CN115984026A - Intelligent agricultural management system based on cloud computing - Google Patents
Intelligent agricultural management system based on cloud computing Download PDFInfo
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Abstract
The application provides a cloud computing-based intelligent agricultural management system which comprises a data acquisition module, an Internet of things platform, a cloud computing platform and an equipment control module, wherein the data acquisition module can realize comprehensive acquisition of initial agricultural data and automatically upload the initial agricultural data to the Internet of things platform for storage; the Internet of things platform can realize the pretreatment of initial agricultural data, so that the target agricultural data obtained after the pretreatment can be conveniently analyzed by the cloud computing platform; the cloud computing platform can realize omnibearing correlation analysis on a large amount of target agricultural data by utilizing a mass data storage technology and distributed computing capacity of cloud computing, the accuracy of target agricultural data identification is improved, the field equipment can be uniformly scheduled timely and accurately through the equipment control module based on an analysis result, automatic remote control on the field equipment is realized, and the field agricultural environment can be controlled more truly, comprehensively and accurately.
Description
Technical Field
The application relates to the technical field of agricultural management, in particular to an intelligent agricultural management system based on cloud computing.
Background
With the development of society and the progress of science and technology, the agriculture in China is developed more and more rapidly, under the promotion of the rapid development of modern computers and electronic technologies, the traditional extensive agricultural production mode gradually transits to intelligent agriculture, and the intelligent agriculture is a high-efficiency, low-consumption and environment-friendly emerging agricultural production mode integrating technologies such as Internet of things, internet, wireless communication and the like, is a new direction of agricultural development, and is also an important application of the Internet of things technology in modern agricultural production. The intelligent agriculture reduces the production cost and energy consumption by reasonably and efficiently utilizing agricultural resources; wisdom agricultural uses internet technology as the extension, realizes remote data transmission and bottom equipment control.
However, for agricultural management, monitoring and control in the environment of the internet of things, a relatively perfect and mature technical scheme still does not exist domestically, and the traditional agricultural management system can only perform local control, and adopts complicated lines to connect various data acquisition and transmission devices, so that the system is poor in reliability and stability. Meanwhile, agricultural data acquired by the traditional agricultural Internet of things mode are various in types and large in data quantity, and field devices work independently, so that comprehensive and accurate analysis on a large amount of agricultural data is difficult to perform, and timely and accurate unified scheduling is performed on the field devices.
Disclosure of Invention
The application provides a wisdom agricultural management system based on cloud to solve the problem that it is difficult to make comprehensive accurate analysis and carry out timely accurate unified dispatch to field device to a large amount of agricultural data that prior art exists.
In order to solve the above problems, the present application adopts the following technical solutions:
in a first aspect, the embodiment of the application provides a cloud computing-based smart agricultural management system, which is characterized by comprising a data acquisition module, an internet of things platform, a cloud computing platform and an equipment control module; the data acquisition module and the equipment control module are both connected with the Internet of things platform, and the Internet of things platform is connected with the cloud computing platform;
the data acquisition module is used for acquiring initial agricultural data and sending 5 the initial agricultural data to the Internet of things platform;
the Internet of things platform is used for storing and preprocessing the initial agricultural data and sending the preprocessed target agricultural data to the cloud computing platform;
the cloud computing platform is used for storing and analyzing target agricultural data, generating a first control instruction for first target equipment based on an analysis result, and sending the first control instruction to the Internet of things platform 0 so that the Internet of things platform sends the first control instruction to the equipment control module;
and the device control module is used for responding to the first control instruction and controlling the first target device to execute the action corresponding to the first control instruction.
In an embodiment of the present application, the data acquisition module includes a plurality of sensor nodes and a plurality of convergence 5 node; the plurality of sink nodes are connected with the Internet of things platform, and each sink node is connected with a plurality of sensor nodes corresponding to the sink node;
the sensor nodes are used for acquiring the initial agricultural data and sending the initial agricultural data to the corresponding sink nodes; wherein different sensor nodes correspond to different types of initial agricultural data, the initial agricultural data including environmental data and/or crop biological data;
the aggregation node 0 is used for acquiring initial agricultural data sent by sensor nodes in a preset range corresponding to the aggregation node and sending the initial agricultural data to the Internet of things platform; different aggregation nodes correspond to different preset ranges.
