A digital rural management system based on the Internet of Things

Abstract

The present invention provides a digital village management system based on the Internet of Things, which relates to the technical field of village management and comprises a crop information library, an Internet of Things acquisition module, a growth analysis module, an auxiliary growth module and a growth judgment module. The Internet of Things acquisition module is used to obtain soil moisture, weather information and crop images, and detect the nutrient content of the soil; the growth analysis module is used to analyze soil moisture and weather information; the auxiliary growth module is used to perform sprinkler irrigation on farmland and output detailed fertilization information; the growth judgment module is used to analyze crop images and crop colors corresponding to crop growth days, and output crop growth information. The present invention is used to solve the problem that the existing digital village management system lacks judgment on the growth information of crops after sprinkler irrigation and fertilization, resulting in failure to judge whether there is poor crop growth in the farmland.

Description

Technical Field

[0001] The present invention relates to the technical field of village management, and in particular to a digital village management system based on the Internet of Things. Background Art

[0002] Digital villages are the application of networking, informatization and digitization in the economic and social development of agriculture and rural areas. It is an endogenous process of agricultural and rural modernization and transformation caused by the improvement of farmers' modern information skills. Smart agriculture can be realized through the digital technology of digital villages. Smart agriculture refers to the use of information-based management methods to carry out agricultural production and management. In the production process, the "35" technology can be used to timely obtain and perceive environmental factors of crop production such as humidity and temperature, and automatically adjust production conditions and intervene in the production process through "interconnection of things", thereby effectively improving the quality of agricultural products and improving agricultural production efficiency and competitiveness.

[0003] Existing smart agricultural systems usually perform a single analysis of soil moisture or fertilizer, and lack judgment on the growth status of crops; for example, in the patent with application publication number CN111399508A, a smart agricultural system and a smart agricultural method are disclosed. The solution is to analyze soil information and crop information to determine the amount of fertilizer to be applied in each area, but lacks analysis of the growth status of crops after fertilization. For another example, in the patent with application publication number CN111507857A, a digital agricultural planting system and method based on Internet of Things technology are disclosed. This method realizes intelligent agricultural production by accurately remotely controlling agricultural facilities through robots, saves manpower, reduces human errors, and enables users to remotely control the farmland planting environment online and accurately manage crops. However, this method lacks judgment on the demand for the state of the crop growth process. In view of this, it is necessary to optimize the existing digital rural management system. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a digital village management system based on the Internet of Things, which can obtain soil moisture, weather information and crop images, analyze the soil moisture and weather information, and perform sprinkler irrigation on farmland; detect the nutrient content of the soil, output the remaining nutrient content, and output detailed fertilization information; analyze the crop images and the crop colors corresponding to the crop growth days, and output crop growth information; so as to solve the problem that the existing digital village management system lacks the judgment of the growth information of crops after sprinkler irrigation and fertilization treatment, resulting in the inability to judge whether there is poor crop growth in the farmland.

[0005] In order to achieve the above-mentioned object, the present invention provides a digital village management system based on the Internet of Things, including a crop information database, an Internet of Things collection module, a growth analysis module, an auxiliary growth module and a growth judgment module; the crop information database stores the required nutrient content of multiple crops, the crop water requirement data of multiple crops and the crop color corresponding to the crop growth days;

[0006] The IoT acquisition module is used to obtain soil moisture, weather information and crop images, and is also used to receive nutrient detection signals, detect the nutrient content of the soil, and output the remaining nutrient content;

[0007] The growth analysis module includes a humidity analysis unit, a weather analysis unit and a sprinkler analysis unit. The humidity analysis unit is used to analyze soil humidity and crop water demand data to obtain crop moisture information; the weather analysis unit is used to analyze weather information to obtain irrigation reference information; the sprinkler analysis unit is used to analyze crop moisture information and irrigation reference information, and output sprinkler information based on the analysis results;

[0008] The auxiliary growth module includes a sprinkler irrigation implementation unit and a fertilization analysis unit. The sprinkler irrigation implementation unit is used to perform sprinkler irrigation on the farmland according to the sprinkler irrigation information and output normal water information and nutrient detection signals; the fertilization analysis unit is used to analyze the remaining nutrient content and the required nutrient content, and output fertilization details information and normal nutrient information based on the analysis results;

[0009] When the growth judgment module receives the normal water content information and the normal nutrient content information, it analyzes the crop image and the crop color corresponding to the crop growth days, and outputs the crop growth information based on the analysis result.

[0010] Further, the Internet of Things acquisition module includes a humidity detection unit; the humidity detection unit includes a first number of soil moisture sensors, and the humidity detection unit is configured with a humidity detection strategy; the humidity detection strategy includes: obtaining a first number of humidity data; calculating an average value of the first number of humidity data, and marking it as soil humidity;

[0011] The Internet of Things acquisition module also includes a climate acquisition unit, which is used to obtain weather information of the first day in the future by using network communication, and the weather information includes no rain information and rain information;

[0012] The growth analysis module includes a humidity analysis unit, and the humidity analysis unit is configured with a humidity analysis strategy, and the humidity analysis strategy includes: obtaining crop water requirement data from a crop information database;

[0013] Calculate the ratio of soil moisture to crop water requirement data, marked as moisture ratio;

[0014] When the humidity ratio is less than or equal to the first humidity ratio, the crop drying information is output; when the humidity ratio is greater than the first humidity ratio and less than or equal to the second humidity ratio, the crop water shortage information is output; when the humidity ratio is greater than the second humidity ratio, the crop water abundance information is output;

[0015] The crop moisture information includes crop drying information, crop water shortage information and crop water abundance information.

