416 results about "Communication layer" patented technology

The present invention relates to the field of water affair monitoring and early warning, and provides a smart urban water affair early warning system and method integrating the Internet of Things and the Internet, for solving the problems of existing urban water affair systems. The present invention comprises a sensing layer, a communication layer, a data layer and a decision-making layer. The sensing layer constructs, on the basis of the Internet of Things technology, an integrated sky-ground water conservancy Internet of Things sensing system covering water sources, pipeline tunnels, water plants, and river collection points, to collect multi-source data. The communication layer is used for sending to the data layer a large amount of multi-source data collected by the sensing layer. The data layer constructs, on the basis of the large amount of collected multi-source data, an urban water affair hydrological database, including a foundation database, a hydrological database, an engineering database, a water quality database, a management database and a remote sensing database. The decision-making layer is used for performing analysis and decision-making on the large number of multi-source data collected by the sensing layer, performing water quality prediction on all the collection points on the basis of each type of database, and when prediction results exceed a threshold, integrating a BIM platform and a GIS platform to display an alarm.

The invention relates to the technical field of robot scheduling, in particular to a distributed robot collaborative scheduling system and method in a dynamic environment, and the system comprises an environment sensing layer which is used for collecting environment dynamic data in real time; the distributed decision-making layer comprises local task scheduling modules of a plurality of robots; the cooperative communication layer is used for realizing task state synchronization and conflict detection among the robots based on a low-delay communication protocol; the dynamic weight calculation module is used for generating a real-time optimization weight according to the task emergency degree, the robot energy consumption and the path risk factor; according to the invention, by using a completely distributed collaborative scheduling architecture, through a decentralized task distribution mechanism and a distributed consensus protocol, a single-point fault risk existing in a traditional centralized scheduling system is thoroughly eliminated, and even if a part of robot nodes have faults or communication is interrupted, the system can work normally. And the system can still run continuously through autonomous negotiation of the remaining nodes, so that the reliability of the system in a complex environment is remarkably improved.

The invention discloses an Internet of Things test platform adaptation method, system and device based on post quantum cryptography. The method comprises the following steps: constructing a quantum threat perception model; establishing a multi-dimensional adaptive decision matrix, and generating a candidate post-quantum cryptography algorithm set; dynamic injection of a cryptographic protocol is executed, and lossless replacement of a communication layer encryption suite is achieved; deploying a runtime performance monitoring engine, and collecting encryption and decryption delay, memory occupancy rate and electromagnetic radiation characteristic data in real time; and constructing an algorithm switching decision tree based on reinforcement learning, and when a quantum attack feature or an equipment performance threshold is detected to break through, triggering cryptographic algorithm dynamic migration. A quantum threat perception driven Internet of Things security adaptation system is constructed, and by introducing a dynamic password switching mechanism, a hardware acceleration optimization scheme and a trusted execution environment, the security upgrading problem of traditional Internet of Things equipment in the post-quantum era is solved. According to the invention, the execution efficiency of the PQC algorithm of the resource-constrained equipment can be improved, and the key updating delay is reduced.

The invention discloses a visual algorithm self-training method based on multi-agent collaborative optimization, and the method comprises the following steps: constructing a multi-agent system architecture which comprises a user interaction layer, an intelligent scheduling layer, an A2A protocol communication layer and a professional agent cluster layer; the user interaction layer analyzes a user task intention and generates an execution plan; the scheduling agent calls the professional agent to complete data processing, model construction, training, testing and deployment; a task process is coordinated through a standardized communication mechanism, and task execution is supported by combining an MCP tool set, a knowledge base module and a memory system; and when the task fails, automatically executing rescheduling operation, and finally outputting a self-training result. According to the method, the development efficiency, the self-adaptability and the intelligent level are remarkably improved, and the method is suitable for computer vision tasks such as industrial detection, intelligent security and protection and automatic driving.

The invention relates to the field of wireless communication and intelligent networks, in particular to a software defined radio-based ad hoc network dynamic slicing architecture and a management and control method, comprising a basic communication layer, an intelligent control layer and a service execution layer. The basic communication layer adopts a multi-distribution multi-center clustering architecture; the intelligent control layer is responsible for intelligent management and resource scheduling of the self-organizing network, and the intelligent control layer comprises a plurality of command and control nodes; and the service execution layer adopts a micro-service-based architecture, and encapsulates different network functions and service logics into independent micro-service modules. According to the method, the technical problems of high plane coupling, resource scheduling rigidness, insufficient survivability and high hardware dependency in the prior art are solved.