In an embodiment of the present application, the data acquisition module further includes a data classification unit; the data classification unit is respectively connected with the Internet of things platform and the plurality of sink nodes;
the aggregation node is used for acquiring initial agricultural data sent by the sensor nodes in a preset range corresponding to the aggregation node and sending the initial agricultural data to the data classification unit;
the data classification unit is used for classifying the initial agricultural data according to the type of the initial agricultural data and sending the classified initial agricultural data to the Internet of things platform.
In an embodiment of the application, the internet of things platform comprises an analysis module and a formatting module;
the analysis module is used for verifying and analyzing the data packet sent by the data acquisition module to obtain the initial agricultural data and sending the initial agricultural data to the formatting module;
the formatting module is used for formatting different types of initial agricultural data 5 according to different data formats to obtain the target agricultural data; different types of initial agricultural data correspond to different data formats.
In an embodiment of the present application, the device control module includes an instruction forwarding unit and a plurality of device nodes; the instruction forwarding unit is respectively connected with the plurality of equipment nodes; different target devices corresponding to different device nodes;
0, the instruction forwarding unit is configured to obtain the first control instruction sent by the internet of things platform,
analyzing the first control instruction, determining the first target equipment, and sending the first control instruction to the first target equipment;
and the first target device is used for responding to the first control instruction and executing the action corresponding to the first control instruction.
In an embodiment of the present application, the system further includes a smart agriculture management platform connected to the cloud computing platform, where the smart agriculture management platform includes a real-time monitoring module;
the real-time monitoring module is used for responding to a first query instruction triggered by a user and displaying the target agricultural data in real time;
the real-time monitoring module is further used for responding to a second control 0 command triggered by a user aiming at a second target device, and sending the second control command to the cloud computing platform;
the cloud computing platform is further configured to send the second control instruction to the internet of things platform, so that the internet of things platform sends the second control instruction to the device control module;
and the device control module is used for responding to the second control instruction and controlling the second target device to execute the action corresponding to the second control instruction.
In an embodiment of the present application, the smart agriculture management platform further includes a log report statistics module;
the log report form counting module is used for acquiring target agricultural data in a preset historical time period and historical control instructions sent by the Internet of things platform to the equipment control module, and generating a log report form based on the target agricultural data and the historical control instructions.
In an embodiment of the present application, the smart agriculture management platform further includes an early warning module;
the early warning module is used for judging abnormal values of the target agricultural data and sending early warning information corresponding to the abnormal agricultural data to a preset terminal under the condition that the abnormal agricultural data is detected in the target agricultural data.
In an embodiment of the present application, the smart agriculture management platform further includes an intelligent management module;
the intelligent management module is used for acquiring dynamic adjustment parameters input by a user and sending the dynamic adjustment parameters to the cloud computing platform;
the cloud computing platform is further configured to generate a dynamic adjustment instruction for the third target device based on the dynamic adjustment parameter, and send the dynamic adjustment instruction to the internet of things platform, so that the internet of things platform sends the dynamic adjustment instruction to the device control module;
and the device control module is used for responding to the dynamic adjustment instruction and controlling the third target device to operate according to the dynamic adjustment parameter.
In an embodiment of the present application, the smart agriculture management platform further includes a rights management module;
the authority management module is used for determining the user role of the user according to the login information input by the user; different user roles correspond to different system permissions.
Compared with the prior art, the method has the following advantages:
the intelligent agricultural management system based on cloud computing comprises a data acquisition module, an Internet of things platform, a cloud computing platform and an equipment control module, wherein the data acquisition module can comprehensively acquire initial agricultural data and automatically upload the initial agricultural data to the Internet of things platform for storage, so that the reliability and stability of the system are improved; the Internet of things platform can realize the pretreatment of initial agricultural data, so that the target agricultural data obtained after the pretreatment can be conveniently analyzed by the cloud computing platform; the cloud computing platform can realize all-round correlation analysis of a large amount of target agricultural data by utilizing mass data storage technology and distributed computing capability of cloud computing, improves the accuracy of target agricultural data identification, can carry out timely and accurate unified scheduling on field equipment through the equipment control module based on an analysis result, realizes automatic remote control on the field equipment, and can control the field agricultural environment more truly, comprehensively and accurately.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic structural diagram of a smart agriculture management system based on cloud computing according to an embodiment of the present application.