[0016] Furthermore, the weather analysis unit is also configured with a weather analysis strategy, and the weather analysis strategy includes:

[0017] Analyze weather information, and when all weather information indicates no rain, output urgent irrigation information;

[0018] When rain information is obtained, the date corresponding to the rain information is marked as the rainy date, and the number of days obtained by subtracting the current date from the rainy date is marked as the waiting days; when the waiting days are greater than the second day, the irrigation information is output;

[0019] When the number of waiting days is less than or equal to the second day, output the information that no irrigation is needed;

[0020] The irrigation reference information includes urgent irrigation information, required irrigation information, and no irrigation information.

[0021] Furthermore, the sprinkler irrigation analysis unit is also configured with a sprinkler irrigation analysis strategy, and the sprinkler irrigation analysis strategy includes:

[0022] Receive crop moisture information and irrigation reference information;

[0023] When crop drying information is received, the irrigation reference information is analyzed; when the irrigation reference information is urgent irrigation information, the first irrigation water volume is output; when the irrigation reference information is not urgent irrigation information, the second irrigation water volume is output;

[0024] When crop water shortage information is received, the irrigation reference information is analyzed; when the irrigation reference information is urgent irrigation information or irrigation information is required, the second irrigation water volume is output; when the irrigation reference information is no irrigation information, the third irrigation water volume is output;

[0025] When receiving the information of sufficient water, outputting the third irrigation water amount;

[0026] Marking the first irrigation water amount, the second irrigation water amount, and the third irrigation water amount as irrigation water amounts; outputting a control signal;

[0027] The sprinkler irrigation information includes irrigation water volume and control signals;

[0028] The auxiliary growth module includes a sprinkler irrigation implementation unit, the sprinkler irrigation implementation unit includes a flow meter, and the flow meter is used to detect the sprinkler irrigation flow; the sprinkler irrigation implementation unit is configured with a sprinkler irrigation strategy, and the sprinkler irrigation strategy includes: when receiving a control signal, sprinkler irrigation processing is performed according to the irrigation water volume corresponding to the control signal;

[0029] When the sprinkler irrigation process begins, the flow meter is started for detection, and when it is detected that the sprinkler irrigation flow is equal to the irrigation water volume, the sprinkler irrigation process is stopped;

[0030] Output nutrient detection signals and normal moisture information.

[0031] Furthermore, the Internet of Things acquisition module also includes a nutrient acquisition unit, the nutrient acquisition unit includes a second number of soil nitrogen, phosphorus and potassium sensors, and the soil nitrogen, phosphorus and potassium sensors are used to obtain the nutrient content of the soil; the nutrient acquisition unit is configured with a nutrient acquisition strategy, and the nutrient acquisition strategy includes:

[0032] When the detection signal is received, the nutrient content of the second amount of soil after the sprinkler irrigation treatment is obtained, a frequency histogram of the nutrient content of the soil is established, the median of the highest frequency group in the frequency histogram is marked as the remaining nutrient content, and the remaining nutrient content is output.

[0033] Furthermore, the auxiliary growth module further includes a fertilization analysis unit, and the fertilization analysis unit is configured with a fertilization analysis strategy, and the fertilization analysis strategy includes:

[0034] Obtain required nutrient content;

[0035] Compare the remaining nutrient content with the required nutrient content;

[0036] When the remaining nutrient content is greater than the required nutrient content, the output indicates that no fertilization is needed; when the remaining nutrient content is less than or equal to the required nutrient content, the output indicates that fertilization is needed;

[0037] Output normal nutrient information;

[0038] The detailed fertilization information includes information that fertilization is not required and information that fertilization is required.

[0039] Furthermore, the Internet of Things acquisition module also includes an image acquisition unit, the image acquisition unit includes a high-resolution camera device, the high-resolution camera device can adjust the focal length within a first focal length to a second focal length, wherein the first focal length is smaller than the second focal length; the high-resolution camera device is used to capture high-resolution crop images; the image acquisition unit is configured with an image acquisition strategy, the image acquisition strategy includes:

[0040] When the normal water content information and the normal nutrient content information are received, a crop image is acquired at a first focal length;

[0041] The growth judgment module includes a growth detection unit, and when receiving detection adjustment information sent by the growth detection unit, the focal length is adjusted from the first focal length to the second focal length to obtain a crop image.

