CN113841593A - Intelligent farmland irrigation system and irrigation method based on Internet of things - Google Patents
Intelligent farmland irrigation system and irrigation method based on Internet of things Download PDFInfo
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- CN113841593A CN113841593A CN202111273630.2A CN202111273630A CN113841593A CN 113841593 A CN113841593 A CN 113841593A CN 202111273630 A CN202111273630 A CN 202111273630A CN 113841593 A CN113841593 A CN 113841593A
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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
- A01G25/02—Watering arrangements located above the soil which make use of perforated pipe-lines or pipe-lines with dispensing fittings, e.g. for drip irrigation
- A01G25/023—Dispensing fittings for drip irrigation, e.g. drippers
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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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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16Y—INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR THE INTERNET OF THINGS [IoT]
- G16Y10/00—Economic sectors
- G16Y10/05—Agriculture
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- 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 an Internet of things-based farmland intelligent irrigation system which comprises a crop growth characteristic database, a data acquisition mechanism, an alarm unit, a cloud end, a background service unit, a mobile terminal, a monitoring interface, an irrigation main control unit and an irrigation execution mechanism.
Description
Technical Field
The invention belongs to the technical field of intelligent irrigation, and particularly relates to an intelligent farmland irrigation system and an intelligent farmland irrigation method based on the Internet of things.
Background
The population of China is rapidly increased, the growth level of industry and agriculture is continuously developed, and the shortage of water resources is increasingly serious. In China, the agricultural water consumption accounts for about 80% of the total water consumption, the agricultural irrigation efficiency is generally low, the water utilization rate is only 45%, and the country with high water resource utilization rate reaches 70% -80%, so that the problem of agricultural irrigation water is solved, and the method is very important for relieving the shortage of water resources. The urgent need of relieving the shortage of water resources is to solve the problem of agricultural irrigation water, the cultivated land area of China is a big agricultural country, a large amount of manpower and material resources are wasted in agriculture, and the urgent need of relieving the shortage of water resources and the waste of manpower and material resources is to solve the problem of agricultural irrigation water and reduce the use of manpower in intelligent irrigation operation.
With the rapid development of scientific technology, the internet of things is applied more and more in industry, and the internet of things has the capability of remote interference, so that the labor intensity of operators is greatly reduced, and the speed of related operations is increased. In the prior art, the internet of things technology is applied more and more in the fields of monitoring and the like, the technology is more and more mature, however, in the prior art, the application of the internet of things technology in agriculture is less, the labor intensity of operators is reduced by adopting the mechanical technology in the field of agriculture, but the mechanical technology is applied more in early-stage sowing and later-stage harvesting, and the management and the application of the mechanical technology to crops in the middle stage are less. For example, in the irrigation technology in crop middle-term management, in the prior art, irrigation is controlled in a manual control mode, and the control mode is not low in mastering of the irrigation time and is not beneficial to the growth of crops.
Disclosure of Invention
The invention provides an Internet of things-based farmland intelligent irrigation system which comprises a crop growth characteristic database, a data acquisition mechanism, an alarm unit, a cloud end, a background service unit, a mobile terminal, a monitoring interface, an irrigation main control unit and an irrigation execution mechanism.
The technical scheme of the invention is as follows:
an intelligent farmland irrigation system based on the Internet of things comprises:
a crop growth characteristic database storing growth characteristic data of crops;
the data acquisition mechanism is used for detecting the environment data of the farmland;
the alarm unit is electrically connected with the data acquisition mechanism;
the cloud end is in wireless communication connection with the database and the data acquisition mechanism, can acquire detection data of the data acquisition mechanism, and transfers crop growth characteristic data according to the current farmland crop variety to form cloud end data;
the background service unit is connected with the cloud end and used for storing and analyzing cloud end data and generating an irrigation operation instruction based on a multi-sensor information fusion algorithm;
the mobile terminal is in wireless communication connection with the background service unit and can acquire an irrigation operation instruction;
the monitoring interface is connected with the output end of the background service unit and is used for displaying an irrigation operation instruction;
the irrigation main control unit is in wireless communication connection with the background service unit and the mobile terminal respectively;
and the irrigation executing mechanism is electrically connected with the irrigation main control unit.
