457 results about "Consensus algorithm" patented technology

A computer-implemented method and system for privacy-preserving location verification in distributed networks comprises initializing a multi-modal biometric authentication system on a user device, generating cryptographic keys using a distributed key generation protocol, binding the cryptographic keys to biometric templates using a fuzzy vault scheme, constructing and broadcasting encrypted location beacons, and generating zero-knowledge proofs of location claims. The system includes user devices equipped with biometric sensors and verifier devices configured to validate location claims and maintain consensus in a blockchain network. The method implements real-time liveness detection for multiple biometric input types, executes fault-tolerant consensus algorithms with privacy preservation, and maintains a dual-scoring mechanism comprising device trust scores and user reputation scores. The system enables secure location verification while preserving user privacy through cryptographic protocols and biometric authentication in decentralized environments.

The invention relates to the technical field of intelligent navigation and control of ships. The invention provides a complex channel ship intelligent navigation and emergency decision-making method and system. The method comprises the following steps: acquiring environment data through a multi-source heterogeneous sensor array, and establishing a channel three-dimensional dynamic environment model; establishing a multi-objective optimization function, and performing dynamic path planning by adopting an improved model prediction control algorithm; synchronizing motion state parameters of an actual ship and a virtual ship model in real time, constructing an emergency decision tree in combination with an expert knowledge base, and verifying the feasibility of an emergency decision through Monte Carlo simulation; carrying out local route optimization by adopting edge computing nodes, carrying out multi-ship trajectory prediction through a federated learning mechanism, and generating a corresponding collaborative collision avoidance strategy; and establishing a dynamic priority scheduling mechanism, implementing hierarchical response, and confirming a global avoidance scheme through a distributed consensus algorithm. The problems that an existing inland ship intelligent system is limited in perception, rigid in decision and weak in collaboration in a complex scene are solved.

The invention discloses a digital production plan scheduling method and system, and belongs to the technical field of optimal scheduling, and the method comprises the steps: constructing a distributed storage architecture based on edge computing nodes; a central coordinator is adopted to realize cross-node data synchronization through an improved Raft consensus algorithm, multi-version concurrency control is realized based on a vector clock, and a global consistent data view is established; a visual scheduling platform is built based on a Vue3 framework, and man-machine interaction is realized by adopting a Canvas and WebGL collaborative rendering framework; establishing a dynamic coordinate conversion model based on bilinear interpolation, designing a space mapping function containing distortion compensation, establishing a multi-thread coordinate service based on WebWorker, and realizing submillimeter-level bidirectional mapping of pixel coordinates and physical coordinates; constructing a three-dimensional space-time analysis model fused with the multi-dimensional features; and all the units are subjected to feature fusion through residual connection, and finally a scheduling scheme with a confidence coefficient weight is output. The method and the device have the effect of meeting various scheduling requirements.

According to the archive data tracking and multi-party cooperation auditing method based on the block chain smart contract provided by the invention, the authenticity and non-tampering property of archive data are guaranteed through a block chain technology, and an efficient and transparent auditing process is realized in combination with the smart contract. According to the method, a multi-level encryption storage and unique identifier generation mechanism of archive data is designed and is used for accurately tracking an archive circulation process; the access behavior is automatically recorded and verified through the intelligent contract, and the operation compliance is ensured. A distributed consensus algorithm is adopted for multi-party cooperative auditing, multiple auditing parties are allowed to participate together, and meanwhile objectivity and authority of auditing results are ensured. The method improves the safety, transparency and efficiency of archive data management and auditing, and can be widely applied to archive management and auditing scenes in the fields of governments, enterprises, education and the like.

The invention relates to the technical field of unmanned aerial vehicle cluster control, and particularly discloses an intelligent cooperative flight path planning method and system for an unmanned aerial vehicle cluster system, and the method comprises the steps: firstly constructing a dynamic environment perception model, collecting data through all unmanned aerial vehicle sensors, and carrying out the preprocessing, attention feature extraction and federal learning fusion, and generating a global environment situation map; planning and screening a candidate track set by adopting a particle swarm-genetic hybrid optimization algorithm for adaptive weight adjustment on the basis of the image; a global optimal track consensus is achieved through an improved consensus algorithm and conflict resolution through a distributed collaborative negotiation mechanism and no human-computer interaction evaluation indexes; and finally, monitoring the environment in real time during execution, triggering dynamic re-planning when the environment is abnormal, and ensuring track adaptation through multi-level threshold and incremental planning. According to the method, the unmanned aerial vehicle cluster can quickly respond to the environment change and adjust the flight path, so that the task execution efficiency and success rate of the unmanned aerial vehicle cluster in the complex dynamic environment are improved.

