Computer internet of things based agricultural planting irrigation detection device and detection method thereof

Abstract

The application discloses a computer Internet of Things based agricultural planting irrigation detection device and a detection method thereof, and relates to the technical field of agricultural irrigation.The computer Internet of Things based agricultural planting irrigation detection device and the detection method thereof are provided with multiple soil humidity detection components, can detect the soil in a certain range from multiple directions, can analyze the soil humidity based on the soil humidity detection data of multiple positions, and thus avoid the inaccurate detection data of single area detection.The detection probe is arranged in the inside of the drill rod, can be pushed out of the drill rod during use, and can be stored in the drill rod after use, so that the damage of the detection probe caused by external force collision is avoided, the service life of the detection probe is prolonged, the distance between the adjusting rod and the mounting sleeve is adjusted through the telescopic arm component, the position of the guide cylinder is changed, the position of the soil humidity detection component is changed, and the detection range of the soil humidity detection component can be increased or decreased.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of agricultural irrigation technology, in particular to an agricultural planting irrigation detection device based on computer Internet of Things and a detection method thereof. BACKGROUND

[0002] The intelligent irrigation system of the Internet of Things automatic control utilizes sensors and processing systems to realize intelligent management of irrigation, so as to improve the irrigation management level, reduce the cost and maximize the benefit. The intelligent irrigation control system often utilizes soil humidity sensors and other sensors to collect soil humidity data, and transmits these data to the processing system. The processing system analyzes and compares the data to determine whether the soil humidity is lower than the water level required for normal growth of crops. When the processing system determines that the soil humidity is lower than the normal value, it means that the soil is short of water. The processing system sends an irrigation instruction to the irrigation execution mechanism to start water supply. In this way, the water in the soil can be increased until the soil humidity returns to the normal range. Through this intelligent control means, the intelligent irrigation system can implement irrigation according to the actual soil humidity condition to avoid excessive or insufficient irrigation, thereby improving the management level of soil humidity.

[0003] At present, most soil humidity detection devices use a single humidity probe to detect soil humidity. The single humidity probe can only monitor the humidity of the surface layer of the soil and cannot accurately obtain the humidity condition of the deep root part of crops, so the water condition of the root part position may be ignored. In addition, during the irrigation process, the soil is often not fully soaked, so that the irrigation water is mainly retained in the surface layer of the soil, and the soil moisture of the plant root layer is still insufficient. Due to the poor water retention of the soil, the water is easily evaporated and lost, resulting in frequent irrigation and waste of a large amount of water resources. Therefore, relying on a single soil humidity probe for pre-irrigation detection cannot obtain accurate soil humidity data, so that the crops cannot be fully irrigated in time.

[0004] Therefore, the present application provides an agricultural planting irrigation detection device based on computer Internet of Things and a detection method thereof to solve the above problems. SUMMARY

[0005] In view of the deficiencies of the prior art, the present application provides an agricultural planting irrigation detection device based on computer Internet of Things and a detection method thereof, which solves the problem that the single humidity probe of the current soil humidity detection device can only monitor the humidity of the surface layer of the soil and cannot accurately obtain the humidity condition of the deep root part of crops, and the problem that relying on a single soil humidity probe for pre-irrigation detection cannot obtain accurate soil humidity data, so that the crops cannot be fully irrigated in time.

[0006] In order to achieve the above object, the present application is realized by the following technical scheme: the agricultural planting irrigation detection device based on computer Internet of Things and the detection method thereof, comprising a supporting mechanism, a measurement range adjusting mechanism, a driving mechanism and a soil humidity detection assembly, the supporting mechanism is used for bearing the measurement range adjusting mechanism, the driving mechanism and the soil humidity detection assembly, the measurement range adjusting mechanism is arranged on the side wall of the supporting mechanism and is used for adjusting the sampling range of the soil sampling mechanism, the driving mechanism is arranged on the top of the supporting mechanism and is used for driving the soil sampling mechanism to carry out the soil sampling operation, the bottom of the supporting mechanism is provided with an evapotranspiration prediction assembly for detecting the evapotranspiration of crops and a data transmission module, the evapotranspiration prediction assembly is used for detecting the evapotranspiration of crops, and the data transmission module is used for transmitting the detected soil humidity data and evapotranspiration data to a mobile device.

[0007] Further, the supporting mechanism comprises a lower bearing plate, a sharp cone, a stand column and an upper bearing plate, the sharp cones are uniformly fixed on the bottom of the lower bearing plate and are used for penetrating into the soil to stabilize the support, the stand column is fixedly connected to the top of the lower bearing plate, and the upper bearing plate is fixedly connected to the top end of the stand column.