[0042] Furthermore, the growth judgment module includes an image processing unit, and the image processing unit is configured with an image processing strategy, and the image processing strategy includes:

[0043] Acquire a crop image, perform grayscale processing on the crop image, and then perform binarization processing on the crop image to obtain a crop contour map;

[0044] Based on the crop contour map, the area not surrounded by the contour map is deleted in the crop image to obtain a crop analysis map.

[0045] Furthermore, the growth detection unit is configured with a growth detection strategy, and the growth detection strategy includes:

[0046] The crop growth days and the RGB values ​​of the crop colors corresponding to the crop growth days are obtained from the crop information database, and are marked as R reference color value, G reference color value and B reference color value respectively;

[0047] Each pixel in the crop analysis image is marked with RGB [R(a1), G(a2), B(a3)], where R(a1) represents the red component of the pixel, G(a2) represents the green component of the pixel, and B(a3) represents the blue component of the pixel. The value ranges of a1, a2, and a3 are all 0-255.

[0048] Calculate the difference between the RGB value of each pixel and the corresponding reference color value, and mark it as the color analysis value; set the pixel reference value with an initial value of 0, and when the color analysis value is less than or equal to the first color difference value, add one to the pixel reference value corresponding to the pixel; when the color analysis value is greater than the first color difference value, do not process it;

[0049] When the pixel reference value is less than or equal to the first analysis value, the pixel point is marked as an analysis pixel point; when the pixel reference value is greater than the first analysis value, no marking is performed;

[0050] The ratio of the analysis pixel to the total number of pixel points is calculated and marked as a growth analysis value. When the growth analysis value is greater than or equal to the first growth ratio, poor growth information is output; when the growth analysis value is less than the first growth ratio and greater than or equal to the second growth ratio, detection adjustment information is output, and the image acquisition strategy, image processing strategy and growth detection strategy are repeatedly executed; when the growth analysis value is less than the second growth ratio, normal crop growth information is output;

[0051] The crop growth information includes poor growth information and normal crop growth information.

[0052] Beneficial effects of the present invention: The present invention can analyze soil moisture and crop water requirement data to obtain crop moisture information through the humidity analysis unit of the growth analysis module; can analyze weather information to obtain irrigation reference information through the weather analysis unit; can analyze crop moisture information and irrigation reference information through the sprinkler analysis unit, and output sprinkler information based on the analysis results. This method can determine whether crops need irrigation based on a comprehensive analysis of crops and weather, thereby improving the accuracy of digital analysis of crop irrigation;

[0053] The present invention can perform sprinkler irrigation on farmland according to sprinkler irrigation information through the sprinkler irrigation implementation unit of the auxiliary growth module, and output normal water information and nutrient detection signals; the fertilization analysis unit can analyze the remaining nutrient content and the required nutrient content, and output fertilization details information and normal nutrient information based on the analysis results. This method can improve the comprehensiveness of crop monitoring and further ensure the normal growth of crops;

[0054] The present invention can analyze crop images and crop colors corresponding to crop growth days through a growth judgment module, and output crop growth information based on the analysis results. The method first analyzes the moisture of the crops and the nutrients of the soil, performs sprinkler irrigation processing and outputs fertilization details information based on the analysis results, and after the moisture and nutrients can support the normal growth of the crops, the crop images are processed and analyzed, and the crop growth information can be obtained based on the analysis results, thereby improving the comprehensiveness of digital supervision of crops and comprehensively ensuring the growth stability of crops throughout the entire growth cycle.

[0055] Advantages of additional aspects of the present invention will be given in part in the description of the following specific embodiments, and in part will become apparent from the following description, or will be learned through the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0057] Figure 1 is a functional block diagram of the system of the present invention;

[0058] Figure 2 is a schematic diagram of a farmland of the present invention;

[0059] Figure 3 It is the frequency histogram of the nutrient content of the soil of the present invention. DETAILED DESCRIPTION

[0060] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the present invention is further explained below in conjunction with specific implementation methods.

[0061] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0062] Example 1

[0063] See also Figure 1 As shown, the present invention provides a digital rural management system based on the Internet of Things, which can obtain soil moisture, weather information and crop images, analyze soil moisture and weather information, and perform sprinkler irrigation on farmland; detect the nutrient content of the soil, output the remaining nutrient content, and output fertilization details; analyze the crop images and the crop colors corresponding to the crop growth days, and output crop growth information.

[0064] Specifically, the present invention provides a digital village management system based on the Internet of Things, including a crop information database, an Internet of Things collection module, a growth analysis module, an auxiliary growth module, and a growth judgment module;

[0065] The IoT acquisition module includes a humidity detection unit, a climate acquisition unit, a nutrient acquisition unit, and an image acquisition unit;

[0066] The humidity detection unit includes a first number of soil humidity sensors, and the humidity detection unit is configured with a humidity detection strategy; the humidity detection strategy includes: obtaining a first number of humidity data; calculating an average value of the first number of humidity data, and marking it as soil humidity;

