Environmental engineering Internet of Things cloud platform system

Abstract

The invention provides an environmental engineering internet of things cloud platform system, which comprises a data acquisition module used for acquiring project environment data and project equipment operation state data; the contract evaluation and decision module is used for performing multi-dimensional integrating degree evaluation analysis on the project environment data and the project equipment operation state data based on a preset evaluation model, performing autonomous decision making on the project based on a multi-dimensional integrating degree evaluation analysis result, and starting an adjustment plan based on an autonomous decision making result; and the block chain module is used for performing synchronous processing instruction on the existing cross-project based on the block chain after the adjustment plan is started, and performing linkage coordination control on each project device based on the processing result. The consistency, traceability and overall reliability of multi-project operation are ensured, the cooperative efficiency in complex environment engineering is effectively improved, and the overall operation state of project equipment is accurately and effectively known, managed and controlled.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of Internet of Things, and particularly relates to an environmental engineering Internet of Things cloud platform system. BACKGROUND

[0002] At present, with the development of environmental engineering, many projects such as air purification, sewage treatment, solid waste treatment and the like need to monitor and manage a large number of equipment and environmental parameters in real time, and a fan is one of the applications;

[0003] However, the existing project equipment has many problems in operation management, and the traditional project equipment monitoring and control mode is mostly limited to local operation, cannot realize real-time monitoring and intelligent control remotely, and the collection of operation data is often not comprehensive, so that the overall operation state, energy consumption and the influence on the environment of the project equipment cannot be comprehensively evaluated, and in the environmental engineering scene where multiple project equipment work together, there is a lack of a unified platform to coordinate management, which easily causes problems such as resource waste and low operation efficiency;

[0004] Therefore, in order to overcome the above defects, the present application provides an environmental engineering Internet of Things cloud platform system. SUMMARY

[0005] The present application provides an environmental engineering Internet of Things cloud platform system, which realizes accurate intelligent evaluation and autonomous decision of project operation state by collecting data in real time and comprehensively, and performing multi-dimensional fitness evaluation and comprehensive quantitative analysis, significantly improves response speed and control accuracy, and further synchronizes the existing cross-project disposal instructions and coordinates linkage by means of the blockchain network, ensures the consistency, traceability and overall reliability of multi-project operation, effectively solves the coordination efficiency in complex environmental engineering, and realizes accurate and effective understanding and control of the overall operation state of the project equipment.

[0006] The present application provides an environmental engineering Internet of Things cloud platform system, which includes:

[0007] A data acquisition module is used to acquire project environment data and project equipment operation state data;

[0008] A contract evaluation and decision module is used to perform multi-dimensional fitness evaluation and analysis on the project environment data and the project equipment operation state data based on a preset evaluation model, and to make autonomous decisions for the project based on the multi-dimensional fitness evaluation and analysis results, and to start an adjustment plan based on the autonomous decision results;

[0009] A blockchain module is used to synchronize disposal instructions for the existing cross-project based on the blockchain after the adjustment plan is started, and to perform linkage and coordination control on each project equipment based on the disposal results.

[0010] Preferably, an environmental engineering Internet of Things cloud platform system, a data acquisition module, comprising:

[0011] A sensor configuration unit for:

[0012] Determining the collection category and collection standard of environmental data based on collection requirements, and determining the required sensor category based on the collection category, and determining the performance configuration parameters and collection frequency of each sensor category based on the collection standard;

[0013] Parameter adaptation of the corresponding sensor based on the performance configuration parameters, and collection time configuration of the clock trigger associated with the sensor based on the collection frequency;

[0014] An environmental data acquisition unit for collecting project environmental data based on the configuration results according to each sensor category, and adding data type labels to each project environmental data based on the source of the corresponding sensor category of the project environmental data.

[0015] Preferably, an environmental engineering Internet of Things cloud platform system, a data acquisition module, comprising:

[0016] A monitoring mechanism construction unit for determining the supervision dimension of the project equipment based on management requirements, and constructing a dynamic monitoring mechanism based on the supervision dimension;

[0017] An operation data acquisition unit for:

[0018] Obtaining the equipment number of the project equipment, and allocating monitoring ports to the dynamic monitoring mechanism based on the equipment number;

[0019] Based on the monitoring port allocation result, the dynamic monitoring mechanism is connected with each project equipment, and the operation state data of each project equipment is collected based on the dynamic monitoring mechanism according to the connection result.

[0020] Preferably, an environmental engineering Internet of Things cloud platform system, a data acquisition module, comprising:

[0021] A local area network construction unit for allocating communication addresses and communication routes to each project equipment based on a preset gateway, and constructing a local area network between each project equipment based on the allocation result;

[0022] A data encryption unit for determining the importance level of each project equipment based on the working attributes of each project equipment, and performing level-based differentiated encryption on the operation state data of each project equipment based on the importance level and a preset encryption level key;

[0023] A data transmission unit for transmitting the operation state data of each project equipment after level-based differentiated encryption to the main control center based on the local area network.

