CN114004458A - Polymorphic potential perception fusion plant growth management system - Google Patents
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Abstract
The invention relates to the technical field of agricultural automatic management and discloses a plant growth management system with integrated polymorphic potential perception; the plant growth management system with the multi-state perception fusion comprises a plant growth situation comprehensive analysis system, a sensing system, an image acquisition system, an edge computing system, a dimming system, an automation equipment system and an agricultural Internet of things management cloud platform, overcomes the defect that a global optimal control mode cannot be obtained because the traditional control is only adjusted by a single factor, establishes the plant growth situation comprehensive analysis system, obtains the optimal control mode through the optimal solution of a control strategy model, and reduces the energy consumption and improves the control precision and the crop yield compared with the traditional agricultural equipment control mode; and the multi-sensing data are fused, so that the sensing equipment can be used as a controllable factor to be fed back to the plant growth environment, and the plant growth regulation is promoted.
Description
Technical Field
The invention belongs to the technical field of agricultural automatic management, and particularly relates to a plant growth management system with multi-state perception fusion.
Background
Agriculture is an industry for obtaining products by artificial cultivation by utilizing growth and development rules of animals and plants, belongs to a first industry, and is a basic industry for supporting national economic construction and development. The agricultural working object is living animals and plants, and the obtained products are the animals and plants.
Generally, the traditional agricultural manual management is lack of an effective technical means for collecting the crop growth environment parameters; the manual control is adopted to realize the control of irrigation, fertilization, roller shutters, fans and the like, the labor and time are consumed, and the error rate is high. The modern agricultural control technology has the problems that the sensing data is relatively single, the sensor only plays a monitoring role and cannot play a promoting role in plant growth regulation, the acquired data needs to be manually counted and analyzed, and an intelligent data management and analysis platform is lacked; therefore, improvements are now needed in view of the current situation.
Disclosure of Invention
Aiming at the situation, in order to overcome the defects of the prior art, the invention provides the plant growth management system with the multi-state perception fusion, which effectively solves the problems that the common traditional agricultural manual management is lack of effective technical means to collect the crop growth environment parameters; the manual control is adopted to realize the control of irrigation, fertilization, roller shutters, fans and the like, the labor and time are consumed, and the error rate is high. And the modern agricultural control technology, the sensing data is relatively single, the sensor only plays a monitoring role and cannot play a promoting role in plant growth regulation, the acquired data is manually counted and analyzed, and an intelligent data management and analysis platform is lacked.
In order to achieve the purpose, the invention provides the following technical scheme: a plant growth management system with multi-state perception fusion comprises a plant growth situation comprehensive analysis system, a sensing system, an image acquisition system, an edge computing system, a dimming system, an automation equipment system and an agricultural Internet of things management cloud platform;
plant growth situation comprehensive analysis system: the plant growth situation comprehensive analysis system is used for comprehensively analyzing, evaluating and controlling the growth situation of the plant, giving out a global optimal control strategy according to the overall evaluation result and controlling related equipment, integrates image acquisition data, GIS (geographic information System) geographic position information data, environment sensing detection data and an algorithm model library, is linked with edge calculation and adopts a digital circuit as a data transmission channel;
a sensing system: the sensing system is used for collecting information of a plant growing environment and packaging and sending data to the edge computing system according to a set time interval, the sensing system comprises a sensing equipment input end, a data storage module, a data transmission module and a data monitoring module, and the data monitoring module comprises a temperature and humidity sensor, a GIS (geographic information system), a light sensor, a CO2 sensor and a photosynthesis sensor;
an image acquisition system: the image acquisition system is used for acquiring plant images and video data of a planting area, scanning and shooting plants in the whole area according to a set time interval, and sending packed image video data to the edge computing system, and comprises a data storage module, a data transmission module and a camera module;
an edge computing system: the edge computing system is used for preprocessing and analyzing real-time data from a multi-channel sensor of the sensing system and image video data of the image acquisition system, transmitting the processed and analyzed data to the plant growth situation comprehensive analysis system, and performing related identification and detection tasks of plant types, growth stages, plant diseases and insect pests and growth situations;
a dimming system: the light adjusting system is used for controlling the on-off state, the power, the deflection angle and the irradiation duration of the light supplementing device according to a control instruction after receiving the control instruction from the plant growth situation comprehensive analysis system, so that the whole plant can obtain the optimal light supplementing effect;
an automated equipment system: the automatic equipment system is used for receiving a control instruction sent by the plant growth situation comprehensive analysis system and adjusting the on-off and working modes of relevant equipment according to the control instruction;
agricultural thing networking management cloud platform: the agricultural Internet of things management cloud platform is used for receiving plant data sent by the plant growth situation comprehensive analysis system, performing control strategy model training on the plant data, combining the obtained data subjected to the control strategy model training with relevant data of an agricultural knowledge base to obtain final data, and feeding the final data back to the plant growth situation comprehensive analysis system, and comprises a data interface, a control strategy model training module, an agricultural knowledge base module and a cloud framework module.