[0008] Further, the measurement range adjusting mechanism comprises a plurality of telescopic arm assemblies which are uniformly arranged on the outer walls of the lower bearing plate and the upper bearing plate respectively, the telescopic arm assembly comprises a mounting sleeve, an adjusting rod, a guide cylinder and a long strip block, the mounting sleeve is fixedly connected to the side wall of the upper bearing plate, the adjusting rod is slidingly connected to the inside of the mounting sleeve, the mounting sleeve and the adjusting rod are connected through bolts, the guide cylinder is fixedly connected to the end of the adjusting rod, and the long strip blocks are uniformly fixedly connected to the inner wall of the guide cylinder.

[0009] Further, the soil humidity detection assembly comprises a drill rod and guide grooves uniformly arranged on the outer wall of the drill rod, a lifting cylinder is slidably connected in the drill rod, a screw rod is threadedly connected in the lifting cylinder, the top end of the screw rod penetrates through the drill rod and extends to the outside, the screw rod and the drill rod are rotatably connected through a bearing, guide sliding grooves are uniformly arranged on the inner wall of the drill rod, guide sliding blocks that are matched with the guide sliding grooves are uniformly and fixedly arranged on the outer wall of the lifting cylinder, the guide sliding blocks are slidably connected in the guide sliding grooves, a detection component for detecting soil humidity is arranged in the drill rod, the detection component comprises a supporting plate, guide sleeves, a detection probe, first wedge plates and springs, the supporting plate is fixedly connected on the inner wall of the drill rod, a plurality of guide sleeves are uniformly and fixedly connected on the top of the supporting plate, the detection probe is slidably connected in each guide sleeve, the first wedge plate is fixedly connected to one end of the detection probe, the spring is sleeved on the outer wall of the detection probe and between the guide sleeve and the first wedge plate, second wedge plates that are matched with the first wedge plates in structure and position are uniformly and fixedly arranged at the bottom end of the lifting cylinder, the second wedge plates are used for driving the first wedge plates to move to the outside of the drill rod, through holes are arranged on the outer wall of the drill rod and opposite to the detection probe, the detection probe penetrates through the through holes and penetrates into the soil to detect the soil humidity, a threaded sleeve is threadedly sleeved on the outer wall of the drill rod, a first bevel gear disc is fixedly sleeved on the outer wall of the threaded sleeve, and the threaded sleeve is rotatably connected to the top of one of the guide cylinders.

[0010] Further, the driving mechanism comprises a second bevel gear disc, a transmission assembly, a motor bracket and a servo motor, the second bevel gear disc is rotatably connected to the top of the upper bearing plate, the motor bracket is fixedly connected to the top of the upper bearing plate, the servo motor is fixedly connected to the top of the motor bracket, the output shaft of the servo motor penetrates through the motor bracket and is connected with the second bevel gear disc, the transmission assembly comprises a first bevel gear, a transmission shaft and a second bevel gear, the first bevel gear and the second bevel gear are fixedly connected to the two ends of the transmission shaft respectively, the first bevel gear is meshedly connected with the second bevel gear disc, and the second bevel gear is meshedly connected with the first bevel gear disc.

[0011] Further, the long strip block is slidably connected in the guide groove, and the bottom end of the drill rod is provided with a sharp cone angle.

[0012] Further, the evapotranspiration amount prediction assembly comprises an original data acquisition module, a data preprocessing module, an evapotranspiration amount influence factor screening module, an evapotranspiration amount prediction module, a prediction model optimization module and an output predicted evapotranspiration amount module, the output end of the original data acquisition module is connected with the input end of the data preprocessing module, the output end of the data preprocessing module is connected with the input end of the evapotranspiration amount influence factor screening module, the output end of the evapotranspiration amount influence factor screening module is connected with the input end of the evapotranspiration amount prediction module, the output end of the evapotranspiration amount prediction module is connected with the input end of the prediction model optimization module, and the output end of the prediction model optimization module is connected with the input end of the output predicted evapotranspiration amount module.

[0013] The application further provides a detection method of the agricultural planting irrigation detection device based on computer Internet of Things.

[0014] Step one, erecting equipment: erecting the support mechanism on the ground of the crop planting area, and inserting the bottom end of the support mechanism into the soil, and measuring the horizontal state of the support mechanism by using a level, to ensure that the support mechanism is in a horizontal state.

[0015] Step two, soil sampling: driving the bottom end of the soil humidity detection assembly into the soil by using the driving equipment, manually operating to detect the soil humidity, and simultaneously detecting the plant evapotranspiration amount by using the evapotranspiration amount prediction assembly.