The invention discloses a goaf unmanned aerial vehicle inspection system based on monitoring and early warning, and the system comprises an observation data collection module which is used for collecting settlement and fracture main variables to form a time stamp observation set; the data fusion module is used for generating a unified monitoring data set by adopting a fractal small-world network coding consensus algorithm; the initial route planning module is used for constructing a route sequence based on a main variable evolution tensor and a risk map; the flight path execution module is used for collecting a flight path and environment data; the fault-tolerant control module triggers a fractional order sliding mode fault-tolerant and degradation mechanism based on the consistency error; and the closed-loop optimization module is used for dynamically updating the main variable tensor and the path cost function and outputting an optimized track and a structured early warning result. The system has high dynamic responsiveness and multi-source risk adaptability.

The invention discloses a rural industry agricultural product full-process traceability method based on a block chain. The method comprises the following steps: collecting agricultural product full-life-cycle process data and environmental parameter data through Internet of Things sensing equipment; preprocessing the agricultural product traceability data by using a space-time agricultural data compression technology; storing the compressed key traceability data in a block chain network, and storing high-capacity original data through a content addressing interstellar file system; maintaining the consistency of the block chain network based on an adaptive agricultural season consensus algorithm; automatically executing data verification and business logic processing through the smart contract; the authenticity of agricultural product traceability information is verified based on a zero-knowledge proving technology, and meanwhile peasant household sensitive data are protected.

AI neural networks are integrated with distributed ledger technology (DLT), including the integration of decentralized oracles, to enhance the functionality, security, and efficiency of systems. The integration incorporates several components and methods comprising novel neural network architectures, data preprocessing techniques, DLT integration approaches, privacy and security measures, consensus mechanisms, and others. The invention enables the development of neural smart contracts, neural consensus algorithms, dynamic neural network training, neural network optimization techniques, hybrid DLT architectures, neural network interpretability methods, and reinforcement learning for neural smart contract execution. By integrating decentralized oracles into the system, the invention has the capability to further enhance the reliability, accuracy, and diversity of data used within the DLT, improving transaction validation, consensus mechanisms, and overall system performance.

The present invention relates to the technical field of communication anti-interference, and relates to an interference confrontation method, system, device and medium for a wireless communication network, the method comprising: obtaining spectrum data, the spectrum data comprising spectrum data deployed and collected by a wireless network according to an initial deployment scheme; performing feature extraction and fusion processing on the spectrum data to generate a spectrum situation map; performing reinforcement learning decision processing according to the frequency spectrum situation map to generate a dynamic anti-interference strategy; according to transmitting node combination parameters in the dynamic anti-interference strategy, a collaborative bait node group is obtained through distributed consensus algorithm processing; sending a virtual signal to an interference source according to the dynamic anti-interference strategy and the collaborative bait node group; and calculating the strategy effect of the virtual signal by using a reinforcement learning reward function to obtain an optimized anti-interference strategy, thereby breaking through the limitation of insufficient static coping and cooperation of a traditional anti-interference method, and realizing communication reliability and anti-interference adaptability in a complex dynamic interference environment.

The invention relates to a carbon emission checking system and method based on a block chain, and the system comprises a basic resource layer which collects enterprise energy consumption data in real time, employs cloud computing resources to provide data storage and computing capability, and employs a Hash algorithm to process the enterprise energy consumption data, and obtains a data abstract; the block chain network layer carries out distributed storage through an alliance chain architecture, carries out consensus evidence storage on the data abstract by adopting a PBFT consensus algorithm, and generates an encrypted data abstract; the intelligent contract layer receives the encrypted data abstract transmitted by the block chain network layer, and executes verification, calculation and supervision rules; and the application service layer calls the processing result of the intelligent contract layer, and respectively provides an enterprise carbon checking terminal service interface, an institution carbon checking terminal service interface and a competent department carbon supervision terminal service interface for the enterprise, a third-party checking institution and the competent department to check the carbon emission. According to the invention, high-efficiency check, high-credibility verification and whole-process traceable supervision of the carbon emission data are realized.

