A smart agriculture holographic system based on a honeycomb internet of things ecology

Abstract

The present application relates to a kind of based on wisdom agricultural holographic system of the ecological of Hong Meng Internet of Things, comprising;Based on the parameter of soil acquisition of electrochemical sensor;Based on unmanned aerial vehicle carries multispectral camera and thermal imager and collects the growth state of crop;Weather parameter acquisition module is used to obtain the forecast meteorological parameter information of meteorological bureau and real-time meteorological parameter information collected by sensor;Hong Meng edge computing node is used to the data of the data acquisition unit of multi-source data collection is extracted with the feature and abnormality detection, the feature data and abnormality detection result extracted are sent to Hong Meng Internet of Things platform;Hong Meng Internet of Things platform converts the data sent by each Hong Meng edge computing node into holographic display instruction and then carries out holographic display.Data acquisition is directly called nearby edge node and carries out AI inference, and then analysis result is sent to cloud end and does statistics, cloud end is only responsible for global data summary and strategy update, and real-time performance achieves tens of milliseconds level, and bandwidth occupation directly reduces an order of magnitude.

Description

Technical Field

[0001] This invention relates to the field of smart agriculture technology, and in particular to a smart agriculture holographic system based on the HarmonyOS Internet of Things ecosystem. Background Technology

[0002] The core demand of smart agriculture is to achieve "precise perception, intelligent decision-making, and efficient execution" through technological means. However, the industry currently faces three major technological bottlenecks: First, the problem of equipment heterogeneity, where the communication protocols (such as Modbus, MQTT, and LoRaWAN) of sensors and execution devices from different manufacturers are incompatible, resulting in low data interaction efficiency and poor collaboration capabilities; second, the contradiction between real-time performance and reliability, where traditional cloud-based centralized architectures rely on network transmission, which is prone to latency (usually > 1 second) and network outages in complex agricultural environments (remote areas, severe obstruction); and third, insufficient visualization and interactive experience, where two-dimensional data charts cannot intuitively present the three-dimensional scene and dynamic changes of agricultural production, making it difficult to support refined management decisions. Summary of the Invention

[0003] This invention addresses the technical problems existing in the prior art by providing a smart agriculture holographic system based on the HarmonyOS IoT ecosystem. The smart agriculture holographic system is built on HarmonyOS edge computing nodes and the HarmonyOS IoT platform. After data collection, it directly calls nearby edge nodes to perform AI inference, and then sends the analysis results to the cloud for statistics. The cloud is only responsible for global data aggregation and strategy updates. The real-time performance is achieved at the tens of millisecond level, and the bandwidth usage is reduced by an order of magnitude.

[0004] According to a first aspect of the present invention, a smart agriculture holographic system based on the HarmonyOS IoT ecosystem is provided, comprising: a multi-source data acquisition unit, a HarmonyOS edge computing node, and a HarmonyOS IoT platform; The multi-source data acquisition unit includes: a soil parameter acquisition module, a crop growth status acquisition module, and a meteorological parameter acquisition module; The soil parameter acquisition module is used to acquire soil parameters based on electrochemical sensors; the crop growth status acquisition module is used to acquire the crop growth status based on a multispectral camera and thermal imager mounted on a UAV; the meteorological parameter acquisition module is used to acquire forecast meteorological parameter information from the meteorological bureau and real-time meteorological parameter information acquired by sensors. The HarmonyOS edge computing node is used to perform feature extraction and anomaly detection on the data collected by the multi-source data acquisition unit, and send the extracted feature data and anomaly detection results to the HarmonyOS IoT platform. The HarmonyOS IoT platform converts the data sent by each HarmonyOS edge computing node into holographic display instructions and then displays them holographically.

[0005] Based on the above technical solution, the present invention can also be improved as follows.

[0006] Optionally, the soil parameters include: soil temperature, soil moisture, soil pH, soil EC value, and soil nitrogen, phosphorus, and potassium values; The data includes: plant height, leaf area, leaf color, and the health status of leaves, stems, and fruits; The meteorological parameters include precipitation, temperature, and light intensity.

[0007] Optionally, the multi-source data acquisition unit further includes: an inventory storage quantity acquisition module, which determines the inventory storage quantity of various types of crops based on the types and quantities of crops entering and leaving the warehouse input by the user; The inventory storage quantity acquisition module also includes a laser rangefinder installed at the top of the warehouse. The laser rangefinder calculates the volume of the crops by measuring the distance from the highest point of the crops at various locations in the warehouse, and determines the real-time inventory storage quantity of the crops based on the volume. When the difference between the real-time inventory quantity and the inventory storage quantity exceeds a set threshold, an alarm message is issued through the HarmonyOS IoT platform.

