372 results about "Real time data transmission" patented technology

The embodiment of the invention provides an industrial real-time data transmission guarantee method and system based on a TSN. The method is applied to the field of industrial communication and intelligent scheduling, and comprises the steps of obtaining industrial field network node information, completing TSN topology deployment and time synchronization, extracting communication characteristics and historical load data of various task flows, constructing a unified time sequence, and inputting a prediction model to generate a load prediction result. And in combination with task parameters, a scheduling strategy list and a prediction result, inputting a TSN digital twin network model to carry out analogue simulation, evaluating performance indexes under multiple strategies, selecting an optimal scheduling strategy and issuing the optimal scheduling strategy to TSN switching equipment, thereby realizing accurate scheduling control configuration of various task flows. According to the scheme, intelligent evaluation and automatic optimization issuing of the scheduling strategy are realized, the real-time performance and the deterministic communication capability of an industrial network are remarkably improved, the resource utilization efficiency and the adaptability of the scheduling decision are enhanced, and the key task flow is ensured to be reliably transmitted on time.

Disclosed is a digital twin-based deduction and optimization method and system for an intelligent reflecting surface (IRS) communication system, including: collecting data from a scenario, including relevant data of an IRS physical model and real channel data; performing real-time data transmission on the collected data; establishing a digital twin three-dimensional (3D) model in a digital twin space based on the data after the real-time data transmission; establishing an IRS reflection mechanism model before fusing with the digital twin 3D model, the generalized Snell Equation being used to simplify a complex system in the IRS reflection mechanism model; deducing and optimizing the IRS communication system to obtain an optimization strategy; and feeding the optimization strategy back to the real world to realize the deduction and optimization of the IRS communication system.

The invention relates to the technical field of offshore data monitoring, and discloses an offshore data monitoring method based on a wireless communication system, and the method comprises the following steps: S1, data collection: obtaining offshore monitoring data of a target; s2, data preprocessing: performing format conversion, duplicate removal, time alignment and data interpolation processing on the data acquired by the data acquisition; s3, data fusion: matching and fusing the processed data based on a time interleaving algorithm and a spatial clustering algorithm; s4, performing target tracking, and performing target trajectory prediction by adopting a Kalman filtering method under the condition of target data missing; and S5, monitoring output, generating a fusion data set, and outputting dynamic information of the target. Through combination of deep learning target identification, LSTM network state prediction and an efficient wireless communication technology, more accurate marine target monitoring, stable real-time data transmission and efficient target state tracking are realized.

The invention relates to the technical field of power system management, in particular to a Beidou-based power grid emergency wireless communication monitoring system, which comprises a Beidou No.3 communication subsystem for realizing power business data encryption transmission, positioning and long message processing through a Beidou data transmission terminal and a handheld terminal; the short-wave communication subsystem establishes a communication link by using an autonomous frequency selection technology when no public network coverage exists; the Tiantong satellite communication subsystem provides voice and real-time data transmission service by means of a Tiantong satellite terminal; the converged communication control module dynamically switches communication links according to the channel quality, the service priority and the energy consumption index; the protocol conversion module realizes mutual conversion between electric power meter reading and a Beidou protocol; and the unmanned aerial vehicle relay extension module constructs an air relay link with the ground relay base station through the unmanned aerial vehicle group to extend Beidou signal coverage. According to the invention, efficient, reliable and wide power grid emergency communication is realized, and remarkable creativity and practicability are achieved.

The invention provides a reflux valve supporting remote monitoring of the Internet of Things. The reflux valve comprises a valve body provided with a fluid inlet, a fluid outlet and an internal flow channel, and an electric actuating mechanism is configured for controlling the opening degree of the valve; a microprocessor and a memory are arranged in the control unit, and the control unit processes data of the sensor, calculates a fluid density correction coefficient and a pressure correction coefficient, corrects original flow data collected by the flow sensor and generates an actual flow value; the control unit further identifies the current fluid type and adaptively adjusts the countercurrent detection threshold value of the upstream and downstream pressure difference based on the relationship between the flow and the pressure data; when the pressure difference exceeds the adjusted threshold value, the electric executing mechanism executes emergency turn-off operation; meanwhile, a wireless communication unit is arranged, real-time data transmission is supported, control parameters issued by external monitoring equipment are received, and intelligent control and remote management are achieved; the intelligence and the operation efficiency of the reflux valve can be effectively improved, and the reflux valve is suitable for safety protection and operation optimization under the complex fluid working condition.