Preferably, the wireless communication connection comprises any one or more of GPRS, WIFI, 4G and 5G communication.
Preferably, the data acquisition mechanism comprises a temperature detection unit, a humidity detection unit and an illumination detection unit;
the temperature detection unit is a plurality of temperature sensors arranged in an array;
the humidity detection unit is a plurality of humidity sensors arranged in an array;
the illumination detection unit is a plurality of illumination sensors arranged in an array.
Preferably, the irrigation actuator comprises:
a main motor;
a secondary motor;
the main pump is in transmission connection with the main motor;
the auxiliary pump is in transmission connection with the auxiliary motor;
the water outlet pipeline is communicated with the water outlet ends of the main pump and the auxiliary pump;
a plurality of irrigation devices connected in parallel to each other on the water outlet pipeline;
the irrigation well and the reservoir are communicated through a water inlet pipeline at the water inlet ends of the main pump and the auxiliary pump, an auxiliary pressure release valve is arranged at the position where the water outlet pipeline is communicated with the irrigation device, and a main pressure release valve is arranged at the water outlet end of the water outlet pipeline, which is close to the main pump and the auxiliary pump.
Preferably, the irrigation device comprises:
a base;
the supporting frame is rotatably supported on the base;
the spray head is detachably connected with one end of the support frame, can rotate 360 degrees along with the support frame and is communicated with the water outlet pipeline;
the controller, it and support frame and auxiliary relief valve electric connection can adjust the rotation rate of support frame and the spray pressure of shower head according to irrigation operation instruction.
Preferably, the system further comprises a pressure sensor arranged on a water outlet pipeline of the main pressure relief valve, which is far away from the water outlet ends of the main pump and the auxiliary pump.
Preferably, the irrigation water circulation system further comprises:
a drainage channel for collecting excess irrigation water;
the sedimentation tank is communicated with the drainage channel;
the circulating motor is connected with the irrigation main control unit;
the water inlet end of the circulating pump is communicated with the sedimentation tank through a water inlet pipe, and the water outlet end of the circulating pump is communicated with the water storage tank through a water outlet pipe and is in transmission connection with a circulating motor;
wherein, the water inlet end of the circulating pump is provided with a filter, and the sedimentation tank is provided with a water level sensor.
Preferably, the multi-sensor information fusion algorithm includes:
respectively carrying out threshold segmentation on the temperature detection data, the humidity detection data and the illumination detection data, deleting interference data, and then carrying out normalization processing;
respectively calculating the variance and the total mean square error of temperature detection data, humidity detection data and illumination detection data to obtain a function equation of the total mean square error relative to the weight of the sensor, and analyzing the function equation to obtain a temperature state model, a humidity state model and an illumination state model so as to obtain a state value of the detection data;
establishing a prediction model based on a BP neural network algorithm, wherein the input layer of the prediction model is a state value and a target humidity, and the output layer of the prediction model is irrigation density and irrigation time;
and acquiring the state value of the measured data in real time, calling the target humidity required by the current crop growth, inputting the target humidity into a prediction model to obtain the irrigation density and the irrigation time, and generating an irrigation operation instruction.
An intelligent farmland irrigation method based on the Internet of things comprises the following steps:
the data acquisition mechanism acquires detection data of the sensors and uploads the detection data to the cloud end through wireless communication;
the cloud retrieves the growth characteristic data of the current crops from the crop growth characteristic database according to the current crop varieties to obtain the target humidity;
the background service unit performs homogeneous fusion on the detection data to obtain a state value, inputs the state value and the target humidity into a prediction model to obtain irrigation density and irrigation time, generates an irrigation instruction and issues the irrigation instruction to a monitoring interface and the mobile terminal;
the irrigation main control unit obtains an irrigation instruction and calculates the rotation speed and the spraying pressure of the support frame of the irrigation device according to the irrigation instruction;
the mobile terminal confirms to execute the irrigation instruction;
the irrigation executing mechanism controls the irrigation device to execute farmland irrigation according to the rotating speed and the spraying pressure.
Preferably, the method further comprises sending alarm information to the mobile terminal when the detection data exceeds a threshold value.