Fig. 2 is a schematic structural diagram of an intelligent agriculture management platform according to an embodiment of the present application.
Reference numerals are as follows: 101-a data acquisition module; 102-an internet of things platform; 103-a cloud computing platform; 104-a device control module; 105-an intelligent agricultural management platform; 1051-a real-time monitoring module; 1052-log report statistics module; 1053-an early warning module; 1054-intelligent management module; 1055-rights management module.
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.
The seasonal characteristic of agricultural production is required to be explained, and the greenhouse can help to overcome the seasonal characteristic of agricultural production and improve the agricultural production efficiency. Environmental factors influencing the growth of crops in the greenhouse include temperature, humidity, soil pH value, soil moisture content and the like. In order to achieve efficiency and quality improvement of agricultural production, it is important to monitor the above-mentioned various environmental parameters and the life and quality of animals and plants. The prior greenhouse environment control device is mainly controlled manually, can only control partial parameters, needs people to control various actuators by means of production experience of the people, needs people to walk into a greenhouse or control equipment to manually start the equipment around, cannot remotely measure and control the environment parameters of the greenhouse, cannot meet the requirements of informatization and networking of agricultural production technology, and has low automation degree and poor temperature control performance. When the agricultural production scale is large, various sensors need to be arranged at each production site to collect agricultural data, and complicated lines are adopted to connect each data collection device, so that the system reliability and stability are poor. Meanwhile, agricultural data acquired by various sensors are various in types and large in data quantity, and field devices work independently, so that comprehensive and accurate analysis of a large amount of agricultural data is difficult to perform, and timely and accurate unified scheduling is performed on the field devices.
Aiming at the problems that comprehensive and accurate analysis on a large amount of agricultural data is difficult to perform and timely and accurate unified scheduling on field equipment is difficult to perform in the prior art, the application aims to provide the intelligent agricultural management system based on cloud computing.
Referring to fig. 1, a cloud computing-based smart agriculture management system according to the present application is shown, and includes a data acquisition module 101, an internet of things platform 102, a cloud computing platform 103, and an equipment control module 104; the data acquisition module 101 and the equipment control module 104 are both connected with the internet of things platform 102, and the internet of things platform 102 is connected with the cloud computing platform 103.
In this embodiment, the data acquisition module 101 is configured to acquire initial agricultural data and send the initial agricultural data to the internet of things platform 102. Specifically, the data acquisition module 101 includes various sensors, specifically three sensors including a physical property sensor, a biosensor and a micro-electromechanical sensor, wherein the physical property sensor is a sensor for converting signals by using physical changes thereof, for example, a thermistor sensor can detect a temperature of a target area, and a photoelectric sensor can detect light irradiation of the target area; the biosensor is an instrument which is sensitive to biological substances and converts the concentration of the biological substances into an electric signal for detection, and is an analysis tool or system which is composed of an immobilized biological sensitive material as a recognition element (comprising biological active substances such as enzyme, antibody, antigen, microorganism, cell, tissue, nucleic acid and the like), a proper physicochemical transducer (such as an oxygen electrode, a photosensitive tube, a field effect tube, a piezoelectric crystal and the like) and a signal amplification device, and biological data of crops can be collected through the biosensor, such as parameters representing the life and quality of animals and plants, such as the oxygen content of plants and the like; the micro-electromechanical sensor is a novel sensor manufactured by adopting micro-electronics and micro-machining technology, compared with the traditional sensor, the micro-electromechanical sensor has the characteristics of small volume, light weight, low cost, low power consumption, high reliability, suitability for batch production, easiness in integration and realization of intellectualization, and can also utilize the micro-electromechanical sensor to monitor environmental data such as illumination, temperature and humidity, soil pH value, soil moisture content and the like of a target area.
In this embodiment, the internet of things platform 102 is configured to store and preprocess the initial agricultural data, and send the preprocessed target agricultural data to the cloud computing platform 103. Specifically, the internet of things platform 102 can store the collected initial agricultural data including the environmental data and the crop biological data, and meanwhile, the internet of things platform 102 further has a data processing function and can preprocess the collected data, so that the preprocessed target agricultural data can be analyzed by the cloud computing platform 103 conveniently. If errors occur in acquisition or data processing is abnormal, the system can be automatically repaired and restarted. The internet of things platform 102 can also control and adjust the environment by controlling temperature reduction and temperature rise, irrigation, fertilization, illumination and the like after analyzing the crop environment data.
