116results about How to "Improve collaboration" patented technology

The invention provides a privacy protection method and system based on big data security and privacy calculation, and relates to the technical field of data processing, and the method comprises the steps: obtaining original data feature extraction, obtaining data features, selecting a data desensitization algorithm to carry out data desensitization, carrying out encryption processing through a hybrid fully homomorphic encryption algorithm, and carrying out encryption processing through a hybrid fully homomorphic encryption algorithm. Homomorphic encrypted ciphertext data is generated and sent to the privacy protection computing platform; a data preprocessing protocol for privacy protection is constructed, data filtering and data dimension compression are carried out, multi-party security calculation is executed, a ciphertext calculation result is generated and returned to a data provider, verification is carried out, and if verification passes, decryption and filtering are carried out through a decryption algorithm to obtain a pure plaintext calculation analysis result; and constructing a reverse data desensitization model for reduction to obtain an analysis calculation result, constructing a dual-target optimization model for solving, obtaining an optimal balance point and generating an optimal decision result, desensitizing, uploading to a privacy protection block chain network, and performing distributed credible storage and sharing.

The invention discloses a multi-underwater-robot cooperative control system and method based on predictive control, and relates to the technical field of cooperative control. During operation of the system, underwater environment data are collected through sensor equipment, an underwater three-dimensional dynamic environment model is generated by using a data fusion technology, and the underwater three-dimensional dynamic environment model is established based on task requirements; tasks are decomposed and distributed to all the robots, through an optimization algorithm, optimal paths of the robots and the mechanical arms are planned, the motion trails of the underwater robot mechanical arms are dynamically optimized based on model predictive control MPC, a real-time control strategy is provided for task division among the multiple mechanical arms, and the real-time control strategy of the underwater robot mechanical arms is provided based on environment modeling and the real-time state. Future motion states of the robot and the mechanical arm of the robot are predicted, an optimization objective function including task completion time, energy consumption and mechanical arm operation precision is constructed, a rolling optimization method is utilized, a control instruction is updated in real time, and real-time data sharing among multiple underwater robots is supported based on an acoustic communication technology.

The invention discloses a power distribution network visual management and control method and device, a storage medium and a product, and the method comprises the steps: obtaining the multi-dimensional information of a power distribution network in a target region, carrying out the preprocessing of the multi-dimensional information, obtaining a standardized power distribution network data set, carrying out the recognition of a power distribution network problem according to the power distribution network data set, and obtaining a power distribution network fault. The method comprises the following steps: obtaining a structured problem list of a power distribution network, carrying out spatial positioning and attribute mapping processing on the structured problem list in a preset geographic information system to obtain a power distribution network problem spatial distribution representation, and carrying out multi-dimensional analysis and prediction on the operation condition of the power distribution network according to the power distribution network problem spatial distribution representation. And obtaining a management and control strategy of the power distribution network, carrying out resource allocation according to the management and control strategy to obtain a cooperative work flow, and visualizing the problem space distribution representation of the power distribution network and the cooperative work flow in a geographic information system to provide a visual management and control mode. And the management efficiency and safety of the power distribution network are improved.

The invention discloses a simulation-oriented multi-agent maneuvering behavior decision-making system and method, and the system comprises a message transmission module which introduces the signal intensity into the communication among multiple agents, simulates a complex simulation environment with interference in a probabilistic communication mode for the discrete quantification of the communication intensity among the agents, and transmits the signal intensity to a decision-making module; obtaining joint state information influencing a maneuvering behavior decision; the state coding module is used for discretely quantifying the obtained joint state information into a unified index and coding the unified index to obtain a joint state code corresponding to each agent; the reward optimization module is used for determining a target reward of each agent in combination with the task target and the historical trajectory of each agent, and the target reward is used for optimizing the deep reinforcement learning network model of the strategy execution module; and the strategy execution module is used for determining and executing a final decision result of each agent by adopting a deep reinforcement learning network model based on an MADDPG algorithm by each agent. According to the invention, the problem of multi-agent collaborative navigation in a complex high-dimensional environment is solved.