The invention discloses an unmanned ship control system based on a digital twin and deep learning technology in the technical field, and the system comprises a perception information fusion module which collects real-time data in real time, and transmits the real-time data to a digital twin module; the digital twin module predicts the change of the marine environment in a period of time in the future through the real-time data collected by the perception information fusion module, and the prediction result provides a basis for subsequent path planning and navigation control; the deep learning module is used for extracting a feature recognition result in the marine environment, and the feature recognition result is used for optimizing path planning and navigation control of the unmanned ship; and the controller execution module is used for receiving a prediction result from the digital twin module and a feature recognition result from the deep learning module, realizing accurate control of a main engine, a steering engine and a load of the unmanned ship, and realizing high-precision and self-adaptive control of the unmanned ship by simulating and predicting a marine environment in real time. And the adaptability and robustness of the unmanned ship in a complex environment are improved.

The invention discloses a fresh flower selling management system and method based on a block chain technology, and relates to the technical field of fresh flower management. A data acquisition module acquires real-time data of a fresh flower planting link and a logistics transportation link, transmits the real-time data to a block chain storage module, and binds an identifier of a fresh flower; the block chain storage module is used for storing the fresh flower information and storing the data of the full life cycle of the fresh flowers in a distributed account book; the user access module is used for checking a display legend of the fresh flower and related information of the fresh flower at a user side, and the intelligent contract module is used for generating order information and carrying out payment settlement and automatic account division; the inspection module is used for inspecting flower quality and flower information; and the abnormity monitoring and feedback module is used for timely recording and sending notifications when abnormity is found in the planting, transportation or sales process, and quickly positioning problem nodes. According to the method, the transparency of the whole flow of fresh flower planting and transportation is improved, the data security and credibility are ensured, and rapid traceability is realized.

The invention discloses an intelligent logistics system based on optimal scheduling, and relates to the field of logistics management, and the system comprises the steps: arranging environment sensors at key nodes of a logistics network, and transmitting collected real-time data to edge computing equipment for preprocessing; analyzing the preprocessed data by using a deep learning model, and predicting an environment change trend in a non-period of time; dynamically adjusting a logistics scheduling strategy based on the prediction result; after receiving the adjusted scheduling strategy, defining a state space, an action space and a reward function of the logistics system; training a reinforcement learning algorithm model, and continuously optimizing a decision strategy through interaction with the environment; and calling the reinforcement learning model through an API interface to make a real-time decision, and generating an optimal scheduling scheme. According to the invention, by integrating environment perception, deep learning prediction, adaptive scheduling and reinforcement learning, the defects of an existing intelligent logistics system in the aspects of environment perception, prediction and dynamic scheduling optimization are overcome, and the intelligent level and operation efficiency of logistics management are significantly improved.

The invention belongs to the technical field of artificial intelligence, and particularly relates to an unmanned aerial vehicle cluster collaborative search and rescue algorithm based on reinforcement learning and a virtual simulation verification method, which are used for planning unmanned aerial vehicle cluster collaborative search and rescue tasks by combining the requirements of unmanned aerial vehicle cluster search and rescue and adopting an algorithm based on deep reinforcement learning. A virtual simulation verification platform is developed by utilizing Unity, a real unmanned aerial vehicle cluster model and a complex environment are established, and a real-time data transmission function with a reinforcement learning algorithm end is realized, so that the actual execution effect and effectiveness of the designed collaborative search rescue algorithm are verified.

The invention discloses an automatic protocol matching system for intelligent gateway sensor equipment of a power distribution station house. The automatic protocol matching system comprises a protocol feature deep analysis unit, a graph convolutional neural network topology construction unit, an equipment protocol suitability evaluation unit, a real-time data transmission monitoring unit, an abnormal protocol correction unit and a protocol matching result output unit. The system analyzes sensor protocol characteristics, combines power station house sensor deployment and transmission path construction graph models, evaluates protocol suitability, monitors transmission data, corrects abnormal protocols, and finally outputs a matching scheme. The graph convolutional neural network and the power station room data transmission detection model are utilized to realize automatic protocol matching, improve the fit degree of adaptation and an actual scene, form an exception handling closed loop, reduce interaction failures, improve the data transmission efficiency and stability of the power distribution station room, and meet the requirement of intelligent reconstruction.