[0008] Optionally, the multi-source data acquisition unit further includes: a crop market price acquisition module; The crop market price acquisition module periodically acquires the market prices of various crops and plots a price change curve over time. The HarmonyOS IoT platform issues alerts based on user-defined needs, prices, and inventory.

[0009] Optionally, the HarmonyOS edge computing nodes are deployed with various types of lightweight AI models; the lightweight AI models include: soil environment data monitoring models, weather environment data monitoring models, crop growth data monitoring models, pest and disease image recognition models, and target image detection models; The soil environmental data monitoring model determines whether the soil parameters collected by the soil parameter acquisition module are within the set threshold range. The weather and environment data monitoring model determines whether the predicted weather and environment or the real-time weather and environment are abnormal based on the data collected by the meteorological parameter acquisition module. The pest and disease image recognition model determines whether the crop is affected by pests and diseases based on the state of the leaves, stems and fruits of the plant in the images collected by the crop growth status acquisition module. The target image detection model determines whether fruit or weeds have been produced based on the image data collected by the crop growth status acquisition module.

[0010] Optionally, the HarmonyOS edge computing node is also deployed with a water / fertilizer application decision model; the smart agriculture holographic system further includes a water / fertilizer application control unit; The water / fertilizer application decision model issues a decision on applying water / fertilizer based on the judgment results of the soil environment data monitoring model and the weather environment data monitoring model, and implements the decision through the water / fertilizer application control unit.

[0011] Optionally, the HarmonyOS IoT platform uses a holographic display unit to display crop models, soil monitoring data, meteorological monitoring data, crop growth status, and production management processes. The production management process demonstrates the establishment of various types of crop information archives by utilizing planting batches, water and fertilizer application records, harvesting and storage, and realizing the information management of the entire crop production process.

[0012] Optionally, the HarmonyOS IoT platform also includes a user interaction unit; The user interaction unit includes: a user instruction receiving module and an alarm notification push module; The user instruction receiving module is based on instructions issued by the user via voice, keyboard, or interactive gestures; The alarm notification push module sends alarm information through the HarmonyOS IoT platform, or sends it to a mobile smart terminal bound to the HarmonyOS IoT platform via APP push / SMS / voice call.

[0013] This invention provides a smart agriculture holographic system based on the HarmonyOS IoT ecosystem. A multi-source data acquisition module collects soil, crop growth status, and meteorological parameters. Combined with HarmonyOS edge computing nodes, various lightweight AI models are deployed, enabling direct monitoring of soil environment data, weather environment data, crop growth data, pest and disease image recognition, and target detection of fruits / weeds. After data collection, it directly calls nearby edge nodes for AI inference, then sends the analysis results to the cloud for statistical analysis. The cloud is only responsible for global data aggregation and strategy updates, achieving real-time performance in the tens of milliseconds and reducing bandwidth usage by an order of magnitude. Based on the judgment results of the soil and weather environment data monitoring models, it issues decisions regarding water / fertilizer application. The HarmonyOS IoT platform displays crop models, soil monitoring status, meteorological monitoring status, crop growth status, and production management processes through a holographic display unit. It can also push real-time alarms through various modes. Attached Figure Description

[0014] Figure 1 A structural block diagram of a smart agriculture hologram based on the HarmonyOS IoT ecosystem provided by this invention; Figure 2This is a structural block diagram of an embodiment of smart agriculture holography based on the HarmonyOS IoT ecosystem provided by the present invention. Detailed Implementation

[0015] The principles and features of the present invention are described below with reference to the accompanying drawings. The examples given are only for explaining the present invention and are not intended to limit the scope of the present invention.

[0016] Figure 1 A structural diagram of a smart agriculture holographic system based on the HarmonyOS IoT ecosystem provided by this invention is shown below. Figure 1 As shown, the system includes: a multi-source data acquisition unit, a HarmonyOS edge computing node, and a HarmonyOS IoT platform.

[0017] The multi-source data acquisition unit includes: a soil parameter acquisition module, a crop growth status acquisition module, and a meteorological parameter acquisition module.

[0018] The soil parameter acquisition module is used to collect soil parameters based on electrochemical sensors; the crop growth status acquisition module is used to collect crop growth status based on a multispectral camera and thermal imager mounted on a UAV; and the meteorological parameter acquisition module is used to obtain forecast meteorological parameter information from the meteorological bureau and real-time meteorological parameter information collected by sensors.