The invention provides a thermal power network security consensus verification method and system based on artificial intelligence, and relates to the technical field of network security, and the method comprises the steps: collecting thermal power network equipment data, carrying out the feature extraction, inputting a deep neural network model, and carrying out the analysis, thereby obtaining a network security state evaluation result. Constructing a consensus mechanism based on a block chain technology, and storing an evaluation result to a plurality of nodes; when an evaluation result triggers a threshold condition, an improved practical Byzantine fault-tolerant consensus algorithm is started for verification, a credibility weight mechanism is introduced into the algorithm, and a credibility score is calculated according to node historical behaviors to serve as a voting weight. And an evaluation result exceeding two-thirds weighted voting is confirmed as a valid result, and safety early warning information is generated and broadcasted to all the control units. The accuracy and reliability of thermal power network security state evaluation can be effectively improved, security threats can be found and early warned in time, and the security protection capability of the thermal power network is enhanced.

The invention discloses a data integrity verification method based on a block chain, and particularly relates to the field of data verifier.The method comprises the steps that firstly, a mixed framework of a relational database and a non-relational database is constructed, various kinds of data and statistical information are stored, and then image and text data are subjected to multi-dimensional segmentation; a specific algorithm is adopted to calculate a data unit hash value, a data block hash value and a top level hash value are obtained through hash aggregation, an alliance chain architecture and an intelligent contract are utilized to realize data uploading and storage, access permissions of different block chains are set, and a consensus algorithm is dynamically adjusted by monitoring a network load and a node performance state in real time, so that the network load and the node performance state are monitored in real time. According to the method, the block chain network is guaranteed to run stably, in the data integrity verification link, through preliminary verification and detailed verification, comparison of hash values of all levels and accurate judgment of data integrity, complex data can be effectively processed, tampering positions can be quickly positioned, and verification efficiency and safety are improved.

The invention discloses a dynamic security authentication method for cross-platform information system integration, and relates to the technical field of cross-platform dynamic authentication. A non-tampering identity trust chain is established through a block chain consensus algorithm, the problems of single-point fault and expansibility of centralized identity management are solved, cross-platform unified identity verification is realized, the problem that multi-factor authentication lacks intelligent risk assessment is solved through intelligent contract automatic verification and user behavior analysis, threats can be dynamically responded, and the user experience is improved. The authority is dynamically adjusted based on the risk level, and a real-time access control decision engine is combined, so that the problem of response lag of traditional access control is solved, accurate authority control is realized, and finally, a continuously optimized security authentication mechanism and a unified and coordinated cross-platform security protection system are formed.

The invention provides an information security risk management method and management system. The system is composed of four core modules: a multi-modal data acquisition layer: probes deployed at a terminal and a server support heterogeneous data acquisition of network traffic, operation logs and an API (Application Program Interface) call chain; according to the block chain log storage layer, a private chain is constructed based on an improved BFT consensus algorithm, and each block comprises a timestamp hash value and a preorder block fingerprint; the dynamic risk assessment engine adopts an LSTM-Transform hybrid neural network, and input dimensions comprise a user behavior baseline, a vulnerability library version and threat intelligence feed; and the intelligent response decision module is used for integrating a reinforcement learning algorithm, automatically generating a disposal strategy and triggering the SDN controller to execute network isolation. According to the method, a local chain-alliance chain-audit chain three-level structure is applied to data island treatment and data integration in organization, the problem of internal data fragmentation is solved through the local chain structure, unified storage and rapid source tracing of heterogeneous logs are achieved, and data authenticity and time sequence integrity are ensured.

The present invention relates to the technical field of blockchains, and in particular to a blockchain-based multi-partition asynchronous parallel consensus method. The method comprises: constructing a multi-partition asynchronous parallel consensus blockchain system comprising a plurality of partitions and a plurality of guide nodes; for each partition, each ordinary node publishes and broadcasts transaction information in the partition to which it belongs, and each ordinary node collects and stores the transaction information published in the partition to which it belongs; each partition creates a partition block by executing an intra-partition consensus algorithm, and uses a main node to upload the partition block to a guide node; and each guide node sorts the collected partition blocks, and selects one partition block therefrom to execute an inter-partition consensus algorithm. The present invention enables the synchronous intra-partition consensus initiation and execution provided for in existing sharded blockchain systems to now be performed asynchronously, thus improving system parallelism, transaction information processing throughput, and cross-shard communication processing efficiency.