The invention relates to the technical field of communication control, and discloses a communication control method and system based on a dual-mode communication module, the system integrates two communication modes of 4G and 5G, and flexible and reliable real-time data transmission is realized. The core is that a communication quality evaluation module is introduced, and 4G and 5G communication quality is scored by analyzing data such as signal strength, data transmission rate and packet loss rate. The system constructs a fault prediction module, and predicts the type and probability of future communication faults by using historical communication quality scores and equipment operation state data. And the maintenance early warning module carries out early warning on the maintenance demand of the communication equipment in combination with the evaluation and prediction results. And the maintenance scheme generation module automatically generates a maintenance scheme according to the early warning result, triggers an emergency notification when the maintenance demand is high and provides detailed steps. According to the invention, the stability and reliability of communication service are improved, and the maintenance process of communication equipment is optimized.

The invention relates to the technical field of ultra-far offshore data transmission, and discloses an ultra-far offshore distance real-time data stable transmission method and system. The method comprises the following steps: acquiring target transmission link data, and extracting dynamic fluctuation characteristics containing signal strength distribution information and a delay jitter relationship from the target transmission link data; calling the trained channel estimation network to carry out signal positioning processing on transmission link data, and generating a signal transmission path set containing a channel type identifier and phase code mapping relation; based on the set, calling a waveform analysis network to perform multi-modal feature fusion on the signal intensity distribution information to obtain a fusion result containing time-frequency domain features and modulation mode features; and inputting a fusion result into a transmission strategy model to perform dynamic path selection, and outputting a real-time data transmission element containing a control instruction generated based on a signal transmission sequence and a phase self-calibration parameter. According to the method, stable transmission of real-time data under the ultra-far offshore distance can be realized.

The invention belongs to the technical field of cooperative control, and particularly relates to a development experiment box multi-device cooperative control method based on an open-source gap system. According to the method, access, identity authentication, automatic discovery and dynamic connection of experimental box equipment are realized through a distributed equipment management platform of an open-source Gao Mongolia system; a uniform resource scheduling mechanism is utilized to complete resource information collection, strategy matching and dynamic allocation; task allocation is carried out by adopting an intelligent task scheduling algorithm and combining equipment states and task requirements; real-time data transmission between devices is realized by means of a low-delay communication protocol; and finally, automatically summarizing and analyzing experimental data and generating a report. According to the method, the problems of low equipment identification efficiency, low resource utilization rate, low task allocation efficiency and the like in the existing development experiment box are solved, the intelligent level and the system stability of equipment cooperative control are improved, and the method is suitable for a multi-equipment cooperative control scene of the development experiment box.

The present invention is a wireless vehicle tank monitoring system using non-contact fluid level sensors with adjustable sensitivity to measure fluid levels in recreational vehicle holding tanks. A smart device application on a portable computer receives real-time data via Bluetooth Low Energy (BLE) communication. The user-friendly interface displays graphical tank states. The system optimizes power efficiency through deep sleep and selective notification techniques, extending battery life. Sensors' sensitivity adapts to different tank wall thicknesses for accurate readings. The integration of non-contact sensors and power-efficient communication ensures reliability, easy installation, and real-time data transmission. This cost-effective solution effectively manages fluid levels in recreational vehicles.

The invention provides a cross-system cooperative control method and system based on a digital thread, and the method comprises the steps: building a cross-system interaction architecture, and building real-time data transmission and instruction interaction among a plurality of business systems through a distributed node communication protocol; collecting dynamic operation characteristic data of each service system based on the cross-system interaction architecture, and generating a cross-system cooperative control logic; converting the cross-system cooperative control logic into a standardized control instruction, distributing the standardized control instruction to a corresponding service system, executing real-time cooperative control, and collecting state feedback characteristics in a control process; performing dynamic deviation analysis on the state feedback characteristics to generate cooperative control strategy adjustment parameters; and synchronizing the cooperative control strategy adjustment parameter to each service system through the cross-system interaction architecture. According to the invention, the efficiency of cross-system cooperative control is improved.

