieval result into an answer candidate set; the state value of the latest retrieval result is calculated through a state evaluation function fusing the confusion degree and the confidence degree; judging whether the state value of the latest retrieval result is lower than the state value of the previous retrieval result of the answer candidate set, and if so, triggering a rollback mechanism; and summarizing each retrieval result in the answer candidate set through a large language model, and outputting a final answer. According to the reflection rollback type retrieval enhancement generation method provided by the invention, a self-reflection and rollback mechanism is introduced, so that the problem of performance reduction caused by low-quality external retrieval information in a large language model is effectively solved.

The invention discloses an AI Agent implementation method based on a large language model and a knowledge graph, and relates to the technical field of artificial intelligence, and the method comprises the steps: taking a semantic feature embedding vector as a query basis, obtaining an entity node and a relation path in the knowledge graph, carrying out structure embedding coding, and generating a structure embedding vector; performing two-channel semantic structure alignment on the semantic feature embedding vector and the structure embedding vector, and performing alignment processing on entity nodes and relation paths in the knowledge graph to generate a path candidate set; performing structured coding on the path candidate set to generate prompt information, combining the prompt information with a natural language instruction, inputting the combined prompt information into a large language model, and generating a response draft; and performing path consistency verification on the response draft, if the response draft is not consistent, executing rollback and regenerating a new response text draft, and if the response draft is consistent, outputting a final response text. According to the method, the quality and the credibility of the response text are remarkably improved, and the interaction stability and the user experience of the intelligent agent are enhanced.

The invention relates to a large-model-driven adaptive closed-loop optimization method for machining process parameters of an aviation complex thin-wall component. The method comprises the following steps: acquiring multi-source heterogeneous machining data and quality detection data of the aviation complex component; constructing and training an aviation complex component processing quality prediction model and a multi-target process parameter optimization model; packaging the trained model into a micro service and deploying the micro service to a DeepSeek large model container platform; a DeepSeek large model is used as a controller, and closed-loop calling of the micro-service is achieved; an online self-adaptive optimization process is formed; an analysis report is automatically generated based on an optimization result; and optimizing the processing quality prediction model by using the new data increment and designing an automatic rollback strategy. According to the method, deep learning and a large model technology are fused, accurate prediction of the machining quality and efficient regulation and control of the technological parameters are achieved, and meanwhile the manufacturing efficiency and quality of the aviation complex component are effectively improved.

The invention relates to the technical field of application state diagnosis, in particular to an application state dynamic diagnosis and automatic repair method and system.The method comprises the steps that multi-source heterogeneous logs are collected and standardized in real time, key fields are extracted, context information is injected, and structured log data are generated; inputting the structured log data into a dynamic anomaly detection model, constructing a dual-path detection mechanism based on LSTM time sequence analysis and a graph neural network, identifying an abnormal mode and positioning a fault root cause; according to the output of the anomaly detection model, a repair action is triggered in a grading manner through an intelligent repair strategy engine; in the repairing process, system state changes are stored and recorded through a pre-writing type redundancy log, automatic rollback during abnormity is achieved on the basis of check point information, and data consistency and system stability are guaranteed. The problem of service interruption or data inconsistency possibly caused by traditional automatic repair is avoided, and the reliability of automatic operation and maintenance is improved.

The invention discloses a data collaborative directory management method and system, and relates to the technical field of government affair informatization, and the method comprises the steps: generating a directory snapshot containing a global hash value; calculating a directory node hash value of each edge directory node based on the directory snapshot identifier; eliminating clock drift interference through time sequence alignment and dynamic tolerance filtering; inputting the Hash difference time sequence into an isolated forest model to judge a substantial change node; based on the difference entry number and the historical calling weight, combining a dual-threshold rule and an online dichotomy model to hierarchically synchronize requirements; according to a grading result, matching an incremental push mode or a full pull mode, and constructing a synchronous transaction context containing an exponential backoff retry mechanism; synchronous operation is executed through the two-stage state model, and compensation rollback is triggered when the synchronous operation fails; and calculating a health index of the substantially changed node, dynamically selecting a self-healing action and optimizing system parameters. The problem of misjudgment caused by time sequence drift is effectively solved, the synchronization efficiency is improved, and the consistency of directory versions is guaranteed.

