State monitoring method and system for service digital granary

Abstract

The invention discloses a service digital granary state monitoring method and system, and the method comprises the steps: obtaining the state data of a granary, and the state data comprise environment data, grain state data and storage condition data; based on the state data, training a man-machine interaction large model; based on the trained man-machine interaction large model, processing an input language instruction, and outputting feedback of the language instruction; and monitoring the state data based on the trained man-machine interaction large model, and automatically adjusting parameters of corresponding equipment in the granary based on a preset rule when monitoring that the state data changes. The digital supervision provided by the technical scheme of the invention can replace the traditional manual safeguards to complete daily storage, storage and inspection work, so that the demand of human resources is reduced.

Description

Technical Field

[0001] The present invention relates to the field of information technology application technology, and more specifically, to a status monitoring method and system for serving digital granaries. Background Art

[0002] In the context of globalization, food security has become the focus of attention of all countries. With the advancement of science and technology, grain depot informatization has achieved basic coverage, but the level of intelligence still needs to be improved. Intelligence and greening have become the main directions for the future development of the grain industry.

[0003] With the comprehensive coverage of grain depot informatization, the improvement of the level of intelligence has become the key to the development of the industry. This article introduces an intelligent digital human custodian that combines digital human technology and large model capabilities, aiming to improve the intelligent management level of grain depots through intelligent equipment and systems, and achieve the goals of reducing manpower, increasing efficiency, and energy conservation and environmental protection. Through the interactive screen equipment in front of the warehouse, the digital human custodian can perform tasks such as voice interaction, grain condition analysis, and intelligent ventilation, thereby improving storage efficiency and reducing manual intervention.

[0004] Therefore, a technology is needed to realize digital supervision services for future granaries. Summary of the invention

[0005] The technical solution of the present invention provides a status monitoring method and system for serving digital granaries, so as to solve the problem of how to serve digital granaries based on digital supervision.

[0006] In order to solve the above problems, the present invention provides a digital supervision method for serving future granaries, the method comprising:

[0007] Acquire status data of the granary, the status data including: environmental data, grain status data and storage condition data;

[0008] Based on the state data, training a large human-computer interaction model;

[0009] Based on the trained human-computer interaction large model, the input language instruction is processed and feedback of the language instruction is output;

[0010] Based on the trained human-computer interaction model, the status data is monitored in real time. When changes in the status data are detected, it is judged whether the status data exceeds a preset standard threshold based on preset rules; when it is judged that the status data exceeds the standard threshold, the corresponding equipment in the granary is automatically controlled to adjust the granary environment.

[0011] Preferably, it also includes: collecting the state data through deployed sensors, the sensors including: temperature and humidity sensors, gas sensors and insect pest sensors;

[0012] Periodically collecting the status data through the sensor, and analyzing the periodically collected status data;

[0013] Based on the analysis results, an inspection and maintenance work plan for the granary is generated, and based on the work plan, the granary is supervised.

[0014] Preferably, the method further comprises: analyzing the status data based on a grain condition abnormality model to identify and predict risks of grain silo management;

[0015] Based on the results of identification and prediction, operational recommendations for grain silo prevention and storage are generated according to grain types and storage conditions.

[0016] Preferably, the method further comprises: analyzing the state data based on an intelligent ventilation model, and proposing a ventilation strategy for granary management based on the analysis result;

[0017] Based on the ventilation strategy, adjusting the parameters of the ventilation equipment, and ventilating the granary through the ventilation equipment with the adjusted parameters;

[0018] Monitoring the status data during ventilation and determining whether the status data reaches a ventilation threshold;

[0019] When the status data reaches a ventilation threshold, the ventilation device is turned off.

[0020] Preferably, the step of processing the input language instruction based on the trained human-computer interaction large model and outputting feedback of the language instruction includes:

[0021] Identify the user through account number or user ID;

[0022] When the user's identity is identified, based on the identified user's identity authority, the language instruction corresponding to the identity authority submitted by the user is obtained through the preset interface layer;

[0023] Feedback on the language instruction is provided through the human-computer interaction large model, and the feedback on the language instruction is displayed in text through an interface, or output through language.

