1. An intelligent agricultural monitoring system based on the Internet of things is characterized by comprising a data acquisition module, a wireless transmission module, a data processing module, a pest and disease database, an intelligent analysis and judgment module, a prediction and early warning module, an upper computer display and control platform, an expert diagnosis platform and crop auxiliary facilities;

wherein, the data acquisition module comprises a sensor unit, an RS unit and a GPS positioning unit, the sensor unit comprises a temperature sensor, a humidity sensor and a CO²A concentration sensor, a illuminance sensor and a pH value sensor; the upper computer display and control platform comprises a display unit, a data receiving unit, an information communication unit, a management decision unit, a remote control unit and an updating and uploading unit.

2. The intelligent agricultural monitoring system based on the internet of things of claim 1, wherein the sensor unit is used for collecting various environmental data of a crop planting field; the various environmental data comprise air and soil temperature data, air and soil humidity data, carbon dioxide concentration data, illuminance data and soil pH value data; the RS unit is used for acquiring a remote sensing image of the crop planting field by using the aerial camera; the GPS positioning unit is used for collecting the position data of the crop planting field.

3. The intelligent agricultural monitoring system based on the internet of things according to claim 1, wherein the wireless transmission module is used for transmitting the collected various environmental data, remote sensing images and position data to the data processing module in a wireless transmission mode; the data processing module is used for carrying out denoising and analog-to-digital conversion processing on various environment data, remote sensing images and position data.

4. The intelligent agricultural monitoring system based on the internet of things according to claim 1, wherein the pest database is used for storing data description information and image information of pest phenomena of crops; the intelligent analysis and judgment module is used for analyzing according to various environmental data and remote sensing images, judging the pest and disease conditions of crops in a planting field and obtaining a judgment result report, and the specific analysis and judgment process is as follows:

s1: firstly, extracting various environmental data and extracting data description information of pest phenomena in a pest database;

s2: calculating a data correlation coefficient X of the various environmental data and the data description information in the step S1 by using a correlation analysis algorithm;

s3: extracting a remote sensing image, and simultaneously taking image information of the pest phenomenon in a pest database;

s4: calculating an image correlation coefficient Y between the remote sensing image and the image information in the step S3 by using the correlation analysis algorithm in the step S2;

s5: the data correlation coefficient X of step S2 and the image correlation coefficient Y of step S4 are extracted, and a judgment is made:

if the data correlation coefficient X and the image correlation coefficient Y are both in the range of 0-0.25, judging that the crop pest and disease condition of the planting field is basically absent;

if the data correlation coefficient X and the image correlation coefficient Y are both in the range of 0.25-0.5, judging that the crop pest and disease conditions of the planting field are general;

if the data correlation coefficient X and the image correlation coefficient Y are both in the range of 0.5-0.75, judging that the crop pest and disease conditions of the planting field are serious;

if the data correlation coefficient X and the image correlation coefficient Y are both in the range of 0.75-1, judging that the crop pest and disease conditions of the planting field are very serious;

if the data correlation coefficient X and the image correlation coefficient Y are both 0, displaying and judging that the crop pest and disease conditions of the planting field cannot be matched;

the correlation analysis algorithm is specifically Apriori algorithm; and the prediction early warning module is used for reporting and sending early warning information to the upper computer display and control platform according to the judgment result.

5. The intelligent agricultural monitoring system based on the internet of things of claim 1, wherein the display unit is used for displaying early warning information; the data receiving unit is used for receiving various environmental data, remote sensing images, position data and judgment result reports; the information communication unit is used for sending various environmental data, remote sensing images, position data and judgment result reports to the expert diagnosis platform; the expert diagnosis platform is used for agricultural experts to provide treatment schemes and suggestions according to various environmental data, remote sensing images, position data and judgment result reports; the management decision unit is used for making a crop management decision of a planting field according to a treatment scheme and a suggestion provided by an expert; the remote control unit is used for remotely controlling the crop auxiliary facilities according to crop management decisions of a planting place; and the updating uploading module is used for arranging the character description information of the plant diseases and insect pests in the treatment scheme and uploading the character description information of the plant diseases and insect pests and the remote sensing image to a plant disease and insect pest database for updating.

6. The internet of things-based intelligent agricultural monitoring system of claim 1, wherein the crop auxiliary facilities comprise irrigation equipment, pesticide spraying equipment, electric sun visors, solar heaters, humidifiers, dehumidifiers, and carbon dioxide generators.

