CN117016151A - Intelligent agricultural water and fertilizer integrated irrigation system - Google Patents

Intelligent agricultural water and fertilizer integrated irrigation system Download PDF

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CN117016151A
CN117016151A CN202311156316.5A CN202311156316A CN117016151A CN 117016151 A CN117016151 A CN 117016151A CN 202311156316 A CN202311156316 A CN 202311156316A CN 117016151 A CN117016151 A CN 117016151A
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李俊子
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Anhui Wanxinda Network Technology Co ltd
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    • A—HUMAN NECESSITIES
    • A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01C—PLANTING; SOWING; FERTILISING
    • A01C23/00—Distributing devices specially adapted for liquid manure or other fertilising liquid, including ammonia, e.g. transport tanks or sprinkling wagons
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Abstract

The invention relates to the technical field of intelligent agriculture, and discloses an intelligent agriculture water and fertilizer integrated irrigation system, which comprises a data acquisition and processing module, an artificial intelligence and big data analysis module, a remote sensing technology module, a self-adaptive control system module, a water resource management module, a remote monitoring and automatic alarm module and a water saving technology module; s1, data acquisition and processing; s2, data analysis and model learning; s3, remote sensing data acquisition; s4, self-adaptive control; s5, water resource management; s6, water resource management. The system ensures that the farmland is supplied with a proper amount of water and nutrients through real-time data acquisition, analysis and automatic control, improves the utilization efficiency of resources to the greatest extent, reduces the resource waste, thereby realizing sustainable high-yield agricultural production.