[0024] Preferably, the environmental engineering Internet of Things cloud platform system, the contract evaluation and decision module, comprises:

[0025] The multi-dimensional matching degree evaluation comprises: energy efficiency matching degree evaluation, environmental protection index matching degree evaluation, and equipment health degree matching degree evaluation.

[0026] Preferably, the environmental engineering Internet of Things cloud platform system, the contract evaluation and decision module, comprises:

[0027] The matching degree evaluation analysis unit is configured to:

[0028] Based on the management terminal, the evaluation indexes required for each dimension matching degree evaluation are obtained, at the same time, the corresponding key points of attention are determined based on the purpose of each dimension matching degree evaluation, and the preference degree configuration is performed on the preset attention mechanism based on the key points of attention;

[0029] Based on the corresponding evaluation indexes and the preference degree configuration results of each dimension matching degree evaluation, the preset evaluation algorithm in the preset evaluation model is integrated for conditional iterative loss training, and a target preset evaluation model is obtained;

[0030] Based on the target preset evaluation model, the key feature data are extracted from the project environment data and the project equipment operation state data, and the multi-dimensional matching degree evaluation analysis is performed on the extracted key feature data, so as to obtain the quantitative evaluation reference value corresponding to each dimension matching degree evaluation analysis;

[0031] The autonomous decision unit is configured to:

[0032] Based on the management terminal, the individual matching degree standards of the project equipment at different positions are obtained, and the obtained quantitative evaluation reference values are respectively compared with the corresponding individual matching degree standards;

[0033] Based on the difference comparison, the state correction amount of each project equipment is determined, at the same time, the action amount is quantified based on the component composition and the operation protocol of each project equipment, and the execution parameter of each component in each project equipment is determined based on the action amount quantification result;

[0034] Based on the execution parameter of each component in each project equipment, the autonomous decision adjustment plan of each project equipment is generated;

[0035] The plan starting unit is configured to start and take effect on the obtained autonomous decision adjustment plan.

[0036] Preferably, the environmental engineering Internet of Things cloud platform system, the autonomous decision unit, comprises:

[0037] The simulation subunit is configured to construct a simulation device of each project equipment in the calculation based on the operation characteristics and the structure characteristics of each project equipment, and to build a virtual scene of the project equipment based on the project environment data;

[0038] The verification subunit is configured to:

[0039] synchronize the obtained autonomous decision adjustment plan to the simulation devices of the project equipment based on a preset communication interface to simulate state adjustment, and monitor the simulation state adjustment process in real time;

[0040] determine the intervention operation state of the simulation devices of the project equipment based on the real-time monitoring result, and perform multi-dimensional fit degree assessment review on the project equipment based on the intervention operation state;

[0041] When it is determined that the project equipment meets the corresponding individualized fit degree standard based on the multi-dimensional fit degree assessment review, it is determined that the obtained autonomous decision adjustment plan is qualified.

[0042] Preferably, an environmental engineering Internet of Things cloud platform system, a blockchain module, comprises:

[0043] The blockchain management unit is configured to:

[0044] After the adjustment plan is started, the running state of each project equipment is monitored in real time, and when there is cross-project debugging, cross-project disposal instructions are generated synchronously;

[0045] The cross-project disposal instructions are sent to the blockchain network, and the instruction sending authority and format legality are verified based on the pre-set smart contract in the blockchain network;

[0046] The linkage coordination control unit is configured to:

[0047] After verification, the cross-project disposal instructions are synchronized to the edge computing nodes associated with the current project equipment based on the blockchain network;

[0048] Based on the synchronization result, a linkage coordination control strategy is generated based on the edge computing nodes;

[0049] The linkage coordination control strategy is used to perform linkage coordination control on each project equipment.

[0050] Preferably, an environmental engineering Internet of Things cloud platform system, a linkage coordination control unit, comprises:

[0051] The state perception subunit is configured to perform collaborative state monitoring on each project equipment after performing linkage coordination control on each project equipment, and obtain linkage coordination control results for each project equipment;

[0052] The data feedback subunit is configured to:

[0053] The linkage coordination control results are fed back to the blockchain network, and the linkage coordination control results are notarized based on the blockchain network;

[0054] The evidence storage result is time-series correlated based on a time series, and the last evidence storage result is taken as the linkage coordination basis of the next period of each project device based on the time-series correlation result;

[0055] The linkage coordination control of the next period is feedback adjusted based on the linkage coordination basis.

[0056] Preferably, an environmental engineering Internet of Things cloud platform system, a blockchain module comprises:

[0057] A parameter determination unit is configured to:

[0058] The linkage coordination control result of each project device is obtained, and the control item and control execution parameter of each project device are determined based on the linkage coordination control result;

[0059] A report generation unit is configured to:

[0060] The control item and control execution parameter of each project device are recorded, and a control report is generated based on the recording result.