[0024] Based on another aspect of the present invention, the present invention provides a status monitoring system for serving a digital granary, the system comprising:

[0025] An acquisition unit, used for acquiring status data of a granary, wherein the status data includes: environmental data, grain status data and storage condition data;

[0026] A training unit, used for training a large human-computer interaction model based on the state data;

[0027] The execution unit is used to monitor the status data in real time based on the trained human-computer interaction model. When a change in the status data is detected, whether the status data exceeds a preset standard threshold is judged based on preset rules; when it is judged that the status data exceeds the standard threshold, the corresponding equipment in the granary is automatically controlled to adjust the granary environment.

[0028] Preferably, the acquisition unit is further used to collect the status data through deployed sensors, and the sensors include: temperature and humidity sensors, gas sensors and insect pest sensors;

[0029] Periodically collecting the status data through the sensor, and analyzing the periodically collected status data;

[0030] Based on the analysis results, an inspection and maintenance work plan for the granary is generated, and based on the work plan, the granary is supervised.

[0031] Preferably, the execution unit is further used to: analyze the status data based on the grain condition abnormality model to identify and predict the risk of grain silo management;

[0032] Based on the results of identification and prediction, operational recommendations for grain silo prevention and storage are generated according to grain types and storage conditions.

[0033] Preferably, the execution unit is further used to: analyze the state data based on the intelligent ventilation model, and propose a ventilation strategy for granary management based on the analysis result;

[0034] Based on the ventilation strategy, adjusting the parameters of the ventilation equipment, and ventilating the granary through the ventilation equipment with the adjusted parameters;

[0035] Monitoring the status data during ventilation and determining whether the status data reaches a ventilation threshold;

[0036] When the status data reaches a ventilation threshold, the ventilation device is turned off.

[0037] Preferably, the execution unit is used to process the input language instruction based on the trained human-computer interaction large model and output feedback of the language instruction, and is also used to:

[0038] Identify the user through account number or user ID;

[0039] When the user's identity is identified, based on the identified user's identity authority, the language instruction corresponding to the identity authority submitted by the user is obtained through the preset interface layer;

[0040] Feedback on the language instruction is provided through the human-computer interaction large model, and the feedback on the language instruction is displayed in text through an interface, or output through language.

[0041] The technical solution of the present invention provides a state monitoring method and system for serving digital granaries, wherein the method comprises: obtaining the state data of the granary, the state data comprising: environmental data, grain state data and storage condition data; training a large human-computer interaction model based on the state data; processing the input language instructions based on the trained large human-computer interaction model, and outputting feedback of the language instructions; monitoring the state data based on the trained large human-computer interaction model, and automatically adjusting the parameters of the corresponding equipment in the granary based on preset rules when changes in the state data are detected. The digital technology of the present invention not only improves the naturalness of user interaction and the efficiency of information acquisition, but also enhances the user experience by simulating the image of a real custodian. The digital supervision of the present invention can replace traditional manual custodians to complete daily warehousing, storage and inspection work, reducing the demand for human resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] A more complete understanding of exemplary embodiments of the present invention may be obtained by referring to the following drawings:

[0043] Figure 1 A flow chart of a method for monitoring the status of a digital granary according to a preferred embodiment of the present invention;

[0044] Figure 2 A flow chart of a method for monitoring the status of a digital granary according to a preferred embodiment of the present invention; and

[0045] Figure 3 It is a structural diagram of a status monitoring system serving a digital granary according to a preferred embodiment of the present invention. DETAILED DESCRIPTION

[0046] Now, exemplary embodiments of the present invention are described with reference to the accompanying drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. These embodiments are provided to disclose the present invention in detail and completely and to fully convey the scope of the present invention to those skilled in the art. The terms used in the exemplary embodiments shown in the accompanying drawings are not intended to limit the present invention. In the accompanying drawings, the same units / elements are marked with the same reference numerals.

[0047] Unless otherwise specified, the terms (including technical terms) used herein have the commonly understood meanings to those skilled in the art. In addition, it is understood that the terms defined in commonly used dictionaries should be understood to have the same meanings as those in the context of the relevant fields, and should not be understood as idealized or overly formal meanings.