The invention relates to the technical field of power equipment monitoring, in particular to a power equipment state monitoring data acquisition method based on a Beidou navigation system, which comprises the following steps: S1, equipment state data acquisition: acquiring state data of equipment in real time; s2, establishing an inter-equipment collaborative learning mechanism: establishing an inter-power equipment collaborative learning mechanism; s3, data fusion and standardization: performing standardization processing and fusion on the state data acquired by each device; s4, performing equipment state correlation analysis: identifying state correlation and potential fault modes between the equipment; and S5, a state evaluation and feedback mechanism: according to an analysis result associated with the equipment state, evaluating the equipment state, and feeding back an evaluation result to an inter-equipment collaborative learning mechanism. According to the invention, equipment monitoring and maintenance strategies can be dynamically optimized, the accuracy and efficiency of equipment health management are improved, the risk of fault diffusion is reduced, and the service life of equipment is prolonged.

The invention discloses a method, a system and equipment for optimizing batching parameters in an industrial silicon smelting process. The method comprises the following steps: firstly, acquiring process parameters in an industrial silicon smelting process, standardizing the process parameters, then converting the process parameters into weight factors influencing a smelting result, and mapping a relation between the smelting result and the weight factors into a parameter equation based on a preset multiple linear regression model, obtaining a parameter set containing a weight factor and a linear regression coefficient; then, based on the parameter set, the initial raw material parameters and the reaction process parameters, an equivalent circuit model is constructed and simulated to generate smelting result data under different parameter combinations, and therefore parameter adjustment variables are obtained; according to the numerical range of the parameter adjustment variables and the initial raw material parameters, an optimal batching parameter combination is obtained; and finally, performing optimization treatment on batching parameters in the industrial silicon smelting process. According to the method, accurate control and rapid optimization adjustment of batching parameters can be stably achieved in the industrial silicon smelting process.

The invention relates to the technical field of intelligent route generation, in particular to a multi-modal large model-based route generation method and system and a storage medium, and the multi-modal large model-based route generation method provided by the invention comprises the following steps: extracting target information corresponding to an obtained webpage link; a target webpage corresponding to the webpage link comprises tourism information of at least two geographic points; determining description information and geographic information corresponding to all target geographic points in the target information based on a multi-modal large model; performing structured processing on the description information and the geographic information of all the target geographic points to obtain structured information; and automatically generating an editable route according to the structured information based on the multi-modal large model, and generating a route text representation and / or a route audio representation of the editable route. The webpage content corresponding to the webpage link is extracted and processed through the multi-modal large model, so that the tourism route of the place where the user wants to go is made by directly utilizing the tourism strategy on the platform.

The invention relates to the field of robot collaborative optimization, in particular to an industrial robot collaborative optimization system. Comprising the following steps: creating a task distribution matrix, optimizing the task distribution matrix by adopting a multi-objective optimization strategy, setting constraint conditions, and introducing a self-adaptive feedback adjustment mechanism to obtain an optimized task distribution matrix; and performing path optimization based on the optimized task allocation matrix. The problems that a fixed or simple scheduling algorithm is adopted for existing task allocation, and overload of part of industrial robots is likely to be caused; a dynamic feedback adjustment mechanism for resource consumption and state of the industrial robot is lacked, and optimization of task allocation cannot be performed according to real-time load and resource state of the industrial robot; the technical problems that path planning is prone to falling into a local optimal solution, and an industrial robot may frequently select a fixed path when executing a task, resulting in path resource competition and overall efficiency reduction are solved.

The invention provides a joint service equipment test optimization method and system based on digital twinning modeling, and relates to the technical field of digital twinning, and the method comprises the steps: collecting target multi-source heterogeneous data of target joint service equipment, and carrying out simulation modeling to generate a target twinning model; performing use association analysis to obtain a plurality of groups of associated twin models; obtaining a running environment condition set; simulation operation is carried out, an operation performance data set is collected for performance deviation analysis, and a first performance short board set is positioned; carrying out a cooperative operation test on the target twin model and the multiple groups of associated twin models, carrying out performance deviation identification based on operation process data, and positioning a second performance short plate set; and carrying out equipment design optimization on the target joint service equipment based on a short board integration analysis result. The technical problems that the prior art depends on limited experimental data, the test data is usually limited in a specific environment, and comprehensive data coverage under multi-dimension and multi-scene is lacked, so that the test efficiency and precision are poor are solved.

