CN115088596B - Farmland irrigation system based on Internet of things and control method thereof - Google Patents
Farmland irrigation system based on Internet of things and control method thereof Download PDFInfo
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- CN115088596B CN115088596B CN202210783213.0A CN202210783213A CN115088596B CN 115088596 B CN115088596 B CN 115088596B CN 202210783213 A CN202210783213 A CN 202210783213A CN 115088596 B CN115088596 B CN 115088596B
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- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
- A01G—HORTICULTURE; CULTIVATION OF VEGETABLES, FLOWERS, RICE, FRUIT, VINES, HOPS OR SEAWEED; FORESTRY; WATERING
- A01G25/00—Watering gardens, fields, sports grounds or the like
- A01G25/16—Control of watering
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- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
- A01G—HORTICULTURE; CULTIVATION OF VEGETABLES, FLOWERS, RICE, FRUIT, VINES, HOPS OR SEAWEED; FORESTRY; WATERING
- A01G25/00—Watering gardens, fields, sports grounds or the like
- A01G25/16—Control of watering
- A01G25/167—Control by humidity of the soil itself or of devices simulating soil or of the atmosphere; Soil humidity sensors
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A40/00—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production
- Y02A40/10—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production in agriculture
- Y02A40/22—Improving land use; Improving water use or availability; Controlling erosion
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Abstract
The invention discloses a farmland irrigation system based on the Internet of things, which comprises: a plurality of temperature sensors distributed in the irrigation area for collecting the temperature of the installation position; a plurality of soil humidity sensors distributed in the irrigation area for collecting soil humidity at the installation position; a temperature sensor and a soil humidity sensor are respectively arranged at one installation position; the meteorological data communication module is used for receiving and forwarding meteorological data of an irrigation area; the central control module is used for receiving the data information sent by the temperature sensor, the soil humidity sensor and the meteorological data communication module, processing and analyzing the data information, controlling the different temperature sensors and the soil humidity sensor to switch between a dormant state and a working state, and controlling the opening and closing of the electromagnetic valve on the irrigation pipeline. The invention can improve the defects of the prior art, and improves the prediction accuracy of irrigation water consumption on the premise of not increasing the number of the sensors.
Description
Technical Field
The invention relates to the technical field of farmland irrigation, in particular to a farmland irrigation system based on the Internet of things and a control method thereof.
Background
With the development of the Internet of things technology, the Internet of things technology gradually permeates the agricultural field, and the agricultural automation degree is effectively improved. In the field of farm irrigation, the accurate irrigation can be realized through the control of thing networking, can further improve the water conservation effect in traditional drip irrigation, micro-irrigation technology. However, in order to improve the control accuracy, the existing irrigation control system based on the internet of things needs to increase the installation number of various sensors, which brings about an increase in the use cost of the system. Therefore, how to achieve improvement of control accuracy on the premise of control cost is one of the research hotspots in the art.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a farmland irrigation system based on the Internet of things and a control method thereof, which can solve the defects of the prior art and improve the prediction accuracy of irrigation water consumption on the premise of not increasing the installation quantity of sensors.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows.
A farmland irrigation system based on the Internet of things comprises,
a plurality of temperature sensors distributed in the irrigation area for collecting the temperature of the installation position;
a plurality of soil humidity sensors distributed in the irrigation area for collecting soil humidity at the installation position;
a temperature sensor and a soil humidity sensor are respectively arranged at one installation position;
the meteorological data communication module is used for receiving and forwarding meteorological data of an irrigation area;
the central control module is used for receiving the data information sent by the temperature sensor, the soil humidity sensor and the meteorological data communication module, processing and analyzing the data information, controlling the different temperature sensors and the soil humidity sensor to switch between a dormant state and a working state, and controlling the opening and closing of the electromagnetic valve on the irrigation pipeline.
The control method of the farmland irrigation system based on the Internet of things comprises the following steps:
A. the central control module performs switching control of a dormant state and a working state on the temperature sensor and the soil humidity sensor;
B. the temperature sensor and the soil humidity sensor in the working state send collected data to the central control module, and the meteorological data communication module sends meteorological data to the central control module;
C. the central control module processes and analyzes the data information and controls the opening and closing of the electromagnetic valve on the irrigation pipeline according to the analysis result.