Preferably, the plant growth situation comprehensive analysis system is electrically connected with the sensing system, the image acquisition system, the edge computing system, the dimming system, the automation equipment system and the agricultural internet of things management cloud platform.
Preferably, the image acquired by the image acquisition system comprises a mildew plant area image, an insect pest plant area image, an area growth distribution image, a plant growth stage image and a plant variety image.
Preferably, the processing of the image video data by the edge computing system comprises: firstly, identifying the plant region image of the plant diseases and insect pests: the regional positions of the insect pest and mildew plants are obtained through the image acquisition system, so that data are sent to the utilization dimming system, the illumination intensity and angle are adjusted, and insect pest and mildew treatment is carried out in time; secondly, identifying the plant variety and the growth stage image: the variety of the plant and the growth stage of the plant are analyzed through the image, so that the ratio of illumination, water fertilizer and the like can be adjusted in time according to different plants and different illumination, water fertilizer and the like required by different growth stages; and thirdly, identifying growth situation distribution images: and (4) analyzing the plant growth situation through images, and obtaining a regional growth situation distribution diagram through image comparison analysis.
Preferably, the automatic equipment system comprises an automatic curtain rolling machine, a water and fertilizer all-in-one machine, a ventilator and CO2An automatic controller.
Preferably, the control strategy model specifically takes various types of sensing data processed by the edge calculation module as data input; the plant model achieves the optimal growth situation as a target; low energy consumption and micro adjustment as constraint conditions; the growth situation evaluation result is output; the method is an analysis model which can reduce the adjustment amplitude and the equipment adjustment quantity as much as possible while achieving the optimal control output, and finally converts the output into a control command to carry out equipment control.
Preferably, the agricultural internet of things management cloud platform is specifically a mobile phone or a webpage applet, a public service number or APP software.
Preferably, the cloud architecture of the cloud framework module is specifically one or a combination of several of a private cloud, a mobile cloud, a unicom cloud, a telecommunication cloud, an IBM cloud, and a google cloud.
Preferably, the use method of the plant growth management system with the fusion of polymorphic potential perception comprises the following steps:
s1: data acquisition: collecting data information of a plant growing environment through a temperature and humidity sensor, a GIS (geographic information system), a light sensor, a CO2 sensor and a photosynthesis sensor of a sensing system, collecting plant images and video data of a planting area through a camera module of an image acquisition system, and sending the obtained data information, the plant images and the video data to an edge computing system according to a set time interval by the sensing system and the image acquisition system;
s2: data processing: after receiving the data, the edge computing system preprocesses and analyzes the data information, the plant image and the video data, identifies the plant region image of the plant diseases and insect pests, identifies the plant variety and the growth stage image and the growth situation distribution image, and sends the identified data to the plant growth situation comprehensive analysis system;
s3: data fusion: after receiving the data sent by the edge computing system, the plant growth situation comprehensive analysis system sends the data to an agricultural Internet of things management cloud platform, the agricultural Internet of things management cloud platform performs control strategy model training on the plant data, the data obtained through the control strategy model training is combined with the data related to an agricultural knowledge base to obtain fusion data, and the fusion data are fed back to the plant growth situation comprehensive analysis system;
s4: and (4) strategy output: after the plant growth situation comprehensive analysis system receives the fusion data, each instruction is sent to the corresponding dimming system and the corresponding automation equipment system according to the fusion data, the dimming system controls the on-off state, the power, the deflection angle and the irradiation duration of the light supplementing device, and the automation equipment system adjusts the on-off state and the working mode of the relevant equipment, so that the dynamic control with low energy consumption, micro-adjustment and high quality is realized.
