8172 results about "Remote control" patented technology

The invention relates to the technical field of management of the Internet of Things, and discloses a security control method and system for remote control of the Internet of Things, and the system comprises a security remote control platform, a zero-trust gateway, an authentication module, a security policy engine, edge proxy equipment and an encryption communication module. And the authentication module is used for performing identity authentication on the equipment and the user. The security policy engine dynamic access control table comprises access rule entries and associated signature information, and is issued to the edge proxy device through the zero-trust gateway. And the edge proxy device stores the dynamic access control table, verifies the signature information based on the platform public key, and performs matching and verification according to the access rule entry when receiving the control instruction. And the encryption communication module is used for performing encryption transmission on the access control table, the control instruction and the execution result. According to the invention, the whole process of remote control of the Internet of Things is dynamic, secure and credible, and the anti-attack capability and operation reliability of the system are effectively improved.

The embodiment of the invention relates to the technical field of artificial intelligence, and provides a linkage method and system of an apartment network and intelligent equipment, and the method comprises the steps: collecting network operation data and equipment operation data of a target apartment in real time; based on the equipment operation data, determining currently achievable candidate service scenes of the target apartment; fusing the network operation data and the equipment operation data into a joint operation map of the target apartment through the space-time diagram attention network; a multi-agent depth deterministic strategy gradient algorithm is adopted to carry out network resource allocation and equipment control decision making on the joint operation map, scene adaptive optimization is realized in combination with candidate service scenes, and a linkage strategy of a target apartment is obtained; and generating a decision instruction based on the linkage strategy, and adopting the decision instruction to realize remote control of the network equipment and the intelligent equipment. Through deep fusion of the space-time diagram attention network and multi-agent reinforcement learning, dynamic collaborative management and control of the network and equipment are realized, and the resource utilization rate and the service response speed are improved.

The invention relates to a remote-control system of a stratospheric airship and a control method thereof. The control system is divided to four levels: a decision-making level for executing the selection and switch of a remote-control flight mode according to the actual working state data, and sending a corresponding mode command; a planning level for dynamically planning and generating an airship motor drive command according to the mode command sent by the decision-making level; an executing level for realizing the drive control to an airship motor according to the motor drive command of the planning level; and a perceiving level for finishing the real-time monitoring and data collection of the airship working state, and providing the original data of the airship working state to the decision-making level. The four-level control system architecture design of the control system is capable of simplifying the control device, improving the control efficiency, and fundamentally solving the problems of the function, efficiency and reliability of the near space airship ground and airborne control system.

A pest control system is disclosed comprising an optical, computational, and monitoring subsystem, optionally mounted on a mobile platform. The optical system may include a neutralizing laser or multi-wavelength light source, discovery and detail cameras (optionally stereo), a beam-steering mechanism, tunable focus, and optional thermal or depth sensors. The processor, such as a GPU or FPGA, identifies insect or biological targets, adjusts laser focus by depth, and controls beam activation. A monitoring system verifies safety by detecting humans or other non-target entities using environmental and thermal cameras; if detected, laser firing is inhibited. The mobile platform may use wheels, propellers, tracks, or cables, with GPS and data links for remote control. A visible light pre-flash may induce a blink reflex before firing. In some embodiments, a scouting drone transmits target coordinates to the neutralization unit, enabling coordinated, efficient, and safe laser-based pest control.

The invention discloses an intelligent coordination control method and system for power plant equipment based on multi-source heterogeneous data, and belongs to the technical field of intelligent manufacturing and industrial automation, and the method comprises the steps: deploying a multi-mode sensor network in the power plant equipment, collecting the multi-source heterogeneous data in real time, and carrying out the real-time data preprocessing through an edge calculation node; carrying out collaborative modeling on the preprocessed data by adopting a hybrid analysis framework, predicting an equipment state trend, identifying a fault propagation path, positioning a root cause and optimizing a maintenance decision scheme; the equipment failure probability is evaluated through a fault diagnosis result, a grading early warning mechanism is triggered, and a rule base is updated and optimized in combination with a dynamic knowledge base; a three-dimensional model is constructed by using a digital twinning technology to carry out virtual simulation and remote control, and maintenance guidance is carried out through an augmented reality auxiliary technology. According to the method, efficient real-time monitoring and fault prediction are achieved, the fault diagnosis time and the operation and maintenance cost are remarkably reduced by combining the fault tree model and the digital twinning technology, and the equipment operation safety and reliability are improved.