The invention provides an intelligent cold station control system based on machine learning, which relates to the technical field of energy and power engineering and is divided into an infrastructure part and an intelligent auxiliary part, the infrastructure part comprises a data acquisition subsystem, a data analysis and preprocessing subsystem, a machine learning model training subsystem, an intelligent control strategy generation subsystem, a real-time monitoring subsystem, a fault diagnosis and early warning subsystem, a man-machine interaction subsystem, an energy management subsystem and a communication subsystem. The intelligent auxiliary part comprises a self-adaptive optimization subsystem, a load prediction subsystem, an equipment health assessment subsystem, an intelligent cooperation subsystem, a virtual simulation subsystem, a green energy access subsystem and a safety protection subsystem, and the energy management subsystem generates output of the subsystems according to an intelligent control strategy and performs optimization management on energy consumption of the cold station. Through precise load prediction, intelligent control strategy generation and energy management optimization, the energy consumption of the cold station is reduced, and energy-saving operation is realized.

The invention relates to the technical field of enterprise evaluation, in particular to an enterprise digital capability operation detection and evaluation method, which comprises the following steps of: collecting data from digital systems of a plurality of departments in an enterprise, and generating data flow information of each department; based on the data flow information of all the departments, a cross-department digital cooperation graph is constructed by adopting a graph model cooperation graph, nodes in the cooperation graph represent all the departments of the enterprise, and edges in the cooperation graph represent cooperation relations and data flow among all the departments; analyzing the collaboration map by using data flow network analysis, and identifying a data island of cross-department data flow; and constructing a cross-department cooperation efficiency scoring model, and calculating cooperation efficiency scores of all departments and the whole enterprise. According to the invention, an enterprise can accurately know the cooperation efficiency and the overall digitization capability level of each department, so that a reliable data basis is provided for a management layer, low-efficiency departments and cooperation bottlenecks can be found, and an accurate promotion plan can be made.

The embodiment of the invention provides a vehicle control method and device, a server and a computer readable storage medium, and relates to the technical field of intelligent network connection traffic. According to the invention, road network data, real-time road information, and vehicle basic information and vehicle real-time information uploaded by a vehicle can be obtained, and the vehicle real-time information comprises information obtained in the driving process of the vehicle; grouping the vehicles according to the road network data, the real-time road information, the basic information of the vehicles and the real-time information of the vehicles to obtain vehicle team information; and controlling the vehicle according to the vehicle team information. The vehicles are grouped according to the road network data, the real-time road information, the vehicle basic information and the vehicle real-time information, and the vehicles are uniformly controlled according to the grouped vehicle team information, so that the cooperation capability between the vehicles can be improved, orderly passing of the vehicles on the road is realized, and the road passing efficiency is improved.

The invention discloses an agent man-machine cooperation strategy training system, method and device and a medium. The system comprises a teammate strategy population generation module, a centralized training module and a distributed optimization module. The teammate strategy population generation module is used for determining an initial strategy population according to a preset population number, and performing co-evolution on the initial strategy population to determine a target teammate strategy population; the centralized training module is used for acquiring global trajectory information according to the target teammate strategy population and performing centralized training on a global context encoder according to the global trajectory information; and the distributed optimization module is used for determining individual track information from the global track information and optimizing the local context encoder according to the individual track information. Based on the technical scheme, the cooperation effect of the intelligent agent in the complex heterogeneous environment is remarkably improved, a control strategy capable of being matched with any multi-behavior style human teammates can be achieved, and then the cooperation effect of the intelligent agent in the complex heterogeneous environment is improved.

The invention belongs to the technical field of intelligent power grid energy management, and particularly relates to a heterogeneous multi-agent cooperative comprehensive park electric energy scheduling method and system, and the method comprises the steps: customizing a corresponding heterogeneous agent through analyzing the characteristics and operation conditions of each energy system; utilizing a causal relationship graph and a conditional mutual information quantification method to establish a model of situation-dependent causal relationship between the intelligent agents; performing causal intervention collection and condition mutual information calculation between the agents; measuring a causal relationship among the agents to construct an internal reward mechanism of each agent; designing a total reward function of each agent based on the internal reward mechanism of each agent in combination with the direct reward parameter of each agent in the environment; performing strategy optimization based on the total reward function of each agent, and outputting a corresponding scheduling strategy; and executing a corresponding control action according to the scheduling strategy. The cooperative work capability among multiple agents is enhanced, and the overall optimization of park electric energy scheduling is realized.