[0061] Compared with the prior art, the beneficial effects of the present application are as follows:

[0062] By comprehensively collecting data in real time and performing multi-dimensional fitness evaluation and comprehensive quantitative analysis, accurate intelligent evaluation and autonomous decision of the project operation state are realized, the response speed and control accuracy are significantly improved, and further, the existing cross-project is disposed of and the synchronous instruction is coordinated and linked by means of the blockchain network, so as to ensure the consistency, traceability and overall reliability of multi-project operation, effectively solve the coordination efficiency in complex environmental engineering, and realize accurate and effective understanding and control of the overall operation state of the project equipment.

[0063] Other features and advantages of the present application will be described in the following description, and some will become apparent from the description, or will be understood by those skilled in the art from the description. The purpose and other advantages of the present application can be achieved and obtained by the structure specifically pointed out in the present application file.

[0064] The technical solutions of the present application will be further described in detail below with the help of the drawings and examples. BRIEF DESCRIPTION OF DRAWINGS

[0065] The accompanying drawings are used to provide a further understanding of the present application, and constitute a part of the specification, together with the embodiments of the present application, for explaining the present application, and do not constitute a limitation on the present application. In the drawings:

[0066] Figure 1 is a structure diagram of an environmental engineering Internet of Things cloud platform system in the embodiments of the present application;

[0067] Figure 2 FIG. 1 is a structural diagram of a data collection module in an environmental engineering Internet of Things cloud platform system according to an embodiment of the present application;

[0068] Figure 3 FIG. 2 is a structural diagram of a contract evaluation and decision module in an environmental engineering Internet of Things cloud platform system according to an embodiment of the present application. DETAILED DESCRIPTION

[0069] The preferred embodiments of the present application will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to explain and illustrate the present application, and are not used to limit the present application.

[0070] Embodiment 1

[0071] The present embodiment provides an environmental engineering Internet of Things cloud platform system, as shown in FIG. 1, which comprises: Figure 1

[0072] a data collection module for collecting project environment data and project equipment operation state data;

[0073] a contract evaluation and decision module for performing multi-dimensional fit degree evaluation analysis on the project environment data and the project equipment operation state data based on a preset evaluation model, and autonomously deciding on the project based on the multi-dimensional fit degree evaluation analysis result, and starting an adjustment plan based on the autonomous decision result;

[0074] a blockchain module for synchronizing disposal instructions for existing cross-projects based on the blockchain after the adjustment plan is started, and performing linkage and coordination control on each project equipment based on the disposal result.

[0075] In this embodiment, the project environment data refers to the specific circumstances of the environment in which the equipment (for example, a fan) is located, including data such as environmental temperature and humidity.

[0076] In this embodiment, the project equipment operation state data refers to the current operation of the project equipment, including operating power, etc.

[0077] In this embodiment, the preset evaluation model is trained in advance and is used to perform multi-dimensional fit degree evaluation analysis on the project environment data and the project equipment operation state data, with the purpose of ensuring the adaptation degree of the current operation state of the equipment to the current environment.

[0078] In this embodiment, the multi-dimensional fit degree evaluation refers to a comprehensive quantitative analysis from multiple key dimensions, including the matching degree of equipment operation energy efficiency and current environmental conditions (energy efficiency fit degree), the compliance degree of project emission indicators and preset environmental protection standards (environmental protection fit degree), and the deviation degree of current equipment operation parameters from the healthy operation interval of the equipment (equipment health fit degree).

[0079] ​In this embodiment, the adjustment plan refers to a set of specific device control strategies prepared in the system for different evaluation results and scenarios, for example, adjusting the speed of the device, starting and stopping the standby unit, modifying the process parameters, and the combination of specific operation instructions.

[0080] In this embodiment, the synchronization treatment instruction for the existing cross-project refers to parallel control of different devices through the blockchain when the types of devices to be controlled are different, so as to achieve the purpose of linkage and coordination.

[0081] The beneficial effects of the above technical solutions are: through real-time comprehensive data collection and multi-dimensional fit degree evaluation comprehensive quantitative analysis, accurate intelligent evaluation and autonomous decision of the project operation state are realized, the response speed and control accuracy are significantly improved, at the same time, the synchronization treatment instruction for the existing cross-project is further coordinated by the blockchain network, and the consistency, traceability and overall reliability of multi-project operation are ensured, which effectively solves the coordination efficiency in complex environmental engineering, and also realizes accurate and effective understanding and control of the overall operation state of the project equipment.