Preferably, in the step A, the temperature sensor and the soil humidity sensor which account for 10% -15% of the total number are respectively kept in the working state at the same time, and at least 3% of the temperature sensor and the soil humidity sensor which are in the working state are positioned at the same installation position;
a1, the central control module calculates irrigation water quantity corresponding to the installation position according to collected data of a temperature sensor and a soil humidity sensor which are in working states at the same installation position and combined with meteorological data;
a2, the central control module calculates the irrigation water quantity of the corresponding installation position according to the calculated irrigation water quantity and the acquired data of the temperature sensor or the soil humidity sensor at other installation positions and the meteorological data;
a3, changing the temperature sensor and the soil humidity sensor in the working state into the dormant state, then selecting the same number of temperature sensors and soil humidity sensors from the temperature sensor and the soil humidity sensor in the dormant state to be changed into the working state, simultaneously keeping at least 3% of the temperature sensors and the soil humidity sensor in the working state at the same mounting position, and obtaining irrigation water quantity in the previous round of calculation at the mounting positions where the temperature sensor and the soil humidity sensor in the working state are located at the same time, wherein one half of the mounting positions obtain irrigation water quantity in the previous round of calculation, and the other mounting positions do not obtain irrigation water quantity in the previous round of calculation.
Preferably, in step C, the processing analysis of the data information includes the steps of,
c1, inputting temperature data, soil humidity data and meteorological data into a preset neural network prediction model for the installation position with the temperature data, the soil humidity data and the meteorological data at the same time to obtain irrigation water quantity;
c2, fitting the missing item of data for the installation position with any one of temperature data and soil humidity data and meteorological data, and inputting the acquired data and the fitted data into a preset neural network prediction model to obtain irrigation water quantity;
and C3, after the working/dormant states of the temperature sensor and the soil humidity sensor are changed, recalculating the irrigation water quantity according to the steps C1 and C2, and correcting the fitting process of the missing data by using the acquired data and the corresponding fitting data for the installation position of the irrigation water quantity obtained by calculation.
Preferably, in step C2, fitting the missing data comprises the steps of,
c21, establishing a correlation function set of another acquired data on the installation position where the missing data is located and similar acquired data on other installation positions;
c22, establishing a correction function of temperature data and soil humidity data according to historical meteorological data, and correcting the association function set by using the correction function;
and C23, inputting the data which are acquired at other installation positions and are similar to the missing data into the corrected association function set to calculate the missing data.
Preferably, in step C3, the correction of the fitting process of the missing data comprises the steps of,
c31, calculating deviation data of the acquired data and corresponding fitting data;
c32, dividing the deviation data counted in the step C31 into a common deviation and a characteristic deviation, wherein the common deviation is the deviation data with the same characteristics in the deviation data, and the rest deviation data are characteristic deviations;
c33, correcting the correction function by using the common deviation;
and C34, correcting the correlation function related to the correlation function set by using the characteristic deviation.
The beneficial effects brought by adopting the technical scheme are as follows: according to the invention, by establishing the correlation function of the data collected by the sensors between different mounting positions and effectively correcting the historical meteorological data, the accurate fitting of missing data can be realized, and the prediction of irrigation water consumption under the condition that all the temperature and humidity data are not collected is realized. Meanwhile, the fitting process of the system is corrected by using the fitting value and the actual collecting value of the same data between adjacent rounds of data collection, so that the whole prediction system can synchronously and self-correct, the system is kept at a high-precision prediction level for a long time, and the influence of external environment factor change on the prediction system is reduced.
Drawings
Fig. 1 is a schematic diagram of one embodiment of the present invention.
Detailed Description
Referring to fig. 1, one embodiment of the present invention includes,
a plurality of temperature sensors 1 distributed in the irrigation area for collecting the temperature of the installation position;
a plurality of soil humidity sensors 2 distributed in the irrigation area for collecting soil humidity at the installation position;
a temperature sensor 1 and a soil humidity sensor 2 are respectively arranged at one installation position;
the meteorological data communication module 3 is used for receiving and forwarding meteorological data of an irrigation area;
the central control module 4 is used for receiving the data information sent by the temperature sensor 1, the soil humidity sensor 2 and the meteorological data communication module 3, processing and analyzing the data information, controlling the different temperature sensors 1 and the soil humidity sensor 2 to switch between a dormant state and a working state, and controlling the opening and closing of the electromagnetic valve 5 on the irrigation pipeline.