The invention discloses a UHPC jet 3D printing device based on an unmanned aerial vehicle. The UHPC jet 3D printing device comprises the unmanned aerial vehicle. A flight control device is arranged on the unmanned aerial vehicle and used for adjusting the flight attitude and direction in real time; a real-time data transmission device is arranged on the unmanned aerial vehicle and used for transmitting data in the flight process and monitoring result data back to the ground control center in real time; a 3D printing UHPC device is arranged below the unmanned aerial vehicle and comprises a UHPC spraying device, one end of the UHPC spraying device is connected with a high-precision spraying printing head, and the other end of the UHPC spraying device is connected with a UHPC pumping connecting device through a spraying flow device and a power transmission device. The power transmission device controls the jetting speed and the jetting angle through a jetting speed adjusting device and a jetting angle control device. The flexibility of the unmanned aerial vehicle and the jet printing technology are combined, and UHPC construction under the high-altitude, complex or dangerous environment is achieved.

The invention belongs to the technical field of agricultural robots, and discloses a visual perception digital twinborn cotton weeding robot identification obstacle avoidance method, which comprises the following specific steps: step 1, establishing a digital cotton and weed database, cotton field image information and cotton field environment information of real scenes in the same area under the condition of changing illumination in different time periods of the whole day are collected through a data collection system, and timestamps during collection and collected real-time data are transmitted to a cloud server. Through mutual cooperation of the data acquisition system, the cloud server and the virtual simulation platform, a cotton and weed virtual scene is established, through simulation of a cotton field and a weeding robot on the simulation platform, time-varying digital scene construction is perfected, and the time-varying digital scene construction efficiency is improved. The problem that an existing digital scene is not perfect in reduction of the time-varying process of the influence of illumination on the cotton field in the real environment is solved, and therefore the consistency of the virtual scene and the real environment and the weeding accuracy are further improved.

The invention belongs to the field of hydraulic machinery state monitoring, and particularly discloses a digital twinning-based pumped storage unit shafting operation state monitoring method and system, and the method comprises the steps: building a multi-physics field coupling finite element full-order model of a pumped storage unit shafting, carrying out the model reduction of the finite element full-order model, and obtaining a digital twinning model; utilizing a multi-physics field coupling reduced-order model to construct a digital twinborn body of the pumping and storage unit shafting for real-time simulation; acquiring operation state data corresponding to the monitoring signal, and establishing an operation state knowledge base of the pumped storage unit; and according to the established virtual-real interaction subsystem, the three-dimensional visualization subsystem and the operation state knowledge base, constructing an operation state monitoring system of the pumping and storage unit shaft system, and performing real-time data transmission of the operation state monitoring system by using a sensor so as to evaluate the operation state of the pumping and storage unit in real time and realize operation state early warning of the pumping and storage unit. According to the invention, the real-time performance of monitoring the operation state of the shaft system of the pumping and storage unit can be improved, and the monitoring efficiency is further improved.

The invention relates to the technical field of crop growth monitoring, in particular to a method and system for monitoring crop growth through images, and the method comprises the following steps: deploying an unmanned aerial vehicle, flying over a target paddy field, collecting image data, transmitting the image data to a ground station in real time through data transmission, and generating a preliminary image data set; and cutting and correcting the initial image data set. According to the invention, the unmanned aerial vehicle is used for image acquisition, the problem that the visual angle of a fixed ground camera is limited is avoided, and the data hysteresis is reduced through real-time data transmission, so that the monitoring is more timely. In the image data cutting and correcting process, angle deviation and background noise are eliminated, and the leaf area index calculation accuracy is improved. Through introduction of time sequence analysis, dynamic monitoring of crop growth trend is realized, growth evaluation is no longer limited to a single time point, historical data comparison is formed, and the prediction capability of the growth state is improved.

Disclosed are a maize on-demand fertilization control system and a soil nitrogen soft measurement method. Sensors transmit real-time data to a control unit, which calculates soil nitrogen content using an optimized BP neural network model. Based on maize's nitrogen demand, the system adjusts fertilization amounts using solenoid valves, achieving precise, cost-effective fertilization.