The invention has the beneficial effects that:
1. according to the invention, the target humidity is obtained by acquiring the farmland environment data and calling the crop growth characteristic data, the irrigation operation instruction is obtained by analyzing and fusing the data, and the irrigation execution mechanism is controlled to carry out spray irrigation, so that the humidity environment suitable for crop growth is met, the working intensity of operators is reduced, and the water resource is saved.
2. According to the intelligent farmland irrigation system based on the Internet of things, the rotation angle and the spraying pressure of the irrigation device are controlled according to the irrigation operation instruction, so that the irrigation is uniform and efficient, scientific irrigation is facilitated, and the performance of the intelligent farmland irrigation system based on the Internet of things is optimized.
Drawings
Fig. 1 is a frame diagram of an intelligent farmland irrigation system based on the internet of things.
Fig. 2 is a flow chart of an intelligent farmland irrigation method based on the internet of things.
Detailed Description
The present invention is described in terms of particular embodiments, other advantages and features of the invention will become apparent to those skilled in the art from the following disclosure, and it is to be understood that the described embodiments are merely exemplary of the invention and that it is not intended to limit the invention to the particular embodiments disclosed. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terms "in" and the like refer to directions or positional relationships based on those shown in the drawings, which are for convenience of description only, and do not indicate or imply that a device or element must have a particular orientation, be constructed and operated in a particular orientation, and thus should not be construed as limiting the present invention. Furthermore, the terms "first" and "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
Furthermore, it should be noted that, in the description of the present invention, unless otherwise explicitly specified or limited, the terms "disposed," "mounted," "connected," and "connected" are to be construed broadly and may be, for example, fixedly connected, detachably connected, or integrally connected; may be a mechanical connection; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
As shown in fig. 1, an intelligent farmland irrigation system based on the internet of things includes a data acquisition mechanism 100, crop growth characteristic data 200, a cloud 300, a background service unit 400, a monitoring interface 500, a mobile terminal 600, an irrigation main control unit 700, an irrigation execution mechanism 800 and an alarm unit 900.
The crop growth characteristic database 200 stores growth characteristic data of crops, the data acquisition mechanism 100 is used for detecting environment data of a farmland, the alarm unit 900 is electrically connected with the data acquisition mechanism 100, the cloud 300 is in wireless communication connection with the database 200 and the data acquisition mechanism 100 and can acquire detection data of the data acquisition mechanism and call the crop growth characteristic data according to current farmland crop varieties to form cloud data, the background service unit 400 is connected with the cloud 300 and is used for storing and analyzing the cloud data and generating irrigation operation instructions based on a multi-sensor information fusion algorithm, the mobile terminal 600 is in wireless communication connection with the background service unit 400 and can acquire the irrigation operation instructions, the monitoring interface 500 is connected with the output end of the background service unit 400 and is used for displaying the irrigation operation instructions, and the irrigation main control unit 700 is in wireless communication connection with the background service unit 400 and the mobile terminal 600 respectively, the irrigation actuator 800 is electrically connected to the irrigation main control unit 700.
Preferably, the illumination sensor is installed in the air 3-8m away from the farmland, and the temperature sensor and the humidity sensor are installed in the air 1-20cm below the ground or in the air 1-2m away from the farmland.
The multi-sensor information fusion algorithm comprises the following steps:
and respectively carrying out threshold segmentation on the temperature detection data, the humidity detection data and the illumination detection data, deleting the interference data, and then carrying out normalization processing to eliminate the influence of dimension and magnitude between variables.
Wherein the content of the first and second substances,
denotes the normalized value, xiRepresenting the detected value, xminRepresenting the minimum detection value, xmaxRepresenting the maximum detection value.