In this embodiment, the cloud computing platform 103 is configured to store and analyze the target agricultural data, generate a first control instruction for the first target device based on the analysis result, and send the first control instruction to the internet of things platform 102, so that the internet of things platform 102 sends the first control instruction to the device control module 104. The device control module 104 is configured to, in response to the first control instruction, control the first target device to execute an action corresponding to the first control instruction.
In a particular implementation, the device control module 104 includes an instruction forwarding unit and a plurality of device nodes; the instruction forwarding unit is respectively connected with a plurality of equipment nodes; different target devices corresponding to different device nodes. The instruction forwarding unit is used for acquiring a first control instruction sent by the internet of things platform 102, analyzing the first control instruction, determining first target equipment, and sending the first control instruction to the first target equipment; the first target device is used for responding to the first control instruction and executing the action corresponding to the first control instruction.
In this embodiment, the cloud computing platform 103 may perform regional division on the target agricultural data according to different regions, for example, when the number of greenhouses is n, the target agricultural data may be divided into n data packets according to an ID address pre-marked on the initial agricultural data when the data acquisition module 101 acquires data, and then the target agricultural data corresponding to n greenhouses is subjected to distributed computation by using the distributed computing capability of the cloud computing platform 103 to obtain an analysis result in each greenhouse, and then the field device in each greenhouse is controlled according to the analysis result corresponding to each greenhouse. For example, when the cloud computing platform 103 detects that both the illumination intensity and the temperature of the greenhouse a do not reach the standard values, at this time, the cloud computing platform 103 determines a target device a for adjusting the illumination intensity of the greenhouse a and a target device b for adjusting the temperature from a device list stored in advance, generates a control instruction packet for the target device a and the target device b, and sends the control instruction packet to the internet of things platform 102, so that the internet of things platform 102 sends the control instruction packet to the target device control module 104, and an instruction forwarding unit in the target device control module 104 analyzes the control instruction packet to obtain the control instruction a for the target device a and the control instruction b for the target device b, respectively. The instruction forwarding unit sends the control instruction a to the target device a so that the target device a can execute the action corresponding to the control instruction a and adjust the illumination intensity of the greenhouse A to the illumination standard value, and meanwhile, the instruction forwarding unit sends the control instruction b to the target device b so that the target device b can execute the action corresponding to the control instruction b and adjust the temperature of the greenhouse A to the temperature standard value.
In the embodiment, the data acquisition module 101 can realize comprehensive acquisition of initial agricultural data and automatically upload the initial agricultural data to the internet of things platform 102 for storage in a wireless communication manner, so that the reliability and stability of the system can be improved; the internet of things platform 102 can realize the preprocessing of the initial agricultural data, so that the target agricultural data obtained after preprocessing can be conveniently analyzed by the cloud computing platform 103; the cloud computing platform 103 can realize all-around correlation analysis of a large amount of target agricultural data by utilizing a mass data storage technology and distributed computing capability of cloud computing, improve the accuracy of target agricultural data identification, and can perform timely and accurate unified scheduling on field devices through the device control module 104 based on an analysis result, realize automatic remote control on the field devices, and control the field agricultural environment more truly, comprehensively and accurately.
In one possible embodiment, the data collection module 101 includes a plurality of sensor nodes and a plurality of sink nodes; the plurality of aggregation nodes are connected with the internet of things platform 102, and each aggregation node is connected with a plurality of sensor nodes corresponding to each aggregation node. The sensor nodes are used for acquiring initial agricultural data and sending the initial agricultural data to the corresponding sink nodes; the aggregation node is used for acquiring initial agricultural data sent by the sensor node in a preset range corresponding to the aggregation node and sending the initial agricultural data to the internet of things platform 102; different aggregation nodes correspond to different preset ranges.