[0082] Embodiment 2:

[0083] Based on embodiment 1, this embodiment provides an environmental engineering Internet of Things cloud platform system, as shown in Figure 2 The data acquisition module comprises:

[0084] The sensor configuration unit is configured to:

[0085] Determine the collection category and collection standard of environmental data based on the collection requirements, and determine the required sensor category based on the collection category, and determine the performance configuration parameters and collection frequency of each sensor category based on the collection standard;

[0086] Parameter adaptation is performed on the corresponding sensor based on the performance configuration parameters, and the collection time configuration is performed on the clock trigger associated with the sensor based on the collection frequency;

[0087] The environmental data acquisition unit is configured to collect project environmental data according to each sensor category based on the configuration result, and add data category labels to each project environmental data based on the source of the sensor category corresponding to the project environmental data.

[0088] In this embodiment, the collection requirement refers to the data collection standard determined according to a specific environmental monitoring target, which specifically includes the data category to be collected (such as temperature, humidity, PM2.5 concentration), the accuracy or range requirement of each data category, and the time frequency of data collection (such as 1 time per second or 1 time per minute).

[0089] In this embodiment, performance configuration parameters refer to the specific operating parameters that need to be set in order for the sensor to meet specific acquisition standards, such as the range, sensitivity, sampling accuracy, alarm threshold, and other configuration items that directly affect the sensor's output performance.

[0090] In this embodiment, the clock trigger is a device for generating a periodic trigger signal to periodically trigger the sensor.

[0091] In this embodiment, the data type label is a marker symbol used to distinguish the types of project environmental data. It is generated based on the sensor category source, and different sensors have different data type labels.

[0092] The beneficial effects of the above technical solution are: it can adaptively select and configure sensor types and parameters according to the monitoring target, achieving the optimal balance between acquisition accuracy and resource consumption; through automated acquisition strategy deployment and data tagging processing, it significantly improves the standardization, relevance and efficiency of environmental data acquisition, providing a high-quality, structured and reliable data foundation for subsequent analysis and decision-making.

[0093] Example 3:

[0094] Based on Example 1, this example provides an environmental engineering IoT cloud platform system, including a data acquisition module:

[0095] The monitoring mechanism construction unit is used to determine the regulatory dimensions of project equipment based on management requirements, and to construct a dynamic monitoring mechanism based on the regulatory dimensions.

[0096] The data acquisition unit is used to:

[0097] Obtain the device number of the project equipment, and allocate monitoring ports to the dynamic monitoring mechanism based on the device number;

[0098] Based on the monitoring port allocation results, the dynamic monitoring mechanism is connected to the equipment of each project, and the operating status data of each project equipment is collected according to the dynamic monitoring mechanism based on the connection results.

[0099] In this embodiment, the management requirements are pre-set.

[0100] In this embodiment, the regulatory dimension refers to a specific observation angle or indicator type set for monitoring the operating status of project equipment, such as monitoring needs for different aspects such as operating efficiency, energy consumption level, fault warning, and safety status.

[0101] In this embodiment, the dynamic monitoring mechanism refers to a set of specific monitoring rules and configurations generated based on the set regulatory dimensions, including but not limited to the specific data items to be collected, the collection frequency, the data processing algorithm, and the threshold for triggering alarms. This mechanism can be adjusted according to changes in management requirements.

[0102] The beneficial effects of the above technical solution are: it can flexibly define the monitoring focus according to actual management needs, automatically generate and deploy customized monitoring solutions, and realize refined and adaptive perception of equipment operating status; through automated resource allocation and system docking, it can significantly improve the construction efficiency and accuracy of large-scale equipment monitoring networks, ensure the integrity and consistency of data collection, and provide a solid foundation for upper-level intelligent decision-making.

[0103] Example 4:

[0104] Based on Example 1, this example provides an environmental engineering IoT cloud platform system, including a data acquisition module:

[0105] The local area network (LAN) construction unit is used to assign communication addresses and communication routes to each project device based on a preset gateway, and to build a LAN between the project devices based on the assignment results.

[0106] The data encryption unit is used to determine the importance level of each project device based on the working attributes of each project device, and to classify and encrypt the operating status data of each project device according to the importance level and the preset encryption level key.

[0107] The data transmission unit is used to transmit the operational status data of each project device, after being encrypted according to its classification, to the main control center via a local area network.

[0108] In this embodiment, the preset gateway is a network component used to assign communication addresses and communication routes to different project devices.

[0109] In this embodiment, the work attribute refers to the work type and business requirements corresponding to each project device.

[0110] In this embodiment, the importance level refers to the priority level divided according to the criticality of the project equipment in the system and the importance or sensitivity of its operating data. For example, core control equipment can be defined as "high" level, and ordinary sensing equipment can be defined as "medium" or "low" level.

[0111] In this embodiment, the preset encryption level key is pre-constructed and used as the basis for encrypting the operating status data of the project equipment.