The invention relates to the technical field of energy storage systems, and provides a self-adaptive power distribution method and system for multiple energy storage units of an island microgrid. According to the invention, a discrete consistency algorithm is adopted to realize coordination control of multiple units, each unit only exchanges information with adjacent units, and power distribution targets of all the units are converged to a consistent value through iterative computation, so that the communication bottleneck and the single-point fault risk of centralized control are avoided; according to the invention, a complete fault-tolerant processing mechanism is designed, the operation state of each energy storage unit is monitored in real time, topology updating and power redistribution are automatically carried out when a unit fault is detected, and the self-healing operation of the system is realized. Experiments show that compared with a traditional method, the method has remarkable advantages in key performance indexes such as capacity balance among energy storage units, system operation efficiency, communication overhead and fault recovery time, and the operation efficiency and reliability of the island microgrid system are remarkably improved.

A heterogeneous storage-oriented hot and cold data management method and system, wherein hot and cold data are managed by means of the following steps: at table granularity, storing data from each table into an independent data bucket in the form of object storage, each data bucket comprising a plurality of partitions, the data being randomly distributed in each partition, and the consistency of replicas of the partitioned data being ensured by means of a distributed consensus algorithm; collecting statistics about the access frequencies of the partitions in one data bucket; when the access frequency of one partition reaches a set threshold, adding a new replica to a target storage medium by means of a membership change in the distributed consensus algorithm; and when data synchronization between the new replica and an old replica is completed, detecting the old replica. In this way, the migration of the partitioned data on different storage media is realized, and data cooling and heating are implemented. The method and system can maximize the use efficiency of high-performance storage media, ensure the access efficiency of users, and can reduce the costs of data migration and maintenance.

The invention discloses a carbon right-green certificate collaborative transaction method based on a block chain, and belongs to the field of block chain technology and environment management. The method specifically comprises the following steps: 1) deploying an intelligent contract based on an Ethereum platform, and integrating power transaction, carbon quota delivery and green certificate issuing process chains to realize automatic execution of transaction rules and non-tampering of data; (2) a Carbon Token excitation mechanism is innovatively designed, a DPoS-CT consensus algorithm considering the right of the Carbon Token is proposed, and a market subject is excited to continuously reduce emission; 3) a dynamic reputation model and a reward and punishment mechanism are used to quantify subject performance behaviors and distribute on-chain rights and interests; and 4) resetting the transaction cycle every 24 hours, and optimizing quota allocation and consensus parameters based on historical data. According to the mechanism provided by the invention, renewable energy transaction can be effectively stimulated, and after the block chain carbon pass system is introduced, the quota completion rate, the green electricity utilization rate, the carbon emission, the carbon right-green certificate transaction volume and the economic benefit are optimized to a certain extent.

The invention relates to the technical field of data information operation and maintenance management, and discloses a data information operation and maintenance management method based on an AI chain trust mechanism, and the method comprises the steps: obtaining multi-source heterogeneous data through a distributed collection terminal composed of an edge calculation node, an Internet of Things sensor and a third-party interface module; and after format conversion, a data trust value is calculated by using a multi-dimensional trust evaluation model containing a source reliable item, a content consistent item and the like, then the data trust value and a historical trust record in a block chain distributed account book are subjected to association verification, and a trusted data identifier is generated through a consensus algorithm. And constructing an on-chain storage index based on the data type, the timestamp and the source node, encapsulating the data by adopting a hierarchical structure of a metadata layer, a content layer and a verification layer, and outputting a storage address. A monitoring layer of the dynamic operation and maintenance control model identifies abnormity in real time, a decision-making layer generates an operation and maintenance strategy in combination with credible data identification and historical records, and an execution layer triggers repairing and updating operation through an intelligent contract, so that on-chain credible operation and maintenance management of data information is realized.

The invention discloses a radiotherapy mold full-process block chain traceability storage method and system, and relates to the technical field of medical user management, and the method comprises the steps: building a radiotherapy mold storage block chain platform, and deploying an identity verification smart contract; establishing a medical institution radiotherapy mold management block chain platform, and integrating an Internet of Things data acquisition module; establishing a radiotherapy order collaborative block chain platform; a cross-chain relay protocol is adopted to establish data mapping between the radiotherapy mold storage block chain platform and the medical institution management platform, and a mold state synchronization rule is defined; data transmission among all platforms is encrypted by adopting a BFT consensus algorithm, a non-tampering auditing chain is generated by data access operation of a medical institution, and a supervision institution verifies data integrity through a zero-knowledge proof technology. The method has the advantages that through deep cooperation of the block chain and the Internet of Things technology, a credible traceability closed loop of the whole life cycle of the radiotherapy mold is constructed.