In this embodiment, different types of sensors are used to collect different types of initial agricultural data, including environmental data and/or crop biological data;
in this embodiment, the same number of aggregation nodes may be set in units of greenhouses, a preset range corresponding to each aggregation node is an area where the greenhouses corresponding to the aggregation node are located, and each aggregation node is connected to a sensor node in the corresponding greenhouses to obtain different initial agricultural data in the same greenhouses. In specific implementation, each sink node can also add an ID address corresponding to the greenhouse where the sink node is located to the acquired initial agricultural data, so as to facilitate subsequent data processing.
In this embodiment, the data acquisition module 101 may further include a data classification unit; the data classification unit is respectively connected with the internet of things platform 102 and the plurality of sink nodes. The sink node is used for acquiring initial agricultural data sent by the sensor nodes within a preset range and sending the initial agricultural data to the data classification unit; the data classification unit is used for classifying the initial agricultural data according to the type of the initial agricultural data and sending the classified initial agricultural data to the internet of things platform 102.
In the embodiment, the initial agricultural data are classified through the data classification unit, so that a large amount of initial agricultural data can be effectively integrated, and the subsequent data processing efficiency is improved.
In this embodiment, after classifying the initial agricultural data, the data classification unit may encrypt the classified initial agricultural data according to a preset private key, and upload the encrypted data packet to the internet of things platform 102, so as to ensure confidentiality and security of data transmission.
In one possible embodiment, the internet of things platform 102 includes a parsing module and a formatting module; the analysis module is used for verifying and analyzing the data packet sent by the data acquisition module 101 to obtain initial agricultural data and sending the initial agricultural data to the formatting module; the formatting module is used for formatting different types of initial agricultural data according to different data formats to obtain target agricultural data; different types of initial agricultural data correspond to different data formats.
In this embodiment, after receiving the encrypted data packet uploaded by the data classification unit, the parsing module performs verification parsing on the data packet to obtain initial agricultural data, and the formatting module performs formatting processing on the initial agricultural data to process the same type of data into the same data format, for example, unifies units of the same type of data, so that subsequent data processing can be more accurate.
In one possible embodiment, with continued reference to fig. 1, the cloud computing-based smart agriculture management system further includes a smart agriculture management platform 105 connected to the cloud computing platform 103, and with reference to fig. 2, the smart agriculture management platform 105 may specifically include a real-time monitoring module 1051.
In this embodiment, the real-time monitoring module 1051 is configured to display the target agricultural data in real time in response to a first query instruction triggered by a user.
In this embodiment, the user can log in the smart agriculture management platform 105 to check the relevant agriculture data of the agriculture production site. Specifically, the real-time monitoring module 1051 can analyze various target agricultural data of the agricultural production site stored by the cloud computing platform 103 according to a first query instruction triggered by a user, and display the target agricultural data to the user in an intuitive graph and/or curve manner.
In this embodiment, the real-time monitoring module 1051 is further configured to send a second control instruction to the cloud computing platform 103 in response to the second control instruction triggered by the user for the second target device; cloud computing
The platform 103 is further configured to send a second control instruction to the internet of things platform 102, so that the internet of things platform 1025 sends the second control instruction to the device control module 104; device control module 104 for responding to
And the second control instruction controls the second target equipment to execute the action corresponding to the second control instruction.
In this embodiment, the user can manually control the field device, such as manually adjusting the field agricultural environment, based on the query result.
For example, the user may adjust the parameters of the on-site agricultural environment by 0 through the real-time monitoring module 1051, for example, the temperature parameter set for the greenhouse a is 24 ℃, and the user may adjust the parameters according to different crops
The growth requirement of the stage needs to be adjusted to 26 ℃ at 24 ℃, and at this time, the user can modify 24 ℃ to 26 ℃ through the real-time monitoring module 1051. The real-time monitoring module 1051 sends a second control instruction representing that the temperature of the greenhouse a is adjusted to 26 ℃ to the internet of things platform 102, the internet of things platform 102 sends the second control instruction to the equipment control module 104, and the instruction forwarding module 5 of the equipment control module 104 analyzes the second control instruction, determines a second target equipment for adjusting the temperature of the greenhouse a, and sends the second control instruction to the second target equipment; the second target device adjusts the temperature of the greenhouse a from the adjustment of 24 ℃ to 26 ℃ in response to the second control instruction.