The invention discloses a ship-shore cooperation-based cabin intelligent diagnosis management system, which comprises a ship-end intelligent sensing layer, a ship-shore cooperation communication layer and a shore-based intelligent decision-making layer, and is characterized in that the ship-end intelligent sensing layer comprises a ship-end data acquisition module, and the ship-shore cooperation communication layer comprises a data transmission module, a shore-end data center and a cloud server; the shore-based intelligent decision-making layer comprises an intelligent diagnosis module, a predictive maintenance module and a ship-shore cooperation module. The invention belongs to the technical field of cabin intelligent management, and particularly provides an intelligent cabin diagnosis management system based on ship-shore cooperation and a predictive maintenance method, which can reduce the equipment failure rate, optimize the maintenance cost and prolong the equipment life cycle through real-time data acquisition, cloud intelligent analysis and dynamic maintenance decision.

An adaptive modular multimodal communication and computing panel includes a multilayer stack with a protective layer transmissive in selected bands, a reconfigurable communication layer operable in phased array, reflectarray, hybrid phased reflector, free space optical, or quantum modes, and electronics with heterogeneous processors. A multi scale interconnect and input and output fabric couples electrical, radio frequency, guided optical, and free space optical domains through interfaces including electro optic transduction and RF or baseband conversion. The fabric may implement programmable true time delay, resonators, and comb referenced timing. A management system coordinates beamforming, sensing, routing, calibration, workload placement, and security. Panels tessellate and connect by electrical, radio frequency, and fiber optic interfaces, supporting hot swappable modules, blind mate connectors, robotic servicing, and anti tamper features. Power and thermal subsystems harvest, store, regulate, and dissipate energy. The architecture scales from chip level modules to vehicle, airborne, maritime, orbital, and deployable systems.

The invention provides a controllable SCADA (supervisory control and data acquisition) industrial production control platform based on an industrial internet architecture. The controllable SCADA industrial production control platform comprises a field layer, an edge layer, a communication layer, a cloud / fog computing layer and a data management layer, wherein the field layer is composed of a sensor array, an execution mechanism, a PLC controller and an RTU terminal; the sensor array comprises a temperature sensor, a pressure sensor, a flow sensor and a position sensor, and adopts 4-20mA current loop signal output; the execution mechanism comprises an electric valve, a servo motor and a variable frequency driver, and communicates with the PLC through a Modbus RTU protocol; the PLC controller is provided with a dual-core processor and is provided with 16 digital quantity input / output channels and 8 analog quantity input channels; the RTU terminal is internally provided with a LoRa wireless communication module; the edge layer comprises an edge computing node and a protocol conversion gateway; the edge computing node is provided with an FPGA coprocessor and supports an edge reasoning framework; and multi-protocol conversion is realized through the protocol conversion gateway.

The various embodiments herein provide a system and method for networked digital twins with autonomous collaborative decision-making. The system comprises a Digital Twin Engine for real-time data acquisition, model synthesis, and simulation, an AI Module for advanced data analysis, an autonomous collaborative decision-making module for optimized decision-making, a communication layer for secure data exchange, and supporting modules for coordination, storage, security, and user interaction. The method for generating and deploying digital twins comprises data collection, transmission, preprocessing, model synthesis, simulation, validation, and deployment. The method for networking and collaboration comprises AI-based data processing, complex event processing, autonomous decision-making, task distribution, decision communication, real-time monitoring, and continuous improvement. This system enhances operational efficiency, scalability, and security, reducing the need for human intervention and providing a comprehensive management solution for complex systems.

The invention discloses an intelligent reservoir inspection system based on a knowledge graph and digital twinning. The system comprises a sensing acquisition layer, a modeling simulation layer, a data processing and decision support layer, a communication layer and an interactive visualization layer, the sensing acquisition layer obtains image video data, water level data, rainfall data and temperature and humidity data of the reservoir and the surrounding environment through a camera and a sensor; the modeling simulation layer maps an actual reservoir and a surrounding environment into a virtual model, imports data acquired by the sensing acquisition layer into the virtual model, and realizes dynamic monitoring and analysis through a digital twinborn technology; the data processing and decision support layer is used for processing, analyzing and mining data and providing decision support; the communication layer is responsible for interconnection, remote control and automatic task execution of the system; and the interactive visualization layer provides an operation interface and data display.