[0067] See also Figure 2 As shown, Figure 2 In the figure, T1 is a high-resolution camera; T2 is a soil nitrogen, phosphorus and potassium sensor; T3 is a soil moisture sensor; T4 is a crop planting area; T5 is a sprinkler irrigation implementation unit; T1 is a triangular area in the figure, T2 is a square area in the figure, T3 is a circular area in the figure, T4 is a rectangular area in the figure; T5 is a pentagonal area in the figure. In specific implementation, the first number is set to 5, and the soil moisture sensor is set in the center of the farmland and near the edge of the farmland. Due to the absorption of crops, the humidity data in different areas are different, but the water in the soil will flow, so that the soil moisture maintains a relatively average value, so the average value of the 5 data is calculated as the soil moisture;

[0068] The climate acquisition unit is used to acquire weather information of the first day in the future by using network communication, and the weather information includes information of no rain and information of rain;

[0069] In specific implementation, the first day is set to 7 days; a 7-day cycle can ensure that the weather forecast is as accurate as possible while having a certain degree of predictability;

[0070] The nutrient acquisition unit includes a second number of soil nitrogen, phosphorus and potassium sensors, which are arranged at the edge of the farmland, the farmland aisle and between multiple adjacent crops to obtain the nutrient content of the soil; the nutrient acquisition unit is configured with a nutrient acquisition strategy, which includes:

[0071] See also Figure 3 As shown, when a detection signal is received, the nutrient content of the soil after the sprinkler irrigation treatment is obtained, a frequency histogram of the nutrient content of the soil is established, the median of the highest frequency group in the frequency histogram is marked as the remaining nutrient content, and the remaining nutrient content is output;

[0072] In specific implementation, the second number is set to 10, and the soil nitrogen, phosphorus and potassium sensors are set at the edge of the farmland, the farmland aisle and between multiple adjacent crops to analyze the impact of crop absorption of nutrients on the nutrient content of the soil; due to the absorption of nutrients by crops, it is impossible to use the average value to represent the nutrient content in the farmland, so a frequency histogram of the nutrient content is drawn, and the median of the group interval with the highest frequency is selected as the remaining nutrient content; when the detection signal is received, the nutrient content of the soil is obtained to analyze the impact of sprinkler irrigation on the nutrient content of the soil;

[0073] The image acquisition unit includes a high-resolution camera device, which is arranged around the farmland and can adjust the focal length from a first focal length to a second focal length, wherein the first focal length is smaller than the second focal length; the high-resolution camera device is used to capture a high-resolution crop image; the image acquisition unit is configured with an image acquisition strategy, which includes:

[0074] When the normal water content information and the normal nutrient content information are received, a crop image is acquired at a first focal length;

[0075] When receiving the detection adjustment information sent by the growth detection unit, adjusting the focal length from the first focal length to the second focal length to obtain the crop image;

[0076] In a specific implementation, the first focal length is 50 mm and the second focal length is 60 mm; the focal length is adjusted to obtain a more detailed crop image that is easier to analyze;

[0077] The growth analysis module includes a humidity analysis unit, a weather analysis unit, and a sprinkler analysis unit;

[0078] The humidity analysis unit is configured with a humidity analysis strategy, which includes: obtaining crop water requirement data from a crop information database;

[0079] Calculate the ratio of soil moisture to crop water requirement data, marked as moisture ratio;

[0080] When the humidity ratio is less than or equal to the first humidity ratio, the crop drying information is output; when the humidity ratio is greater than the first humidity ratio and less than or equal to the second humidity ratio, the crop water shortage information is output; when the humidity ratio is greater than the second humidity ratio, the crop water abundance information is output;

[0081] Crop moisture information includes crop drying information, crop water shortage information, and crop water abundance information;

[0082] In specific implementation, the first humidity ratio is set to 0.7, and the second humidity ratio is set to 0.9; when the humidity ratio is less than 0.7, it means that the soil moisture does not meet the crop growth requirements at this time, and the crop may dry up, so the crop drying information is output, which does not mean that the crop has dried up; similarly, when the humidity ratio is greater than 0.9, it does not mean that the crop is completely not short of water. In the range of humidity ratios from 0.9 to 1, the crop can grow normally, so the water-sufficient information is output; in the range of humidity ratios from 0.7 to 0.9, the crop can grow, but the growth is limited, and the crop water shortage information is output; in order to determine the subsequent irrigation water volume based on the crop water information, the crop water information is divided into three types for output;

[0083] The weather analysis unit is also configured with a weather analysis strategy, which includes:

[0084] Analyze weather information, and when all weather information indicates no rain, output urgent irrigation information;

[0085] When rain information is obtained, the date corresponding to the rain information is marked as the rainy date, and the number of days obtained by subtracting the current date from the rainy date is marked as the waiting days; when the waiting days are greater than the second day, the irrigation information is output;

[0086] When the number of waiting days is less than or equal to the second day, output the information that no irrigation is needed;

[0087] Irrigation reference information includes urgent irrigation information, irrigation required information and no irrigation required information;

[0088] In specific implementation, the second day is set to 3 days; the irrigation reference information needs to be analyzed together with the crop moisture information. For example, when the urgent irrigation information is output, it only means that it will not rain in the next 7 days. If the crop is short of water at this time, sprinkler irrigation is urgently needed. If the crop is not short of water, sprinkler irrigation is not needed.