The embodiment of the invention relates to the technical field of artificial intelligence, and provides an apartment security linkage method and system based on artificial intelligence, and the method comprises the steps: enabling initial security data obtained in real time to form a security space data set matched with an apartment space according to a space-time association relation; performing conjoint analysis on the security space data set by adopting a security intelligent decision engine to generate a corresponding linkage strategy; sending the corresponding control instruction and the security control parameter to the corresponding target security equipment based on the linkage strategy; the linkage priority of the security and protection equipment is set according to the security and protection event type and the mapping relation between the security and protection equipment and the security and protection event emergency degree, and a control array containing all levels of target security and protection equipment is constructed according to the linkage priority in combination with the current security and protection event type. The control array preferentially triggers the core target security and protection equipment to respond to the indication of the linkage strategy, so that remote control and linkage response of the security and protection equipment are realized, and the intelligent level and the emergency processing capability of apartment security and protection are improved.

The embodiment of the invention provides an excavator handle control system for remote operation, a handle control method based on a Hall sensor is adopted, non-contact rocker data sensing is achieved, the influence of contact and movement abrasion on the service life of a handle is reduced, and the excavator handle control system has the advantages of being high in sensitivity and good in performance; the handle mechanism is more flexible to operate, and the service life of the handle is prolonged; a two-hand cooperative control mode is adopted, and two three-degree-of-freedom handles are used for simulating the driving environment of a real excavator, so that a good remote control effect is achieved, and the feeling of presence of an operator in the remote operation process is improved; the operation habits of a driver are fully considered, the walking and working of the excavator are respectively controlled through combination of different degrees of freedom of the left hand handle and the right hand handle, an operating lever of the real excavator is simulated in the aspects of structure, motion degree of freedom and working range, and the man-machine interaction environment of excavator driving is restored.

The invention discloses a dexterous hand teleoperation method based on vision-touch fusion. The method comprises the following steps: 1) vision detection; the method comprises the following steps of (1) carrying out remote control, (2) carrying out redirection, (3) carrying out tactile grabbing, (4) carrying out vision-tactile interaction, (5) carrying out a communication process and (6) carrying out dexterous hand.The method can stably map human hand actions under the complex vision condition, safe and reliable grabbing control is achieved through tactile feedback, meanwhile, multiple dexterous hand configurations and cross-platform deployment are supported, and the precision, robustness and practicability of teleoperation can be improved.

The invention relates to the technical field of power system automation, discloses a remote operation and maintenance method, system and equipment for wide-area substation automation equipment, and aims to solve the problems of data islanding, inaccurate diagnosis, strategy stiffness, low safety cooperation efficiency and the like in remote operation and maintenance of the wide-area substation automation equipment. According to the method and the system, a comprehensive platform is constructed, and multi-source heterogeneous data acquisition, intelligent fusion analysis, fault diagnosis and prediction, adaptive strategy generation, security remote control and block chain evidence storage and collaborative operation and maintenance are integrated. The method can solve the problem of data islands, improve the diagnosis and prediction precision and timeliness, optimize the operation and maintenance strategy, prolong the service life of equipment, and enhance the remote operation and maintenance safety and cooperation efficiency.

A jack assembly that has a base member having a handle assembly extending therefrom, a remote control positioned in the handle assembly, a handle base section of the handle assembly that comprises a battery coupler and a control unit, an electric motor coupled to the base member and providing a torque to a gear assembly, the gear assembly coupled to a ball screw, a carriage slidably coupled to the base member, the carriage having a lift nut coupled thereto, the ball screw threaded through the lift nut such that rotation of the ball screw moves the lift nut, and carriage, linearly along the base member, and a lifting arm pivotally coupled to the carriage on one end and pivotally coupled to a pivot arm at an intermediate location.

The derrick type continuous oil pipe integrated sidetrack drilling operation device is provided with a base, a derrick, an injection head installation support, an injection head, a lifting oil cylinder, a hydraulic clamp and a remote operation room, one side of the derrick is fully opened, the derrick and the base are both of a lightweight rigid structure, and the injection head is installed at the top of the derrick for remote control. After the base is arranged at a wellhead and is unfolded and installed, one side of the base is connected with the lifting oil cylinder, the other side of the base is in butt joint with the ramp and the pipe rack, the derrick is rapidly erected through the lifting oil cylinder, and after the injection head is hoisted to the top of the derrick, the injection head is rapidly installed and subjected to alignment adjustment through the injection head installation support and the adjusting structure. Meanwhile, the tool rod and the elevator are arranged at the injection head, the tool rod is pulled and placed through the injection head, an oil pipe column and a sucker rod can be independently lifted or lowered, the oil pipe column and the sucker rod are pushed into a ramp from one side of an opening of a derrick, integrated sidetrack drilling operation of the coiled tubing is achieved, and sidetrack drilling efficiency and operation safety of the coiled tubing are remarkably improved.