Respectively calculating the variance and the total mean square error of temperature detection data, humidity detection data and illumination detection data to obtain a function equation of the total mean square error relative to the weight of the sensor, and analyzing the function equation to obtain a temperature state model, a humidity state model and an illumination state model so as to obtain a state value of the detection data;
wherein the state estimation value satisfies
And the weight satisfies
The total mean square error is then:
since the detection values are independent of each other and are unbiased estimates of a, an unbiased estimate of a is obtained
E＝[(a-ai)(a-aj)]＝0,(i,j＝1,2…n,i≠j)；
The total mean square error can be obtained:
according to the theory of extreme value of multivariate function, the current value can be obtained
And then, establishing a state model according to the corresponding minimum mean square error:
wherein the content of the first and second substances,
representing a sensor state value, aiRepresenting sensor measurements, piRepresenting sensor weight, i representing sensor, S2Representing the total mean square error, n representing the number of sensors,
having the advantage of viewing state estimation, delta2The variance is indicated.
Establishing a prediction model based on a BP neural network algorithm, wherein the input layer of the prediction model is a state value and a target humidity, and the output layer of the prediction model is irrigation density and irrigation time;
and acquiring the state value of the measured data in real time, calling the target humidity required by the current crop growth, inputting the target humidity into a prediction model to obtain the irrigation density and the irrigation time, and generating an irrigation operation instruction.
In order to accurately acquire farmland environment detection data, a plurality of sensors are arranged to monitor various environmental factors in real time, a temperature sensor, a humidity sensor and an illumination sensor are arranged on each node to acquire detection values of the sensors, the acquired similar sensor data are firstly grouped, then local self-adaptive weighted fusion is carried out on each group of data, and then the data of the similar sensors are fused by a self-adaptive weighted fusion algorithm to obtain an optimal fusion result. The self-adaptive fusion process is to calculate the variance of the initial measurement value of each sensor, calculate the total mean square error, and multiply the obtained optimal weight by the initial value to obtain the optimal fusion result.
The heterogeneous sensor adopts a BP neural network algorithm to analyze data, has high speed and high precision, and is beneficial to realizing the accurate regulation and control of an irrigation system.
Preferably, the alarm unit 900 includes a buzzer and an LED warning light set. Real-time acousto-optic combination alarm is carried out through the buzzer and the LED alarm lamp set, and a good alarm effect is achieved.
Specifically, the wireless communication connection includes any one or more of GPRS, WIFI, 4G, and 5G communications. By adopting the wireless communication modes for transmission and feedback, the wireless communication system has the characteristic of diversification and is convenient to use.
Specifically, the data acquisition mechanism 100 comprises a temperature detection unit 110, a humidity detection unit 120 and an illumination detection unit 130, wherein the temperature detection unit 110 is a plurality of temperature sensors 111-11 n arranged in an array, the humidity detection unit 120 is a plurality of humidity sensors 121-12 m arranged in an array, and the illumination detection unit 130 is a plurality of illumination sensors 131-13 k arranged in an array.
Specifically, the irrigation actuator 800 includes a primary motor 810, a secondary motor 820, a primary pump 811, a secondary pump 812, a water outlet conduit, a plurality of irrigation devices 830, an irrigation well 830, and a water reservoir 840.
The main pump 811 is in transmission connection with the main motor 810, the auxiliary pump 821 is in transmission connection with the auxiliary motor 820, the water outlet pipeline is communicated with the water outlet ends of the main pump 811 and the auxiliary pump 821, and the plurality of irrigation devices 830 are connected in parallel with one another on the water outlet pipeline.
The water inlet ends of the main pump 811 and the auxiliary pump 821 are communicated with the irrigation well 830 and the reservoir 840 through a water inlet pipeline, an auxiliary pressure relief valve 822 is arranged at the position where the water outlet pipeline is communicated with the irrigation device, and a main pressure relief valve 812 is arranged at the water outlet end of the water outlet pipeline close to the main pump and the auxiliary pump.
Specifically, irrigation device 830 includes a base, a support bracket 831, a showerhead 832, and a controller 833. Support frame 831 rotatable support is on the base, and shower head 832 can dismantle connection support frame 831 one end to can be along with the 360 rotations of support frame, and with outlet pipe UNICOM, controller 833 and support frame 831 and supplementary relief valve 822 electric connection can adjust the rotation rate of support frame 831 and the pressure that sprays of shower head 832 according to irrigation operation instruction.