The invention relates to the technical field of base frame operation and maintenance, can be applied to business scenes such as financial science and technology and medical health, and discloses a context object-driven patch processing method, device, equipment and medium, and the method comprises the steps: extracting an equipment attribute identifier, an operation state identifier and a routing path identifier from an operation environment of target equipment to generate a context object, creating a patch definition, verifying the patch definition in a security sandbox, submitting and approving the patch definition to form a patch version identifier, configuring an environment isolation condition in combination with an effective range, issuing a patch execution instruction carrying the patch version identifier, the environment isolation condition and a hook definition, triggering patch script application repair logic, and calling a cache cleaning tool to process a resource cache. And collecting logs and indexes to generate a monitoring record, and executing rollback or off-shelf operation based on the monitoring record to finish the patch task. Through combination of dynamic patch definition, instruction issuing and version management, safe distribution of front-end patches is realized, and the stability and maintainability of the system are improved.

The invention discloses a remote monitoring cooperation system based on intelligent network connection, and relates to the technical field of cooperation control, and the system comprises a protocol analysis and normalization module which analyzes an original protocol message uploaded by a heterogeneous terminal, and generates standard event metadata; the arrangement scheduling module injects an execution token into a linkage execution sequence generated based on the standard event metadata and the strategy library, issues an action instruction, and triggers a remedial sub-process along a rollback edge when feedback is abnormal; the parameter intelligent setting module is used for generating an operation portrait based on the execution track log and obtaining a strategy parameter set based on the operation portrait; the intelligent cooperative processing module executes digital signature verification, certificate rolling rotation, deterministic transmission control and video adaptive adjustment according to the strategy parameter set; according to the invention, through organic combination of strategy analysis, arrangement scheduling, parameter intelligent setting and intelligent cooperative processing modules, automatic response and efficient control during coupling of multiple types of events in an intelligent network connection remote monitoring scene are realized.

The invention discloses a data auditing method based on big data, and relates to the technical field of big data, and the method comprises the steps: obtaining multi-modal data in a big data platform form, extracting features of the multi-modal data to generate a feature set, creating a rule base based on the feature set, and constructing a cross-form dependency graph according to the feature set and the rule base; cascade auditing is executed through a cross-form dependency map, when auditing fails, an affected field is reversely positioned according to the connection direction of the map, and incremental state rollback and re-auditing are executed on the affected field; when it is detected that the high-frequency data is changed, an anti-rollback storm mechanism is started, a cascade load index is obtained, and a rollback instruction set is generated through cascade blocking based on the index; and executing distributed fault-tolerant control, constructing a node collaborative protection system through cascade loads, and outputting a fault-tolerant operation instruction.

The invention discloses a multi-platform data synchronization-based commodity middle platform management system and method, and relates to the technical field of data synchronization management, and the method comprises the steps: configuring card and coupon basic information and selling information at a middle platform background, creating a coupon mother set data model, generating a valuable coupon data model adaptive to a platform based on the coupon mother set, expanding the specific field of the platform, and carrying out the management of the middle platform; unified management and cross-platform synchronization of commodity information are achieved, meanwhile, commodity data are distributed to all platform interfaces through a GBS layer, a platform side auditing process is triggered, timing sequences are synchronized based on interface response portraits and user active period model decisions, timely synchronization and auditing efficiency of the commodity information are ensured, in addition, the auditing state is monitored in real time, and the auditing efficiency is improved. The method comprises the steps of performing automatic rollback on conflict operation, responding to platform rule change, triggering commodity off-shelf or information updating, calculating user cancel-after-verification confidence coefficient in real time in a user cancel-after-verification link, and triggering a dynamic cancel-after-verification strategy when the confidence coefficient is lower than a confidence coefficient threshold value, thereby effectively preventing and controlling risks.

The invention discloses an industrial Internet of Things control method for multi-type working parameter deployment, which relates to the technical field of industrial automation control, and comprises the following steps: S001, establishing a time sequence observation baseline of a multi-stage redundant path, injecting micro-amplitude identification pulses into all control nodes, generating an instruction time delay distribution curve and a resource occupation track, and establishing a time sequence observation baseline of a multi-stage redundant path; the method is used for revealing potential conflict sources and providing initial conditions. According to the method, a conflict source is revealed by establishing a time sequence observation baseline, competition nodes are identified by using a loop retrieval graph, a conflict list is formed, a single-source control right token is issued to realize link convergence, token stagnation is monitored, snapshot rollback and standby path takeover are combined to avoid interruption, and after takeover, time delay shaping is implemented to ensure stable landing of an instruction. Finally, the topological weight, the token priority and the fusing threshold value are dynamically updated, a self-evolution closed loop is constructed, and high reliability and high safety of industrial Internet of Things control are achieved.