[0048] Figure 1 The present invention is a flow chart of a method for status monitoring of a digital granary service according to a preferred embodiment of the present invention.

[0049] like Figure 1 As shown, the present invention provides a state monitoring method for serving a digital granary, the method comprising:

[0050] Step 101: Obtaining the status data of the granary, the status data including: environmental data, grain status data and storage condition data;

[0051] Step 102: Based on the state data, train the human-computer interaction model;

[0052] Step 103: Based on the trained human-computer interaction model, the input language instruction is processed and feedback of the language instruction is output;

[0053] Step 104: Based on the trained human-computer interaction model, the status data is monitored in real time. When a change in the status data is detected, it is judged whether the status data exceeds a preset standard threshold based on preset rules; when it is judged that the status data exceeds the standard threshold, the corresponding equipment in the granary is automatically controlled to adjust the granary environment.

[0054] Preferably, the method further comprises: collecting status data through deployed sensors, the sensors comprising: temperature and humidity sensors, gas sensors and insect pest sensors;

[0055] Periodically collect status data through sensors and analyze the periodically collected status data;

[0056] Based on the analysis results, an inspection and maintenance work plan for the granary is generated, and the granary is supervised based on the work plan.

[0057] Preferably, the method further comprises: analyzing the status data based on the grain condition abnormality model to identify and predict the risks of grain silo management;

[0058] Based on the results of identification and prediction, operational recommendations for grain silo prevention and storage are generated according to grain types and storage conditions.

[0059] Preferably, the method further comprises: analyzing the state data based on the intelligent ventilation model, and proposing a ventilation strategy for granary management based on the analysis result;

[0060] Based on the ventilation strategy, the parameters of the ventilation equipment are adjusted, and the granary is ventilated through the ventilation equipment with the adjusted parameters;

[0061] Monitor the status data during ventilation and determine whether the status data reaches the ventilation threshold;

[0062] When the status data reaches the ventilation threshold, the ventilation equipment is turned off.

[0063] Preferably, based on the trained human-computer interaction model, the input language instruction is processed and feedback of the language instruction is output, including:

[0064] Identify the user through account number or user ID;

[0065] When the user's identity is identified, based on the identified user's identity authority, the language instruction corresponding to the identity authority submitted by the user is obtained through the preset interface layer;

[0066] Feedback on language commands is provided through a large human-computer interaction model, and the feedback on language commands is displayed in text through the interface or output through language.

[0067] The present invention provides an interactive screen device in front of the warehouse. When designing the interactive screen device in front of the warehouse, the present invention adopts advanced display technology and user interface design to ensure intuitiveness and ease of operation. As a window for information display, the device replaces the traditional paper cargo location card, which not only improves the accessibility and accuracy of information, but also enhances the real-time nature of data. At the same time, it is the core of the intelligent warehouse management system. By integrating high-precision sensors and intelligent algorithms, the interactive screen can monitor and display environmental parameters in the granary, such as temperature, humidity, gas concentration, etc. in real time, providing decision support for digital human custodians. Through advanced face recognition cameras, it is possible to identify people in the warehouse and display different function pages according to permissions, which not only improves security but also enhances personalized services. Figure 2 shown.

[0068] Sensor integration in the present invention: The interactive screen device can integrate multiple sensors in the docking warehouse, including temperature sensors, humidity sensors and gas sensors, to monitor the environmental status in the granary in real time.

[0069] Data processing: Edge computing technology is used to perform preliminary processing of sensor data locally, reducing dependence on central servers and improving response speed.

[0070] User Interface: An intuitive user interface is designed to allow operators to easily view and control various parameters within the grain silo.

[0071] The present invention realizes the linkage between the digital human and the warehouse front interactive screen system. The integration of digital human technology is the key to this solution. We endow the digital human with a high level of cognitive and interactive capabilities by training a large model suitable for grain warehouse data. The digital human can not only understand complex language instructions, but also provide intelligent suggestions based on the real-time data of the grain warehouse.

[0072] The present invention trains a large model, including:

[0073] Data collection: Collect historical data of grain depots, including environmental parameters, grain types, storage conditions, etc., to provide a rich data foundation for large-scale model training.