[0016] Step three, data feedback: the soil humidity detection data and the evapotranspiration amount detection data are transmitted to the mobile equipment by using the data transmission module for viewing.

[0017] Beneficial effects

[0018] The application provides an agricultural planting irrigation detection device based on computer Internet of Things and a detection method thereof.

[0019] Compared with the prior art, the application has the following beneficial effects:

[0020] 1. The agricultural planting irrigation detection device based on computer Internet of Things and its detection method, through the support mechanism for bearing the measurement range adjusting mechanism and the driving mechanism and the soil humidity detection assembly, the measurement range adjusting mechanism is arranged on the side wall of the support mechanism, for adjusting the sampling range of the soil sampling mechanism, the driving mechanism is arranged on the top of the support mechanism, for driving the soil sampling mechanism to take soil operation, the bottom of the support mechanism is provided with the evapotranspiration prediction assembly for detecting the evapotranspiration of crops and the data transmission module, the evapotranspiration prediction assembly is used for detecting the evapotranspiration of crops, and the data transmission module is used for transmitting the detected soil humidity data and evapotranspiration data to a mobile device, which solves the problem that the single humidity probe of the soil humidity detection device can only monitor the humidity of the soil surface, cannot accurately know the humidity condition of the deep part of the crop root, and cannot obtain accurate soil humidity data by relying on single soil humidity probe detection before irrigation, so that the crop cannot be irrigated in time.

[0021] 2. The agricultural planting irrigation detection device based on computer Internet of Things and its detection method, by arranging a plurality of soil humidity detection assemblies, the soil in a certain range can be detected in multiple directions, and the soil humidity condition can be comprehensively analyzed according to the soil humidity detection data of multiple positions, so that the problem of inaccurate detection data in single area detection is avoided.

[0022] 3. The agricultural planting irrigation detection device based on computer Internet of Things and its detection method, by arranging the detection probe in the inside of the drill rod, the detection probe can be pushed out of the drill rod during use, and can be stored in the drill rod after use, so that the damage caused by external force collision is avoided, and the service life is prolonged.

[0023] 4. The agricultural planting irrigation detection device based on computer Internet of Things and its detection method, by arranging the telescopic arm assembly, the distance between the adjusting rod and the mounting sleeve can be adjusted, the position of the guide cylinder is changed, so that the position of the soil humidity detection assembly is changed, the detection range can be increased or reduced, the soil humidity detection range is further increased, and the accuracy of the detection data is improved.

[0024] 5. The agricultural planting irrigation detection device based on computer Internet of Things and its detection method, by arranging the evapotranspiration prediction assembly, whether the irrigation condition is met can be judged by combining the crop evapotranspiration data with the soil humidity detection data, so that the suitable irrigation time point can be found more accurately, and the water resources can be saved. BRIEF DESCRIPTION OF DRAWINGS

[0025] Figure 1 It is an assembled state structure schematic view of the present application;

[0026] Figure 2 It is an exploded state structure schematic view of the present application;

[0027] Figure 3 It is a schematic diagram of the bottom structure of the application;

[0028] Figure 4 It is a schematic diagram of the enlarged structure of part A of the application;

[0029] Figure 5 It is a schematic diagram of the cross-sectional structure of the soil moisture detection assembly of the application;

[0030] Figure 6 It is a schematic diagram of the enlarged structure of part B of the application;

[0031] Figure 7 It is a schematic diagram of the structure of the extension arm assembly in the disassembled state of the application;

[0032] Figure 8 It is a structure principle block diagram of the evapotranspiration prediction assembly of the application;

[0033] Figure 9 It is a PCA-IGWO-DELM model diagram of the application.

[0034] In the figure: 1, lower bearing plate; 2, sharp cone; 3, stand column; 4, upper bearing plate; 5, extension arm assembly; 51, mounting sleeve; 52, adjusting rod; 53, guide cylinder; 54, long strip block; 6, soil moisture detection assembly; 61, drill rod; 62, guide groove; 63, lifting cylinder; 64, screw rod; 65, support plate; 66, guide sleeve; 67, detection probe; 68, first wedge-shaped plate; 69, spring; 610, second wedge-shaped plate; 611, threaded sleeve; 612, first bevel gear disc; 7, second bevel gear disc; 8, first bevel gear; 9, transmission shaft; 10, second bevel gear; 11, motor bracket; 12, servo motor; 14, evapotranspiration prediction assembly; 141, original data acquisition module; 142, data preprocessing module; 143, evapotranspiration influence factor screening module; 144, evapotranspiration prediction module; 145, prediction model optimization module; 146, output predicted evapotranspiration module. DETAILED DESCRIPTION

[0035] The technical solutions in the embodiments of the application will be described clearly and completely below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, rather than all the embodiments of the application. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor fall within the protection scope of the application.