The invention discloses a large language model knowledge base self-adaptive updating method combining documents and interactive feedback, and relates to the technical field of knowledge base updating, and the method comprises the steps that a real-time change detection module monitors streaming documents and interactive feedback, and captures and marks a single fact change event; the decision module calculates a shunting decision coefficient according to the heat density index and the linkage sweep index, and the event is shunted to a Micro-Edit or Incremental-Tune path; if shunting to the Micro-Edit path, the positioning module executes attention backtracking and gradient sensitivity analysis, and determines a to-be-updated weight address; the rank-one editing module implements rank-one updating and records an audit log; the verification module generates an online token or a rollback instruction through consistency comparison; the version management module manages a version, activates a new version route and cleans out expired branches. Through event granularity identification, intelligent shunting, local updating and multi-version management, the timeliness of knowledge base updating is remarkably improved, and resource consumption and maintenance cost are reduced.

The invention discloses a remote control method for smart home equipment, relates to the technical field of home equipment control, and is used for solving the problems of simple identity authentication, difficulty in cross-protocol control and poor complex scene control effect in the prior art. The method comprises the following steps: initiating a control request at a mobile terminal, synchronously triggering a two-factor verification operation, when verification succeeds, constructing a temporary access secret key, and dynamically distributing equipment control authority, when verification fails, requesting rollback, and automatically matching a corresponding optimal communication protocol from a protocol library according to the type of each piece of target home equipment, so as to achieve the purpose of controlling the home equipment according to the optimal communication protocol. The method comprises the following steps: evaluating network quality after communication interaction, dynamically switching a transmission mode according to an evaluation result, deploying a local computing node and a cloud computing node, respectively carrying out respective equipment remote control in simple and complex scenes, constructing an equipment relation graph to analyze a household equipment dependency relationship, optimizing a control execution sequence, and monitoring equipment feedback data. Mandatory intervention management is carried out in case of abnormity, and efficient and accurate equipment control is realized.

The invention discloses a campus intelligent terminal equipment management method and system based on multi-source state synchronization, and relates to the technical field of intelligent terminals. The campus intelligent terminal equipment management method and system based on multi-source state synchronization comprises the following steps: S1, a terminal cooperatively collects a context state data set, and normalization processing is carried out; s2, constructing a migration mirror image synchronization state data set, and carrying out migration handover of stage switching and playback; s3, constructing a pulse interference detection model, and performing interference window suppression and online correction; and S4, constructing a dual-time reference transaction consistency verification and migration submission determination closed loop, and carrying out linkage rollback and governance. According to the method, the state consistency and the operation stability in the cross-node migration process of the campus intelligent terminal are effectively improved, and the problem of pulse interference in equipment state migration is solved.

A distributed task scheduling system based on RabbitMQ, Redis and MongoDB. The task scheduling system comprises a task system service, Redis, MongoDB, RabbitMQ and an SDK, wherein the task system service comprises a data and object storage management module, a message queue management module, a task management module, a timing task module and a workflow module. By means of the design of a task system service, Redis, MongoDB, RabbitMQ and an SDK, the functions of an asynchronous task, a timing task and a workflow in a distributed and micro-service environment are provided. By means of the technical solution of a message queue, trigger-based scheduling of a task is realized, and a reliable and unique task scheduling capability exists; moreover, a timing task trigger capability exists, and thus the present invention is suitable for a scenario in which the execution of a certain task is triggered in a timing or delayed manner; a workflow capability is provided, and thus serial and parallel execution of a plurality of tasks can be performed; and capabilities such as task rollback and interruption are provided, and thus a system which unifies the asynchronous task, the timing task and the workflow is achieved.