A medical monitoring system comprises a wearable garment incorporating multiple physiological sensors for real-time patient monitoring. The garment integrates an embedded processing unit that receives sensor data and transmits it wirelessly to a base station or remote server. A multi-modal physiological signal processing unit analyses the data to generate composite physiological indices, including metabolic rate, work of breathing, and fall risk assessments. The garment includes optional monitoring features such as transcutaneous carbon dioxide measurement, electrocardiography, pulse oximetry, blood pressure monitoring, and accelerometer - gyroscope-based motion tracking. The system provides early-warning alerts for clinical deterioration, enabling proactive therapeutic interventions. A wireless communication module ensures real-time data transmission, supporting remote monitoring and integration with hospital networks. The garment's modular design allows for non-invasive physiological assessment while maintaining patient mobility, making it suitable for critical care, ambulatory monitoring, and telemedicine applications.

The invention discloses a smart home safety monitoring system and method based on multi-modal sensing and intelligent analysis. The system comprises a multi-modal sensing module, an intelligent analysis module, a communication module, a cloud server, a user terminal and a smart home central control screen module. According to the invention, through multi-mode sensing fusion and intelligent analysis technologies, all-around and multi-level sensing of an intelligent home environment can be realized, compared with a traditional single-sensor monitoring system, various security events can be detected and identified more accurately, the reliability and the security of the system are improved, the identity and behavior actions of personnel can be judged accurately, and the safety of the personnel is improved. The multi-mode sensing module, the intelligent analysis module and the cloud server are integrated, abnormal behaviors are recognized, early warning is given out in time, potential risks are reduced, in addition, real-time data transmission among the multi-mode sensing module, the intelligent analysis module and the cloud server is achieved by adopting multiple wireless communication protocols, and safety and privacy of data transmission are guaranteed in the transmission process in combination with the data encryption unit.

The invention discloses a large-scale low-orbit satellite network domain-division intelligent routing method, which belongs to the technical field of satellite communication, and comprises the following steps: constructing a network model based on multi-dimensional resource characteristics, and providing resource constraint conditions and space-time correlation characteristics for routing decision by combining with a regional flow prediction algorithm of an improved Transform architecture; virtual nodes and an autonomous domain are divided based on a geographic area, and a low-orbit satellite network routing process is decoupled into an intra-domain part and an inter-domain part; a multi-agent deep Q network is adopted in a domain, a sum tree mechanism-based deep Q network is adopted between domains, a routing algorithm and a resource scheduling algorithm are respectively designed, and a domain intelligent routing system with flexibility and expandability is constructed through hierarchical routing and resource decoupling scheduling. According to the method, the service capability of the low earth orbit satellite network in extreme scenes such as topology high-frequency change, strict resource limitation and traffic space-time mutation is remarkably enhanced, and a high-reliability and low-delay routing solution is provided for space-ground integrated communication, emergency disaster early warning and global real-time data transmission.

The invention discloses a dysarthria speech evaluation system based on acoustic analysis. The dysarthria speech evaluation system comprises a speech evaluation module, a system management module and a cloud management platform, the speech evaluation module is used for performing vowel composition evaluation, voice evaluation, definition evaluation and composition motion evaluation on the user; the system management module is used for carrying out login authentication management, authority management, data management and evaluation record management on a user, and maintaining the safety of system operation and the integrity of data; and the cloud management platform is used for performing real-time data transmission and data analysis on the speech evaluation module and the system management module to complete dysarthria speech evaluation. According to the invention, objectivity and standard consistency of dysarthria assessment are improved.

The disclosure provides a method for remotely diagnosing faults in a powertrain of an electric vehicle. The method can comprise collecting real-time data from the powertrain of the electric vehicle; transmitting the real-time data to a cloud platform; ranking a feature importance on the real-time data using a random forest model; optimizing hyperparameters of the random forest model using a simulated annealing algorithm; deploying the optimized random forest model on the cloud platform for real-time fault classification and diagnosis; and using the cloud platform to provide real-time fault alerts and diagnostic reports for the powertrain of the electric vehicle.