[0074] Model selection: Choose a deep learning model suitable for processing natural language and making complex decisions, such as BERT or GPT series.

[0075] Training process: Through a combination of supervised learning and reinforcement learning, the model is trained to understand the instructions of the grain warehouse operators and make appropriate responses based on the grain warehouse data.

[0076] The digital human of the present invention is linked with the system, including:

[0077] Interface design: A unified interface layer is designed to enable the digital human to seamlessly connect with the warehouse front interactive screen system to achieve two-way data flow.

[0078] Interaction logic: Based on the language input received, the digital human combines the relevant data from the grain storage system and the warehouse front interactive screen system, performs semantic understanding and decision analysis through a large model, forms a text answer and outputs it through voice.

[0079] Real-time feedback: The digital human can receive real-time environmental changes in the granary and automatically adjust ventilation, temperature control and other equipment in the granary according to preset rules or model suggestions to achieve intelligent management.

[0080] The invention performs automatic inspections, and automated storage and inspection operations are the key to improving efficiency and reducing human errors. By integrating intelligent sensors for automatic inspections, real-time monitoring and analysis of grain status can be achieved, and abnormal grain conditions can be promptly warned and storage operations prompted.

[0081] Technical implementation includes:

[0082] Sensor integration: Deploy multiple sensors in the granary, such as temperature and humidity sensors, gas sensors, and pest sensors, to monitor the storage environment of grain.

[0083] Data collection: The automation system collects sensor data at regular intervals and sends it to a central server via wireless networks for analysis.

[0084] Work plan: Based on the analysis results, the system automatically generates inspection and maintenance work plans and guides the custodians to implement them.

[0085] The present invention performs intelligent warehousing operations, including:

[0086] Collect all-round information on grain and oil tanks (grain / insects / gas, oil temperature / liquid level, etc.) to visualize grain conditions, predict and warn. Intelligently judge ventilation strategies, recommend reasonable operation suggestions, realize closed-loop ventilation control, and enhance the "smart warehouse" capabilities.

[0087] Grain condition analysis is a key link in ensuring food security. Through big data analysis, the system can predict and identify potential risks and provide decision support. Based on the abnormal grain condition model analysis, it can judge abnormal conditions such as high temperature in the whole warehouse or local high temperature, and issue early warnings in time to perform relevant storage operations.

[0088] The intelligent ventilation model is the key technology to achieve environmental control in grain silos. By optimizing the ventilation strategy, the system is able to maintain the best environmental conditions for grain storage.

[0089] During the operation, the system monitors the grain condition in real time. Once the cooling target temperature or energy consumption limit is reached, the operating equipment will be automatically shut down and the ventilation energy consumption will be recorded, forming a complete closed-loop control system. The closed-loop control system ensures the automation and intelligence of grain silo management. Through real-time monitoring and automatic adjustment, the system can achieve efficient resource utilization and energy conservation.

[0090] Technical implementation includes:

[0091] Data collection: Collect environmental data and grain status data in the granary to provide a basis for analysis.

[0092] Pattern recognition: Using machine learning algorithms to identify abnormal patterns that may occur during grain storage.

[0093] Decision support: Based on the grain type and storage conditions, the system provides preventive measures and storage operation suggestions based on the analysis results to achieve optimal environmental control.

[0094] Automatic Control: Based on model output, ventilation equipment such as fans and air conditioners are automatically adjusted to maintain an ideal storage environment.

[0095] Energy consumption management: The system can automatically adjust the operation intensity according to energy consumption limits to achieve energy saving goals.

[0096] Key points of the invention

[0097] The key innovative points of the present invention are as follows:

[0098] Application of Digital Human Technology:

[0099] Personalized interaction: Digital human technology not only improves the naturalness of user interaction and the efficiency of information acquisition, but also enhances the user experience by simulating the image of a real custodian.

[0100] Multilingual support: Digital humans can understand and respond to multiple languages ​​or dialects, providing services to users with different language backgrounds and broadening the application scope of the technology.