Compared with the prior art, the invention has the beneficial effects that: 1. according to the invention, the defect that a global optimal control mode cannot be obtained because the traditional control is only adjusted by a single factor is overcome, a plant growth situation comprehensive analysis system is established, and the optimal control mode is obtained through the optimal solution of the control strategy model, so that the energy consumption is reduced and the control precision and the crop yield are improved compared with the traditional agricultural equipment control mode;
2. according to the invention, multiple sensing data are fused, so that the sensing equipment can not only play a monitoring role but also serve as a controllable factor to be fed back to a plant growth environment, thereby playing a role in promoting plant growth regulation;
3. according to the invention, the edge calculation module is added, so that the data transmission and processing are faster and more flexible, the image processing technology is utilized, the damage of plant diseases and insect pests is comprehensively prevented, the crop yield is improved, and the possibility of green agriculture, digital agriculture and intelligent agriculture is changed;
4. according to the method, an optimal control mode is obtained through a control strategy model on the basis of fusion of multi-sensing data, data interaction is achieved with an Internet of things management cloud platform, and digital management is achieved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention.
In the drawings:
FIG. 1 is a block diagram of a plant growth management system with multi-state perception fusion according to the present invention;
FIG. 2 is a block diagram of a control strategy model of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments; all other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, the present invention provides a technical solution: a plant growth management system with multi-state perception fusion comprises a plant growth situation comprehensive analysis system, a sensing system, an image acquisition system, an edge computing system, a dimming system, an automation equipment system and an agricultural Internet of things management cloud platform;
plant growth situation comprehensive analysis system: the plant growth situation comprehensive analysis system is used for comprehensively analyzing, evaluating and controlling the growth situation of the plant, giving out a global optimal control strategy according to the overall evaluation result and controlling related equipment, integrates image acquisition data, GIS (geographic information system) geographic position information data, environment sensing detection data and an algorithm model library, is linked with edge calculation and adopts a digital circuit as a data transmission channel;
a sensing system: the sensing system is used for collecting information of a plant growing environment and packaging and sending data to the edge computing system according to a set time interval, the sensing system comprises a sensing equipment input end, a data storage module, a data transmission module and a data monitoring module, and the data monitoring module comprises a temperature and humidity sensor, a GIS (geographic information system), a light sensor, a CO2 sensor and a photosynthesis sensor;
an image acquisition system: the image acquisition system is used for acquiring plant images and video data of a planting area, scanning and shooting plants in the whole area according to a set time interval, and sending packed image video data to the edge computing system, and comprises a data storage module, a data transmission module and a camera module;
an edge computing system: the edge computing system is used for preprocessing and analyzing real-time data of a multi-channel sensor from the sensing system and image video data of the image acquisition system, transmitting the processed and analyzed data to the plant growth situation comprehensive analysis system, and performing related identification and detection tasks of plant types, growth stages, plant diseases and insect pests and growth situations;
a dimming system: the light adjusting system is used for controlling the on-off state, the power, the deflection angle and the irradiation duration of the light supplementing device according to the control instruction after receiving the control instruction from the plant growth situation comprehensive analysis system, so that the whole plant can obtain the optimal light supplementing effect;
an automated equipment system: the automatic equipment system is used for receiving the control instruction sent by the plant growth situation comprehensive analysis system and adjusting the on-off and working modes of the related equipment according to the control instruction;
agricultural thing networking management cloud platform: the agricultural Internet of things management cloud platform is used for receiving plant data sent by the plant growth situation comprehensive analysis system, performing control strategy model training on the plant data, combining the obtained data subjected to the control strategy model training with relevant data of an agricultural knowledge base to obtain final data, and feeding the final data back to the plant growth situation comprehensive analysis system, and comprises a data interface, a control strategy model training module, an agricultural knowledge base module and a cloud framework module.