[0036] The application provides two technical solutions:

[0037] For example, Figures 1-7The first embodiment is shown: based on the computer Internet of Things agricultural planting irrigation detection device, including support mechanism, measurement range adjusting mechanism, drive mechanism and soil humidity detection assembly 6, support mechanism is used for bearing measurement range adjusting mechanism and drive mechanism and soil humidity detection assembly 6, measurement range adjusting mechanism is arranged on the side wall of support mechanism, for adjusting the sampling range of soil sampling mechanism, drive mechanism is arranged on the top of support mechanism, for driving soil sampling mechanism to carry out the operation of taking soil, the bottom of support mechanism is provided with evapotranspiration prediction assembly 14 for detecting the evapotranspiration of crops and data transmission module, evapotranspiration prediction assembly 14 is used for detecting the evapotranspiration of crops, and data transmission module is used for transmitting the detected soil humidity data and evapotranspiration data to mobile equipment.

[0038] The support mechanism includes a lower bearing plate 1, a sharp cone 2, a column 3 and an upper bearing plate 4, the sharp cone 2 is uniformly fixed on the bottom of the lower bearing plate 1, used for penetrating into the soil to stabilize the support, the column 3 is fixedly connected on the top of the lower bearing plate 1, and the upper bearing plate 4 is fixedly connected on the top end of the column 3, the sharp cone 2 is inserted into the ground to realize the purpose of fixing the whole device.

[0039] The measurement range adjusting mechanism includes a plurality of telescopic arm assemblies 5 uniformly arranged on the outer walls of the lower bearing plate 1 and the upper bearing plate 4 respectively, the telescopic arm assembly 5 includes a mounting sleeve 51, an adjusting rod 52, a guide cylinder 53 and a long strip block 54, the mounting sleeve 51 is fixedly connected on the side wall of the upper bearing plate 4, the adjusting rod 52 is slidingly connected in the inside of the mounting sleeve 51, the mounting sleeve 51 and the adjusting rod 52 are connected by bolts, the guide cylinder 53 is fixedly connected on the end of the adjusting rod 52, and the long strip block 54 is uniformly fixedly connected on the inner wall of the guide cylinder 53, by loosening the bolts for fixing the mounting sleeve 51 and the adjusting rod 52, the position of the adjusting rod 52 relative to the mounting sleeve 51 can be changed, the purpose of changing the position of the guide cylinder 53 is realized, and the detection range of the soil humidity detection assembly 6 is further expanded.

[0040] The soil humidity detection assembly 6 comprises a drill rod 61 and guide grooves 62 uniformly opened on the outer wall of the drill rod 61, a lifting cylinder 63 slidably connected in the inside of the drill rod 61, a screw rod 64 threadedly connected in the inside of the lifting cylinder 63, the top end of the screw rod 64 penetrating through the drill rod 61 and extending to the outside, the screw rod 64 being rotatably connected with the drill rod 61 through a bearing, guide sliding grooves uniformly opened on the inner wall of the drill rod 61, guide sliding blocks uniformly and fixedly arranged on the outer wall of the lifting cylinder 63 and matched with the guide sliding groove structure, the guide sliding blocks being slidably connected in the guide sliding grooves, a detection component for detecting soil humidity arranged in the inside of the drill rod 61, the detection component comprising a supporting plate 65, guide sleeves 66, a detection probe 67, a first wedge plate 68 and a spring 69, the supporting plate 65 being fixedly connected on the inner wall of the drill rod 61, the guide sleeves 66 being uniformly and fixedly connected on the top of the supporting plate 65, the detection probe 67 being slidably connected in the inside of each guide sleeve 66, the first wedge plate 68 being fixedly connected at one end of the detection probe 67, the spring 69 being sleeved on the outer wall of the detection probe 67 and between the guide sleeve 66 and the first wedge plate 68, a second wedge plate 610 being uniformly and fixedly arranged at the bottom end of the lifting cylinder 63 and matched with the structure and position of the first wedge plate 68, for driving the first wedge plate 68 to move to the outside of the drill rod 61, through holes being uniformly opened on the outer wall of the drill rod 61 and opposite to the detection probe 67, for the detection probe 67 to pass through the through holes and penetrate into the soil to detect the soil humidity, a threaded sleeve 611 being threadedly sleeved on the outer wall of the drill rod 61, a first bevel gear disc 612 being fixedly sleeved on the outer wall of the threaded sleeve 611, the threaded sleeve 611 being rotatably connected at the top of one of the guide cylinders 53. The outer wall of the drill rod 61 is provided with a threaded groove above the guide groove 62, the threaded groove is threadedly connected in the inside of the threaded sleeve 611, the drill rod 61 can only be directionally slid up and down on the inner wall of the guide cylinder 53 by rotating the threaded sleeve 611 and limiting the guide groove 62 by the long strip block 54, when the soil is sampled, the drill rod 61 penetrates into the soil, the screw rod 64 is rotated, the lifting cylinder 63 is threadedly sleeved on the outer wall of the screw rod 64 and the guide sliding blocks on the outer wall of the lifting cylinder 63 are slid in the guide sliding grooves on the inner wall of the drill rod 61, therefore, after the screw rod 64 is rotated, the lifting cylinder 63 is lowered to push the second wedge plate 610 to move downwards, the first wedge plate 68 is pushed by the second wedge plate 610 to move to the outside of the drill rod 61, the detection probe 67 penetrates into the soil to detect the soil humidity data, the detected data is sent to the mobile terminal through the data transmission module, the detection probe 67 is reset by the spring 69 after the second wedge plate 610 moves upwards.