The invention discloses a land-based virtual-real symbiosis experiment system for traveling cable swing, which comprises a land-based cable experiment table carrying a driving and loading module, and a mapping module for collecting real parameters of a traveling cable based on the driving and loading module to establish a mechanical model, the driving and loading module comprises driving equipment arranged on the land-based cable experiment table, the mapping module defines boundary conditions of the mapping module in a fixing mode of the land-based cable experiment table, and the boundary conditions serve as constraints of a dynamic model in the mapping module. By establishing real-time data transmission between the physical experiment table and the digital twin model, the problem of mapping lag is solved on the basis of real parameters collected by the driving and loading module, a simulation result can be fed back to the physical experiment table, parameter adjustment is guided, a digital research platform is provided for trailing cable reliability research in a land-based environment, and the reliability of a trailing cable is improved. And an effective guarantee is provided for ensuring absolute safety of cable running.

The invention discloses a power distribution network fault maintenance VR scene processing method and training system in the technical field of electric power, and the method comprises the following steps: collecting the fault types of a previous power distribution network, building a power distribution network fault database, and carrying out the training classification; establishing a power distribution network fault simulation unit, and performing power distribution network fault scene simulation according to the data of the power distribution network fault data; the VR device generates a corresponding virtual training scene, and the student wears the VR device to prepare for training; real-time data transmission is carried out during VR equipment operation, and student operation data is compared with internal data of a power distribution network fault database. Through the virtual training scene generated by the VR equipment, the real-time data transmission during the operation of the VR equipment and the comparison with the internal data of the power distribution network fault database, operation feedback can be provided for students in time, the students are helped to rapidly improve the fault maintenance skills, and errors and mistakes in actual work are reduced.

The invention discloses an SCADA data display method and system for an oil and gas pipe network, and relates to the technical field of SCADA data processing, and the method comprises the steps: generating a first display picture for a user based on SCADA data from each service node and stored in a cache node when a display instruction is received; selecting at least one target service node interested by the user from the service nodes; generating a second display picture for the user based on the stored SCADA data acquired from the target service node, and transmitting the acquired real-time SCADA data to the cache node; and generating a third display picture for the user based on the real-time SCADA data. According to the scheme, after the SCADA data is detected to be collected by each service node, the SCADA data is not completely transmitted to the storage node at the first time, but the data stored in the service node is called to be displayed when the display requirement of a user on the SCADA data of a certain service node is detected.

The invention discloses an automatic driving virtual simulation test platform and a test method thereof, and relates to the technical field of virtual simulation driving, and the test platform comprises a virtual simulation module which is used for constructing a high-precision three-dimensional virtual scene and simulating sensor data; the automatic driving trolley is used for executing an automatic driving algorithm in a physical environment and collecting real sensor data; the road simulation system is used for simulating various road working conditions and forming a data closed loop with the virtual simulation module and the desktop-level automatic driving trolley; and the data interaction module is used for realizing real-time data transmission and synchronization among the virtual simulation module, the desktop-level automatic driving trolley and the road simulation system. According to the invention, by integrating a virtual high-fidelity scene library, a real sensor, trolley hardware and a flexibly adjustable rotating hub testing device, multi-level closed-loop verification from simulation to a real vehicle can be realized, and meanwhile, acquisition and playback of sensor data and multi-modal data fusion in a real environment are supported.

A system and method for placing and configuring physical security sensors & barriers, are described. The system generates and analyzes a three-dimensional model of a customer's premises using non-imaging sensors to determine optimal sensor placement. Based on customer requirements, the system distributes sensor models within the premises while accounting for environmental obstructions, coverage gaps, and redundancy minimization. An extended reality (XR) interface allows users to visualize and refine sensor configurations before deployment. The system integrates AI-driven analytics to optimize surveillance coverage, adjust sensor orientations dynamically, and generate detailed reports outlining sensor locations and configurations. The sensor stand transmits real-time data to the system for continuous monitoring, predictive maintenance, and security threat analysis. The system enhances security planning by reducing design time, installation costs, preventing post-deployment modifications, and ensuring comprehensive monitoring coverage across diverse environments, including commercial, industrial, and critical infrastructure sites.