The plant growth situation comprehensive analysis system is electrically connected with the sensing system, the image acquisition system, the edge computing system, the dimming system, the automation equipment system and the agricultural Internet of things management cloud platform; the image acquired by the image acquisition system comprises a mildew plant area image, a pest plant area image, an area growth distribution image, a plant growth stage image and a plant variety image; the processing of image video data by the edge computing system includes: firstly, identifying the plant region image of the plant diseases and insect pests: the regional positions of the insect pest and mildew plants are obtained through the image acquisition system, so that data are sent to the utilization dimming system, the illumination intensity and angle are adjusted, and insect pest and mildew treatment is carried out in time; secondly, identifying the plant variety and the growth stage image: the variety of the plant and the growth stage of the plant are analyzed through the image, so that the ratio of illumination, water fertilizer and the like can be adjusted in time according to different plants and different illumination, water fertilizer and the like required by different growth stages; and thirdly, identifying growth situation distribution images: plant growth situation is analyzed through images, and a regional growth situation distribution diagram is obtained through image comparison analysis; the automatic equipment system comprises an automatic curtain rolling machine, a water and fertilizer integrated machine, a ventilator and CO2An automatic controller; the control strategy model specifically takes various sensing data processed by the edge calculation module as data input; the plant model achieves the optimal growth situation as a target; low energy consumption and micro adjustment as constraint conditions; the growth situation evaluation result is output; the method is characterized by comprising the following steps of (1) solving an analysis model for reducing the adjustment amplitude and the equipment adjustment quantity as much as possible while achieving the optimal control output, and finally converting the output into a control instruction to carry out equipment control; the agricultural Internet of things management cloud platform is specifically a mobile phone or a small program of a webpage, a public service number or APP software; the cloud architecture of the cloud architecture module is specifically a private cloudOne or a combination of a plurality of mobile cloud, Unicom cloud, telecom cloud, IBM cloud or google cloud.
The method overcomes the defect that the overall optimal control mode cannot be obtained only by depending on a single factor in the traditional control, establishes a plant growth situation comprehensive analysis system, obtains the optimal control mode by optimizing and solving a control strategy model, and reduces energy consumption and improves control precision and crop yield compared with the traditional agricultural equipment control mode; the multi-sensing data are fused, so that the sensing equipment can not only play a monitoring role but also serve as a controllable factor to be fed back to a plant growth environment, and the plant growth regulation is promoted; the edge calculation module is added, so that data transmission and processing are faster and more flexible, the image processing technology is utilized, the damage of plant diseases and insect pests is comprehensively prevented, the crop yield is improved, and the possibility of green agriculture, digital agriculture and intelligent agriculture is changed.
As shown in fig. 1, a method for using a plant growth management system with fusion of polymorphic perception includes the following steps:
s1: data acquisition: collecting data information of a plant growing environment through a temperature and humidity sensor, a GIS (geographic information system), a light sensor, a CO2 sensor and a photosynthesis sensor of a sensing system, collecting plant images and video data of a planting area through a camera module of an image acquisition system, and sending the obtained data information, the plant images and the video data to an edge computing system according to a set time interval by the sensing system and the image acquisition system;
s2: data processing: after receiving the data, the edge computing system preprocesses and analyzes the data information, the plant image and the video data, identifies the plant region image of the plant diseases and insect pests, identifies the plant variety and the growth stage image and the growth situation distribution image, and sends the identified data to the plant growth situation comprehensive analysis system;
s3: data fusion: after receiving the data sent by the edge computing system, the plant growth situation comprehensive analysis system sends the data to an agricultural Internet of things management cloud platform, the agricultural Internet of things management cloud platform performs control strategy model training on the plant data, the data obtained through the control strategy model training is combined with the data related to an agricultural knowledge base to obtain fusion data, and the fusion data are fed back to the plant growth situation comprehensive analysis system;
s4: and (4) strategy output: after the plant growth situation comprehensive analysis system receives the fusion data, each instruction is sent to the corresponding dimming system and the corresponding automation equipment system according to the fusion data, the dimming system controls the on-off state, the power, the deflection angle and the irradiation duration of the light supplementing device, and the automation equipment system adjusts the on-off state and the working mode of the relevant equipment, so that the dynamic control with low energy consumption, micro-adjustment and high quality is realized.