The invention discloses an oxygenerator remote control system and method based on the Internet of Things, and belongs to the technical field of intelligent medical equipment and remote health management, and the method comprises the steps: S1, collecting multi-dimensional physiological data of a user in real time through a multi-source physiological signal collection module, a heart rate variability index and a body movement signal; s2, based on the multi-dimensional physiological data, processing is performed through a preset physiological state prediction model, and a unified physiological stress index is solved; s3, determining a predictive oxygen supply flow rate value in combination with the physiological stress index and a preset user basic oxygen supply flow rate; s4, according to the predictive oxygen supply flow velocity value, a control signal for a physical execution component of the oxygen generator is generated so as to dynamically adjust oxygen supply parameters, and conversion from passive compensation to active prediction is achieved.

The invention belongs to the technical field of wastewater treatment, and provides a wastewater treatment equipment remote control system based on the Internet of Things, which aims at solving the problems that the traditional fixed DO concentration control cannot adapt to water inlet load fluctuation, the effluent is easy to be substandard or the aeration energy consumption is high, the monitoring data noise is large, and the time sequence is misplaced. According to the scheme, a multi-dimensional real-time sensing network is constructed, flow, COD, BOD, ammonia nitrogen, water temperature, distributed DO and sludge activity sensors are deployed, discrete wavelet transform is adopted for noise reduction, and a data time sequence is aligned; a three-layer load-DO-energy consumption dynamic correlation model is designed, a basic layer predicts a load trend through LSTM, a middle layer quantifies a DO demand through a microbial metabolism model, and an optimization layer outputs an optimal DO set value through a PPO algorithm; and developing a dynamic decision-making system, adaptively generating a DO interval according to a load state, and adjusting fan parameters and number in a linkage manner. According to the invention, load dynamic adaptation is realized, effluent ammonia nitrogen is guaranteed to reach the standard, aeration energy consumption is reduced, and remote control precision and equipment operation efficiency are improved.

The invention discloses an abnormal behavior detection method and device, a nonvolatile storage medium and electronic equipment. The method comprises the following steps: acquiring user behavior data; behavior feature vectors are determined in the user behavior data, and the behavior feature vectors comprise at least one of a mouse behavior feature vector, a keyboard behavior feature vector, a process behavior feature vector and a window interaction feature vector; and analyzing the behavior feature vector by using a machine learning model to obtain an anomaly score output by the machine learning model, the anomaly score being used for representing the degree of deviation of the behavior feature vector from a preset normal behavior feature vector. According to the method and the device, the technical problem that the accuracy of distinguishing the normal user activity from the remote control Trojan abnormal operation is insufficient due to the fact that a related abnormal behavior detection method lacks a refined behavior modeling technology and a dynamic behavior analysis mechanism is solved.

The invention discloses a new energy charging pile remote control method considering a battery health state. The method comprises the following steps of obtaining battery full life cycle data, charging pile real-time working condition data and charging area power grid dynamic data, and performing preprocessing to generate battery health baseline data, pile body operation reference data and power grid dispatching reference data; extracting current health state parameters of the battery based on the health baseline data of the battery, calculating a charging adaptation coefficient in combination with the operation reference data of the pile body, analyzing the redundant capacity of the power grid, and constructing a charging control decision model; outputting an initial charging parameter combination based on the charging control decision model, performing health protection correction, and generating a basic remote control instruction; and issuing the basic remote control instruction to the target charging pile to calculate an instruction execution deviation degree, and performing dynamic iterative optimization to generate a new energy charging pile remote control scheme. According to the invention, collaborative optimization of safety and high efficiency of new energy vehicle charging and battery charging protection can be realized.