[0019] HarmonyOS edge computing nodes are used to extract features and detect anomalies in data collected by multi-source data acquisition units, and send the extracted feature data and anomaly detection results to the HarmonyOS IoT platform.

[0020] The HarmonyOS IoT platform converts the data sent by each HarmonyOS edge computing node into holographic display instructions and then displays them holographically.

[0021] This invention provides a smart agriculture holographic system based on the HarmonyOS IoT ecosystem. The smart agriculture holographic system is built on HarmonyOS edge computing nodes and the HarmonyOS IoT platform. After data collection, it directly calls nearby edge nodes to perform AI inference, and then sends the analysis results to the cloud for statistics. The cloud is only responsible for global data aggregation and strategy updates. The real-time performance is in the tens of milliseconds range, and the bandwidth usage is reduced by an order of magnitude.

[0022] Example 1 Embodiment 1 provided by this invention is an embodiment of a smart agriculture holographic system based on the HarmonyOS IoT ecosystem, as provided by this invention. Figure 2 The diagram shown is a structural schematic of an embodiment of a smart agriculture holographic system based on the HarmonyOS IoT ecosystem provided by the present invention. Figure 1 and Figure 2 It is known that the implementation of this smart agriculture holographic system includes: a multi-source data acquisition unit, a HarmonyOS edge computing node, and a HarmonyOS IoT platform.

[0023] The multi-source data acquisition unit includes: a soil parameter acquisition module, a crop growth status acquisition module, and a meteorological parameter acquisition module.

[0024] The soil parameter acquisition module is used to collect soil parameters based on electrochemical sensors; the crop growth status acquisition module is used to collect crop growth status based on a multispectral camera and thermal imager mounted on a UAV; and the meteorological parameter acquisition module is used to obtain forecast meteorological parameter information from the meteorological bureau and real-time meteorological parameter information collected by sensors.

[0025] HarmonyOS edge computing nodes are used to extract features and detect anomalies in data collected by multi-source data acquisition units, and send the extracted feature data and anomaly detection results to the HarmonyOS IoT platform.

[0026] The HarmonyOS IoT platform converts the data sent by each HarmonyOS edge computing node into holographic display instructions and then displays them holographically.

[0027] In one possible embodiment, the soil parameters include: soil temperature, soil moisture, soil pH, soil EC (Electrical Conductivity) value, and soil nitrogen, phosphorus, and potassium values.

[0028] In practice, the timer interrupt mechanism of the HarmonyOS system can be used to collect data from various electrochemical sensors according to a set period, amplify the data, and then filter it to remove noise. This filtering method can be moving average filtering, median filtering, or Kalman filtering.

[0029] This includes: plant height, leaf area, leaf color, and the health status of leaves, stems, and fruits.

[0030] In practice, the presence of pests, fertilizer damage, or nutrient deficiency in the leaves can be determined by observing whether the leaves develop spots, fall off, turn yellow, curl, or have blemishes.

[0031] Meteorological parameters include precipitation, temperature, and light intensity.

[0032] In practice, obtaining forecast meteorological parameters from the meteorological bureau allows for proactive measures to address the crop planting environment, while real-time meteorological parameters enable timely intervention when precipitation, temperature, and light intensity exceed the set thresholds that crops can tolerate.

[0033] In one possible embodiment, the multi-source data acquisition unit further includes: an inventory storage acquisition module that determines the inventory storage of various types of crops based on the types and quantities of crops entering and leaving the warehouse as input by the user.

[0034] The inventory storage acquisition module also includes a laser rangefinder installed at the top of the warehouse. The laser rangefinder calculates the volume of the crops by measuring the distance from the highest point of the crops in various locations in the warehouse, and determines the real-time inventory storage of the crops based on the volume. When the difference between the real-time inventory and the inventory storage exceeds a set threshold, an alarm message is issued through the HarmonyOS IoT platform.

[0035] In practice, a gimbal and track can be set up, and the laser rangefinder can be placed on the gimbal. When the gimbal slides on the track, the laser rangefinder measures the height of the crops directly below, making the data measured by the laser rangefinder more accurate.

[0036] In the process of calculating the volume of crops, a coordinate system of the warehouse can be constructed to determine the point cloud coordinates of the height of each position of the crops in the warehouse. Based on these point cloud coordinates, the volume of the crops can be calculated using convex hull or voxelization algorithms.

[0037] You can also set up cameras and AI models to identify crop types.

[0038] In one possible embodiment, the multi-source data acquisition unit further includes a crop market price acquisition module.

[0039] The crop market price acquisition module periodically acquires the market prices of various crops and plots price curves over time. The HarmonyOS IoT platform then issues alerts based on user-defined requirements, prices, and inventory.