[0041] The driving mechanism comprises a second bevel gear disc 7, a transmission assembly, a motor frame 11 and a servo motor 12, the second bevel gear disc 7 is rotationally connected to the top of the upper bearing plate 4, the motor frame 11 is fixedly connected to the top of the upper bearing plate 4, the servo motor 12 is fixedly connected to the top of the motor frame 11, the output shaft of the servo motor 12 rotationally penetrates through the motor frame 11 and is connected with the second bevel gear disc 7, the transmission assembly comprises a first bevel gear 8, a transmission shaft 9 and a second bevel gear 10, the first bevel gear 8 and the second bevel gear 10 are fixedly connected to the two ends of the transmission shaft 9 respectively, the first bevel gear 8 is in meshing connection with the second bevel gear disc 7, the second bevel gear 10 is in meshing connection with the first bevel gear disc 612, the servo motor 12 drives the second bevel gear disc 7 to rotate, the second bevel gear disc 7 is in meshing connection with the plurality of first bevel gears 8, so that the plurality of first bevel gears 8 can be simultaneously driven to rotate, power is transmitted to the second bevel gear 10 through the transmission shaft 9, since the second bevel gear 10 is in meshing connection with the first bevel gear disc 612, the second bevel gear 10 can drive the first bevel gear disc 612 to rotate when the second bevel gear 10 rotates.

[0042] The long strip block 54 is slidingly connected in the interior of the guide groove 62, and the bottom end of the drill rod 61 is provided with a sharp taper angle.

[0043] As Figures 8-9 The second embodiment is shown, and the main difference from the first embodiment is that the evapotranspiration amount prediction assembly 14 comprises an original data acquisition module 141, a data preprocessing module 142, an evapotranspiration amount influence factor screening module 143, an evapotranspiration amount prediction module 144, a prediction model optimization module 145 and an output predicted evapotranspiration amount module 146, the output end of the original data acquisition module 141 is connected with the input end of the data preprocessing module 142, the output end of the data preprocessing module 142 is connected with the input end of the evapotranspiration amount influence factor screening module 143, the output end of the evapotranspiration amount influence factor screening module 143 is connected with the input end of the evapotranspiration amount prediction module 144, the output end of the evapotranspiration amount prediction module 144 is connected with the input end of the prediction model optimization module 145, and the output end of the prediction model optimization module 145 is connected with the input end of the output predicted evapotranspiration amount module 146.

[0044] In view of the problem of too large input data dimension, the kernel principal component analysis method is used to preprocess the input data to obtain important influence factors affecting the evapotranspiration amount. Secondly, in view of the problem of low accuracy of the current plant evapotranspiration prediction model, the intelligent optimization algorithm is used to improve the deep extreme learning machine to construct a wheat evapotranspiration prediction model.

[0045] Based on the principle of thermal equivalence, such as the Penman-Monteth (PM) formula. The Penman-Monteth formula was proposed by Penman in 1948, and has small calculation error and high accuracy, so it is widely used. The Penman-Monteth formula is set as the standard method for calculating the evapotranspiration amount of reference crops by the Food and Agriculture Organization of the United Nations. The formula is calculated as follows:

[0046]

[0047] wherein ET0represents the evapotranspiration amount of the reference crop, and the unit is mm / d; Δ represents the slope of the saturated water vapor pressure temperature curve, and the unit is kPa / °C; Rn represents the average net radiation on the surface of the crop, and the unit is MJ / m2d; G represents the soil heat flux, and the unit is MJ / m2d; T hr represents the average temperature, and the unit is °C; u2 represents the average wind speed at 2 meters, and the unit is m / s; e s and e a represent the saturated water vapor pressure and the actual water vapor pressure, respectively, and the unit is kPa.