The invention relates to the technical field of industrial valve control, in particular to a floater control-based remote control and monitoring system for a quick-switching blind plate valve, which comprises a data acquisition unit, a cross-dimension data analysis unit and an instruction generation and feedback unit, and is characterized in that the data acquisition unit constructs a three-dimensional motion matrix through a floater trajectory tracking algorithm; an effective pressure fluctuation period is extracted in combination with a pressure-temperature coupling denoising algorithm, a cross-dimension data analysis unit extracts time-frequency fusion features by using a residual convolutional neural network, and dual verification of a fluid phase state is realized through a support vector machine and a dynamic time warping algorithm; and the instruction generation and feedback unit triggers a standard control strategy or a self-learning compensation mechanism according to the confidence coefficient, and corrects control deviation through a negative feedback optimization coefficient matrix, so that the problems of insufficient multi-source data fusion and poor complex working condition adaptability in the traditional technology are solved, accurate remote control and intelligent monitoring of the quick-switching blind plate valve are realized, and the working efficiency of the quick-switching blind plate valve is improved. And the leakage early warning success rate and the valve action reliability are improved.

The invention discloses a comprehensive management system for intelligent power distribution, and the system comprises a sensing layer which is provided with a plurality of sensors, the sensors are disposed on power distribution equipment, and are used for collecting the operation data of a power distribution system in real time, and the operation data comprise a current I, a voltage U, a power P, an equipment temperature T, a power factor cos phi, and an insulation resistance R; the transmission layer is used for transmitting the operation data to a data layer; the data layer is used for preprocessing the operation data to generate standardized data, and preprocessing comprises data cleaning and normalization conversion; and the application layer comprises a fault early warning module, a predictive maintenance module, an energy consumption analysis module and a remote control module, and the application layer realizes collaborative management by calling the standardized data. Multi-dimensional data fusion, a dynamic intelligent algorithm and a module interaction mechanism are introduced, and full-process intelligence of power distribution management is achieved.

The invention provides an intelligent gas pipe network valve remote control supervision Internet of Things system and method, and relates to the field of intelligent gas control. The method is realized based on the Internet of Things system, and comprises the following steps: obtaining pipe network information and performance parameters of a control assembly, and uploading the performance parameters to a government safety supervision management platform; obtaining a parameter confirmation instruction, determining layout parameters, and uploading the layout parameters to a government safety supervision management platform; a layout confirmation instruction is obtained, and layout parameters are sent to a gas maintenance object platform; after the layout is completed, the regulation and control compensation amount of the control assembly is determined based on the correction period and uploaded to a government safety supervision management platform; and a correction confirmation instruction is obtained, the control assembly is corrected based on the regulation and control compensation amount, the control assembly is controlled to regulate and control the coverage valve based on the regulation and control parameter set in the correction period, a regulation and control gas data pair is obtained, and the regulation and control compensation amount is determined. The arrangement position of the control assembly can be reasonably determined, and the regulation and control deviation is accurately evaluated to ensure the remote control effectiveness of the valve.

The invention provides a coal face mining auxiliary method based on visual and point cloud data fusion modeling, and the method comprises the steps: collecting the visual image data of a coal face, collecting the three-dimensional point cloud data through a point cloud sensor, and obtaining the motion state information through an inertial sensor; based on internal and external parameters and IMU data of joint calibration, mapping point cloud data to an image plane, establishing a geometric mapping relationship between three-dimensional points and pixels, generating an attribute point cloud model containing geometry, color and semantics, and generating a high-precision global three-dimensional digital twinning model; and identifying and tracking equipment instances in the digital twinborn model, and resolving motion parameters of key components based on a URDF kinematics model and a principal component analysis algorithm to support remote control decisions. According to the invention, high-precision real-time sensing and three-dimensional visualization of the working space size, the equipment connection relation and the movement position of the coal face can be realized, and the remote control precision and the response efficiency of unmanned mining are remarkably improved.

In an infusion pump system that includes a pump that may have a user interface for pump programming, one or more smartphones or other remote control devices that interface with the infusion pump, and / or an automated insulin delivery algorithm, there is a potential conflict between commands such as boluses being programmed on multiple devices and / or calculated by the AID algorithm at the same time. In order to avoid low glucose levels that could result from delivering multiple boluses from these various sources when only one bolus is needed, systems and methods disclosed herein provide a bolus permissions and prioritization scheme that prioritizes boluses programmed with the infusion pump and one or more remote control devices and calculated by a closed loop delivery algorithm.