[0112] In this embodiment, grade-based encryption refers to classifying and encrypting data according to the importance level of the data source device, using different strengths or algorithms (such as using keys of different lengths) to provide stronger security protection for high-level data.

[0113] The beneficial effects of the above technical solution are: by automating network address allocation and routing planning, a secure and reliable device interconnection network can be quickly built, greatly improving networking efficiency and stability. At the same time, by adopting a differentiated encryption strategy based on the importance of devices, the optimal configuration of security protection resources can be achieved, ensuring the security of critical data while taking into account overall transmission efficiency, and ensuring that the transmission process of operational status data to the main control center is secure, reliable and efficient.

[0114] Example 5:

[0115] Based on Example 1, this example provides an environmental engineering IoT cloud platform system, including a contract evaluation and decision-making module, comprising:

[0116] The multi-dimensional fit assessment includes: energy efficiency fit assessment, environmental protection indicator fit assessment, and equipment health fit assessment.

[0117] Example 6:

[0118] Based on Example 1, this example provides an environmental engineering Internet of Things (IoT) cloud platform system, such as... Figure 3 As shown, the contract evaluation and decision-making module includes:

[0119] The fit assessment and analysis unit is used for:

[0120] The management terminal acquires the evaluation indicators required for each dimension of fit assessment. At the same time, it determines the corresponding key concerns based on the purpose of each dimension of fit assessment and configures the preference of the preset attention mechanism based on the key concerns.

[0121] Based on the evaluation indicators and preference configuration results corresponding to the fit evaluation of each dimension, the pre-set evaluation algorithm in the pre-set evaluation model is trained by integrating the conditional iterative loss to obtain the target pre-set evaluation model.

[0122] Based on the target-preset evaluation model, key feature data of project environmental data and project equipment operation status data are extracted, and multi-dimensional fit evaluation analysis is performed on the extracted key feature data to obtain the quantitative evaluation reference value corresponding to each dimension fit evaluation analysis.

[0123] Autonomous decision-making units are used for:

[0124] The personalized fit standards of project equipment at different locations are obtained based on the management terminal, and the obtained quantitative evaluation reference values ​​are compared with the corresponding personalized fit standards.

[0125] The state correction amount of each project equipment is determined based on the difference comparison. At the same time, the state correction amount is quantified based on the component composition and operation protocol of each project equipment, and the execution parameters of each component in each project equipment are determined based on the action quantification results.

[0126] Based on the execution parameters of each component in each project's equipment, generate autonomous decision-making and adjustment plans for each project's equipment;

[0127] The contingency plan activation unit is used to activate and make effective the obtained autonomous decision-making adjustment contingency plan.

[0128] In this embodiment, the evaluation index refers to the measurement basis corresponding to the fit evaluation of each dimension, such as energy efficiency fit.

[0129] In this embodiment, key concerns refer to the data characteristics or indicators that need to be focused on in order to achieve the assessment purpose of a specific assessment dimension (such as energy efficiency, environmental protection, or equipment health). These characteristics or indicators include energy consumption rate under specific operating conditions, instantaneous emissions of a certain pollutant, vibration frequency of a certain key component, etc.

[0130] In this embodiment, the preset attention mechanism is pre-built.

[0131] In this embodiment, preference configuration refers to adjusting the attention weight or priority parameter in the evaluation algorithm according to the key points of concern, so that the algorithm can assign higher computational weight or attention to the specified key data features during the calculation process.

[0132] In this embodiment, conditional iterative loss training refers to a model training method that dynamically adjusts the calculation method or objective of the loss function (i.e., conditional iteration) during the training process according to different evaluation metrics and configuration conditions (preference configuration) so that the model can learn the optimal evaluation capability under a specific focus more quickly and better.

[0133] In this embodiment, the target preset evaluation model refers to the result obtained after training the preset evaluation algorithm in the preset evaluation model.

[0134] In this embodiment, the quantitative evaluation reference value refers to representing the results of the fit evaluation analysis of each dimension with specific numerical values, such as an energy efficiency fit of 90%.

[0135] In this embodiment, the personalized fit standard refers to the fit standard that the project equipment needs to achieve in different environments, and the fit degree varies for different locations.

[0136] In this embodiment, action quantization refers to converting the calculated abstract quantity (state correction quantity, such as "efficiency increase by 5%) that needs to be adjusted into specific physical operation parameters (such as "increase the water pump speed by 50 RPM" or "increase the valve opening by 10%) that can be understood and executed by each component of the equipment, based on the specific composition of the internal components and its control protocol.