[0089] The sprinkler analysis unit is also equipped with sprinkler analysis strategies, which include:

[0090] Receive crop moisture information and irrigation reference information;

[0091] When crop drying information is received, the irrigation reference information is analyzed; when the irrigation reference information is urgent irrigation information, the first irrigation water volume is output; when the irrigation reference information is not urgent irrigation information, the second irrigation water volume is output;

[0092] When crop water shortage information is received, the irrigation reference information is analyzed; when the irrigation reference information is urgent irrigation information or irrigation information is required, the second irrigation water volume is output; when the irrigation reference information is no irrigation information, the third irrigation water volume is output;

[0093] When receiving the information of sufficient water, outputting the third irrigation water amount;

[0094] Marking the first irrigation water amount, the second irrigation water amount, and the third irrigation water amount as irrigation water amounts; outputting a control signal;

[0095] Sprinkler irrigation information includes irrigation water volume and control signals;

[0096] In specific implementation, since the weather information in the next 7 days is no rain information, and the crop moisture information is crop drying information, sprinkler irrigation is needed to support the moisture demand of crops within a week, so the first irrigation water volume is set to 20L; the second irrigation water volume is set to 5L to support the moisture demand of crops within 2 to 3 days, and the subsequent moisture demand is supported by rainfall; the third irrigation water volume is set to 0L, because the crops are not short of water or can grow at this time, and the crops can grow normally after rainfall;

[0097] The auxiliary growth module includes a sprinkler irrigation implementation unit and a fertilization analysis unit;

[0098] The sprinkler irrigation implementation unit includes a flow meter and a sprinkler irrigation device, the flow meter is used to detect the sprinkler irrigation flow of the sprinkler irrigation device; the sprinkler irrigation implementation unit is configured with a sprinkler irrigation strategy, and the sprinkler irrigation strategy includes: when receiving a control signal, sprinkler irrigation processing is performed according to the irrigation water volume corresponding to the control signal;

[0099] When the sprinkler irrigation process begins, the flow meter is started for detection, and when it is detected that the sprinkler irrigation flow is equal to the irrigation water volume, the sprinkler irrigation process is stopped;

[0100] Output nutrient detection signals and normal water content information;

[0101] In specific implementation, when the sprinkler irrigation is completed, the nutrient detection signal is output to analyze the impact of the sprinkler irrigation treatment on the nutrient content of the soil; the normal moisture information indicates that the soil moisture supports the normal growth of crops between this analysis and the next analysis;

[0102] The fertilization analysis unit is configured with a fertilization analysis strategy, which includes:

[0103] Obtain required nutrient content;

[0104] Compare the remaining nutrient content with the required nutrient content;

[0105] When the remaining nutrient content is greater than the required nutrient content, the output indicates that no fertilization is needed; when the remaining nutrient content is less than or equal to the required nutrient content, the output indicates that fertilization is needed;

[0106] Output normal nutrient information;

[0107] The detailed information of fertilization includes information of no fertilization and information of needing fertilization;

[0108] In specific implementation, when the remaining nutrient content is less than or equal to the required nutrient content, since the crop will continuously absorb nutrients during growth, fertilization is required, and fertilization-required information is output; normal nutrient information means that between this analysis and the next analysis, after fertilization or without fertilization, the nutrient content of the soil supports normal crop growth;

[0109] The growth judgment module includes an image processing unit and a growth detection unit;

[0110] The image processing unit is configured with an image processing strategy, which includes:

[0111] Acquire a crop image, perform grayscale processing on the crop image, and then perform binarization processing on the crop image to obtain a crop contour map;

[0112] Based on the crop contour map, the area not surrounded by the contour map is deleted in the crop image to obtain a crop analysis map;

[0113] The growth detection unit is configured with a growth detection strategy, which includes:

[0114] The crop growth days and the RGB values ​​of the crop colors corresponding to the crop growth days are obtained from the crop information database, and are marked as R reference color value, G reference color value and B reference color value respectively;

[0115] Each pixel in the crop analysis image is marked with RGB [R(a1), G(a2), B(a3)], where R(a1) represents the red component of the pixel, G(a2) represents the green component of the pixel, and B(a3) represents the blue component of the pixel. The value ranges of a1, a2, and a3 are all 0-255.