[0101] Smart ventilation model:

[0102] Adaptive control: The intelligent ventilation model can automatically adjust the ventilation strategy according to the actual environment and grain status in the granary to achieve optimal storage conditions.

[0103] Automated operation process: The closed-loop control system realizes a fully automated process from monitoring to execution, reducing manual intervention and improving operation efficiency.

[0104] Energy consumption optimization: The model reduces unnecessary energy consumption and improves energy efficiency by precisely controlling ventilation equipment.

[0105] Big data analysis and decision support:

[0106] Deep insights: By deeply analyzing silo data, digital humans can provide deeper insights and help managers make more informed decisions.

[0107] Continuous Learning: The system is able to learn from each operation, constantly optimizing its analysis and decision-making capabilities and improving long-term performance.

[0108] The present invention simplifies the interaction process:

[0109] Intuitive operation: Through language interaction and electronic storage location cards, users can intuitively obtain and operate grain silo information without complicated training or learning process.

[0110] Environmental adaptability: The design of the interactive screen equipment takes into account the challenges of outdoor environments, such as strong light and bad weather, ensuring reliability and ease of use under various conditions.

[0111] The present invention improves operating efficiency:

[0112] Automated inspection: The automated inspection system reduces reliance on manual inspections, increases the frequency and coverage of operations, and thus improves the safety of grain storage.

[0113] Quick response: Intelligent ventilation models and closed-loop control systems can quickly respond to environmental changes and adjust ventilation strategies in a timely manner to ensure stable grain storage conditions.

[0114] The present invention reduces labor costs:

[0115] Reduce the demand for human resources: Digital custodians can replace traditional manual custodians to complete daily warehousing, storage and inspection work, reducing the demand for human resources.

[0116] Improve the efficiency of human resource utilization: Released human resources can be reallocated to tasks that require more manual intervention, thereby improving overall work efficiency.

[0117] The invention improves energy efficiency:

[0118] Intelligent energy consumption management: Through intelligent ventilation models and closed-loop control systems, the system can optimize energy use, reduce unnecessary energy consumption and achieve energy saving goals.

[0119] The present invention is environmentally friendly: the optimized ventilation strategy not only improves energy efficiency, but also reduces the impact on the environment, which is in line with the concept of green grain storage.

[0120] The present invention enhances security:

[0121] Real-time monitoring: Digital human custodians can monitor the environment and grain status in the granary in real time, and promptly detect and warn of potential safety issues.

[0122] Access control: The application of facial recognition technology enhances the security of the grain silo, ensuring that only authorized personnel can access sensitive areas and information.

[0123] The present invention improves the quality of decision making:

[0124] Data-driven decision-making: Intelligent decision support systems based on big data analysis can provide more accurate predictions and suggestions, helping managers make more informed decisions.

[0125] Continuous Optimization: The system is able to learn from each operation, continuously optimizing its analysis and decision-making capabilities and improving long-term performance.

[0126] The present invention improves user experience:

[0127] Personalized services: Digital human custodians can provide personalized services based on user needs and preferences, improving user satisfaction.

[0128] Ease of access: Electronic shelf cards and interactive screen devices are designed with user ease of use in mind, making access to information simple and quick.

[0129] The following is an example of the implementation of the present invention:

[0130] 1. Language question: "Please introduce the grain storage situation in Warehouse No. 1"

[0131] The system automatically switches to the 'Grain Storage Status' display page for Warehouse No. 1 and reports, "Currently, Warehouse No. 1 is in a sealed state, with a storage capacity of 2,500 tons. It stores a total of 2,000 tons of third-grade wheat, which belongs to the provincial reserve grain. The current grain temperature and warehouse temperature are normal."

[0132] 2. Verbal question: "What is the grain situation in warehouse No. 1 now?"

[0133] The system automatically switches to the "Grain Condition Monitoring" display page of Warehouse No. 1 and reports "Grain temperature and warehouse temperature in Warehouse No. 1 are normal; the latest grain condition data is the highest temperature of 25 degrees, the lowest temperature of 15 degrees, and the average temperature of 20 degrees. There is one abnormal high temperature point on the first floor, but no ventilation is required."

[0134] 3. Verbal question: "What is the grain situation in warehouse No. 2 now?"