The invention provides an unmanned aerial vehicle cluster reconnaissance task planning method and device based on a hierarchical model, and the method comprises the following steps: pre-collecting a battlefield situation, carrying out the pre-task planning according to the pre-collected battlefield situation, and enabling each unmanned aerial vehicle in an unmanned aerial vehicle cluster to execute a task according to the pre-task planning; in the task execution process, if a new battlefield situation occurs to cause that the pre-task planning scheme is not suitable any more, dynamic task planning is triggered; after dynamic task planning is triggered, alliance establishment is carried out, unmanned aerial vehicle clusters form a new formation model according to a hierarchical model, a new battlefield situation is collected, and task planning is carried out on the unmanned aerial vehicle clusters again; in the new formation model, the unmanned aerial vehicle cluster is divided into reconnaissance unmanned aerial vehicles and task unmanned aerial vehicles, a new battlefield situation is collected, and tasks are distributed to the unmanned aerial vehicle cluster again. The dynamic instant planning problem under the combat condition is considered, and the task completion efficiency is higher.

The invention relates to the technical field of function chain construction, in particular to a system and a method for constructing a virtual network security function chain, which comprises the following steps of: virtualizing various security functions, deploying the security functions in a network in a virtualized form, constructing a virtual security function chain, identifying security threats and generating a corresponding security event report. When a security threat is identified, a response is quickly made and corresponding protection measures are taken, so that data transmission and instruction communication among the virtualization security functions are realized, tasks of the security functions are dynamically allocated, resource utilization is optimized, system performance bottlenecks and potential faults are detected, and maintenance and optimization are carried out. According to the invention, each virtualization security function cooperatively works through an effective communication interface and a task scheduling mechanism, and it is ensured that the system can quickly respond and take corresponding protection measures when identifying security threats, such as blocking malicious traffic and isolating infected nodes.

The invention discloses an unmanned aerial vehicle body sensing network deployment method based on entropy feedback control, and the method comprises the steps: introducing a real-time feedback mechanism of local entropy, speed entropy and topological connection entropy based on an Olfati-Saber model, and dynamically adjusting the interaction force and obstacle avoidance strategy of each unmanned aerial vehicle through controlling the entropy reduction process of a cluster system, thereby achieving the real-time deployment of the unmanned aerial vehicle body sensing network. The robustness and the adaptive capability of the sensor network in a complex environment are improved, and the connectivity and the collaborative operation efficiency of the network are effectively ensured. The communication complexity is controlled through entropy feedback, unnecessary communication connection in a cluster is effectively reduced, redundancy caused by excessive communication is avoided, the overhead of information transmission is reduced, the allocation weight of communication resources is dynamically adjusted according to entropy value feedback, connection with important nodes is preferentially established, the utilization efficiency of the communication resources is improved, and the communication efficiency is improved. By monitoring the topology connection entropy in real time, the network structure is adaptively adjusted, the communication topology is flexibly optimized according to task requirements, and efficient communication and cluster stability in a complex environment are ensured.

The invention discloses an emergency communication method combining short-distance satellite flash and wireless broadcast, and relates to the technical field of wireless communication. Comprising the following steps: step 1, based on an emergency environment, issuing emergency information through radio broadcasting; 2, converting the emergency message received in real time into text information by using an automatic voice recognition model; 3, performing digital signature on the processed text information; 4, the digital signature is verified, and the text information is encrypted and transmitted; 5, decrypting the received text information by using a natural language processing method, identifying semantics in the text information, and extracting key information; 6, the processed text information is sent to related emergency response personnel and equipment through wireless short-distance star flash; and 7, monitoring the progress of the emergency response in real time by using wireless short-distance star flash, and receiving feedback information.

The invention discloses an assembly line rapid reconstruction method based on a forward variant network, and the method comprises the steps: summarizing a multi-domain conduction principle of product similarity-system configuration similarity-system execution similarity of a man-machine cooperation assembly line; the physical and logic reconstruction connotation of the man-machine cooperation assembly line is described through five dimensions of function-structure-behavior-execution-performance, all levels of the assembly line are comprehensively considered, and the comprehensiveness and coordination of the overall design are improved. In the flexible production line design process with the production line rapid variant design as the core, the parameterized node network model and the set pair theory are adopted, the optimal production line change scheme can be selected more scientifically and objectively, and the time period from information induction to scheme implementation is shortened. According to the method, a mathematical model taking change of propagation risks, change of propagation time and change of propagation cost as a comprehensive target is constructed depending on the actual production condition of an enterprise, fine management and cost optimization are realized, and the cost is reduced.