The control method of the farmland irrigation system based on the Internet of things comprises the following steps:
A. the central control module 4 performs switching control of a dormant state and a working state on the temperature sensor 1 and the soil humidity sensor 2;
B. the temperature sensor 1 and the soil humidity sensor 2 in the working state send collected data to the central control module 4, and the meteorological data communication module 3 sends meteorological data to the central control module 4;
C. the central control module 4 processes and analyzes the data information and controls the opening and closing of the electromagnetic valve 5 on the irrigation pipeline according to the analysis result.
In the step A, the temperature sensor 1 and the soil humidity sensor 2 which account for 10% -15% of the total number are respectively kept in the working state at the same moment, and at least 3% of the temperature sensor 1 and the soil humidity sensor 2 which are in the working state are positioned at the same installation position;
a1, a central control module 4 calculates irrigation water quantity corresponding to an installation position according to collected data of a temperature sensor 1 and a soil humidity sensor 2 which are simultaneously in a working state at the same installation position and combined with meteorological data;
a2, the central control module 4 calculates the irrigation water quantity of the corresponding installation position according to the calculated irrigation water quantity and the acquired data of the temperature sensor 1 or the soil humidity sensor 2 at other installation positions and combining with meteorological data;
a3, changing the temperature sensor 1 and the soil humidity sensor 2 which are in the working state into the dormant state, then selecting the same number of the temperature sensors 1 and the soil humidity sensors 2 which are originally in the dormant state into the working state, simultaneously keeping at least 3% of the temperature sensors 1 and the soil humidity sensors 2 which are in the working state at the same mounting position, and obtaining irrigation water quantity in the previous round of calculation at half of the mounting positions in which the temperature sensors 1 and the soil humidity sensors 2 which are in the working state are located, and not obtaining irrigation water quantity in the previous round of calculation at other mounting positions.
In step C, the processing analysis of the data information includes the steps of,
c1, inputting temperature data, soil humidity data and meteorological data into a preset neural network prediction model for the installation position with the temperature data, the soil humidity data and the meteorological data at the same time to obtain irrigation water quantity;
c2, fitting the missing item of data for the installation position with any one of temperature data and soil humidity data and meteorological data, and inputting the acquired data and the fitted data into a preset neural network prediction model to obtain irrigation water quantity;
and C3, after the working/dormant states of the temperature sensor 1 and the soil humidity sensor 2 are changed, recalculating the irrigation water quantity according to the steps C1 and C2, and correcting the fitting process of the missing data by using the acquired data and the corresponding fitting data for the installation position of the irrigation water quantity obtained by calculation for the two times.
In step C2, fitting the missing data includes the steps of,
c21, establishing a correlation function set of another acquired data on the installation position where the missing data is located and similar acquired data on other installation positions;
c22, establishing a correction function of temperature data and soil humidity data according to historical meteorological data, and correcting the association function set by using the correction function;
and C23, inputting the data which are acquired at other installation positions and are similar to the missing data into the corrected association function set to calculate the missing data.
In step C3, the correction of the fitting process of the missing data includes the steps of,
c31, calculating deviation data of the acquired data and corresponding fitting data;
c32, dividing the deviation data counted in the step C31 into a common deviation and a characteristic deviation, wherein the common deviation is the deviation data with the same characteristics in the deviation data, and the rest deviation data are characteristic deviations;
c33, correcting the correction function by using the common deviation;
and C34, correcting the correlation function related to the correlation function set by using the characteristic deviation.
According to the invention, through the optimized use of limited data, the correlation between soil data and meteorological data is utilized to realize the accurate fitting of missing data, so that the prediction accuracy of irrigation water consumption is improved on the premise of not increasing the number of sensors.
In the description of the present invention, it should be understood that the terms "longitudinal," "transverse," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like indicate or are based on the orientation or positional relationship shown in the drawings, merely to facilitate description of the present invention, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus should not be construed as limiting the present invention.