Further, the irrigation executing mechanism 800 further includes a pressure sensor disposed on the water outlet pipeline of the main pressure relief valve, which is far away from the water outlet ends of the main pump and the auxiliary pump. The pressure sensor can monitor the pressure of the water outlet pipeline at any time, so that the main control unit can give an alarm and open the main pressure release valve when the pressure of the water outlet pipeline exceeds the set pressure, and the water outlet pipeline is safely monitored and protected.
Further, the irrigation actuator 800 further comprises an irrigation water circulation system, and the irrigation water circulation system comprises a circulation motor 851, a circulation pump 852, a sedimentation tank 854 and a drainage channel 855. The drain 855 is used for collecting unnecessary irrigation water, and the sedimentation tank 845 and the drain UNICOM, the irrigation main control unit is connected to circulating motor 851, and circulating pump 852 is gone into the water end and is linked together via inlet tube and sedimentation tank 854, and the play water end is linked together via outlet pipe and cistern 850, and is connected with the circulating motor transmission, still including setting up the end filter 853 that entries at circulating pump 852 and setting up at sedimentation tank 854 level sensor 854 a.
Irrigation water is collected to the sedimentation tank through blowdown canal, through the sediment after, filters, recycles water pump to cistern to realize recycling, thereby saves the water resource.
As shown in fig. 2, an intelligent farmland irrigation method based on the internet of things comprises the following steps:
s110, acquiring detection data of a plurality of sensors by a data acquisition mechanism, and uploading the detection data to a cloud end through wireless communication;
s120, the cloud retrieves the growth characteristic data of the current crop from the crop growth characteristic database according to the current crop variety to obtain the target humidity;
s130, the background service unit performs homogeneous fusion on the detection data to obtain a state value, inputs the state value and the target humidity into a prediction model to obtain irrigation density and irrigation time, generates an irrigation instruction and issues the irrigation instruction to a monitoring interface and the mobile terminal;
s140, the irrigation main control unit obtains an irrigation instruction and calculates the rotation speed and the spraying pressure of the support frame of the irrigation device according to the irrigation instruction;
s150, the mobile terminal confirms to execute the irrigation instruction;
and S160, controlling the irrigation device to irrigate the farmland by the irrigation executing mechanism according to the rotating speed and the spraying pressure.
Further, the method further comprises the step of sending alarm information to the mobile terminal when the detection data exceed the threshold value.
The above descriptions are only examples of the present invention, and common general knowledge of known specific structures, characteristics, and the like in the schemes is not described herein too much, and it is easily understood by those skilled in the art that the scope of the present invention is obviously not limited to these specific embodiments. Without departing from the invention, several changes and modifications can be made, which should also be regarded as the protection scope of the invention, and these will not affect the effect of the invention and the practicality of the patent.
Claims (10)
1. The utility model provides a farmland intelligence irrigation system based on thing networking which characterized in that includes:
a crop growth characteristic database storing growth characteristic data of crops;
the data acquisition mechanism is used for detecting the environment data of the farmland;
the alarm unit is electrically connected with the data acquisition mechanism;
the cloud end is in wireless communication connection with the database and the data acquisition mechanism, can acquire detection data of the data acquisition mechanism, and calls crop growth characteristic data according to the current farmland crop variety to form cloud end data;
the background service unit is connected with the cloud end and used for storing and analyzing the cloud end data and generating an irrigation operation instruction based on a multi-sensor information fusion algorithm;
the mobile terminal is in wireless communication connection with the background service unit and can acquire the irrigation operation instruction;
the monitoring interface is connected with the output end of the background service unit and is used for displaying the irrigation operation instruction;
the irrigation main control unit is in wireless communication connection with the background service unit and the mobile terminal respectively;
and the irrigation executing mechanism is electrically connected with the irrigation main control unit.
2. An intelligent farmland irrigation system based on the internet of things as claimed in claim 1, wherein the wireless communication connection comprises any one or more of GPRS, WIFI, 4G and 5G communication.
3. The Internet of things-based farmland intelligent irrigation system as claimed in claim 2, wherein the data acquisition mechanism comprises a temperature detection unit, a humidity detection unit and an illumination detection unit;
the temperature detection unit is a plurality of temperature sensors arranged in an array;
the humidity detection unit is a plurality of humidity sensors arranged in an array;
the illumination detection unit is a plurality of illumination sensors arranged in an array.