[0137] The beneficial effects of the above technical solution are as follows: By dynamically configuring the focus of the evaluation algorithm, the system can adaptively adapt to the core management objectives in different scenarios, achieving a significant improvement in evaluation accuracy and efficiency. By using a training method that integrates multiple indicators and preference settings to optimize the evaluation model, the system can ensure more accurate and reliable extraction of key features and multi-dimensional quantitative evaluation results for complex operating states. Furthermore, by combining equipment-specific standards and physical constraints, the abstract evaluation difference is transformed into specific and executable action parameters, ultimately generating and executing highly customized adjustment schemes. This achieves a closed-loop autonomous decision-making process from intelligent evaluation to precise execution, greatly improving the intelligence level and control effect of system management.

[0138] Example 7:

[0139] Based on Example 6, this example provides an environmental engineering Internet of Things cloud platform system with an autonomous decision-making unit, including:

[0140] The simulation subunit is used to construct simulation devices for each project device in the calculation based on the operating and structural characteristics of each project device. At the same time, it builds virtual scenes for the project devices based on project environment data.

[0141] Verification subunit, used for:

[0142] Based on the preset communication interface, the obtained autonomous decision-making adjustment plan is synchronized to the simulation equipment of each project equipment to adjust the simulation status, and the simulation status adjustment process is monitored in real time.

[0143] Based on real-time monitoring results, the intervention operation status of the simulated equipment for each project is determined, and a multi-dimensional fit assessment and re-inspection of the equipment for each project is conducted based on the intervention operation status.

[0144] When the equipment for each project meets the corresponding personalized compatibility standard based on the multi-dimensional compatibility assessment and re-inspection, the resulting autonomous decision-making adjustment plan is deemed qualified.

[0145] In this embodiment, the operational characteristics refer to the operational features and operational processes corresponding to the operation of each project's equipment.

[0146] In this embodiment, structural features refer to the specific structural features of each project device, including the connection relationships between components and their appearance.

[0147] In this embodiment, the simulated device refers to a digital twin model built in a computing environment based on the operating and structural characteristics of a real device, capable of simulating its physical behavior and response patterns.

[0148] In this embodiment, the intervention operation state refers to the new operation state presented by the digital twin model after the operation set in the autonomous decision-making adjustment plan is performed on the simulation equipment in the simulation environment.

[0149] The beneficial effects of the above technical solution are: by simulating and verifying the entire process of the adjustment plan in a virtual environment, it is possible to accurately predict its effects and identify potential risks before actual implementation, which greatly avoids equipment damage or system disturbance caused by improper decision-making. The use of digital twins for re-inspection ensures the reliability and security of the plan, thereby significantly improving the robustness and intelligence level of the autonomous decision-making system.

[0150] Example 8:

[0151] Based on Example 1, this example provides an environmental engineering IoT cloud platform system with a blockchain module, including:

[0152] Blockchain management unit, used for:

[0153] After the adjustment plan is activated, the operating status of each project's equipment is monitored in real time, and cross-project handling instructions are generated simultaneously when there is cross-project equipment joint commissioning.

[0154] Cross-project processing instructions are sent to the blockchain network, and the authorization and format of the instructions are verified sequentially based on the smart contracts pre-set in the blockchain network.

[0155] The linkage and coordination control unit is used for:

[0156] After verification, cross-project processing instructions will be synchronized to the edge computing nodes associated with the current project's equipment via the blockchain network;

[0157] Based on the synchronization results, a coordinated control strategy is generated for the edge computing nodes.

[0158] The coordinated control strategy is used to coordinate and control the equipment of each project.

[0159] In this embodiment, the cross-project handling instruction refers to the control command issued to other related projects, requiring their equipment to make coordinated adjustments, in order to achieve system optimization or linkage needs on a larger scale after the adjustment plan of a certain project is activated.

[0160] In this embodiment, the smart contract is pre-built and exists in the blockchain, used to verify the permissions and format legality of instructions when cross-project processing instructions are received.

[0161] In this embodiment, the edge computing node is a data center used to determine the specific control scheme when controlling each device.

[0162] In this embodiment, the linkage coordination control strategy refers to the specific and executable device control scheme generated by the edge computing node after receiving the instruction verified by the blockchain, based on the real-time status of the devices under its jurisdiction. This scheme ensures that the actions of multiple devices are coordinated and consistent in terms of timing and logic.

[0163] The beneficial effects of the above technical solution are as follows: The beneficial effects of the present invention are as follows: By automatically verifying and executing cross-system instructions through blockchain smart contracts, the high credibility and immutability of multi-project joint debugging operations are ensured, the trust barriers in the collaboration process are completely eliminated, and the accurate, efficient and reliable coordination of cross-system resources is achieved with the help of distributed decision-making and linkage control of edge nodes, which significantly improves the collaborative efficiency and overall stability of large-scale environmental engineering.

[0164] Example 9:

[0165] Based on Example 8, this example provides an environmental engineering Internet of Things cloud platform system with a linkage and coordination control unit, including:

[0166] The status awareness subunit is used to perform collaborative status monitoring of each project's equipment after the coordinated control of each project's equipment is carried out, so as to obtain the coordinated control results of each project's equipment.