The invention relates to a data management method for real-time incremental data based on dynamic scheduling and elastic rollback, and belongs to the technical field of information data management. The method comprises the following steps: monitoring system data change in real time through a data change capturing unit, and identifying and recording insertion, deletion and change operations; the incremental data processing unit receives and processes the original incremental data; the real-time updating execution unit updates the target data set according to the data change event; if updating fails or the data are inconsistent, the elastic rollback mechanism unit automatically rolls back the data to a consistent state; and meanwhile, the system monitoring and alarming unit monitors the running state in real time and triggers alarming. The updating efficiency and the data consistency guarantee capability in a large-scale data environment are remarkably improved, and the method is suitable for application scenes with extremely high requirements for real-time performance and data consistency.

The invention discloses a GoldenDB database change risk management and control method and system. The method comprises the steps that change scheme data is obtained, a coding format is recognized, effective change content is extracted, the change content is disassembled into single transactions, semantic analysis is executed, and change types are classified based on keyword matching and a rule base; wherein the change types comprise data change, structure change, parameter change and permission change; generating a distributed execution plan according to the change types, analyzing the distributed execution plan, executing information in parallel, and determining data nodes and computing nodes corresponding to the four change types respectively; respectively constructing risk assessment models in the execution domains corresponding to the four change types; and converting the risk assessment result of each node into a standardized data format, aggregating and analyzing the cross-node common risk, generating a father-child tree management and control report, and executing blocking, rollback or alarm operation according to the risk level.

The invention discloses an EAP unified management and version rollback system, which relates to the technical field of industrial Internet of Things, is designed aiming at the problems of equipment diversification, non-unified protocols, high updating risk, rollback mechanism deficiency and the like, and consists of a system initialization and configuration module, an updating management execution module, a version rollback control module and a monitoring maintenance optimization module. The method can dynamically bind equipment and applications, preset update rollback rules, guarantee data security through cloud backup and MD5 verification, support active or passive update, realize update whole process management and control through a standardized instruction packet and a version file, roll back to a stable version according to a range when abnormity occurs, monitor states and logs in real time, set a threshold alarm, and improve the reliability of the system. The method solves the problems of poor compatibility, disordered versions and the like of the equipment, improves the updating efficiency and reliability, reduces the risk of production interruption, achieves the full-life-cycle efficient management of the equipment, and guarantees the production stability and operation and maintenance efficiency of intelligent manufacturing.

The invention discloses a manufacturing task autonomous negotiation and execution method based on a large language model agent, and the method comprises the steps: constructing a production scheduling agent, an equipment management agent, a material distribution agent and a quality control agent, analyzing a natural language task instruction through the production scheduling agent, and decomposing the natural language task instruction into subtasks; each agent calculates a utility value based on the load rate, the resource matching degree, the estimated completion time and the historical success rate, and performs structured negotiation to achieve a task allocation consensus; a prediction-check-rollback architecture is adopted to generate an action instruction sequence, the sequence is compiled into a time Petri network transition sequence, and reachability verification is carried out based on hard security constraints; production environment data is collected in real time to trigger anomaly detection and re-negotiation, and a formalized security verification and causal anti-factual reasoning parameter updating mechanism is introduced. According to the method, unstructured instruction understanding, autonomous task planning, multi-agent collaborative decision and closed-loop optimization are realized, and the problems of real-time performance, safety and interpretability of a large language model in manufacturing control are solved.

The invention relates to the technical field of firmware upgrading, in particular to an LZ77-based embedded firmware security upgrading method and system, which comprises the following steps: electrifying to obtain guide information and a version identifier, judging a trigger condition and writing in an upgrading mode, generating a start mark to perform LZ77 compression, executing decryption and CRC (Cyclic Redundancy Check) check, and reconstructing a firmware comparison signature. And updating the guide pointer or recovering the snapshot, and monitoring voltage evaluation abnormity to trigger recovery interruption. According to the method, the storage efficiency of the space occupied by the snapshot data is improved through compression ratio evaluation before writing, a data integrity screening mechanism is established in combination with AES encryption head decoding and CRC comparison in the data block receiving process, the data security guarantee in the firmware writing stage is enhanced, decoding recovery is achieved through an original snapshot structure under the condition that comparison fails, and the data integrity screening efficiency is improved. Power supply state dynamic evaluation is realized by combining voltage change rate analysis, snapshot recovery and firmware rollback are triggered through an abnormal trend, and the safety processing capability in a voltage abnormal environment is improved.