[0048] From formula (3-1), it can be seen that various factors affecting the evapotranspiration amount are mainly obtained by sensor measurement, and generally include temperature, humidity, wind speed and other data. The data obtained by measurement are used to calculate the parameter values of Δ, R n , etc., wherein the calculation formula of the slope of the saturated water vapor pressure temperature curve Δ is as follows:

[0049]

[0050] In the actual planting environment, the actual evapotranspiration amount of the crop is related to many factors such as the type of the crop. The calculation of the actual evapotranspiration amount needs to multiply the reference crop evapotranspiration amount ET0by the crop coefficient K c of the corresponding crop. The specific calculation formula is as follows:

[0051] ET c = ET0× K c (3-3)

[0052] wherein ET c represents the actual evapotranspiration amount of the crop, and K c represents the crop coefficient.

[0053] From formula (3-1), it can be seen that there are many factors affecting the wheat evapotranspiration amount, and the calculation amount is large, and there may be redundant information, which will affect the prediction accuracy and calculation speed of the wheat evapotranspiration amount. In order to eliminate the redundant information and speed up the calculation speed of the wheat evapotranspiration amount, the principal component analysis method is used to reduce the dimension of the data characteristics of the wheat evapotranspiration amount, so as to retain a few data characteristics (principal components) with large variance and eliminate the data characteristics with almost zero variance. PCA is the most widely used data dimension reduction algorithm, and its main idea is to map the data characteristics on the high-dimensional n-dimensional space to the low-dimensional k-dimensional space, so as to obtain the k-dimensional which is a new orthogonal characteristic, also known as principal component. Assuming that the data set composed of the original data of the wheat evapotranspiration amount influencing factors is X=[x ij n×d ​where n represents the sample number of wheat, d represents the dimension of the relevant factors (including air humidity, air temperature, soil humidity, light intensity, wind, etc.) affecting the evapotranspiration of wheat per plant characteristics, PCA algorithm can be used to reduce dimension processing of X data, retain key factors, and eliminate redundant information to realize data compression.

[0054] Grey wolf optimization algorithm is inspired by the social hierarchy system within the grey wolf population. The alpha wolf has the privilege of making decisions for the wolf pack, including hunting, defense, and rest. The second-ranked wolf is called beta, which is the successor of the alpha wolf. The third-ranked wolf is named delta, which obeys the orders of the superior alpha wolf and beta wolf. The remaining wolf group is the lowest level, which must obey the orders of the alpha wolf, beta wolf, and delta wolf. In GWO, the optimal solution in the population is represented as X α , the second optimal solution and the third optimal solution are represented as X β and x δ , and the remaining individuals are represented as X. The optimization mechanism of GWO is inspired by the hunting behavior of grey wolves, which can be divided into the following three steps: tracking, chasing, and approaching prey. When the termination condition is met, the optimal solution X α is output.

[0055] (1) Cat chaotic mapping strategy

[0056] In the standard GWO algorithm, the random initialization method of the population produces uneven individual position distribution and poor stability, which reduces the optimization accuracy of the algorithm. Cat mapping strategy is a two-dimensional reversible chaotic mapping with simple structure, better ergodicity and iteration speed, and can calculate uniform chaotic sequences. In order to increase the diversity of the initial population, this paper improves the population initialization process of GWO algorithm by using Cat mapping strategy. The dynamic equation calculation formula of Cat mapping strategy is as follows:

[0057]

[0058] Where the chaotic sequence generated by Cat is in the interval [0, 1], and mod represents the modulo operation.

[0059] (2) Stagnation detection strategy

[0060] GWO algorithm is prone to fall into local optimum for complex optimization problems. In order to overcome the problem of falling into local optimum, this section improves the search strategy selection process of GWO algorithm by using stagnation detection strategy. Stagnation detection strategy compares whether the average position of the previous and subsequent populations is the same to determine whether the population falls into local optimum. The specific detection strategy is as follows:

[0061]

[0062]

[0063] where F stag is a flag indicating whether the population falls into local optimum, X mean is the average position of the individual optimum, X lbest is the current optimum position of the i-th grey wolf.