The foregoing has shown and described the basic principles and main features of the present invention and the advantages of the present invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and that the above embodiments and descriptions are merely illustrative of the principles of the present invention, and various changes and modifications may be made without departing from the spirit and scope of the invention, which is defined in the appended claims. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (2)
1. A control method of a farmland irrigation system based on the Internet of things, the farmland irrigation system based on the Internet of things comprises,
a plurality of temperature sensors (1) distributed in the irrigation area and used for collecting the temperature of the installation position;
a plurality of soil humidity sensors (2) distributed in the irrigation area for collecting soil humidity at the installation position;
a temperature sensor (1) and a soil humidity sensor (2) are respectively arranged at one installation position;
the meteorological data communication module (3) is used for receiving and forwarding meteorological data of an irrigation area;
the central control module (4) is used for receiving the data information sent by the temperature sensor (1), the soil humidity sensor (2) and the meteorological data communication module (3), processing and analyzing the data information, controlling the different temperature sensors (1) and the soil humidity sensor (2) to switch between a dormant state and a working state, and controlling the opening and closing of the electromagnetic valve (5) on the irrigation pipeline;
the method is characterized by comprising the following steps of:
A. the central control module (4) performs switching control of a dormant state and a working state on the temperature sensor (1) and the soil humidity sensor (2);
B. the temperature sensor (1) and the soil humidity sensor (2) in working states send collected data to the central control module (4), and the meteorological data communication module (3) sends meteorological data to the central control module (4);
C. the central control module (4) processes and analyzes the data information and controls the opening and closing of the electromagnetic valve (5) on the irrigation pipeline according to the analysis result;
processing and analyzing the data information includes the steps of,
c1, inputting temperature data, soil humidity data and meteorological data into a preset neural network prediction model for the installation position with the temperature data, the soil humidity data and the meteorological data at the same time to obtain irrigation water quantity;
c2, fitting the missing item of data for the installation position with any one of temperature data and soil humidity data and meteorological data, and inputting the acquired data and the fitted data into a preset neural network prediction model to obtain irrigation water quantity; fitting the missing data includes the steps of,
c21, establishing a correlation function set of another acquired data on the installation position where the missing data is located and similar acquired data on other installation positions;
c22, establishing a correction function of temperature data and soil humidity data according to historical meteorological data, and correcting the association function set by using the correction function;
c23, inputting the data which are acquired from other installation positions and are similar to the missing data into the corrected association function set to calculate the missing data;
c3, after the working/dormant states of the temperature sensor (1) and the soil humidity sensor (2) are changed, recalculating irrigation water quantity according to the steps C1 and C2, and correcting the fitting process of missing data by using acquired data and corresponding fitting data for the installation position of the irrigation water quantity obtained by calculation for the two times; the correction of the fitting process of the missing data includes the steps of,
c31, calculating deviation data of the acquired data and corresponding fitting data;
c32, dividing the deviation data counted in the step C31 into a common deviation and a characteristic deviation, wherein the common deviation is the deviation data with the same characteristics in the deviation data, and the rest deviation data are characteristic deviations;
c33, correcting the correction function by using the common deviation;
and C34, correcting the correlation function related to the correlation function set by using the characteristic deviation.
2. The control method of the farmland irrigation system based on the internet of things according to claim 1, wherein the control method comprises the following steps: in the step A, the temperature sensor (1) and the soil humidity sensor (2) which account for 10-15% of the total number are respectively kept in the working state at the same moment, and the temperature sensor (1) and the soil humidity sensor (2) which are in the working state are positioned at the same mounting position while at least 3% of the temperature sensor and the soil humidity sensor are positioned at the same mounting position;
a1, a central control module (4) obtains irrigation water quantity of a corresponding installation position according to collected data of a temperature sensor (1) and a soil humidity sensor (2) which are simultaneously in a working state at the same installation position and combined with meteorological data;
a2, the central control module (4) calculates the irrigation water quantity of the corresponding installation position according to the calculated irrigation water quantity and the acquired data of the temperature sensor (1) or the soil humidity sensor (2) at other installation positions and combining with meteorological data;
a3, changing the temperature sensor (1) and the soil humidity sensor (2) which are in the working state into the dormant state, then selecting the same number of the temperature sensors (1) and the soil humidity sensor (2) which are in the dormant state from the temperature sensor (1) and the soil humidity sensor (2) which are in the original state into the working state, simultaneously keeping at least 3 percent of the temperature sensors (1) and the soil humidity sensor (2) which are in the working state at the same mounting position, and obtaining irrigation water quantity in the last round of calculation at the mounting positions where the temperature sensor (1) and the soil humidity sensor (2) which are in the working state are located at the same time, wherein the irrigation water quantity is obtained in the last round of calculation at the other mounting positions where the irrigation water quantity is not obtained in the last round of calculation.
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