[0167] The data feedback subunit is used for:

[0168] The coordinated control results are transmitted back to the blockchain network, and the coordinated control results are stored as evidence on the blockchain network.

[0169] The evidence storage results are correlated in time series, and the last evidence storage result is used as the basis for the linkage and coordination of equipment in the next cycle of each project based on the time series correlation results.

[0170] Based on the linkage and coordination criteria, feedback adjustments are made to the linkage and coordination control for the next cycle.

[0171] In this embodiment, temporal association refers to associating linkage control result data generated at different times and stored on the blockchain in chronological order.

[0172] In this embodiment, the linkage coordination basis refers to the decision-making basis or optimization benchmark obtained by performing time-series correlation analysis on the historically stored linkage coordination control results, which guides how to carry out collaborative operations in the next control cycle.

[0173] The beneficial effects of the above technical solution are as follows: By continuously monitoring the results of the coordinated control and storing them on a reliable blockchain, a complete operational closed loop and traceable chain are established. By utilizing time-series correlation technology to transform historical execution results into the basis for optimization in the next cycle, cross-cycle and cross-project feedback adjustment and self-optimization are achieved, significantly improving the adaptability, accuracy, and long-term reliability of multi-device collaborative control.

[0174] Example 10:

[0175] Based on Example 1, this example provides an environmental engineering IoT cloud platform system with a blockchain module, including:

[0176] Parameter determination unit, used for:

[0177] Obtain the linkage and coordination control results for each project's equipment, and determine the control items and control execution parameters for each project's equipment based on the linkage and coordination control results;

[0178] The report generation unit is used for:

[0179] The control items and control execution parameters of the project equipment are recorded, and a control report is generated based on the recorded results.

[0180] In this embodiment, the control item refers to the specific aspects of equipment operation or operation type that need to be adjusted when the equipment is coordinated and controlled, such as adjusting the speed, starting and stopping the equipment, modifying the temperature setpoint, etc.

[0181] In this embodiment, the control execution parameter refers to the specific value or degree that needs to be set for each control item, that is, the quantitative index of the operation to be performed, such as adjusting the speed to 1500 RPM, or modifying the temperature setting to 25 degrees Celsius.

[0182] The beneficial effects of the above technical solution are: it can automatically and accurately extract key operation items and parameter details from complex linkage control results, realize the digital and accurate recording of the control process, and provide complete and reliable data audit and traceability basis for system operation through the automatic generation of structured control reports, significantly improve the transparency and maintainability of multi-device collaborative management, and provide solid data support for subsequent system optimization and strategy adjustment.

[0183] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. An environmental engineering Internet of Things (IoT) cloud platform system, characterized in that, include: The data acquisition module is used to collect project environmental data and project equipment operating status data; The contract evaluation and decision-making module is used to conduct multi-dimensional fit evaluation and analysis of project environmental data and project equipment operation status data based on a preset evaluation model, and to make autonomous decisions on the project based on the results of the multi-dimensional fit evaluation and analysis, and to initiate adjustment plans based on the results of autonomous decisions. The blockchain module is used to issue synchronous disposal instructions across projects based on the blockchain after the adjustment plan is activated, and to coordinate and control the equipment of each project based on the disposal results.

2. The environmental engineering Internet of Things cloud platform system according to claim 1, characterized in that, The data acquisition module includes: Sensor configuration unit, used for: Based on the acquisition requirements, determine the acquisition categories and standards for environmental data, and based on the acquisition categories, determine the required sensor categories. At the same time, based on the acquisition standards, determine the performance configuration parameters and acquisition frequency for each sensor category. Based on the performance configuration parameters, the parameters of the corresponding sensors are adapted, and the acquisition time of the clock trigger associated with the sensor is configured based on the acquisition frequency. The environmental data acquisition unit is used to collect project environmental data according to the configuration results and the sensor categories, and to add data type labels to each project environmental data according to the sensor category source corresponding to the project environmental data.

3. The environmental engineering Internet of Things cloud platform system according to claim 1, characterized in that, The data acquisition module includes: The monitoring mechanism construction unit is used to determine the regulatory dimensions of project equipment based on management requirements, and to construct a dynamic monitoring mechanism based on the regulatory dimensions. The data acquisition unit is used to: Obtain the device number of the project equipment, and allocate monitoring ports to the dynamic monitoring mechanism based on the device number; Based on the monitoring port allocation results, the dynamic monitoring mechanism is connected to the equipment of each project, and the operating status data of each project equipment is collected according to the dynamic monitoring mechanism based on the connection results.