Background

Through retrieval, Chinese patent No. CN108449729A discloses a computer system integrated intelligent agricultural greenhouse monitoring and response system, which is simple in structure, but single in agricultural monitoring means and form, incapable of providing refined and comprehensive monitoring data and data analysis, and further incapable of early warning the growth condition of crops; intelligent agriculture refers to a product formed by jointly developing and mutually combining a plurality of subjects and fields such as communication, computers, agriculture and the like, integrates information acquisition, transmission, processing and control together, enables people to more easily obtain various information of each stage of crop growth, also enables people to more easily control the information, and really realizes human-natural interaction through the combination of artificial intelligence and agricultural production; in the agricultural production process, various natural factors such as temperature, humidity, illumination intensity, concentration, moisture, other nutrients and the like influence the growth of crops; the traditional agricultural monitoring mode far fails to reach the fine standard and only can be a rough artificial feeling, and the environmental parameters can not be monitored by the perception capability of people in the traditional agricultural monitoring mode; therefore, it becomes especially important to invent an intelligent agricultural monitoring system based on the internet of things;

most of the existing intelligent agricultural monitoring systems only adopt a temperature and humidity sensor to monitor crops, the monitoring means and the monitoring form are single, refined and comprehensive crop monitoring data cannot be provided, and the monitoring systems do not provide data analysis service, so that early warning cannot be performed on growth conditions of diseases and insect pests of the crops and the like, and further agricultural production managers cannot be assisted to provide good growth environments for the crops; therefore, an intelligent agricultural monitoring system based on the Internet of things is provided.

Disclosure of Invention

The invention aims to solve the defects in the prior art and provides an intelligent agricultural monitoring system based on the Internet of things.

In order to achieve the purpose, the invention adopts the following technical scheme:

an intelligent agricultural monitoring system based on the Internet of things comprises a data acquisition module, a wireless transmission module, a data processing module, a pest and disease damage database, an intelligent analysis and judgment module, a prediction early warning module, an upper computer display and control platform, an expert diagnosis platform and crop auxiliary facilities;

the data acquisition module comprises a sensor unit, an RS unit and a GPS positioning unit, wherein the sensor unit comprises a temperature sensor, a humidity sensor, a CO2 concentration sensor, a light illumination sensor and a pH value sensor; the upper computer display and control platform comprises a display unit, a data receiving unit, an information communication unit, a management decision unit, a remote control unit and an updating and uploading unit.

Further, the sensor unit is used for collecting various environmental data of the crop planting field; the various environmental data comprise air and soil temperature data, air and soil humidity data, carbon dioxide concentration data, illuminance data and soil pH value data; the RS unit is used for acquiring a remote sensing image of the crop planting field by using the aerial camera; the GPS positioning unit is used for collecting the position data of the crop planting field.

Furthermore, the wireless transmission module is used for transmitting the collected various environmental data, remote sensing images and position data to the data processing module in a wireless transmission mode; the data processing module is used for carrying out denoising and analog-to-digital conversion processing on various environment data, remote sensing images and position data.

Further, the pest database is used for storing data description information and image information of pest phenomena of crops; the intelligent analysis and judgment module is used for analyzing according to various environmental data and remote sensing images, judging the pest and disease conditions of crops in a planting field and obtaining a judgment result report, and the specific analysis and judgment process is as follows:

s1: firstly, extracting various environmental data and extracting data description information of pest phenomena in a pest database;

s2: calculating a data correlation coefficient X of the various environmental data and the data description information in the step S1 by using a correlation analysis algorithm;

s3: extracting a remote sensing image, and simultaneously taking image information of the pest phenomenon in a pest database;

s4: calculating an image correlation coefficient Y between the remote sensing image and the image information in the step S3 by using the correlation analysis algorithm in the step S2;

s5: the data correlation coefficient X of step S2 and the image correlation coefficient Y of step S4 are extracted, and a judgment is made:

if the data correlation coefficient X and the image correlation coefficient Y are both in the range of 0-0.25, judging that the crop pest and disease condition of the planting field is basically absent;

if the data correlation coefficient X and the image correlation coefficient Y are both in the range of 0.25-0.5, judging that the crop pest and disease conditions of the planting field are general;

if the data correlation coefficient X and the image correlation coefficient Y are both in the range of 0.5-0.75, judging that the crop pest and disease conditions of the planting field are serious;

if the data correlation coefficient X and the image correlation coefficient Y are both in the range of 0.75-1, judging that the crop pest and disease conditions of the planting field are very serious;

if the data correlation coefficient X and the image correlation coefficient Y are both 0, displaying and judging that the crop pest and disease conditions of the planting field cannot be matched;

the correlation analysis algorithm is specifically Apriori algorithm; and the prediction early warning module is used for reporting and sending early warning information to the upper computer display and control platform according to the judgment result.