The application discloses a smart community management service system, and particularly relates to the field of service management, comprising a perception layer module, a communication layer module, a data processing layer module and an application layer module; the application realizes global intelligent management through the collaborative architecture of the perception layer module, the communication layer module, the data processing layer module and the application layer module; the perception layer is deployed with multi-source heterogeneous sensors, and data preprocessing is conducted in combination with edge computing; the communication layer adopts multi-protocol fusion transmission, supports 5G+NB-IoT dual-channel redundancy and end-to-end encryption; the data processing layer is based on a cloud-edge collaborative architecture, uses Kalman filtering denoising, D-S evidence theory fusion conflict information, LSTM-Attention prediction device failure, and constructs a digital twin simulation optimization energy consumption; the application layer provides a three-dimensional visual management and control platform, integrates security linkage, air conditioner group control strategy driven by reinforcement learning and convenient service scheduling, and supports cross-platform access and RBAC permission management.

The invention discloses a wireless cooperative control system and method for a multi-node brushless motor, and the system employs a layered architecture design, and comprises a main control layer, a drive layer, a communication layer, and a software layer. The master control layer is composed of a master node and serves as a task instruction scheduling center of the system, the driving layer is composed of N slave nodes, and N is larger than or equal to 3; the driving layer drives the brushless motor by executing an FOC vector control algorithm and monitors the state of the brushless motor; the communication layer constructs a star network topology based on an ESP-NOW protocol, a direct communication link is established between a master node and N slave nodes, and multi-node cooperative control is realized by adopting a dynamic channel switching mechanism and a timestamp alignment mechanism; and the software layer establishes communication with the main control layer through a USART serial port, receives the state data of the brushless motor of each slave node concentrated by the main control layer, and sends an instruction to the main control layer at the same time. Not only are wireless multi-node synchronization and anti-interference problems solved, but also high-precision motor control is realized.

The invention discloses a balance control method for health states of multiple parallel energy storage units. Firstly, a communication-free state-of-health online estimation method based on a battery semi-empirical life model is deduced, the method does not need communication, is small in calculation amount, considers the rated capacity difference, is suitable for the dynamic degradation process of a battery, and is popularized to different rated capacities by introducing the concept of weighted ampere-hour throughput. Then, in order to meet the requirements of health state equalization, accurate current distribution and average direct current bus voltage recovery, a hierarchical control structure is established. Through coordination and cooperation among the main control layer, the secondary control layer and the communication layer in the hierarchical control structure, the provided strategy can realize the control targets of health state balance, accurate current distribution and average DC bus voltage recovery, and can greatly reduce the communication burden of the system.

The invention provides a system for intelligent interaction of a software as a service platform. The system comprises a large language model LLM module, a voice processing module, a model context protocol MCP communication layer and a context management module. According to the system, function operation of the SaaS platform is directly driven through natural language interaction, combination of a menu or button control of a traditional graphical user interface (GUI), an LLM module and historical data of a context management module is not needed, the intention recognition accuracy is larger than or equal to 92%, and repeated correction of a user is reduced.

The invention discloses a healthy indoor environment edge computing system. The edge computing system comprises a sensing equipment layer, an edge node computing layer, a communication layer, a cloud platform layer, a control execution layer, a user interaction layer and an artificial intelligence and machine learning layer. The method has the beneficial effects that the indoor environment is monitored in an edge monitoring, calculation and analysis manner, so that the real-time processing of monitoring data at a monitoring place is realized, the data transmission path is shortened, the data transmission cost and time are saved, the detection efficiency of the indoor environment is higher, and the detection efficiency of the indoor environment is improved. The method has the advantages that the data transmission requirement is reduced, the defect of data loss caused by network delay or interruption is avoided, the detection result is more accurate, the edge calculation detection mode is adopted, the data transmission requirement is reduced, and the limitation of the central server on the system expansibility and the response speed is avoided.