[0135] The system automatically switches to the 'Grain Condition Monitoring' display page of Warehouse No. 2, and reports "The grain temperature and warehouse temperature in Warehouse No. 2 are abnormal; the latest grain condition data are the highest temperature of 35 degrees, the lowest temperature of 25 degrees, and the average temperature of 30 degrees.' There are 10 high temperature abnormal points, which are on the 1st and 2nd floors respectively, and ventilation and cooling are required. Currently, ventilation and cooling are in the process, and ventilation has been carried out for 10 hours. The real-time grain temperature is the highest temperature of 28 degrees, the lowest temperature of 17 degrees, and the average temperature of 22 degrees, generating an energy consumption of 100 degrees. It is estimated that ventilation will take another 2 hours."

[0136] Figure 3 It is a structural diagram of a status monitoring system serving a digital granary according to a preferred embodiment of the present invention.

[0137] like Figure 3 As shown, the present invention provides a status monitoring system for serving digital granaries, the system comprising:

[0138] The acquisition unit 301 is used to acquire the status data of the granary, the status data including: environmental data, grain status data and storage condition data;

[0139] A training unit 302, used for training a large human-computer interaction model based on the state data;

[0140] The execution unit 303 is used to monitor the status data in real time based on the trained human-computer interaction model. When a change in the status data is detected, it is judged whether the status data exceeds a preset standard threshold based on preset rules; when it is judged that the status data exceeds the standard threshold, the corresponding equipment in the granary is automatically controlled to adjust the granary environment.

[0141] Preferably, the acquisition unit 301 is further used to collect status data through deployed sensors, the sensors including: temperature and humidity sensors, gas sensors and insect pest sensors;

[0142] Periodically collect status data through sensors and analyze the periodically collected status data;

[0143] Based on the analysis results, an inspection and maintenance work plan for the granary is generated, and the granary is supervised based on the work plan.

[0144] Preferably, the execution unit 303 is further used to: analyze the status data based on the grain condition abnormality model to identify and predict the risks of grain silo management;

[0145] Based on the results of identification and prediction, operational recommendations for grain silo prevention and storage are generated according to grain types and storage conditions.

[0146] Preferably, the execution unit 303 is further used to: analyze the state data based on the intelligent ventilation model, and propose a ventilation strategy for granary management based on the analysis result;

[0147] Based on the ventilation strategy, the parameters of the ventilation equipment are adjusted, and the granary is ventilated through the ventilation equipment with the adjusted parameters;

[0148] Monitor the status data during ventilation and determine whether the status data reaches the ventilation threshold;

[0149] When the status data reaches the ventilation threshold, the ventilation equipment is turned off.

[0150] Preferably, the execution unit 303 is used to process the input language instruction based on the trained human-computer interaction large model and output feedback of the language instruction, and is also used to:

[0151] Identify the user through account number or user ID;

[0152] When the user's identity is identified, based on the identified user's identity authority, the language instruction corresponding to the identity authority submitted by the user is obtained through the preset interface layer;

[0153] Feedback on language commands is provided through a large human-computer interaction model, and the feedback on language commands is displayed in text through the interface or output through language.

[0154] A status monitoring system for serving a digital granary in a preferred embodiment of the present invention corresponds to a status monitoring method for serving a digital granary in another preferred embodiment of the present invention, which will not be described in detail here.

[0155] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes. The schemes in the embodiments of the present invention may be implemented in various computer languages, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0156] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0157] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0158] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0159] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0160] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

[0161] The invention has been described above with reference to a few embodiments. However, it is readily apparent to a person skilled in the art that other embodiments than the ones disclosed above are equally within the scope of the invention, as defined by the appended patent claims.

[0162] Generally, all terms used in the claims are to be interpreted according to their ordinary meaning in the technical field, unless explicitly defined otherwise herein. All references to "a / said / the [means, components, etc.]" are to be openly interpreted as at least one instance of said means, components, etc., unless explicitly stated otherwise. The steps of any method disclosed herein do not necessarily have to be performed in the exact order disclosed, unless explicitly stated otherwise.