[0116] Calculate the difference between the RGB value of each pixel and the corresponding reference color value, and mark it as the color analysis value; set the pixel reference value with an initial value of 0, and when the color analysis value is less than or equal to the first color difference value, add one to the pixel reference value corresponding to the pixel; when the color analysis value is greater than the first color difference value, do not process it;

[0117] When the pixel reference value is less than or equal to the first analysis value, the pixel point is marked as an analysis pixel point; when the pixel reference value is greater than the first analysis value, no marking is performed;

[0118] The ratio of the analysis pixel to the total number of pixel points is calculated and marked as a growth analysis value. When the growth analysis value is greater than or equal to the first growth ratio, poor growth information is output; when the growth analysis value is less than the first growth ratio and greater than or equal to the second growth ratio, detection adjustment information is output, and the image acquisition strategy, image processing strategy and growth detection strategy are repeatedly executed; when the growth analysis value is less than the second growth ratio, normal crop growth information is output;

[0119] The crop growth information includes poor growth information and normal crop growth information;

[0120] In specific implementation, the first color difference is set to 15, the first analysis value is set to 1, the first growth ratio is set to 0.2, and the second growth ratio is set to 0.1; when the R reference color value is 127, the G reference color value is 255, and the B reference color value is 0, if the two groups of color analysis values ​​are (20, 13, 8) and (10, 25, 18) respectively, the pixel reference value of the first group is 2, and the pixel reference value of the second group is 1, then the pixel points corresponding to the pixel reference values ​​of the second group are marked as analysis pixels.

[0121] Example 2

[0122] The difference between Example 2 and Example 1 is that different irrigation water volumes are set for different growing days of crops; in actual applications, crops have different requirements for soil moisture content at different growing days; for example, when the crop type is corn, the soil moisture content is required to be 70% to 80% during the jointing stage; when corn is heading and flowering, the soil moisture requirement is maintained at 80% to 85%; therefore, setting different irrigation water volumes for different growing days of crops can more comprehensively support the normal growth of crops; specifically: the sprinkler analysis unit is also configured with a sprinkler analysis strategy, and the sprinkler analysis strategy includes:

[0123] Receive crop moisture information and irrigation reference information;

[0124] When crop drying information is received, the irrigation reference information is analyzed; when the irrigation reference information is urgent irrigation information, the first irrigation water volume is output; when the irrigation reference information is not urgent irrigation information, the second irrigation water volume is output;

[0125] When crop water shortage information is received, the irrigation reference information is analyzed; when the irrigation reference information is urgent irrigation information or irrigation information is required, the second irrigation water volume is output; when the irrigation reference information is no irrigation information, the third irrigation water volume is output;

[0126] When receiving the information of sufficient water, outputting the third irrigation water amount;

[0127] Marking the first irrigation water amount, the second irrigation water amount, and the third irrigation water amount as irrigation water amounts; outputting a control signal;

[0128] Sprinkler irrigation information includes irrigation water volume and control signals;

[0129] In specific implementation, if the crop type is corn and the growth period is in the jointing stage, the first irrigation water volume is set to 10L, the second irrigation water volume is set to 3L, and the third irrigation water volume is 0L; in specific applications, users can adjust it according to actual conditions to meet different needs in different periods.

[0130] Example 3

[0131] The difference between Example 3 and Example 1 is that different first color difference values ​​are set for different growing days of crops; in practical applications, for example, when the crop type is rice, the rice is generally green during the growth period, and the color generally changes from green to wheat color in the process of maturing, and the color of each rice may be significantly different, so it is necessary to set different first color difference values. Specifically, the period when the rice is green in the early growth period will account for about 80% of the entire growth period. Therefore, the color difference in the first 80% of the growth period is small, and the color change rate is also small. The setting value of the first color difference value should be smaller than the setting value in the later maturity period. In the last 20% of the maturity period, the color change rate is faster. At this time, the setting range of the first color difference value should be expanded, so that the growth information of the crop can be judged more accurately; specifically: the growth detection unit is configured with a growth detection strategy, and the growth detection strategy includes:

[0132] The crop growth days and the RGB values ​​of the crop colors corresponding to the crop growth days are obtained from the crop information database, and are marked as R reference color value, G reference color value and B reference color value respectively;

[0133] Each pixel in the crop analysis image is marked with RGB [R(a1), G(a2), B(a3)], where R(a1) represents the red component of the pixel, G(a2) represents the green component of the pixel, and B(a3) represents the blue component of the pixel. The value ranges of a1, a2, and a3 are all 0-255.

[0134] Calculate the difference between the RGB value of each pixel and the corresponding reference color value, and mark it as the color analysis value; set the pixel reference value with an initial value of 0, and when the color analysis value is less than or equal to the first color difference value, add one to the pixel reference value corresponding to the pixel; when the color analysis value is greater than the first color difference value, do not process it;

[0135] When the pixel reference value is less than or equal to the first analysis value, the pixel point is marked as an analysis pixel point; when the pixel reference value is greater than the first analysis value, no marking is performed;

[0136] The ratio of the analysis pixel to the total number of pixel points is calculated and marked as a growth analysis value. When the growth analysis value is greater than or equal to the first growth ratio, poor growth information is output; when the growth analysis value is less than the first growth ratio and greater than or equal to the second growth ratio, detection adjustment information is output, and the image acquisition strategy, image processing strategy and growth detection strategy are repeatedly executed; when the growth analysis value is less than the second growth ratio, normal crop growth information is output;

[0137] The crop growth information includes poor growth information and normal crop growth information;

[0138] In specific implementation, the first color difference is set to 30, the first analysis value is set to 1, the first growth ratio is set to 0.2, and the second growth ratio is set to 0.1; when the R reference color value is 127, the G reference color value is 255, and the B reference color value is 0, if the two groups of color analysis values ​​are (20, 13, 8) and (10, 25, 18) respectively, the pixel reference value of the first group is 2, and the pixel reference value of the second group is 2. At this time, the pixel points corresponding to the two groups of pixel reference values ​​are not processed.