4. The environmental engineering Internet of Things cloud platform system according to claim 1, characterized in that, The data acquisition module includes: The local area network (LAN) construction unit is used to assign communication addresses and communication routes to each project device based on a preset gateway, and to build a LAN between the project devices based on the assignment results. The data encryption unit is used to determine the importance level of each project device based on the working attributes of each project device, and to classify and encrypt the operating status data of each project device according to the importance level and the preset encryption level key. The data transmission unit is used to transmit the operational status data of each project device, after being encrypted according to its classification, to the main control center via a local area network.

5. The environmental engineering Internet of Things cloud platform system according to claim 1, characterized in that, The contract evaluation and decision-making module includes: The multi-dimensional fit assessment includes: energy efficiency fit assessment, environmental protection indicator fit assessment, and equipment health fit assessment.

6. The environmental engineering Internet of Things cloud platform system according to claim 1, characterized in that, The contract evaluation and decision-making module includes: The fit assessment and analysis unit is used for: The management terminal acquires the evaluation indicators required for each dimension of fit assessment. At the same time, it determines the corresponding key concerns based on the purpose of each dimension of fit assessment and configures the preference of the preset attention mechanism based on the key concerns. Based on the evaluation indicators and preference configuration results corresponding to the fit evaluation of each dimension, the pre-set evaluation algorithm in the pre-set evaluation model is trained by integrating the conditional iterative loss to obtain the target pre-set evaluation model. Based on the target-preset evaluation model, key feature data of project environmental data and project equipment operation status data are extracted, and multi-dimensional fit evaluation analysis is performed on the extracted key feature data to obtain the quantitative evaluation reference value corresponding to each dimension fit evaluation analysis. Autonomous decision-making units are used for: The personalized fit standards of project equipment at different locations are obtained based on the management terminal, and the obtained quantitative evaluation reference values ​​are compared with the corresponding personalized fit standards. The state correction amount of each project equipment is determined based on the difference comparison. At the same time, the state correction amount is quantified based on the component composition and operation protocol of each project equipment, and the execution parameters of each component in each project equipment are determined based on the action quantification results. Based on the execution parameters of each component in each project's equipment, generate autonomous decision-making and adjustment plans for each project's equipment; The contingency plan activation unit is used to activate and make effective the obtained autonomous decision-making adjustment contingency plan.

7. The environmental engineering Internet of Things cloud platform system according to claim 6, characterized in that, Autonomous decision-making units, including: The simulation subunit is used to construct simulation devices for each project device in the calculation based on the operating and structural characteristics of each project device. At the same time, it builds virtual scenes for the project devices based on project environment data. Verification subunit, used for: Based on the preset communication interface, the obtained autonomous decision-making adjustment plan is synchronized to the simulation equipment of each project equipment to adjust the simulation status, and the simulation status adjustment process is monitored in real time. Based on real-time monitoring results, the intervention operation status of the simulated equipment for each project is determined, and a multi-dimensional fit assessment and re-inspection of the equipment for each project is conducted based on the intervention operation status. When the equipment for each project meets the corresponding personalized compatibility standard based on the multi-dimensional compatibility assessment and re-inspection, the resulting autonomous decision-making adjustment plan is deemed qualified.

8. The environmental engineering Internet of Things cloud platform system according to claim 1, characterized in that, The blockchain module includes: Blockchain management unit, used for: After the adjustment plan is activated, the operating status of each project's equipment is monitored in real time, and cross-project handling instructions are generated simultaneously when there is cross-project equipment joint commissioning. Cross-project processing instructions are sent to the blockchain network, and the authorization and format of the instructions are verified sequentially based on the smart contracts pre-set in the blockchain network. The linkage and coordination control unit is used for: After verification, cross-project processing instructions will be synchronized to the edge computing nodes associated with the current project's equipment via the blockchain network; Based on the synchronization results, a coordinated control strategy is generated for the edge computing nodes. The coordinated control strategy is used to coordinate and control the equipment of each project.

9. The environmental engineering Internet of Things cloud platform system according to claim 8, characterized in that, The linkage and coordination control unit includes: The status awareness subunit is used to perform collaborative status monitoring of each project's equipment after the coordinated control of each project's equipment is carried out, so as to obtain the coordinated control results of each project's equipment. The data feedback subunit is used for: The coordinated control results are transmitted back to the blockchain network, and the coordinated control results are stored as evidence on the blockchain network. The evidence storage results are correlated in time series, and the last evidence storage result is used as the basis for the linkage and coordination of equipment in the next cycle of each project based on the time series correlation results. Based on the linkage and coordination criteria, feedback adjustments are made to the linkage and coordination control for the next cycle.

10. The environmental engineering Internet of Things cloud platform system according to claim 1, characterized in that, The blockchain module includes: Parameter determination unit, used for: Obtain the linkage and coordination control results for each project's equipment, and determine the control items and control execution parameters for each project's equipment based on the linkage and coordination control results; The report generation unit is used for: The control items and control execution parameters of the project equipment are recorded, and a control report is generated based on the recorded results.

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