[0064] (3) Gauss-Levy disturbance strategy

[0065] When the GWO algorithm falls into local optimum, if the standard position updating method is continued, the population will stagnate, the diversity will decrease, and the algorithm will converge too early. In order to avoid falling into local optimum, Gauss-Levy disturbance strategy is introduced in this section. After Gauss random mutation or Levy flight strategy, the grey wolf individual position updating is as follows:

[0066] 1) Gauss random walk strategy

[0067] x i = x α + randn · (x i - x α ) + randn · (x lbest - x i ) (3-7)

[0068] where randn represents a random parameter subject to normal distribution. This strategy mainly uses the global optimal solution and the individual optimal solution to update the individual position, which accelerates the search speed and search efficiency.

[0069] 2) Levy flight strategy

[0070] Levy flight has a small flight step length for a long time, and occasionally produces a longer flight step length to increase the diversity of flight. The specific calculation formula of Levy flight model is as follows:

[0071]

[0072]

[0073] where x i t+1 is the i-th grey wolf individual of the t+1 generation, Levy(·) represents Levy flight model, a represents the proportion factor, which takes value [-1, 1]; s is the random walk step length, which is calculated as follows:

[0074]

[0075]

[0076] σ v = 1 (3-12)

[0077] where u and v are parameters subject to normal distribution, i.e. u 2 ), v N(0,б v 2 ), and Gamma(·) is a gamma function.

[0078] The PCA-IGWO-DELM prediction model based on PCA and improved GWO algorithm mainly includes a data preprocessing module, an optimized weight module and a deep extreme learning machine module. Firstly, the PCA is used for screening the evapotranspiration influencing factors. The IGWO is used for decoding the parameters into weights, so as to construct the DELM network. Then, the training data of the data module are used for training the DELM. The optimal test set is used for prediction, so as to obtain the error between the expected value and the actual output value.

[0079] The embodiment of the present application also provides a detection method of the agricultural planting irrigation detection device based on the computer Internet of Things, which comprises the following steps:

[0080] Step one, erecting equipment: erecting the support mechanism on the ground of the crop planting area, and tying the bottom end of the support mechanism into the soil, and measuring the horizontal state of the support mechanism by using a level, so as to ensure that the support mechanism is in a horizontal state;

[0081] Step two, soil sampling: driving the bottom end of the soil humidity detection assembly (6) into the soil by using the driving equipment, manually operating to detect the soil humidity, and simultaneously detecting the plant evapotranspiration by using the evapotranspiration prediction assembly (14);

[0082] Step three, data feedback: the soil humidity detection data and the evapotranspiration detection data are transmitted to a mobile device through a data transmission module for viewing.

[0083] It should be noted that, in this document, relational terms such as first and second and the like can 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. Moreover, the terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can include other elements not expressly listed or inherent to such process, method, article, or apparatus.

[0084] While embodiments of the application have been shown and described, it is to be understood that the embodiments described are merely exemplary of the principles and application of the present application. Numerous modifications and adaptions can be effected without departing from the spirit and scope of the present application, which is not limited to the exact construction and arrangement described. It is intended, therefore, to cover all modifications and adaptions that fall within the scope of the claims and their equivalents.