The invention discloses a video stream defogging method and system for 5G remote control, and relates to the technical field of image enhancement. The method comprises the following steps: acquiring a foggy video in real time; inputting the single-frame foggy video into a pre-trained monocular depth estimation neural network, and reasoning to obtain a depth map with the same size as the input single-frame foggy video; performing close-shot and long-shot region division on the scene of the current foggy video frame according to the depth map to obtain a region mask with the same size as the depth map; based on the region mask and the foggy video, calculating to obtain an atmospheric light parameter; calculating the transmissivity of each pixel according to the distance estimation result of each pixel in the depth map, and obtaining a transmissivity map with the same size as the depth map; based on the depth map, the atmospheric light parameters and the transmissivity map, adaptive calculation is performed on the foggy video to realize defogging, and a defogged clear video frame is obtained; the method can adapt to different depth-of-field fog effects, realizes different depth-of-field defogging, and outputs clear video frames.

The invention provides a tire crane automatic control system and method based on embedded edge calculation, and relates to the technical field of port automation, the tire crane automatic control system comprises a sensing and detecting layer used for collecting motion states and operation environment information of a cart, a trolley and a lifting appliance of a tire crane in real time; the core control layer is used for processing sensor data in real time and generating a control instruction; the action execution layer comprises a PLC gateway, a main control PLC and a driving motor, the PLC gateway communicates with the core control layer and is used for receiving a control instruction, and the main control PLC drives the motor to execute corresponding actions of a cart, a trolley and a lifting appliance; and the task management layer comprises an intelligent remote control console, is in communication connection with the core control layer, and is used for issuing the operation task instruction to the core control layer and receiving the system state data from the core control layer. Unmanned operation of the tire crane can be achieved, and a complete technical base is provided for port automation.

The invention relates to the technical field of power distribution equipment, and discloses a centralized station terminal which comprises a main control module, an FPGA module, a remote control bus driving circuit, a remote signaling bus driving circuit, a plurality of remote control expansion circuits, a plurality of remote signaling expansion circuits and a plurality of telemetering expansion circuits. Wherein the main control module is provided with a PCIe interface, the FPGA module is connected with the main control module through a PCIe bus, and the remote control bus driving circuit and the remote signaling bus driving circuit are both electrically connected with the FPGA module. And the plurality of remote control expansion circuits are electrically connected with the remote control bus driving circuit and are used for outputting remote control signals. And the plurality of remote signaling expansion circuits are electrically connected with the remote signaling bus driving circuit and are used for receiving the remote signaling signals. And the plurality of telemetering expansion circuits are directly and electrically connected with the FPGA module and are used for receiving telemetering signals. According to the centralized station terminal, the FPGA module can process the telemetering signals received by the multiple telemetering expansion circuits in parallel, and transmits the collected data to the main control module through the PCIe bus at a high speed, so that the equipment data collection efficiency is improved.

The invention discloses a power distribution room remote control inspection and intelligent early warning method based on the Internet of Things, and the method comprises the following steps: arranging multiple types of sensors in a power distribution room to collect environment and equipment data, carrying out the synchronization, filtering and normalization of an edge calculation unit, extracting features through a lightweight artificial intelligence model, and detecting the abnormality; the method comprises the following steps of: uploading to a cloud end through a 4G and LoRa dual-mode network, performing time sequence prediction in a long-short-term memory network containing physical constraint gating, and calculating the fault risk of each monitoring point in combination with a Beta-Bernoulli priori sparse learning dynamic optimization model structure to generate a multi-stage early warning and control instruction so as to realize cloud-side collaborative intelligent inspection and remote control. According to the invention, through fusion of edge lightweight intelligent analysis, cloud physical constraint gating and Bayesian sparse learning, real-time sensing, time sequence prediction and multi-level intelligent early warning control of the operation state of the power distribution room are realized.

The invention discloses a portable underwater vehicle throwing device which comprises a control device and further comprises a hoisting assembly (1), and the upper portion of the hoisting assembly (1) is used for being connected with a marine crane (9) for use; the lifting assembly (2) is detachably installed in the middle of the lower portion of the hoisting assembly (1), and the lower portion of the lifting assembly (2) is connected with an underwater navigation body (7) for use; the supporting assemblies (3) are symmetrically connected to the two sides of the lower portion of the hoisting assembly (1); the two ends of the upper portion of the supporting frame (4) are detachably connected with the lower portions of the corresponding supporting assemblies (3) through adapters (5) respectively; wherein the hoisting assembly (1) is wirelessly connected with the control equipment. The system is easy to operate, stable and reliable, pre-tightening constraint of the underwater vehicle can be stable and controllable in the using and releasing process, and the releasing function of the underwater vehicle can be conveniently and rapidly completed by controlling the middle remote control cordless detacher.