The invention discloses a method and a system for verifying the reliability of remotely acquired data of an electric meter box, particularly relates to the technical field of communication and data transmission, and aims to solve the problem that the reliability of the remotely acquired data of the electric meter box is verified without changing an existing netmeter and a communication protocol. The invention aims to solve the problem of how to execute cross-layer reviewable reliability verification and quantitative credibility evaluation on a single reading result remotely acquired by an electric meter box so as to identify and eliminate the abnormity that communication is successful but data is not credible in real time, and support source end positioning. By introducing fusion of a cross-layer evidence set and an active detection mechanism, the credibility of each copying and reading result can be comprehensively evaluated. Multi-level data of a physical layer, a link layer, an application layer and the like are verified, and data exception is identified through active detection. Through the mechanisms, the method can effectively eliminate reading results which succeed in communication but have errors in actual data, thereby ensuring that the collected data are more reliable and accurately reflect the actual state of the electric meter.

The invention relates to the technical field of safe operation of a power system, in particular to a power distribution network information physical system fault collaborative recovery method, which comprises the following steps of: acquiring basic operation data of a communication layer and a physical layer, and respectively constructing fault recovery models of the communication layer and the physical layer; the communication layer takes optimal link performance as a target and applies constraints such as link capacity and connectivity, the physical layer takes multiple parameters such as load recovery as an optimization target and applies constraints such as network topology and power flow, and a double-layer optimization model, an upper layer optimization communication recovery strategy and a lower layer optimization physical recovery strategy are constructed for concurrent faults; and solving by using a double-layer optimization objective function to realize power distribution network fault collaborative recovery. According to the method, the interaction between the communication layer and the physical layer is comprehensively considered, so that the fault point can be more accurately positioned, the fault area can be quickly identified, the optimal recovery strategy is formulated, the power supply reliability is improved, and the healthy development of the smart power grid is promoted.

The invention provides a client identity authentication security evaluation method and system combined with adversarial sample simulation, and relates to the technical field of information security. According to the invention, end-cloud integrated evaluation is carried out under a white-box and black-box threat model for multi-mode identification objects of human face, voiceprint, fingerprint and behavior characteristics. The method comprises the steps of establishing reference performance through legal samples, generating transferable adversarial input, performing secure injection on a communication layer, calculating a robustness index, performing adaptive optimization, performing differential evaluation on protection effectiveness under protection configuration starting and non-starting, and performing risk grading and reinforcement according to a result. And finally, outputting a reproducible security and compliance conclusion through differential privacy and federal evaluation.

The invention discloses a laser cladding parameter self-adaptive control method and system based on AI digital twinning, and aims to solve the problems that in the prior art, laser cladding process parameter control depends on artificial experience adjustment and is difficult to adapt to material characteristic fluctuation, complex path heat accumulation and the like, and the final forming quality is affected. The invention provides a laser cladding parameter autonomous optimization method fusing digital twinning and Bayesian optimization, and aims to realize adaptive control of laser cladding parameters in a cladding process through Gaussian process modeling and real-time data iteration. According to the method, a digital twin system comprising a physical layer, a digital twin layer and a communication layer is constructed. Real-time data interaction and control instruction issuing are carried out between the physical system and the digital twin system through industrial communication protocols such as OPC UA, and closed-loop control is formed. The method can remarkably improve the quality and consistency of the formed part, reduces manual intervention, shortens the process development period, and has wide application prospects.

The invention belongs to the technical field of electric power system information physical fusion, and discloses an electric power information physical system modeling method and device based on digital twinborn and cross-domain joint simulation, equipment and a medium. The device comprises a physical layer used for acquiring basic data of a power network; the communication layer is used for constructing a communication network model and simulating communication among different subsystems in the power network; the digital twin layer is used for constructing a protocol conversion gateway to align semantics of the physical layer data and the communication layer data, and performing state estimation of the physical layer and the communication layer by adopting digital twin virtual-real interaction based on the physical layer data and the communication layer data which are subjected to semantic alignment; performing joint simulation of the physical layer and the communication layer in different communication time delays and communication fault risk conditions to obtain a simulation result; and the application layer is used for obtaining critical time delay and time delay-frequency sensitivity based on the simulation result.