[0139] In specific applications, users can adjust it according to actual conditions to meet different needs in different periods.

[0140] Working principle: First, the IoT acquisition module obtains soil moisture, weather information and crop images, receives nutrient detection signals, detects the nutrient content of the soil, and outputs the remaining nutrient content;

[0141] Then, the soil moisture and crop water requirement data are analyzed by the humidity analysis unit to obtain crop moisture information; the weather information is analyzed by the weather analysis unit to obtain irrigation reference information; the crop moisture information and irrigation reference information are analyzed by the sprinkler irrigation analysis unit, and sprinkler irrigation information is output based on the analysis results;

[0142] The sprinkler irrigation implementation unit performs sprinkler irrigation on the farmland according to the sprinkler irrigation information, and outputs normal water information and nutrient detection signals; the fertilization analysis unit analyzes the remaining nutrient content and the required nutrient content, and outputs fertilization details information and normal nutrient information based on the analysis results;

[0143] Finally, when the growth judgment module receives the normal water content information and the normal nutrient content information, it analyzes the crop image and the crop color corresponding to the crop growth days, and outputs the crop growth information based on the analysis result.

[0144] It should be understood by those skilled in the art that the embodiments of the present invention can be provided as methods, systems or computer program products. Therefore, the present invention can be in the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention can be in the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program codes. Among them, the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Red Only Memory, referred to as EPROM), programmable read-only memory (Programmable Red-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic memory, flash memory, disk or optical disk. These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0145] The above-described embodiments are only specific implementations of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The protection scope of the present invention is not limited thereto. Although the present invention is described in detail with reference to the above-described embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-described embodiments within the technical scope disclosed by the present invention, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A digital village management system based on the Internet of Things, characterized in that: It includes a crop information database, an Internet of Things collection module, a growth analysis module, an auxiliary growth module and a growth judgment module; the crop information database stores the required nutrient content of various crops, the crop water requirement data of various crops and the crop color corresponding to the crop growth days; The IoT acquisition module is used to obtain soil moisture, weather information and crop images, and is also used to receive nutrient detection signals, detect the nutrient content of the soil, and output the remaining nutrient content; The growth analysis module includes a humidity analysis unit, a weather analysis unit and a sprinkler analysis unit. The humidity analysis unit is used to analyze soil humidity and crop water demand data to obtain crop moisture information; the weather analysis unit is used to analyze weather information to obtain irrigation reference information; The sprinkler irrigation analysis unit is used to analyze crop moisture information and irrigation reference information, and output sprinkler irrigation information based on the analysis results; The auxiliary growth module includes a sprinkler irrigation implementation unit and a fertilization analysis unit. The sprinkler irrigation implementation unit is used to perform sprinkler irrigation on the farmland according to the sprinkler irrigation information and output normal water information and nutrient detection signals; the fertilization analysis unit is used to analyze the remaining nutrient content and the required nutrient content, and output fertilization details information and normal nutrient information based on the analysis results; When the growth judgment module receives the normal water content information and the normal nutrient content information, it analyzes the crop image and the crop color corresponding to the crop growth days, and outputs the crop growth information based on the analysis result; The Internet of Things acquisition module includes a humidity detection unit; the humidity detection unit includes a first number of soil moisture sensors, and the humidity detection unit is configured with a humidity detection strategy; the humidity detection strategy includes: obtaining a first number of humidity data; calculating the average value of the first number of humidity data, and marking it as soil humidity; The Internet of Things acquisition module also includes a climate acquisition unit, which is used to obtain weather information of the first day in the future by using network communication, and the weather information includes no rain information and rain information; The humidity analysis unit is configured with a humidity analysis strategy, which includes: obtaining crop water requirement data from a crop information database; Calculate the ratio of soil moisture to crop water requirement data, marked as moisture ratio; When the humidity ratio is less than or equal to the first humidity ratio, the crop drying information is output; when the humidity ratio is greater than the first humidity ratio and less than or equal to the second humidity ratio, the crop water shortage information is output; when the humidity ratio is greater than the second humidity ratio, the crop water abundance information is output; The crop moisture information includes crop drying information, crop water shortage information and crop water abundance information; The weather analysis unit is also configured with a weather analysis strategy, which includes: Analyze weather information, and when all weather information indicates no rain, output urgent irrigation information; When rain information is obtained, the date corresponding to the rain information is marked as the rainy date, and the number of days obtained by subtracting the current date from the rainy date is marked as the waiting days; when the waiting days are greater than the second day, the irrigation information is output; When the number of waiting days is less than or equal to the second day, output the information that no irrigation is needed; The irrigation reference information includes urgent irrigation information, required irrigation information and no irrigation information; The sprinkler irrigation analysis unit is also configured with a sprinkler irrigation analysis strategy, which includes: Receive crop moisture information and irrigation reference information; When crop drying information is received, the irrigation reference information is analyzed; when the irrigation reference information is urgent irrigation information, the first irrigation water volume is output; when the irrigation reference information is not urgent irrigation information, the second irrigation water volume is output; When crop water shortage information is received, the irrigation reference information is analyzed; when the irrigation reference information is urgent irrigation information or irrigation information is required, the second irrigation water volume is output; when the irrigation reference information is no irrigation information, the third irrigation water volume is output; When receiving the information of sufficient water, outputting the third irrigation water amount; Marking the first irrigation water amount, the second irrigation water amount, and the third irrigation water amount as irrigation water amounts; outputting a control signal; The sprinkler irrigation information includes irrigation water volume and control signals; The sprinkler irrigation implementation unit includes a flow meter, which is used to detect the sprinkler irrigation flow rate; the sprinkler irrigation implementation unit is configured with a sprinkler irrigation strategy, which includes: when receiving a control signal, performing sprinkler irrigation processing according to the irrigation water volume corresponding to the control signal; When the sprinkler irrigation process begins, the flow meter is started for detection, and when it is detected that the sprinkler irrigation flow is equal to the irrigation water volume, the sprinkler irrigation process is stopped; Output nutrient detection signals and normal water content information; The growth judgment module includes an image processing unit, and the image processing unit is configured with an image processing strategy, and the image processing strategy includes: Acquire a crop image, perform grayscale processing on the crop image, and then perform binarization processing on the crop image to obtain a crop contour map; Based on the crop contour map, the area not surrounded by the contour map is deleted in the crop image to obtain a crop analysis map; The growth detection unit is configured with a growth detection strategy, which includes: The crop growth days and the RGB values ​​of the crop colors corresponding to the crop growth days are obtained from the crop information database, and are marked as R reference color value, G reference color value and B reference color value respectively; Each pixel in the crop analysis image is marked with RGB [R (a1), G (a2), B (a3)], where R (a1) represents the red component of the pixel, G (a2) represents the green component of the pixel, and B (a3) ​​represents the blue component of the pixel. The value ranges of a1, a2, and a3 are all 0-255. Calculate the difference between the RGB value of each pixel and the corresponding reference color value, and mark it as the color analysis value; set the pixel reference value with an initial value of 0, and when the color analysis value is less than or equal to the first color difference value, add one to the pixel reference value corresponding to the pixel; when the color analysis value is greater than the first color difference value, do not process it; When the pixel reference value is less than or equal to the first analysis value, the pixel point is marked as an analysis pixel point; when the pixel reference value is greater than the first analysis value, no marking is performed; The ratio of the analysis pixel to the total number of pixel points is calculated and marked as a growth analysis value. When the growth analysis value is greater than or equal to the first growth ratio, poor growth information is output; when the growth analysis value is less than the first growth ratio and greater than or equal to the second growth ratio, detection adjustment information is output, and the image acquisition strategy, image processing strategy and growth detection strategy are repeatedly executed; when the growth analysis value is less than the second growth ratio, normal crop growth information is output; The crop growth information includes poor growth information and normal crop growth information.