4. The Internet of things-based farmland intelligent irrigation system as claimed in claim 3, wherein the irrigation actuator comprises:
a main motor;
a secondary motor;
the main pump is in transmission connection with the main motor;
the auxiliary pump is in transmission connection with the auxiliary motor;
the water outlet pipeline is communicated with the water outlet ends of the main pump and the auxiliary pump;
a plurality of irrigation devices connected in parallel to each other on the water outlet pipeline;
the irrigation device comprises a main pump, an auxiliary pump, an irrigation well, a reservoir, an outlet pipeline, an auxiliary pressure relief valve, a water outlet pipeline and a main pressure relief valve, wherein the water inlet ends of the main pump and the auxiliary pump are communicated with the irrigation well and the reservoir through the water inlet pipeline, the auxiliary pressure relief valve is arranged at the position where the outlet pipeline is communicated with the irrigation device, and the main pressure relief valve is arranged at the water outlet end of the outlet pipeline, which is close to the main pump and the auxiliary pump.
5. The Internet of things-based farmland intelligent irrigation system according to claim 4, wherein the irrigation device comprises:
a base;
a support frame rotatably supported on the base;
the spray head is detachably connected with one end of the support frame, can rotate 360 degrees along with the support frame and is communicated with the water outlet pipeline;
and the controller is electrically connected with the support frame and the auxiliary pressure release valve, and can adjust the rotation speed of the support frame and the spraying pressure of the spraying head according to the irrigation operation instruction.
6. The Internet of things-based farmland intelligent irrigation system according to claim 5, wherein: the auxiliary pump is arranged on the main pressure release valve, and the pressure sensor is arranged on a water outlet pipeline of the main pressure release valve, which is far away from the water outlet ends of the main pump and the auxiliary pump.
7. An intelligent farmland irrigation system based on the internet of things as claimed in claim 6, wherein: still include irrigation water circulation system, irrigation water circulation system includes:
a drainage channel for collecting excess irrigation water;
a settling tank in communication with the drainage channel;
the circulating motor is connected with the irrigation main control unit;
the water inlet end of the circulating pump is communicated with the sedimentation tank through a water inlet pipe, and the water outlet end of the circulating pump is communicated with the water storage tank through a water outlet pipe and is in transmission connection with the circulating motor;
wherein, the water inlet end of the circulating pump is provided with a filter, and the sedimentation tank is provided with a water level sensor.
8. The internet of things-based farmland intelligent irrigation system as claimed in claim 7, wherein said multi-sensor information fusion algorithm comprises:
respectively carrying out threshold segmentation on the temperature detection data, the humidity detection data and the illumination detection data, deleting interference data, and then carrying out normalization processing;
respectively calculating the variance and the total mean square error of the temperature detection data, the humidity detection data and the illumination detection data to obtain a function equation of the total mean square error relative to the weight of the sensor, and analyzing the function equation to obtain a temperature state model, a humidity state model and an illumination state model so as to obtain a state value of the detection data;
establishing a prediction model based on a BP neural network algorithm, wherein the input layer of the prediction model is the state value and the target humidity, and the output layer of the prediction model is irrigation density and irrigation time;
and acquiring the state value of the measurement data in real time, calling the target humidity required by the current crop growth, inputting the target humidity into the prediction model to obtain the irrigation density and the irrigation time, and generating an irrigation operation instruction.
9. An intelligent farmland irrigation method based on the Internet of things, which uses the intelligent farmland irrigation system based on the Internet of things of claims 1-8, and is characterized by comprising the following steps:
the data acquisition mechanism acquires detection data of the sensors and uploads the detection data to the cloud end through wireless communication;
the cloud retrieves the growth characteristic data of the current crop from a crop growth characteristic database according to the current crop variety to obtain a target humidity;
the background service unit performs homogeneous fusion on the detection data to obtain a state value, inputs the state value and the target humidity into a prediction model to obtain irrigation density and irrigation time, generates an irrigation instruction and issues the irrigation instruction to a monitoring interface and a mobile terminal;
the irrigation main control unit obtains an irrigation instruction and calculates the rotation speed and the spraying pressure of the support frame of the irrigation device according to the irrigation instruction;
the mobile terminal confirms to execute the irrigation instruction;
and the irrigation executing mechanism controls the irrigation device to execute farmland irrigation according to the rotating speed and the spraying pressure.