In a possible implementation manner, with continued reference to fig. 2, the smart agriculture management platform 105 further includes a log report statistics module 1052, where the log report statistics module 1052 is configured to obtain the target agriculture data in the preset historical time period 0 and the historical control instruction sent by the internet of things platform 102 to the device control module 104, and generate a log statistical report based on the target agriculture data and the historical control instruction.
In this embodiment, the log report statistics module 1052 can obtain log records of the internet of things platform 102 on agricultural environment monitoring and control actions, specifically including environment and crop change data and user operation records.
For example, the log report statistics module 1052 may update the crop monitoring daily report, the crop monitoring weekly report, and/or the crop monitoring monthly report on a daily, weekly, and/or monthly basis to show the agricultural environmental change of the crop, the crop growth, and the user's operational records triggered for the field devices on a daily, weekly, and/or monthly basis.
In a possible embodiment, with reference to fig. 2, the smart agricultural management platform 105 further includes an early warning module 1053, and the early warning module 1053 is configured to determine an abnormal value of the target agricultural data, and send early warning information corresponding to the abnormal agricultural data to the preset terminal when the abnormal agricultural data is detected in the target agricultural data.
In the embodiment, the standard value and the parameter threshold value of the crop growth environment can be set by combining actual conditions and objective requirements in the production environment, different types of agricultural data correspond to different parameter threshold values, when the target agricultural data of the field environment exceeds the corresponding parameter threshold value, the abnormal agricultural data in the target agricultural data is determined, at the moment, early warning information can be sent to a preset terminal in the modes of short messages, mails, pushing of a third-party platform and the like, and workers can be prompted to go to the field for field investigation in time to perform corresponding abnormal treatment. By performing exception alarm on the field agricultural data through the early warning module 1053, serious problems existing in a production field can be found in time, and the exception handling efficiency is improved.
In one possible embodiment, with continued reference to fig. 2, the smart agriculture management platform 105 further includes an intelligent management module 1054, the intelligent management module 1054 is configured to obtain the dynamic adjustment parameters input by the user, and send the dynamic adjustment parameters to the cloud computing platform 103; the cloud computing platform 103 is further configured to generate a dynamic adjustment instruction for the third target device based on the dynamic adjustment parameter, and send the dynamic adjustment instruction to the internet of things platform 102, so that the internet of things platform 102 sends the dynamic adjustment instruction to the device control module 104; the device control module 104 is further configured to control the third target device to operate according to the dynamic adjustment parameter in response to the dynamic adjustment instruction.
In this embodiment, the user may also enter the intelligent agricultural management platform 105, and set the dynamic adjustment parameters of the field device according to the different agricultural environments required by the crops in different growth stages, such as setting the parameters of illumination parameter, temperature parameter, humidity parameter, soil ph value, etc. of a certain greenhouse in different periods of a week; after acquiring the dynamic adjustment parameters, the cloud computing platform 103 generates dynamic adjustment instructions for the third target device based on the dynamic adjustment parameters, and sends the corresponding dynamic adjustment instructions to the internet of things platform 102 at different times based on time information included in the dynamic adjustment parameters, and the internet of things platform 102 sends the dynamic adjustment instructions to the device control module 104 first, so that the device control module 104 controls the third target device to operate according to the dynamic adjustment parameters, and the field device can execute corresponding operations at different times.
In this embodiment, the user can realize long-term intelligent dynamic adjustment of the field device through the intelligent management module 1054, thereby effectively reducing the input of labor cost and achieving better intelligence and automation.
In one possible embodiment, with continued reference to fig. 2, the smart agriculture management platform 105 further includes a rights management module 1055, and the rights management module 1055 is configured to determine user roles of the users according to the login information input by the users, wherein different user roles correspond to different system rights.
In this embodiment, the authority management module 1055 may set different user roles according to different persons. Specifically, the user roles may include a visitor, a general user, and a management user, wherein the visitor only displays relevant introduction information about the smart agriculture management platform 105 after entering the smart agriculture management platform 105; after entering the intelligent agriculture management platform 105 and passing user authentication, a common user can check agricultural data of an agricultural field in an area bound by the user; after entering the intelligent agricultural management platform 105 and passing user authentication, a management user can not only check related agricultural data, but also manually control the field device through a management interface, control the field device to perform operations such as temperature reduction and temperature rise, fertilization, weeding, irrigation and the like, or set operating parameters of an agricultural environment, and set parameters such as illumination intensity, temperature and humidity, soil acidity and alkalinity of the field.