Further, the display unit is used for displaying early warning information; the data receiving unit is used for receiving various environmental data, remote sensing images, position data and judgment result reports; the information communication unit is used for sending various environmental data, remote sensing images, position data and judgment result reports to the expert diagnosis platform; the expert diagnosis platform is used for agricultural experts to provide treatment schemes and suggestions according to various environmental data, remote sensing images, position data and judgment result reports; the management decision unit is used for making a crop management decision of a planting field according to a treatment scheme and a suggestion provided by an expert; the remote control unit is used for remotely controlling the crop auxiliary facilities according to crop management decisions of a planting place; and the updating uploading module is used for arranging the character description information of the plant diseases and insect pests in the treatment scheme and uploading the character description information of the plant diseases and insect pests and the remote sensing image to a plant disease and insect pest database for updating.

Further, the crop auxiliary facilities comprise irrigation equipment, pesticide spraying equipment, an electric sun shield, a solar heater, a humidifier, a dehumidifier and a carbon dioxide generator.

Compared with the prior art, the invention has the beneficial effects that:

1. the intelligent agricultural monitoring system based on the Internet of things is provided with a data acquisition module, wherein the data acquisition module comprises a sensor unit, an RS unit and a GPS positioning unit; wherein the sensor unit comprises a temperature sensor, a humidity sensor, and CO²The system comprises a concentration sensor, a illuminance sensor and a pH value sensor, and is characterized in that crops in a planting field are monitored in real time by adopting a monitoring form of sensor, remote sensing and positioning, so that refined and comprehensive crop monitoring data can be provided; thereby being beneficial to laying a foundation for subsequent intelligent judgment and analysis;

2. the intelligent agricultural monitoring system based on the Internet of things is provided with an intelligent analysis and judgment module and a disease and pest database, and correlation coefficient calculation is carried out on various environmental data and remote sensing images and data description information and image information in the disease and pest database by utilizing a correlation algorithm, so that the disease and pest condition of crops in a planting field is judged, and timely early warning is facilitated;

3. the intelligent agricultural monitoring system based on the Internet of things is provided with an upper computer display and control platform, the upper computer display and control platform is communicated with an expert diagnosis platform according to early warning information to obtain a treatment scheme and a treatment suggestion, and then the auxiliary crop facility is remotely controlled according to the treatment scheme and the treatment suggestion, so that auxiliary agricultural production managers can provide a good growing environment for crops; in addition, the platform arranges the character description information of the plant diseases and insect pests according to a treatment scheme, and uploads the character description information of the plant diseases and insect pests and the remote sensing image to a plant disease and insect pest database together for updating, so that the precision and the speed of the intelligent analysis and judgment module are improved, and the early warning accuracy is improved.

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.

Fig. 1 is a schematic overall structure diagram of an intelligent agricultural monitoring system based on the internet of things according to the present invention;

fig. 2 is a block diagram of an architecture of an intelligent agricultural monitoring system based on the internet of things.

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.

In the description of the present invention, it is to be understood that the terms "upper", "lower", "front", "rear", "left", "right", "top", "bottom", "inner", "outer", and the like, indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, are merely for convenience in describing the present invention and simplifying the description, and do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present invention.

Referring to fig. 1-2, the embodiment discloses an intelligent agricultural monitoring system based on the internet of things, which comprises a data acquisition module, a wireless transmission module, a data processing module, a pest and disease database, an intelligent analysis and judgment module, a prediction and early warning module, an upper computer display and control platform, an expert diagnosis platform and crop auxiliary facilities;

the data acquisition module comprises a sensor unit, an RS unit and a GPS positioning unit, wherein the sensor unit comprises a temperature sensor, a humidity sensor, a CO2 concentration sensor, a light illumination sensor and a pH value sensor; the upper computer display control platform comprises a display unit, a data receiving unit, an information communication unit, a management decision unit, a remote control unit and an update uploading unit.