The invention provides an agent strategy collaboration method in an unstable environment based on a game theory. The method comprises the following steps: step 1, obtaining an agent state value and earnings; step 2, according to a dynamic difference planning method, obtaining an expected benefit of the intelligent agent, and according to a Markov formula, obtaining an optimal benefit of the intelligent agent; 3, obtaining the most expected action selection of the intelligent agent according to the state value at the current moment and the expected benefit of the intelligent agent; and 4, when the intelligent agent is in the dynamic environment, obtaining the change of the expected benefit of the intelligent agent along with time, and obtaining the optimal action selection according to the changed expected benefit. According to the method, the limitation of a traditional game theory and a reinforcement learning method in a dynamic unstable environment is overcome, and a new and efficient solution is provided for multi-agent collaborative decision-making.

The invention discloses a multi-UAV (unmanned aerial vehicle) collaborative search method imitating bird territory marks. The method comprises the following implementation steps: step 1, initializing a search environment; 2, unmanned aerial vehicle action strategy selection and position updating; 3, updating a search map and a territory smell map; 4, calculating a reward function and an observation matrix; 5, updating the reinforcement learning strategy network; and 6, outputting a search result. The method aims at solving the problem that multiple unmanned aerial vehicles search dynamic targets in an unknown environment, dynamic coverage of a target search area can be achieved in combination with a bionic model marked by a bird territory and an MAPPO reinforcement learning algorithm, efficient and intelligent search of multiple unmanned aerial vehicle dynamic targets is achieved, and the cooperation ability between the unmanned aerial vehicles in the search process is improved.

The invention is suitable for the field of data security assessment, and provides a data center security assessment method and system, and the system comprises a scene library construction module, an event triggering and real-time monitoring module, an event level division recording module, and a summary report generation module. By establishing a scene library, various possible security events and disaster scenes are covered, and the comprehensiveness and systematicness of evaluation are ensured. And each scene is defined and classified in detail, so that the emergency response capability of the data center under different conditions can be comprehensively tested. And the scientificity and objectivity of the evaluation process are ensured by presetting evaluation indexes and result evaluation standards. Each security event and disaster scene has a clear evaluation standard, the evaluation result can be quantified, and the accuracy and repeatability of evaluation are ensured.

The invention relates to the technical field of carbon management, in particular to a carbon metering terminal based on edge intelligent collaboration, and the terminal comprises a model partition updating module which constructs a carbon metering model based on carbon emission data collected in real time according to the carbon emission data, and generates carbon metering information after partition optimization by adjusting and dividing the carbon metering model. According to the invention, through real-time acquisition and partition optimization of the carbon emission data, in combination with an extraction mode of time sequence features and statistical features, the precision and efficiency of carbon emission prediction are significantly enhanced. In a data processing process, abnormal data and repetitive data are effectively eliminated by establishing a filtering threshold range, so that the data quality is improved, and the interference of low-efficiency data on subsequent analysis is avoided. In collaborative optimization of the edge nodes, communication delay and resource waste among the nodes are reduced by means of dynamic weight adjustment and path optimization, and the transmission efficiency and the collaborative effect are improved.

The invention discloses a data synchronization method and system, a computer readable storage medium and computer equipment. The data synchronization method in one embodiment comprises the following steps: joining a conference by using a pre-generated conference ID based on a first operation of a user; starting the writing unit and sending the conference ID to the writing unit; and controlling the writing unit to send the conference ID to a message server by using a software development kit SDK so as to subscribe to the cluster message theme from the message server. According to the data synchronization method provided by the invention, the SDK is used for accessing the message server, so that the conference ID is used for subscribing the cluster message theme, writing synchronization of the multiple intelligent display devices is realized, and the cooperation capability of the devices in the conference is improved.

A component management method based on a Revit component library belongs to the technical field of Revit component libraries, and comprises a component comprehensive management method and a component binding method. According to the component comprehensive management method, a common user uploads a component, and an auditor audits the component to continuously perfect component files, parameters, versions, time and uploader information of a current component; a user can check the historical version of each component and the detailed information of each component modified each time, the difference comparison among the versions is provided, and the authority of designers for component updating is provided; the component binding method comprises the step of carrying out information improvement and binding on the Revit component needing to be bound. According to the method, the component comprehensive management problem and the component information island problem of an existing Revit component library can be solved, the Revit component library can achieve more powerful functions, and greater convenience is provided for designers.