The invention relates to the technical field of power equipment supply chain management, and discloses a power equipment supply chain collaborative management system based on an alliance chain, comprising an alliance chain network layer: a distributed network composed of a manufacturer node, a supplier node, a logistics node, a detection node and a grid company node, each node maintaining account book consistency through a consensus algorithm; the intelligent contract execution layer comprises an order processing contract, a logistics tracking contract, a quality acceptance contract and a settlement management contract, and supports automatic execution of a business process; and the data management platform is provided with a distributed storage unit, an encryption transmission unit and an authority control unit and is used for realizing encryption storage and hierarchical access of key data. Full-process automation of order matching, production plan generation and logistics tracking is realized through an intelligent contract execution layer, an AI prediction module can pre-judge a demand peak value in advance based on historical data, a node processing priority is optimized in combination with a dynamic consensus algorithm, and manufacturer order response time is compressed.

The invention discloses an unmanned aerial vehicle cluster cooperative flight control system and method. The system comprises a task distribution module, a trajectory planning module, a formation control module, a communication module, a state monitoring module and an autonomous navigation and positioning module. The task distribution module performs process control through a consistency algorithm improved by combining an A * algorithm, and executes task distribution; the trajectory planning module performs trajectory planning by constructing and solving a mathematical model and a control model, and determines a flight path; the formation control module enables the unmanned aerial vehicle cluster to fly in a predetermined formation configuration; the communication module is used for realizing real-time information transmission and sharing; the state monitoring module is responsible for monitoring and recording the state of the unmanned aerial vehicle in real time; the autonomous navigation and positioning module is used for providing navigation and positioning information for the unmanned aerial vehicle. According to the invention, through optimizing process control, the efficiency and precision of overall cooperative flight can be improved, and efficient and accurate information exchange between the unmanned aerial vehicles can be ensured.

The invention discloses a multi-unmanned-aerial-vehicle cooperative hoisting method and system, and the method comprises the steps: firstly, enabling each unmanned aerial vehicle to operate an extended state observer, regarding internal and external disturbances (such as airflow, unknown load parameters, internal coupling force and the like) as a lumped disturbance, and carrying out the real-time estimation; and then, through a communication network operation consensus algorithm between the unmanned aerial vehicles, fusing the local disturbance estimation values of the unmanned aerial vehicles into a global consistent system-level disturbance estimation. And finally, each unmanned aerial vehicle actively counteracts the influence of disturbance by using the accurate disturbance estimation value in a feedforward compensation controller, and accurately tracks the respective target trajectory in combination with feedback control. According to the method, active observation of disturbance, distributed fusion and feed-forward compensation are combined, dependence on an accurate system dynamic model is eliminated, and trajectory tracking accuracy, stability and stability of the system in a complex environment are remarkably improved.

The invention discloses a historic building cylindrical structure inclination measurement method considering irregular surfaces and measurement errors, and the method comprises the steps: measuring the three-dimensional coordinates of measurement points at different section heights of a historic building wood structure cylinder with a cutting or irregular surface; determining an optimal solution after a certain error is removed from the coordinates of the circle center of the section by adopting a self-adaptive random sampling consistency algorithm, then obtaining the central axis of the cylinder according to principal component analysis, and calculating the included angle of the earth normal vector of the central axis of the cylinder, namely the inclination angle of the historic building wood structure cylinder. By using the algorithm, the influence of cutting or irregular surfaces and measurement errors on historic building wood structure cylinder inclination measurement can be eliminated, and the reliability and the accuracy of a measurement result are effectively improved.

The invention relates to the field of power equipment management, and discloses a power equipment traceability data management method based on a block chain, and the method comprises the following steps: collecting power equipment data through a block chain technology, the power equipment data including production, transportation, use and maintenance data; the consistency of the power equipment data is optimized based on the maximum entropy principle, and information sharing and data synchronization are carried out by using the entropy value of each node; the data state of each node is dynamically updated through Bayesian inference, and the real-time consistency of the traceability data is guaranteed; a quantum game mechanism is adopted to optimize a consensus algorithm, and a quantum superposition state and quantum entanglement are utilized to improve information sharing and data synchronization. By adopting the block chain technology, the maximum entropy principle, the Bayesian inference and the quantum game mechanism, the efficient, real-time synchronization and consistency of the power equipment data are realized, the security and integrity of the data are ensured, and the node fault recovery efficiency is improved.