2. According to the digital village management system based on the Internet of Things according to claim 1, it is characterized in that: The Internet of Things acquisition module also includes a nutrient acquisition unit, which includes a second number of soil nitrogen, phosphorus and potassium sensors, and the soil nitrogen, phosphorus and potassium sensors are used to obtain the nutrient content of the soil; the nutrient acquisition unit is configured with a nutrient acquisition strategy, and the nutrient acquisition strategy includes: When the detection signal is received, the nutrient content of the second amount of soil after the sprinkler irrigation treatment is obtained, a frequency histogram of the nutrient content of the soil is established, the median of the highest frequency group in the frequency histogram is marked as the remaining nutrient content, and the remaining nutrient content is output.

3. According to claim 2, a digital village management system based on the Internet of Things is characterized in that: The auxiliary growth module further includes a fertilization analysis unit, which is configured with a fertilization analysis strategy, which includes: Obtain required nutrient content; Compare the remaining nutrient content with the required nutrient content; When the remaining nutrient content is greater than the required nutrient content, the output indicates that no fertilization is needed; when the remaining nutrient content is less than or equal to the required nutrient content, the output indicates that fertilization is needed; Output normal nutrient information; The detailed fertilization information includes information that fertilization is not required and information that fertilization is required.

4. According to claim 3, a digital village management system based on the Internet of Things is characterized in that: The Internet of Things acquisition module also includes an image acquisition unit, which includes a high-resolution camera device, which can adjust the focal length within a range from a first focal length to a second focal length, wherein the first focal length is smaller than the second focal length; the high-resolution camera device is used to capture crop images; The image acquisition unit is configured with an image acquisition strategy, and the image acquisition strategy includes: When the normal water content information and the normal nutrient content information are received, a crop image is acquired at a first focal length; The growth judgment module includes a growth detection unit, and when receiving detection adjustment information sent by the growth detection unit, the focal length is adjusted from the first focal length to the second focal length to obtain a crop image.

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