The sensor unit is used for collecting various environmental data of the crop planting field;

specifically, the sensor unit comprises a wireless sensor network consisting of a plurality of temperature sensors, humidity sensors, CO2 concentration sensors, illuminance sensors and pH sensors; it should be noted that the present invention is not limited to the above-mentioned sensors, and is only highlighted by the common sensors, and in addition, the number of all the sensors of the present invention is selected according to the actual requirement; specifically, the various environmental data comprise air and soil temperature data, air and soil humidity data, carbon dioxide concentration data, illuminance data and soil pH value data; similarly, the various environmental data in the present invention not only include the above listed data types, but also the specific data types thereof are collected according to the actually deployed sensors;

the RS unit is used for acquiring a remote sensing image of the crop planting field by using the aerial camera;

the GPS positioning unit is used for collecting the position data of the crop planting field.

The wireless transmission module is used for transmitting the collected various environmental data, remote sensing images and position data to the data processing module in a wireless transmission mode;

the data processing module is used for carrying out denoising and analog-to-digital conversion processing on various environment data, remote sensing images and position data.

The pest database is used for storing data description information and image information of pest phenomena of crops;

the intelligent analysis and judgment module is used for analyzing according to various environmental data and remote sensing images, judging the pest and disease conditions of crops in a planting field and obtaining a judgment result report;

and the prediction early warning module is used for reporting and sending early warning information to the upper computer display and control platform according to the judgment result.

The display unit is used for displaying the early warning information;

the data receiving unit is used for receiving various environmental data, remote sensing images, position data and judgment result reports;

the information communication unit is used for sending various environmental data, remote sensing images, position data and judgment result reports to the expert diagnosis platform;

the expert diagnosis platform is used for agricultural experts to provide treatment schemes and suggestions according to various environmental data, remote sensing images, position data and judgment result reports;

the management decision unit is used for making a crop management decision of the planting field according to a treatment scheme and a suggestion provided by an expert;

the remote control unit is used for remotely controlling the crop auxiliary facilities according to crop management decisions of a planting place;

and the updating uploading module is used for arranging the character description information of the plant diseases and insect pests in the treatment scheme and uploading the character description information of the plant diseases and insect pests and the remote sensing image to a plant disease and insect pest database for updating.

The crop auxiliary facilities comprise irrigation equipment, pesticide spraying equipment, an electric sun shield, a solar heater, a humidifier, a dehumidifier and a carbon dioxide generator.

Referring to fig. 1-2, the embodiment discloses an intelligent agricultural monitoring system based on the internet of things, which comprises a data acquisition module, a wireless transmission module, a data processing module, a pest and disease database, an intelligent analysis and judgment module, a prediction and early warning module, an upper computer display and control platform, an expert diagnosis platform and crop auxiliary facilities;

the data acquisition module comprises a sensor unit, an RS unit and a GPS positioning unit, wherein the sensor unit comprises a temperature sensor, a humidity sensor, a CO2 concentration sensor, a light illumination sensor and a pH value sensor; the upper computer display control platform comprises a display unit, a data receiving unit, an information communication unit, a management decision unit, a remote control unit and an update uploading unit.

Except for the same structure as the above embodiment, this embodiment will specifically describe the processing layer of the intelligent analysis and judgment module, and the process thereof is as follows:

s1: firstly, extracting various environmental data and extracting data description information of pest phenomena in a pest database;

s2: calculating a data correlation coefficient X of the various environmental data and the data description information in the step S1 by using a correlation analysis algorithm;

s3: extracting a remote sensing image, and simultaneously taking image information of the pest phenomenon in a pest database;

s4: calculating an image correlation coefficient Y between the remote sensing image and the image information in the step S3 by using a correlation analysis algorithm in the step S2;

s5: the step S2 data correlation coefficient X and the step S4 image correlation coefficient Y are extracted, and a judgment is made:

if the data correlation coefficient X and the image correlation coefficient Y are both in the range of 0-0.25, judging that the crop pest and disease condition of the planting field is basically absent;

if the data correlation coefficient X and the image correlation coefficient Y are both in the range of 0.25-0.5, judging that the crop pest and disease conditions of the planting field are general;

if the data correlation coefficient X and the image correlation coefficient Y are both in the range of 0.5-0.75, judging that the crop pest and disease conditions of the planting field are serious;

if the data correlation coefficient X and the image correlation coefficient Y are both in the range of 0.75-1, judging that the crop pest and disease conditions of the planting field are very serious;

if the data correlation coefficient X and the image correlation coefficient Y are both 0, displaying and judging that the crop pest and disease conditions of the planting field cannot be matched;

specifically, the correlation analysis algorithm is an Apriori algorithm.

The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.