[0040] In practice, you can set a reminder when the price increase exceeds a set higher value, suggesting that users sell that type of crop. You can also set a reminder when the inventory of a certain type of crop exceeds a set value and the price exceeds the recent average value.

[0041] In one possible implementation, the HarmonyOS edge computing node is deployed with various types of lightweight AI models; these lightweight AI models include: soil environment data monitoring models, weather environment data monitoring models, crop growth data monitoring models, pest and disease image recognition models, and target image detection models.

[0042] The soil environmental data monitoring model determines whether soil parameters collected by the soil parameter acquisition module are within the set threshold range.

[0043] The weather and environmental data monitoring model uses data collected by the meteorological parameter acquisition module to determine whether abnormalities have occurred in the predicted / real-time weather and environmental conditions.

[0044] The pest and disease image recognition model determines whether a crop is affected by pests or diseases based on the state of the leaves, stems, and fruits of the plant in the images collected by the crop growth status acquisition module.

[0045] The target image detection model determines whether fruit or weeds have been produced based on image data collected by the crop growth status acquisition module.

[0046] The training process of the model can integrate historical data from multiple farms for model training, or after obtaining the trained model, the model parameters can be updated in real time based on the real-time data generated by local crops through online learning algorithms to adapt to the production needs of different regions and different crops.

[0047] HarmonyOS IoT is based on a distributed architecture, enabling low latency, high security, device collaboration, and lightweight adaptation. Unlike traditional Android / pure Linux edge solutions, which mostly collect data, send it to the cloud for real-time computation, and then feed the results back, HarmonyOS edge computing nodes can deploy lightweight AI and can choose to perform computations locally before sending the results to the cloud. Therefore, HarmonyOS edge computing nodes not only provide real-time results, but also can run independently offline. Network outages do not affect business operations, and data, models, and policies are automatically synchronized with the cloud after network recovery, achieving integrated cloud-edge management.

[0048] In one possible implementation, the HarmonyOS edge computing node is also deployed with a water / fertilizer application decision model; the smart agriculture holographic system also includes a water / fertilizer application control unit.

[0049] The water / fertilizer application decision model issues a decision on water / fertilizer application based on the judgment results of the soil environmental data monitoring model and the weather environmental data monitoring model, and implements the decision through the water / fertilizer application control unit.

[0050] In one possible embodiment, the HarmonyOS IoT platform uses a holographic display unit to display crop models, soil monitoring data, meteorological monitoring data, crop growth status, and production management processes. The production management process showcases the establishment of planting batches, water and fertilizer application records, harvesting and storage, and the creation of various types of crop information archives to achieve full-process information management of crop production.

[0051] In one possible implementation, the HarmonyOS IoT platform also includes a user interaction unit.

[0052] The user interaction unit includes a user command receiving module and an alarm notification push module.

[0053] The user instruction receiving module receives instructions from the user via voice, keyboard, or interactive gestures.

[0054] The alarm notification push module sends alarm information through the HarmonyOS IoT platform, or sends it to mobile smart terminals bound to the HarmonyOS IoT platform via APP push / SMS / voice call.

[0055] In practice, users receive commands from the user command receiving module, which can be query commands, setting commands, or control commands. Query commands can retrieve environmental parameters, crop status, and full-cycle growth line information. Setting commands can set various thresholds and alarm triggering conditions, as well as bind mobile smart terminals. Control commands can control the working status of various modules.

[0056] This invention provides a smart agriculture holographic system based on the HarmonyOS IoT ecosystem. A multi-source data acquisition module collects soil, crop growth status, and meteorological parameters. Combined with HarmonyOS edge computing nodes, various lightweight AI models are deployed, enabling direct monitoring of soil environment data, weather environment data, crop growth data, pest and disease image recognition, and target detection of fruits / weeds. After data collection, it directly calls nearby edge nodes for AI inference, then sends the analysis results to the cloud for statistical analysis. The cloud is only responsible for global data aggregation and strategy updates, achieving real-time performance in the tens of milliseconds and reducing bandwidth usage by an order of magnitude. Based on the judgment results of the soil and weather environment data monitoring models, it issues decisions regarding water / fertilizer application. The HarmonyOS IoT platform displays crop models, soil monitoring status, meteorological monitoring status, crop growth status, and production management processes through a holographic display unit. It can also push real-time alarms through various modes.