In the embodiment, different user roles are set, various user permissions are determined, management resources can be reasonably distributed, the management efficiency is effectively improved, and unified scheduling management of the field devices is facilitated.
In the embodiment, the intelligent agriculture management platform 105 is combined with the cloud computing platform 103 to perform coordinated management on the field agriculture environment and the field equipment, so that the environment data monitoring and the environment control can be quickly and accurately responded. Under the condition that a user accurately knows the crop growth environment through the intelligent agricultural management platform 105, agricultural resources such as water and fertilizer can be reasonably utilized, waste of the water and fertilizer is avoided, water and fertilizer deficiency in the crop growth process is avoided, and quality guarantee and yield increase are facilitated; meanwhile, manpower and material resources can be saved, trouble, labor and money are wasted in troubleshooting of a traditional limited transmission mode, equipment layout is lack of flexibility, data are acquired by using a sensor in the intelligent agriculture, the data are wirelessly transmitted, manual fixed-point acquisition at regular time is not needed, a large number of data transmission cables are not needed to be arranged, compared with the traditional data recording mode, the data are recorded manually and then recorded into a computer, the probability of misreading and missing recording is high, efficiency is not high, the implementation mode can store sensor data in an automatic lasting classification mode, cloud backup can be carried out, and the high efficiency, accuracy and safety of data storage are guaranteed.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, apparatus, or computer program product. Accordingly, embodiments of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present invention may 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, and the like) having computer-usable program code embodied therein.
Embodiments of the present invention are described with reference to flowchart illustrations and/or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing terminal to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing terminal to cause a series of operational steps to be performed on the computer or other programmable terminal to produce a computer implemented process such that the instructions which execute on the computer or other programmable terminal provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications of these embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the embodiments of the invention.
Finally, it should also be 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. Furthermore, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or terminal 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 terminal
An article or a terminal device. Without further limitation, an element defined by the phrase "comprising 5 of 8230, does not exclude the inclusion of a process, method, article, or the end use of the element
Additional identical elements are present in the end device.
The cloud computing-based intelligent agricultural management system provided by the invention is described in detail above, and specific examples are applied in the text to explain the principle and the implementation mode of the invention so as to
The above description of the embodiments is only intended to facilitate the understanding of the method of the invention and its core ideas; meanwhile, for those skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (10)
1. A smart agricultural management system based on cloud computing is characterized by comprising a data acquisition module, an Internet of things platform, a cloud computing platform and an equipment control module; the data acquisition module and the equipment control module are both connected with the Internet of things platform, and the Internet of things platform is connected with the cloud computing platform;
the data acquisition module is used for acquiring initial agricultural data and sending the initial agricultural data to the Internet of things platform;
the Internet of things platform is used for storing and preprocessing the initial agricultural data and sending the preprocessed target agricultural data to the cloud computing platform;
the cloud computing platform is used for storing and analyzing target agricultural data, generating a first control instruction for first target equipment based on an analysis result, and sending the first control instruction to the Internet of things platform so that the Internet of things platform sends the first control instruction to the equipment control module;
and the device control module is used for responding to the first control instruction and controlling the first target device to execute the action corresponding to the first control instruction.
2. The cloud computing-based smart agriculture management system of claim 1, wherein the data collection module comprises a plurality of sensor nodes and a plurality of aggregation nodes; the plurality of sink nodes are connected with the Internet of things platform, and each sink node is connected with a plurality of sensor nodes corresponding to the sink node;
the sensor node is used for acquiring the initial agricultural data and sending the initial agricultural data to the corresponding sink node; wherein different sensor nodes correspond to different types of initial agricultural data, the initial agricultural data including environmental data and/or crop biological data;
the aggregation node is used for acquiring initial agricultural data sent by the sensor node in a preset range corresponding to the aggregation node and sending the initial agricultural data to the Internet of things platform; different aggregation nodes correspond to different preset ranges.
3. The cloud-computing-based smart agricultural management system of claim 2, wherein the data collection module further comprises a data classification unit; the data classification unit is respectively connected with the Internet of things platform and the plurality of sink nodes;
the aggregation node is used for acquiring initial agricultural data sent by the sensor nodes in a preset range corresponding to the aggregation node and sending the initial agricultural data to the data classification unit;
the data classification unit is used for classifying the initial agricultural data according to the type of the initial agricultural data and sending the classified initial agricultural data to the Internet of things platform.