A smart panel system comprises a network of interconnected smart panels, each including subpanels and micropanels. Each micropanel includes layers, such as a processing layer, communications layer, and module controller. The module controller uses an Artificial Intelligence Operating System (AIOS) to control and monitor the subpanels and micropanels. The AIOS includes software Artificial Intelligence (AI) agents dedicated to specific tasks, such as analyzing data, generating prompts, and applying AI outputs to the smart panels. The system can be monitored and controlled remotely using identification data, state data, and operating data transmitted by the smart panels.

The invention relates to the technical field of cross-platform application development, in particular to a cross-platform sky map component packaging method and device based on a unit-app X framework. According to the method, a four-layer packaging framework comprising an application layer, a communication layer, a WebView layer and a platform adaptation layer is constructed, and unified packaging and calling of sky map components of Android, iOS and a multi-platform gap are achieved. The application layer completes component initialization, instruction verification and standardization processing; the communication layer realizes data interaction and coordinate conversion; the WebView layer executes map API loading, instance management, covering rendering and event monitoring; the platform adaptation layer completes cross-platform authority management, WebView container adaptation and GPS position acquisition; and finally, the application layer integrates the data and encapsulates a TelchinaTdtUnix component to return a result. The problems that an existing cross-platform sky map component is poor in adaptability, disordered in authority management and low in interaction efficiency are solved, and the cross-platform compatibility, stability and development efficiency of the component are improved.

The invention provides a multi-Agent-based workshop management system and a cross-workshop migration method and system. The multi-Agent-based workshop management system comprises a sensing layer, an intelligent layer, an execution layer and a communication layer, a data acquisition module of the sensing layer is used for acquiring sensing data in a physical scene, and a sensing Agent of the sensing layer generates a corresponding virtual mirror image platform according to the sensing data and outputs an analysis result; the intelligent layer comprises a decision-making Agent and a coordination Agent, the decision-making Agent dynamically generates a global or local decision-making result according to an analysis result, and the coordination Agent monitors and evaluates the decision-making result through a preset mechanism and outputs an optimization strategy; the intelligent layer transmits the decision result and the optimization strategy to the execution layer; an execution Agent of the execution layer deploys a lightweight model through an edge calculation module, and analyzes a decision result and an optimization strategy into an equipment control signal to control equipment operation; and the communication layer provides an information interaction channel for the Agent of each layer. The limitation of a traditional layered architecture is broken through, and a self-organized, self-adaptive and self-optimized distributed intelligent ecological architecture is constructed.

The invention relates to the field of energy storage battery communication management, and particularly discloses a large-scale multi-node high-throughput data communication system of an energy storage battery, which comprises an equipment layer, a communication layer and a management scheduling layer, the management of the equipment layer on the battery comprises an IP mode and grouping management based on a battery state; a broadband industrial bus of the communication layer is used for data transmission among a BMU, a BCU and a BAU in the BMS and data interaction between the BMS and an EMS; the distributed domain bus is used for dividing the BMS into different domains, and cluster communication between BMS nodes is achieved in each domain. Cluster management is realized by using a distributed domain bus, the problems of complex wiring and difficult maintenance of traditional networking are solved, unified scheduling of energy storage devices of different manufacturers is realized through a self-defined domain address strategy, and addressing efficiency and distributed management and control capability of large-scale nodes are optimized.

The invention relates to the technical field of Internet of Things, in particular to an Internet of Things equipment collaborative management system based on an intelligent edge, which is composed of an equipment abstraction layer, a converged communication layer, a service logic layer and a firmware upgrading layer, the equipment abstraction layer realizes standardized access and full life cycle management of equipment through modeling, interface abstraction and resource pool management; the converged communication layer comprises protocol adaptation, intelligent routing and QoS guarantee to ensure smooth multi-protocol communication; the business logic layer adopts a micro-service architecture, and flexible business processing is realized through flow arrangement, intelligent decision making and event driving; the firmware upgrading layer comprises state perception, intelligent analysis, intelligent execution and firmware management so as to adaptively select an optimal upgrading strategy according to network state prediction and evaluation. According to the invention, modules at all levels cooperate, intelligent and collaborative management of Internet of Things equipment is realized, and the equipment management efficiency and the operation stability are improved.