[0057] It should be noted that the descriptions of each embodiment in the above embodiments have different focuses. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0058] Those skilled in the art will understand that embodiments of the present invention can be provided as systems, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0059] This invention is described with reference to flowchart illustrations and / or block diagrams of systems, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0060] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0061] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0062] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0063] 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. A smart agriculture holographic system based on the HarmonyOS IoT ecosystem, characterized in that: The smart agriculture holographic system includes: a multi-source data acquisition unit, a HarmonyOS edge computing node, and a HarmonyOS IoT platform; The multi-source data acquisition unit includes: a soil parameter acquisition module, a crop growth status acquisition module, and a meteorological parameter acquisition module; The soil parameter acquisition module is used to acquire soil parameters based on electrochemical sensors; the crop growth status acquisition module is used to acquire the crop growth status based on a multispectral camera and thermal imager mounted on a UAV; the meteorological parameter acquisition module is used to acquire forecast meteorological parameter information from the meteorological bureau and real-time meteorological parameter information acquired by sensors. The HarmonyOS edge computing node is used to perform feature extraction and anomaly detection on the data collected by the multi-source data acquisition unit, and send the extracted feature data and anomaly detection results to the HarmonyOS IoT platform. The HarmonyOS IoT platform converts the data sent by each HarmonyOS edge computing node into holographic display instructions and then displays them holographically.

2. The intelligent agricultural holographic system according to claim 1, characterized in that, The soil parameters include: soil temperature, soil moisture, soil pH, soil EC value, and soil nitrogen, phosphorus, and potassium values. The data includes: plant height, leaf area, leaf color, and the health status of leaves, stems, and fruits; The meteorological parameters include precipitation, temperature, and light intensity.

3. The intelligent agricultural holographic system according to claim 1, characterized in that, The multi-source data acquisition unit further includes: an inventory storage quantity acquisition module, which determines the inventory storage quantity of various types of crops based on the types and quantities of crops entering and leaving the warehouse input by the user; The inventory storage quantity acquisition module also includes a laser rangefinder installed at the top of the warehouse. The laser rangefinder calculates the volume of the crops by measuring the distance from the highest point of the crops at various locations in the warehouse, and determines the real-time inventory storage quantity of the crops based on the volume. When the difference between the real-time inventory quantity and the inventory storage quantity exceeds a set threshold, an alarm message is issued through the HarmonyOS IoT platform.

4. The intelligent agricultural holographic system according to claim 3, characterized in that, The multi-source data acquisition unit also includes: a crop market price acquisition module; The crop market price acquisition module periodically acquires the market prices of various crops and plots a price change curve over time. The HarmonyOS IoT platform issues alerts based on user-defined needs, prices, and inventory.

5. The intelligent agricultural holographic system according to claim 1, characterized in that, The HarmonyOS edge computing nodes are deployed with various types of lightweight AI models, including: soil environment data monitoring models, weather environment data monitoring models, crop growth data monitoring models, pest and disease image recognition models, and target image detection models. The soil environmental data monitoring model determines whether the soil parameters collected by the soil parameter acquisition module are within the set threshold range. The weather and environment data monitoring model determines whether the predicted weather and environment or the real-time weather and environment are abnormal based on the data collected by the meteorological parameter acquisition module. The pest and disease image recognition model determines whether the crop is affected by pests and diseases based on the state of the leaves, stems and fruits of the plant in the images collected by the crop growth status acquisition module. The target image detection model determines whether fruit or weeds have been produced based on the image data collected by the crop growth status acquisition module.

6. The intelligent agricultural holographic system according to claim 5, characterized in that, The HarmonyOS edge computing node is also deployed with a water / fertilizer application decision model; the smart agriculture holographic system also includes a water / fertilizer application control unit; The water / fertilizer application decision model issues a decision on applying water / fertilizer based on the judgment results of the soil environment data monitoring model and the weather environment data monitoring model, and implements the decision through the water / fertilizer application control unit.

7. The intelligent agricultural holographic system according to claim 1, characterized in that, The HarmonyOS IoT platform uses a holographic display unit to display crop models, soil monitoring data, meteorological monitoring data, crop growth status, and production management processes. The production management process demonstrates the establishment of various types of crop information archives by utilizing planting batches, water and fertilizer application records, harvesting and storage, and realizing the information management of the entire crop production process.

8. The intelligent agricultural holographic system according to claim 1, characterized in that, The HarmonyOS IoT platform also includes a user interaction unit; The user interaction unit includes: a user instruction receiving module and an alarm notification push module; The user instruction receiving module is based on instructions issued by the user via voice, keyboard, or interactive gestures; The alarm notification push module sends alarm information through the HarmonyOS IoT platform, or sends it to a mobile smart terminal bound to the HarmonyOS IoT platform via APP push / SMS / voice call.

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