10. The intelligent farmland irrigation method based on the internet of things as claimed in claim 9, further comprising sending alarm information to a mobile terminal when the detection data exceeds a threshold value.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114692777A (en) * | 2022-04-13 | 2022-07-01 | 山东浪潮科学研究院有限公司 | Intelligent agricultural management method based on multi-sensor and micro machine learning |
| CN115486358A (en) * | 2022-09-02 | 2022-12-20 | 水利部牧区水利科学研究所 | Perennial forage grass drip irrigation automatic irrigation management decision control system |
| CN117059214A (en) * | 2023-07-21 | 2023-11-14 | 南京智慧云网络科技有限公司 | Clinical scientific research data integration and intelligent analysis system and method based on artificial intelligence |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106707767A (en) * | 2017-03-13 | 2017-05-24 | 山东农业大学 | System and method for integrally and intelligently controlling water and fertilizer in field based on multi-source information fusion |
| CN206423299U (en) * | 2017-01-24 | 2017-08-22 | 四川农业大学 | A kind of Water saving type watering arrangement |
| CN208940588U (en) * | 2018-10-23 | 2019-06-07 | 河北农耘种业科技有限公司 | A kind of farmland intelligent circulation irrigation equipment |
| CN110036881A (en) * | 2019-03-29 | 2019-07-23 | 河北建涛科技有限公司 | A kind of wisdom agricultural irrigation systems and its control method |
| CN211379094U (en) * | 2019-12-04 | 2020-09-01 | 鄂尔多斯市吉万农牧民科技信息服务有限责任公司 | Remote control's circular sprinkling irrigation district sprinkling irrigation machine |
| CN112650337A (en) * | 2020-12-25 | 2021-04-13 | 北京萨尔科技有限公司 | Device and method for automatically adjusting crop environment |
| CN113435105A (en) * | 2021-05-25 | 2021-09-24 | 杭州申弘智能科技有限公司 | Fire early warning system and method based on smoke detection |
-
2021
- 2021-10-29 CN CN202111273630.2A patent/CN113841593A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN206423299U (en) * | 2017-01-24 | 2017-08-22 | 四川农业大学 | A kind of Water saving type watering arrangement |
| CN106707767A (en) * | 2017-03-13 | 2017-05-24 | 山东农业大学 | System and method for integrally and intelligently controlling water and fertilizer in field based on multi-source information fusion |
| CN208940588U (en) * | 2018-10-23 | 2019-06-07 | 河北农耘种业科技有限公司 | A kind of farmland intelligent circulation irrigation equipment |
| CN110036881A (en) * | 2019-03-29 | 2019-07-23 | 河北建涛科技有限公司 | A kind of wisdom agricultural irrigation systems and its control method |
| CN211379094U (en) * | 2019-12-04 | 2020-09-01 | 鄂尔多斯市吉万农牧民科技信息服务有限责任公司 | Remote control's circular sprinkling irrigation district sprinkling irrigation machine |
| CN112650337A (en) * | 2020-12-25 | 2021-04-13 | 北京萨尔科技有限公司 | Device and method for automatically adjusting crop environment |
| CN113435105A (en) * | 2021-05-25 | 2021-09-24 | 杭州申弘智能科技有限公司 | Fire early warning system and method based on smoke detection |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114692777A (en) * | 2022-04-13 | 2022-07-01 | 山东浪潮科学研究院有限公司 | Intelligent agricultural management method based on multi-sensor and micro machine learning |
| CN115486358A (en) * | 2022-09-02 | 2022-12-20 | 水利部牧区水利科学研究所 | Perennial forage grass drip irrigation automatic irrigation management decision control system |
| CN117059214A (en) * | 2023-07-21 | 2023-11-14 | 南京智慧云网络科技有限公司 | Clinical scientific research data integration and intelligent analysis system and method based on artificial intelligence |
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