The embodiment of the invention provides an unmanned aerial vehicle remote safety control method and system, and the method comprises the steps: obtaining a control instruction inputted by a user on a management platform; performing encryption processing on the control instruction to obtain encrypted control data; and transmitting the encrypted control data to the unmanned aerial vehicle and / or the unmanned aerial vehicle airport accessed to the target network, so that the unmanned aerial vehicle and / or the unmanned aerial vehicle airport decrypts the encrypted control data to obtain a control instruction, and executing a remote control operation according to the control instruction. According to the embodiment of the invention, a data encryption and decryption processing mechanism is introduced in the transmission link of the control instruction, so that the integrity and consistency of the content can be kept when the control instruction is transmitted in various network environments, and the risk that the control instruction is tampered, intercepted or misunderstood due to the difference of intermediate links is reduced. Decryption and execution of the control instruction are completed by the unmanned aerial vehicle and / or the unmanned aerial vehicle airport in a unified mode, intermediate forwarding processing logic is simplified, and clearness and controllability of a control link are enhanced.

The invention provides a cross-platform fusion access method, system and device of equipment and electronic equipment, the method is applied to the technical field of Internet of Things, and the method comprises the following steps: a mobile terminal performs security authentication on target central control equipment; the mobile terminal sends a structured configuration file including the equipment information of the plurality of smart home equipment, the region division rule, the scene mode and the linkage rule to the target central control equipment; the target central control equipment receives and analyzes the structured configuration file, and updates the corresponding smart home equipment according to an analysis result; the target central control equipment receives a control instruction of the cloud platform, converts the control instruction into an internal protocol instruction and then issues the internal protocol instruction so as to control the corresponding smart home equipment to execute operation; the target central control device synchronizes the state information of the smart home device to the cloud platform; and when an upgrading instruction of the cloud platform is received, issuing an upgrading task to execute an upgrading process. According to the method, the real-time performance of remote control of the smart home equipment and the accuracy of state feedback are guaranteed.

The invention discloses a remote-controlled power transmission line inspection device which comprises a tower, the upper end of the tower is fixedly connected with a connecting rod, the top of the connecting rod is fixedly connected with an insulator, the top of the insulator is provided with a power transmission cable, the outer surface of the connecting rod is fixedly connected with a fixed base, and the top of the power transmission cable is slidably provided with an inspection device. According to the scheme, multi-section inspection is achieved, the problem that long-distance inspection cannot be achieved due to long-distance flight of an unmanned aerial vehicle and insufficient power is solved, meanwhile, a background can independently select one section of a power transmission cable for inspection, and the inspection efficiency is improved. Operation and management of the inspector are facilitated, active inspection is achieved, the location and position of a fault are found in the first time, the inspector can conveniently repair the fault in time, loss expansion is avoided, the position of the fault and hidden danger is rapidly found, and the inspection and maintenance efficiency is improved.

The invention discloses an intelligent remote control system for bridge dehumidification, and the system comprises a physical environment layer, a sensing and execution layer, and a data communication and local control layer. The perception and execution layer comprises a perception layer and an execution layer, the perception layer comprises a plurality of sensors, the execution layer comprises a plurality of execution devices, and the plurality of sensors and the plurality of execution devices are arranged in the physical environment layer; the data communication and local control layer comprises a main controller, and the sensing layer and the execution layer are respectively connected with the main controller; the sensors collect environment parameter information in the physical environment layer and send the environment parameter information to the master controller, the master controller determines equipment operation information based on the environment parameter information and sends the equipment operation information to the execution equipment, and the execution equipment executes equipment operation based on the equipment operation information. And the environment parameter information of the physical environment layer is changed. The precision and efficiency of environment control can be improved, and the stability of the environment is guaranteed.

The invention discloses a bullet train section / bullet train station remote shunting system and method, and belongs to the technical field of high-speed railway train operation control. By additionally arranging a ground remote control server, a remote console, a vehicle-mounted remote control unit, a dormancy awakening unit, an environment sensing unit and other devices and combining an ATP / ATO system and a 5G communication technology, the functions of automatic dormancy awakening, remote driving and unmanned shunting of the motor train unit in a motor train section / a motor train station are achieved. The problems that traditional manual shunting is high in labor intensity, low in efficiency and multiple in potential safety hazards are solved.