By the method, on the basis of fusion of multi-sensing data, an optimal control mode is obtained by controlling the strategy model, data interaction with the Internet of things management cloud platform is achieved, and digital management is achieved.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (9)
1. A plant growth management system with multi-state perception fusion is characterized in that: the system comprises a plant growth situation comprehensive analysis system, a sensing system, an image acquisition system, an edge computing system, a dimming system, an automation equipment system and an agricultural Internet of things management cloud platform;
plant growth situation comprehensive analysis system: the plant growth situation comprehensive analysis system is used for comprehensively analyzing, evaluating and controlling the growth situation of the plant, giving out a global optimal control strategy according to the overall evaluation result and controlling related equipment, integrates image acquisition data, GIS (geographic information System) geographic position information data, environment sensing detection data and an algorithm model library, is linked with edge calculation and adopts a digital circuit as a data transmission channel;
a sensing system: the sensing system is used for collecting information of a plant growing environment and packaging and sending data to the edge computing system according to a set time interval, the sensing system comprises a sensing equipment input end, a data storage module, a data transmission module and a data monitoring module, and the data monitoring module comprises a temperature and humidity sensor, a GIS (geographic information system), a light sensor, a CO2 sensor and a photosynthesis sensor;
an image acquisition system: the image acquisition system is used for acquiring plant images and video data of a planting area, scanning and shooting plants in the whole area according to a set time interval, and sending packed image video data to the edge computing system, and comprises a data storage module, a data transmission module and a camera module;
an edge computing system: the edge computing system is used for preprocessing and analyzing real-time data from a multi-channel sensor of the sensing system and image video data of the image acquisition system, transmitting the processed and analyzed data to the plant growth situation comprehensive analysis system, and performing related identification and detection tasks of plant types, growth stages, plant diseases and insect pests and growth situations;
a dimming system: the light adjusting system is used for controlling the on-off state, the power, the deflection angle and the irradiation duration of the light supplementing device according to a control instruction after receiving the control instruction from the plant growth situation comprehensive analysis system, so that the whole plant can obtain the optimal light supplementing effect;
an automated equipment system: the automatic equipment system is used for receiving a control instruction sent by the plant growth situation comprehensive analysis system and adjusting the on-off and working modes of relevant equipment according to the control instruction;
agricultural thing networking management cloud platform: the agricultural Internet of things management cloud platform is used for receiving plant data sent by the plant growth situation comprehensive analysis system, performing control strategy model training on the plant data, combining the obtained data subjected to the control strategy model training with relevant data of an agricultural knowledge base to obtain final data, and feeding the final data back to the plant growth situation comprehensive analysis system, and comprises a data interface, a control strategy model training module, an agricultural knowledge base module and a cloud framework module.
2. A polymorphic potential perception fused plant growth management system according to claim 1, wherein: the plant growth situation comprehensive analysis system is electrically connected with the sensing system, the image acquisition system, the edge computing system, the dimming system, the automation equipment system and the agricultural Internet of things management cloud platform.
3. A polymorphic potential perception fused plant growth management system according to claim 1, wherein: the image acquired by the image acquisition system comprises a mildew plant area image, a pest plant area image, an area growth distribution image, a plant growth stage image and a plant variety image.
4. A polymorphic potential perception fused plant growth management system according to claim 1, wherein: the processing of image video data by the edge computing system comprises: firstly, identifying the plant region image of the plant diseases and insect pests: the regional positions of the insect pest and mildew plants are obtained through the image acquisition system, so that data are sent to the utilization dimming system, the illumination intensity and angle are adjusted, and insect pest and mildew treatment is carried out in time; secondly, identifying the plant variety and the growth stage image: the variety of the plant and the growth stage of the plant are analyzed through the image, so that the ratio of illumination, water fertilizer and the like can be adjusted in time according to different plants and different illumination, water fertilizer and the like required by different growth stages; and thirdly, identifying growth situation distribution images: and (4) analyzing the plant growth situation through images, and obtaining a regional growth situation distribution diagram through image comparison analysis.