The invention relates to an all-in-one domain controller, and the controller comprises a frequency quantity input module which is used for collecting a sensor frequency quantity signal; the switching value input and output module is used for acquiring switching signals of the sensor and performing switching control on an actuator; the analog quantity input and output module is used for collecting analog signals of the sensor and performing analog control on an actuator; the power driving module is used for sending a driving control signal to an actuator; the controller attitude module is used for measuring a pitch angle, a roll angle and a course angle; the communication module is used for providing data communication; the power management module is used for providing power and power control management service; the central processor module controls the frequency quantity input module, the switching value input and output module, the analog quantity input and output module, the power driving module, the controller attitude module, the communication module and the power management module. A series of controllers applied to the whole vehicle are integrated into a control system, the number of ECUs is reduced, and the real-time data processing capacity is improved.

The present invention discloses an unmanned vehicle and a control method, device and medium thereof. The method comprises: obtaining sensor data of the unmanned vehicle, obtaining a global map and the current position of the unmanned vehicle according to the sensor data, planning the path of the unmanned vehicle according to the current position of the unmanned vehicle and the global map, obtaining the reference position, reference yaw angle and reference steering angle of the unmanned vehicle according to the path of the unmanned vehicle, establishing a kinematic model according to control variables, yaw angle variables of the upper platform and yaw angle variables of the lower chassis, establishing a first error state space equation according to the kinematic model, the reference state of the upper platform and the reference state of the lower chassis, solving the first error state space equation to obtain the control amount of the unmanned vehicle, and controlling the unmanned vehicle according to the control amount. The present invention can improve the intelligence and collaboration of the unmanned vehicle platform and can be applied to the technical field of unmanned vehicle.

The present invention discloses a milling steel fiber and its application in ultra-high performance concrete and wear-resistant flooring. The steel fiber is obtained by milling high-strength steel ingots or steel plates. The cross-section of the steel fiber is arc-shaped or approximately rectangular, and its upper and lower surfaces or the entire surface are rough. There are end hooks at both ends. The length of the steel fiber is 12 to 22 mm, the cross-sectional width is 2 to 3 mm, the cross-sectional thickness is 0.2 to 0.4 mm, the length of the end hook is 1 to 2 mm, and the tensile strength of the steel fiber is 1500 to 2500 MPa. Its body can be straight, arched and wavy, and an anti-corrosion layer is provided on the surface. The present invention overcomes the shortcomings of ordinary milling steel fibers, such as low tensile strength and poor toughness; compared with traditional microfilament steel fibers, it has the characteristics of high bonding strength and strong mechanical bite force, which can effectively improve the initial crack strength of ultra-high performance concrete, and can further improve the durability of the structure. The preferred application fields are ultra-high performance concrete and ultra-high performance concrete wear-resistant flooring.

The invention discloses a system and a method for customizing nursing measures based on evaluation results of patients subjected to lung cancer chemotherapy, which are used in the field of data analysis, and the system for customizing nursing measures based on evaluation results of patients subjected to lung cancer chemotherapy comprises a data acquisition module, an evaluation and analysis module, a nursing measure generation module, a nursing monitoring module and an interaction and display module. According to the method, unimportant variable coefficients are reduced to zero through penalty coefficients, so that variables significantly related to life quality and health conditions of patients are identified; an optimal penalty parameter is found by using a cross validation method, so that the prediction precision and generalization ability of the model can be maximized, and the risk of overfitting is reduced; through the multiple linear regression model, the specific influence of each characteristic variable on the life quality and health condition of the patient can be quantified, and possible side effect risks can be identified, so that more personalized and safer treatment suggestions are provided for the patient.

A distributed graphical program development platform based on a lightweight reconstruction mechanism relates to the technical field of computers and comprises an upper computer and a lower computer. The upper computer comprises an equipment manager component, a development platform main body and a server which are mutually independent; wherein the equipment manager component is used for interacting field equipment and data information with the lower computer; the development platform main body is used for designing, managing, compiling and running a graphical program; the server provides role authentication, program version uploading / downloading of distributed development management and shared variable transfer functions for a user based on a C / S architecture; the lower computer comprises an Agent system service and is connected with the equipment manager component; the development platform can improve the program debugging and deployment efficiency.