The invention provides a supply chain front-end architecture method for multi-industry dynamic switching and routing adaptation, which relates to the technical field of front-end architecture and comprises the following steps: establishing a hierarchical model by scanning a component dependency relationship, setting a progressive switching strategy, constructing a routing adaptation layer to realize multi-dimensional decision, monitoring a state and executing difference synchronization. And replacing the components according to a preset sequence and setting rollback points. According to the invention, smooth switching of components in different industries is realized, the coupling degree between the components is reduced, the adaptability and reliability of the front-end architecture are improved, and the system is enabled to maintain stable operation in a multi-industry scene.

The invention discloses an intelligent gray scale and multi-version adaptive deployment system and method based on Kubernetes, and the method comprises the steps: through an Operator which operates in Kubernetes and integrates a plurality of intelligent modules, the Operator can collect and fuse a business performance index and a technical performance index, and generates a comprehensive "version health score"; according to the real-time state of the health score, the rhythm and the step length of flow release are adaptively adjusted; meanwhile, through integration with a service grid, staged and context-based accurate flow routing is realized; when serious problems occur, safe rollback can be automatically executed, and cooling locking can be applied. According to the method, the service target and the release process are deeply bound, so that the intelligence of release decision, the self-adaptive adjustment of the release process and the fine control of the risk are realized, and the security, efficiency and success rate of software release are remarkably improved.

The invention provides a front-end resource dynamic preloading method, system and device and a medium, and belongs to the technical field of front-end engineering. The method comprises the following steps: constructing and training a user behavior prediction model based on a Transform time sequence model architecture, and deploying the user behavior prediction model to a browser side after compression processing; the method comprises the following steps: acquiring behavior data of a user by monitoring a user interaction event, constructing a time sequence operation sequence, and collecting network information and equipment performance information; inputting the time sequence operation sequence into the model, outputting probability distribution of the next operation, and determining related resources; based on the probability distribution, the resource type and the network information, calculating the priority of the resource, and generating a resource priority queue; according to the network information and the equipment performance information, determining a pre-loaded resource type, and adjusting a resource priority queue to generate a pre-loading strategy; a cache rule is defined, a cache configuration file is generated, and a CDN cache is used for preloading resources; and executing the preloading strategy, and carrying out rollback processing after loading fails.

The invention discloses a construction site-oriented multi-mode inspection data intelligent analysis and closed-loop management system, and belongs to the technical field of building construction management. The system comprises a multi-modal data acquisition module, a fusion and feature extraction module, an intelligent analysis module, a decision distribution module and a closed loop verification module. The system performs space-time alignment on the collected visual, sensing and positioning heterogeneous data, and generates unified representation by using cross-modal attention fusion; modal contradictions are eliminated through joint reasoning, risks are evaluated, and a disposal task is automatically generated; after the task is completed, a data rechecking process is automatically started, the improvement degree is calculated by comparing the data before and after rectification so as to verify the effect, and automatic rollback is performed if the result is unqualified. The problem of heterogeneous data integration is effectively solved, a whole-process closed loop from hidden danger recognition to automatic verification is realized, and the risk response speed and management efficiency of a construction site are remarkably improved.

The invention discloses a power distribution terminal upgrading method, system and device based on an SD card and a medium. The method specifically comprises the steps of generating an incremental package of a Linux kernel and / or a root file system, calculating a hash value file of the incremental package, and generating a block chain certificate with a timestamp; encrypting and packaging the incremental package, the hash value file and the block chain certificate into a container mirror image, performing digital signature to form an upgrade package, and writing the upgrade package into an SD card; after it is detected that the SD card is inserted, mounting a boot partition, analyzing metadata of an upgrade package, and setting an upgrade flag bit and an upgrade operation type of Boot; and performing digital signature verification, hash value file verification and block chain certificate verification on the upgrade package in the SD card, if the verification is passed, backing up user parameters to the encrypted storage area, and restarting to enter the Recovery OS to complete replacement upgrade of the Linux kernel and / or the root file system. According to the method, safe, efficient and flexible upgrading of the operating system of the power distribution automation terminal is achieved, the rollback function is achieved, and the upgrading risk and cost are effectively reduced.