5. A polymorphic potential perception fused plant growth management system according to claim 1, wherein: the automatic equipment system comprises an automatic curtain rolling machine, a water and fertilizer integrated machine, a ventilator and CO2An automatic controller.
6. A polymorphic potential perception fused plant growth management system according to claim 1, wherein: the control strategy model specifically takes various sensing data processed by the edge calculation module as data input; the plant model achieves the optimal growth situation as a target; low energy consumption and micro adjustment as constraint conditions; the growth situation evaluation result is output; the method is an analysis model which can reduce the adjustment amplitude and the equipment adjustment quantity as much as possible while achieving the optimal control output, and finally converts the output into a control command to carry out equipment control.
7. A polymorphic potential perception fused plant growth management system according to claim 1, wherein: the agricultural Internet of things management cloud platform is specifically a mobile phone or a webpage applet, a public service number or APP software.
8. A polymorphic potential perception fused plant growth management system according to claim 1, wherein: the cloud architecture of the cloud architecture module is specifically one or a combination of several of a private cloud, a mobile cloud, a Unicom cloud, a telecom cloud, an IBM cloud and a google cloud.
9. Use of a polymorphic potential perception fused plant growth management system according to any of claims 1 to 8, wherein: the method comprises the following steps:
s1: data acquisition: collecting data information of a plant growing environment through a temperature and humidity sensor, a GIS (geographic information system), a light sensor, a CO2 sensor and a photosynthesis sensor of a sensing system, collecting plant images and video data of a planting area through a camera module of an image acquisition system, and sending the obtained data information, the plant images and the video data to an edge computing system according to a set time interval by the sensing system and the image acquisition system;
s2: data processing: after receiving the data, the edge computing system preprocesses and analyzes the data information, the plant image and the video data, identifies the plant region image of the plant diseases and insect pests, identifies the plant variety and the growth stage image and the growth situation distribution image, and sends the identified data to the plant growth situation comprehensive analysis system;
s3: data fusion: after receiving the data sent by the edge computing system, the plant growth situation comprehensive analysis system sends the data to an agricultural Internet of things management cloud platform, the agricultural Internet of things management cloud platform performs control strategy model training on the plant data, the data obtained through the control strategy model training is combined with the data related to an agricultural knowledge base to obtain fusion data, and the fusion data are fed back to the plant growth situation comprehensive analysis system;
s4: and (4) strategy output: after the plant growth situation comprehensive analysis system receives the fusion data, each instruction is sent to the corresponding dimming system and the corresponding automation equipment system according to the fusion data, the dimming system controls the on-off state, the power, the deflection angle and the irradiation duration of the light supplementing device, and the automation equipment system adjusts the on-off state and the working mode of the relevant equipment, so that the dynamic control with low energy consumption, micro-adjustment and high quality is realized.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114911174A (en) * | 2022-02-09 | 2022-08-16 | 北大荒信息有限公司 | Plant bionic method and device |
| CN116934519A (en) * | 2023-09-19 | 2023-10-24 | 四川省商投信息技术有限责任公司 | Digital agriculture management method and device based on edge computing gateway |
| CN117172505A (en) * | 2023-09-27 | 2023-12-05 | 广东省农业科学院农业经济与信息研究所 | Crop planting state monitoring method and system based on Internet of things |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114911174A (en) * | 2022-02-09 | 2022-08-16 | 北大荒信息有限公司 | Plant bionic method and device |
| CN116934519A (en) * | 2023-09-19 | 2023-10-24 | 四川省商投信息技术有限责任公司 | Digital agriculture management method and device based on edge computing gateway |
| CN116934519B (en) * | 2023-09-19 | 2024-01-09 | 四川省商投信息技术有限责任公司 | Digital agriculture management method and device based on edge computing gateway |
| CN117172505A (en) * | 2023-09-27 | 2023-12-05 | 广东省农业科学院农业经济与信息研究所 | Crop planting state monitoring method and system based on Internet of things |
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