The invention provides an intelligent dispatching and remote control method for a tower crane, which is applied to the field of fabricated house building construction and engineering equipment and aims to solve the problems of difficulty in dispatching the tower crane, low construction efficiency, severe operation environment and high safety risk in a clustered fabricated building. The method comprises the following steps: S1, constructing a distributed system architecture comprising a physical layer, a sensing control layer, a data processing decision layer, an application layer and a communication layer, and deploying equipment; s2, collecting environment, tower crane state and BIM model related multi-source data, and transmitting the data to a data fusion processing center for fusion; s3, planning an optimal hoisting path and a task sequence through the intelligent scheduling subsystem based on an ant colony algorithm; s4, a control mode is selected, a hoisting instruction is issued to execute a task, and forced braking is triggered in emergency; and S5, mapping a construction scene through a digital twin system, monitoring and alarming through an intelligent monitoring system, feeding back data to realize closed-loop optimization, and recording a digital file. According to the method, tower crane dispatching and construction efficiency is improved, construction safety is guaranteed, and intelligent construction of the fabricated building is promoted.

The invention belongs to the technical field of energy management, and discloses a user-side-oriented source-load-storage integrated comprehensive energy management system, and the hardware architecture comprises a sensing layer, a communication layer and a platform layer. On-site facilities of a source side, a load side and a storage side in the hardware architecture are accessed to the integrated energy management system based on the data collection and calculation unit, and data analysis and display are performed through the server; the software function architecture comprises a data layer, a service layer, an application layer and a display layer; the software function architecture supports the realization of the functions of stable power utilization, flexible scheduling and intelligent management of the source-load-storage integrated comprehensive energy management system; the system further comprises a terminal sensing module, a data collection and calculation unit and an optimization control strategy of the comprehensive energy management system. By adopting the source-load-storage integrated comprehensive energy management system facing the user side, the power consumption cost of the power consumer is reduced, the monitoring, analysis and management capabilities of the source-load-storage comprehensive energy are improved, and the distributed new energy consumption is promoted.

A system for content encapsulation and secure communication of content includes: a data agency manager configured to facilitate communication of content from a content owner computing device to a user computing device based at least in part on defined governance logic for the content; a data encapsulation layer in communication with the data agency manager, the data encapsulation layer configured to bind the content to the defined governance logic, wherein the content bound to the defined governance logic is associated with a digital agency capsule; and a communication layer in communication with the data agency manager, the communication layer configured to communicate one or more a digital agency capsules from the content owner computing device to the user computing device according to the defined governance logic in each a digital agency capsule.

The invention relates to an NUP-based intelligent control system for a thermal power plant, which combines a DCS with an NPU to construct a novel thermal power control system comprising a control layer, a calculation layer, a communication layer and a management layer. In a calculation layer, traditional control logic is executed in a DCS, and advanced algorithms such as artificial intelligence and the like are executed by an NPU acceleration module; a general compiler is adopted to support a mainstream programming language to construct an algorithm library, and a deep learning framework is combined to improve a function; the data management uses a lightweight database; and the communication layer adopts a high-speed industrial Ethernet and is compatible with a mainstream protocol to realize data interaction. According to the scheme, the defects of insufficient response speed, algorithm processing capability and parallel operation capability when a traditional DCS deals with the problems of new energy fluctuation and the like are solved, and the effects of improving the flexibility and stability of a unit, improving the calculation speed of an AI algorithm, reducing the data query and extraction speed, realizing self-adaptive adjustment of control parameters of the unit and iterative optimization of performance are achieved. And the system has good compatibility and expansibility, and can be seamlessly connected with the existing DCS system.

The invention discloses a task execution method, electronic equipment, a storage medium and a program product, and relates to the technical field of artificial intelligence. According to the task execution method based on the model context protocol, agents integrated by a multi-agent system serve as resources and tools which can be called in a resource tool library of a model context protocol server, and then the task execution efficiency is improved through a communication layer constructed based on the model context protocol. Uniform exposure and dynamic calling of agent tool interfaces are realized, information islands among multiple agents are eliminated, and cross-agent resource scheduling and task collaboration are optimized, so that the technical problem of low efficiency of resource scheduling and task collaboration execution due to the fact that a multi-agent system cannot fully utilize the capability of each integrated agent is solved.