Claims

1. An agricultural planting irrigation monitoring device based on the Internet of Things (IoT), characterized in that: The device includes a support mechanism, a measurement range adjustment mechanism, a drive mechanism, and a soil moisture detection component (6). The support mechanism is used to support the measurement range adjustment mechanism, the drive mechanism, and the soil moisture detection component (6). The measurement range adjustment mechanism is located on the side wall of the support mechanism. The drive mechanism is located on the top of the support mechanism. The bottom of the support mechanism is provided with an evapotranspiration prediction component (14) for detecting crop evapotranspiration and a data transmission module. The evapotranspiration prediction component (14) is used to detect crop evapotranspiration, and the data transmission module is used to transmit the detected soil moisture data and evapotranspiration data to a mobile device. The support mechanism includes a lower bearing plate (1), a cone (2), a column (3) and an upper bearing plate (4). The cone (2) is evenly fixed at the bottom of the lower bearing plate (1) for driving into the soil for stable support. The column (3) is fixedly connected to the top of the lower bearing plate (1), and the upper bearing plate (4) is fixedly connected to the top of the column (3). The measurement range adjustment mechanism includes multiple telescopic arm assemblies (5) evenly arranged on the outer walls of the lower bearing plate (1) and the upper bearing plate (4). Each telescopic arm assembly (5) includes a mounting sleeve (51), an adjusting rod (52), a guide cylinder (53), and a long strip (54). The mounting sleeve (51) is fixedly connected to the side wall of the upper bearing plate (4). The adjusting rod (52) is slidably connected inside the mounting sleeve (51). The mounting sleeve (51) and the adjusting rod (52) are connected by bolts. The guide cylinder (53) is fixedly connected to the end of the adjusting rod (52). The long strip (54) is evenly fixedly connected to the inner wall of the guide cylinder (53). The soil moisture detection component (6) includes a drill rod (61) and guide grooves (62) evenly formed on the outer wall of the drill rod (61). A lifting cylinder (63) is slidably connected inside the drill rod (61), and a screw (64) is threadedly connected inside the lifting cylinder (63). The top end of the screw (64) passes through the drill rod (61) and extends to the outside. The screw (64) and the drill rod (61) are rotatably connected by a bearing. Guide grooves are evenly formed on the inner wall of the drill rod (61). Guide sliders adapted to the structure of the guide groove are uniformly fixed on the outer wall of the cylinder (63). The guide sliders are slidably connected in the guide groove. The drill rod (61) is provided with a detection component for detecting soil moisture. The detection component includes a support plate (65), a guide sleeve (66), a detection probe (67), a first wedge plate (68), and a spring (69). The support plate (65) is fixedly connected to the inner wall of the drill rod (61). Multiple guide sleeves (66) are uniformly fixedly connected to the top of the support plate (65). A detection probe (67) is slidably connected inside each guide sleeve (66). One end of the detection probe (67) is fixedly connected to the first wedge plate (68). A spring (69) is sleeved on the outer wall of the detection probe (67) between the guide sleeve (66) and the first wedge plate (68). A second wedge plate (610) adapted to the structure and position of the first wedge plate (68) is uniformly fixedly provided at the bottom end of the lifting cylinder (63) for driving the first wedge plate. The plate (68) moves outward from the drill rod (61). The drill rod (61) has through holes at positions opposite to the detection probe (67) on its outer wall. The detection probe (67) passes through the through holes and penetrates into the soil to detect soil moisture. A threaded sleeve (611) is threaded on the outer wall of the drill rod (61). A first helical toothed disc (612) is fixedly fitted on the outer wall of the threaded sleeve (611). The threaded sleeve (611) is rotatably connected to the top of one of the guide cylinders (53).

2. The agricultural planting irrigation detection device based on computer Internet of Things as described in claim 1, characterized in that: The drive mechanism includes a second helical gear disk (7), a transmission assembly, a motor frame (11), and a servo motor (12). The second helical gear disk (7) is rotatably connected to the top of the upper support plate (4). The motor frame (11) is fixedly connected to the top of the upper support plate (4). The servo motor (12) is fixedly connected to the top of the motor frame (11). The output shaft of the servo motor (12) rotatably passes through the motor frame (11) and is connected to the second helical gear disk (7). The transmission assembly includes a first bevel gear (8), a transmission shaft (9), and a second bevel gear (10). The first bevel gear (8) and the second bevel gear (10) are respectively fixedly connected to the two ends of the transmission shaft (9). The first bevel gear (8) and the second helical gear disk (7) are meshed together. The second bevel gear (10) and the first helical gear disk (612) are meshed together.

3. The agricultural planting irrigation detection device based on computer Internet of Things as described in claim 1, characterized in that: The long strip (54) is slidably connected inside the guide groove (62), and the bottom end of the drill rod (61) is provided with a pointed cone angle.

4. The agricultural planting irrigation detection device based on computer Internet of Things as described in claim 1, characterized in that: The evapotranspiration prediction component (14) includes a raw data acquisition module (141), a data preprocessing module (142), an evapotranspiration influencing factor screening module (143), an evapotranspiration prediction module (144), a prediction model optimization module (145), and an output prediction evapotranspiration module (146). The output end of the raw data acquisition module (141) is connected to the input end of the data preprocessing module (142). The output end of the data preprocessing module (142) is connected to the input end of the evapotranspiration influencing factor screening module (143). The output end of the evapotranspiration influencing factor screening module (143) is connected to the input end of the evapotranspiration prediction module (144). The output end of the evapotranspiration prediction module (144) is connected to the input end of the prediction model optimization module (145). The output end of the prediction model optimization module (145) is connected to the input end of the output prediction evapotranspiration module (146).

5. The detection method of the agricultural planting irrigation detection device based on computer Internet of Things according to claim 1, characterized in that: Specifically, the following steps are included: Step 1: Erect the equipment: Set up the support structure on the ground in the crop planting area, and drive the bottom of the support structure into the soil. Use a level to measure the horizontal status of the support structure to ensure that the support structure is horizontal. Step 2, Soil testing: Drive the bottom of the soil moisture detection component (6) into the soil using the drive mechanism, and then manually operate to detect the soil moisture. At the same time, use the evapotranspiration prediction component (14) to detect the plant evapotranspiration. Step 3: Data Feedback: Soil moisture and evapotranspiration data are transmitted to mobile devices via a data transmission module for viewing.

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