Claims

1. A state monitoring method for serving a digital granary, the method comprising: Acquire status data of the granary, the status data including: environmental data, grain status data and storage condition data; Based on the state data, training a large human-computer interaction model; Based on the trained human-computer interaction large model, the input language instruction is processed and feedback of the language instruction is output; Based on the trained human-computer interaction model, the status data is monitored in real time. When changes in the status data are detected, it is judged whether the status data exceeds a preset standard threshold based on preset rules; when it is judged that the status data exceeds the standard threshold, the corresponding equipment in the granary is automatically controlled to adjust the granary environment.

2. The method according to claim 1, further comprising: The state data is collected by deployed sensors, the sensors including: temperature and humidity sensors, gas sensors and insect pest sensors; Periodically collecting the status data through the sensor, and analyzing the periodically collected status data; Based on the analysis results, an inspection and maintenance work plan for the granary is generated, and based on the work plan, the granary is supervised.

3. The method according to claim 2, further comprising: Analyze the status data based on the grain abnormality model to identify and predict the risks of grain silo management; Based on the results of identification and prediction, operational recommendations for grain silo prevention and storage are generated according to grain types and storage conditions.

4. The method according to claim 2, further comprising: Analyze the state data based on the intelligent ventilation model, and propose a ventilation strategy for granary management based on the analysis results; Based on the ventilation strategy, adjusting the parameters of the ventilation equipment, and ventilating the granary through the ventilation equipment with the adjusted parameters; Monitoring the status data during ventilation and determining whether the status data reaches a ventilation threshold; When the status data reaches a ventilation threshold, the ventilation device is turned off.

5. The method according to claim 2, wherein the processing of the input language instruction based on the trained human-computer interaction large model and outputting feedback of the language instruction comprises: Identify the user through account number or user ID; When the user's identity is identified, based on the identified user's identity authority, the language instruction corresponding to the identity authority submitted by the user is obtained through the preset interface layer; Feedback on the language instruction is provided through the human-computer interaction large model, and the feedback on the language instruction is displayed in text through an interface, or output through language.

6. A status monitoring system for serving digital granaries, the system comprising: An acquisition unit, used for acquiring status data of a granary, wherein the status data includes: environmental data, grain status data and storage condition data; A training unit, used for training a large human-computer interaction model based on the state data; The execution unit is used to monitor the status data in real time based on the trained human-computer interaction model. When a change in the status data is detected, whether the status data exceeds a preset standard threshold is judged based on preset rules; when it is judged that the status data exceeds the standard threshold, the corresponding equipment in the granary is automatically controlled to adjust the granary environment.

7. The system according to claim 6, wherein the acquisition unit is further configured to collect the status data through deployed sensors, wherein the sensors include: Temperature and humidity sensors, gas sensors, and pest sensors; Periodically collecting the status data through the sensor, and analyzing the periodically collected status data; Based on the analysis results, an inspection and maintenance work plan for the granary is generated, and based on the work plan, the granary is supervised.

8. According to the system of claim 7, the execution unit is further used to: analyze the status data based on the grain condition abnormality model to identify and predict the risk of grain silo management; Based on the results of identification and prediction, operational recommendations for grain silo prevention and storage are generated according to grain types and storage conditions.

9. The system according to claim 7, wherein the execution unit is further used to: analyze the state data based on the intelligent ventilation model, and propose a ventilation strategy for granary management based on the analysis result; Based on the ventilation strategy, adjusting the parameters of the ventilation equipment, and ventilating the granary through the ventilation equipment with the adjusted parameters; Monitoring the status data during ventilation and determining whether the status data reaches a ventilation threshold; When the status data reaches a ventilation threshold, the ventilation device is turned off.

10. The system according to claim 7, wherein the execution unit is used to process the input language instruction based on the trained human-computer interaction large model and output feedback of the language instruction, and is also used to: Identify the user through account number or user ID; When the user's identity is identified, based on the identified user's identity authority, the language instruction corresponding to the identity authority submitted by the user is obtained through the preset interface layer; Feedback on the language instruction is provided through the human-computer interaction large model, and the feedback on the language instruction is displayed in text through an interface, or output through language.

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