The invention provides an optimization method for proposal node selection of a consensus algorithm of a carbon Popingness block chain, and belongs to the technical field of carbon Popingness block chains. The optimization method comprises the following steps: starting a new era through a node, counting candidate node information, calculating a mathematical mean value and a standard deviation of a consensus efficiency score to identify an outlier node; evaluating the network performance of candidate nodes by applying a carbon popularity performance prediction model and a dynamic memory adjustment function, generating a proposal node list after removing outlier nodes, performing transaction verification and state verification by verification nodes, executing a multi-round voting verification process by a consensus algorithm, and adding consensus participation points for participation nodes, and after the block is submitted, each node sends a score list to the next height proposal node and writes the scoring data into the block head part, and through the complete node selection and consensus verification process, the technical problems that the proposal node selection efficiency is low and the nodes with abnormal performance cannot be effectively excluded in the block chain consensus algorithm are solved.

The invention discloses an intelligent water affair water resource tracing and transaction management system fused with a block chain technology, and the system comprises the following steps: a data collection and preprocessing module which is used for collecting real-time water affair data, carrying out the preprocessing of the real-time water affair data, and forming a structured data file; the parameter optimization and intelligent early warning module is used for constructing an anomaly detection model and performing global adjustment; the consensus verification module is used for performing consensus verification based on a practical Byzantine fault-tolerant consensus algorithm; the secure uplink and transaction management module is used for performing secure uplink on the data after the consensus verification to form a non-tampering data storage certificate; and the automatic response and decision support module is used for automatically triggering an intelligent contract and executing water resource scheduling, transaction management and emergency response operation. According to the invention, the block chain, the Internet of Things and an intelligent optimization algorithm are fused, real-time collection, accurate detection, safe chaining and automatic management of water resource data are realized, and the efficiency and transparency of the intelligent water affair system are significantly improved.

The invention provides a block chain-based low-altitude Internet of Things trusted data sharing system and method. The system comprises a clustering module, an authentication module, a terminal module, a cloud storage module, a data chain module, a trust chain module and a trust evaluation module. The method comprises the following steps: carrying out identity verification on an aircraft joining the low-altitude Internet of Things, and issuing a public and private key pair and a digital certificate; data information of the aircraft is encrypted and then uploaded to the cloud; through an evidence theory, combining evidence information on two scales of time and space through a Dempster combination rule to obtain a trust value of the aircraft; clustering aircrafts in the low-altitude intelligent networking through a K-means mean clustering algorithm, and dividing the aircrafts into two layers of low-altitude intelligent networking; a distributed storage system based on a block chain is constructed, data sharing records and trust values of aircrafts are stored respectively, and consensus of two layers of networks is completed through improved DPoS and PBFT consensus algorithms.

The invention relates to the technical field of power systems and energy management, and discloses an energy-carbon integrated virtual power plant multi-agent collaborative management and control method and system, and the method comprises the steps: S1, constructing a three-layer control architecture comprising a resource sensing layer, a region coordination layer and a global optimization layer; s2, establishing an energy-carbon coupling state space model, and outputting a target optimization result by taking photovoltaic output, energy storage charging and discharging power, a load demand elastic coefficient and a carbon emission right transaction volume as input variables; s3, generating a scheduling instruction by adopting a rolling optimization strategy; and S4, realizing multi-agent collaboration through a distributed consistency algorithm, exchanging power deviation information by each node based on a local constraint condition, and carrying out iterative calculation until the power deviation of all nodes is less than 1%. A three-layer control architecture is constructed, scheduling lag is shortened through decision making and stage processing of the global optimization layer after preprocessing of the regional coordination layer, the limitation of a single node is broken through through cross-regional coordination, and the overall operation efficiency of the virtual power plant is enhanced.

The invention discloses a quality safety supervision system based on a block chain and the Internet of Things, and the system comprises an Internet of Things sensor network which is used for collecting the environment data, construction equipment operation data and building material state data of a construction site of a construction project in real time; the edge computing equipment is connected with the Internet of Things sensor network and is used for carrying out primary processing and screening on the acquired data; the block chain node receives the effective data from the edge computing device through a 5G communication technology, and stores and processes the effective data; the system has the beneficial effects that the real-time and comprehensive acquisition of data is realized by fully utilizing the Internet of Things technology, the timeliness and integrity of quality data are ensured, and a more accurate data basis is provided for quality safety supervision; the improved Byzantine fault-tolerant consensus algorithm based on creditworthiness improves the transaction processing efficiency of the block chain, reduces the storage cost, and enhances the responsibility of the node and the data credibility through creditworthiness weight setting.