4. The cloud computing-based smart agricultural management system of claim 1, wherein the internet of things platform comprises a parsing module and a formatting module;
the analysis module is used for verifying and analyzing the data packet sent by the data acquisition module to obtain the initial agricultural data and sending the initial agricultural data to the formatting module;
the formatting module is used for formatting different types of initial agricultural data according to different data formats to obtain the target agricultural data; different types of initial agricultural data correspond to different data formats.
5. The cloud computing-based smart agriculture management system of claim 1, wherein the device control module comprises an instruction forwarding unit and a plurality of device nodes; the instruction forwarding unit is respectively connected with the plurality of equipment nodes; different target devices corresponding to different device nodes;
the instruction forwarding unit is configured to acquire the first control instruction sent by the internet of things platform, analyze the first control instruction, determine the first target device, and send the first control instruction to the first target device;
and the first target device is used for responding to the first control instruction and executing the action corresponding to the first control instruction.
6. The cloud computing-based smart agricultural management system of claim 1, further comprising a smart agricultural management platform connected to the cloud computing platform, the smart agricultural management platform including a real-time monitoring module;
the real-time monitoring module is used for responding to a first query instruction triggered by a user and displaying the target agricultural data in real time;
the real-time monitoring module is further used for responding to a second control instruction triggered by a user aiming at a second target device, and sending the second control instruction to the cloud computing platform;
the cloud computing platform is further configured to send the second control instruction to the internet of things platform, so that the internet of things platform sends the second control instruction to the device control module;
and the device control module is used for responding to the second control instruction and controlling the second target device to execute the action corresponding to the second control instruction.
7. The cloud computing-based smart agriculture management system of claim 6, wherein the smart agriculture management platform further comprises a log report statistics module;
the log report counting module is used for acquiring target agricultural data in a preset historical time period and historical control instructions sent by the Internet of things platform to the equipment control module, and generating a log counting report based on the target agricultural data and the historical control instructions.
8. The cloud computing-based smart agricultural management system of claim 6, wherein the smart agricultural management platform further comprises an early warning module;
the early warning module is used for judging abnormal values of the target agricultural data and sending early warning information corresponding to the abnormal agricultural data to a preset terminal under the condition that the abnormal agricultural data is detected in the target agricultural data.
9. The cloud-computing-based smart agriculture management system of claim 6, wherein the smart agriculture management platform further comprises a smart management module;
the intelligent management module is used for acquiring dynamic adjustment parameters input by a user and sending the dynamic adjustment parameters to the cloud computing platform;
the cloud computing platform is further configured to generate a dynamic adjustment instruction for the third target device based on the dynamic adjustment parameter, and send the dynamic adjustment instruction to the internet of things platform, so that the internet of things platform sends the dynamic adjustment instruction to the device control module;
and the device control module is used for responding to the dynamic adjustment instruction and controlling the third target device to operate according to the dynamic adjustment parameter.
10. The cloud-computing-based smart agriculture management system of claim 6, wherein the smart agriculture management platform further comprises a rights management module;
the authority management module is used for determining the user role of the user according to the login information input by the user; different user roles correspond to different system permissions.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116187716A (en) * | 2023-04-23 | 2023-05-30 | 中关村科学城城市大脑股份有限公司 | Agricultural equipment scheduling method, apparatus, electronic equipment and computer readable medium |
| CN117291291A (en) * | 2023-08-12 | 2023-12-26 | 江苏信实环境工程有限公司 | Insect condition intelligent monitoring system and method based on Internet of things |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116187716A (en) * | 2023-04-23 | 2023-05-30 | 中关村科学城城市大脑股份有限公司 | Agricultural equipment scheduling method, apparatus, electronic equipment and computer readable medium |
| CN117291291A (en) * | 2023-08-12 | 2023-12-26 | 江苏信实环境工程有限公司 | Insect condition intelligent monitoring system and method based on Internet of things |
| CN117291291B (en) * | 2023-08-12 | 2024-04-23 | 江苏信实环境工程有限公司 | Insect condition intelligent monitoring system and method based on Internet of things |
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