Description

Intelligent agricultural water and fertilizer integrated irrigation system
Technical Field
The invention relates to the technical field of intelligent agriculture, in particular to an intelligent agriculture water and fertilizer integrated irrigation system.
Background
Currently, the traditional agricultural irrigation and fertilization method has a series of problems including resource waste, inaccurate water and fertilizer supply, environmental pollution, low production efficiency and the like, and modern agriculture increasingly depends on intelligent agriculture technology to realize accurate management and sustainable agriculture practice;
over the past few years, a series of innovations have emerged in the agricultural field that have been related to sensor technology, data analysis, machine learning, and remote sensing technology. The development of these technologies provides more opportunities for intelligent agricultural systems to better meet the moisture and nutrient requirements of plants while reducing resource waste and environmental risks;
although there have been some technologies related to intelligent agricultural irrigation and fertigation systems, there is still a need for further innovation and integration to address the limitations and disadvantages of existing systems:
the traditional agricultural irrigation and fertilization method generally cannot accurately measure and meet the water and nutrient requirements of plants, so that water resources and fertilizers are excessively used, the production cost is increased, and precious resources are wasted;
traditional agricultural management is often based on experience and static planning and cannot adapt to changing weather and soil conditions. This results in inaccurate irrigation and fertilization decisions, possibly resulting in poor crop growth and reduced yield;
in the traditional agricultural method, excessive use of chemical fertilizers and water resources can have negative effects on soil and water, resulting in degradation of soil quality and water pollution, and such environmental effects are not sustainable;
conventional agricultural methods typically require a significant amount of manual labor and time to monitor and manage the farmland, which results in inefficiency in production, especially for large-scale farms;
traditional agricultural management methods have difficulty accommodating meteorological changes, diversity of soil conditions, and changes in plant growth stages, which can lead to wastage and low yield.
Disclosure of Invention
The invention aims to provide an intelligent agricultural water and fertilizer integrated irrigation system, which improves the efficient utilization of farmland resources, reduces the resource waste to the greatest extent, improves the sustainability and the production efficiency of agricultural production and solves the problems in the background technology through real-time data monitoring and intelligent control.
In order to achieve the above purpose, the present invention provides the following technical solutions: the intelligent agricultural water and fertilizer integrated irrigation system comprises a data acquisition and processing module, an artificial intelligence and big data analysis module, a remote sensing technology module, a self-adaptive control system module, a water resource management module, a remote monitoring and automatic alarm module and a water saving technology module;
the data acquisition and processing module comprises a plurality of groups of soil humidity sensors, temperature sensors, weather stations and plant health sensors, and the data acquisition unit receives the data of each sensor for real-time processing;
the artificial intelligence and big data analysis module stores soil characteristics, plant growth records and meteorological data, trains a deep learning model based on a machine learning algorithm, analyzes historical data and generates a decision model, and the decision model is combined with sensor data to generate an irrigation and fertilization plan;
the remote sensing technology module comprises satellite remote sensing and unmanned aerial vehicle technology, wherein the satellite remote sensing monitors vegetation health and soil humidity of a farmland, and the unmanned aerial vehicle is provided with a multispectral sensor;
the self-adaptive control system module comprises a controller, wherein the controller automatically adjusts the water flow rate of the water source supply system and the fertilizing amount of the fertilizer supply system according to a decision model, and the controller integrates a sensor feedback loop;
the water resource management module comprises a plurality of groups of water quality sensors for monitoring water quality, and the water resource management module formulates a water resource supply strategy based on water quality monitoring data and farmland requirements;
the remote monitoring and automatic alarming module allows a user to remotely monitor system state and real-time data and set an automatic alarming mechanism;
the water-saving technology module comprises a plurality of groups of drip irrigation pipes and micro-spraying equipment.
As a preferred embodiment of the invention, the data acquisition and processing module collects soil humidity, temperature and meteorological data information through sensors, and the data is transmitted to a data acquisition unit for processing.
As a preferred embodiment of the present invention, the artificial intelligence and big data analysis module uses deep learning and data mining techniques to analyze the sensor data and the historical data and generate decision models, including optimization strategies for irrigation and fertilization.
As a preferred implementation mode of the invention, the remote sensing technology module acquires farmland data of vegetation health, soil quality and moisture content by utilizing satellite remote sensing and unmanned aerial vehicle technology.
As a preferred embodiment of the present invention, the adaptive control system module dynamically adjusts irrigation and fertilization parameters based on sensor data, model prediction and remote sensing data using an adaptive control algorithm.
As a preferred embodiment of the invention, the water resource management module monitors the water quality and availability of the water source in real time and establishes a water resource supply strategy according to the system requirements.
As a preferred embodiment of the present invention, the remote monitoring and automatic alarm module provides a user interface allowing a user to remotely monitor the status of the system and set an automatic alarm function to notify the user when the system is abnormal.
As a preferred embodiment of the present invention, the water conservation technology module integrates drip irrigation and micro-spray irrigation technologies, which are used to deliver water directly to plant roots.
Intelligent agriculture liquid manure integrative integrated irrigation system includes following steps:
s1, data acquisition and processing are carried out, farmland environment parameters are monitored in real time through a sensor network, and data are transmitted to a data acquisition unit;
s2, data analysis and model learning, and then combining sensor data with historical data through a data acquisition unit to perform deep learning and data mining analysis to generate a decision model;
s3, acquiring remote sensing data, and simultaneously periodically acquiring farmland data including vegetation health, soil quality and the like by using satellite remote sensing and unmanned aerial vehicle technology;
s4, self-adaptive control is performed, and then a control system uses a self-adaptive control algorithm to adjust irrigation and fertilization parameters according to sensor data, model prediction and remote sensing data, wherein an efficient water-saving technology is used for irrigation, so that water resource waste is minimized;
s5, water resource management, namely monitoring the water quality and availability of a water source in real time, and making a water resource supply strategy;
s6, remote monitoring and automatic alarming, farmers can monitor the system state remotely through a user interface, and the system can automatically alarm to inform the user of system abnormality.
Compared with the prior art, the invention has the following beneficial effects:
1. the intelligent agricultural water and fertilizer integrated irrigation system can accurately calculate the water and nutrient requirements of plants through real-time data acquisition and analysis, so that accurate fertilization and irrigation are realized, the waste of water resources and fertilizers is reduced to the greatest extent, the efficient utilization of farmland resources is improved, the production cost is reduced, and sustainable agricultural practice is facilitated.
2. The intelligent agricultural water and fertilizer integrated irrigation system provided by the invention uses a machine learning and remote sensing technology to monitor soil, vegetation and meteorological conditions in real time, and can be quickly adapted to different meteorological conditions and soil conditions, so that farmers can better manage and optimize farmlands, yield and crop quality are maximized, and errors of manual operation and labor cost are reduced through automatic control.
3. According to the intelligent agricultural water and fertilizer integrated irrigation system, through accurate fertilization and irrigation, excessive use of chemical fertilizers and water resources is reduced, pollution risks of nutrients and chemical substances to soil and water are reduced, the intelligent agricultural water and fertilizer integrated irrigation system is beneficial to maintaining the health of the soil and the sustainability of the water resources, and the intelligent agricultural water and fertilizer integrated irrigation system accords with the principle of environmental protection.
Drawings
For a more clear description of the technical solutions of the embodiments of the present invention, reference will now be made to the following detailed description of non-limiting embodiments, with reference to the accompanying drawings, in which it is apparent that the drawings used in the following description are only some embodiments of the present invention, and from which other drawings can be obtained without inventive effort to a person skilled in the art.
FIG. 1 is a schematic diagram of a modular structure of an intelligent agricultural water and fertilizer integrated irrigation system;
FIG. 2 is a schematic diagram of the operation steps of the intelligent agricultural water and fertilizer integrated irrigation system.
Detailed Description
The invention will now be described in further detail with reference to the accompanying drawings. The drawings are simplified schematic representations which merely illustrate the basic structure of the invention and therefore show only the structures which are relevant to the invention.
Referring to fig. 1-2, an intelligent agricultural water and fertilizer integrated irrigation system includes:
a data acquisition and processing module;
the data acquisition and processing module comprises a plurality of groups of soil humidity sensors, temperature sensors, weather stations and plant health sensors, and the data acquisition unit receives soil humidity, temperature and air image data collected by the sensors and processes various data information in real time.
An artificial intelligence and big data analysis module;
the artificial intelligence and big data analysis module can store soil characteristics, plant growth records and meteorological data, train a deep learning model based on a machine learning algorithm, analyze historical data and generate a decision model, and the decision model is combined with sensor data to generate an irrigation and fertilization plan;
analyzing the sensor data and the historical data by using deep learning and data mining technologies, wherein the decision model comprises an optimization strategy of irrigation and fertilization;
among other things, the optimization strategy for irrigation includes:
sensing soil humidity: monitoring soil humidity in real time through a soil humidity sensor, determining the moisture condition of the soil, and automatically triggering irrigation by a system to ensure the moisture supply of plant roots if the soil humidity is lower than a specific threshold value;
and (3) weather data analysis: analyzing the weather data, including temperature, humidity, and precipitation, to predict future weather conditions, which can help decide whether an increase or decrease in irrigation is needed;
remote sensing monitoring: monitoring vegetation health and soil moisture condition by using a remote sensing technology, and adjusting an irrigation plan according to a monitoring result to ensure that plants obtain proper moisture supply;
the water-saving technology comprises the following steps: the drip irrigation or micro-spray irrigation system is used to accurately deliver water to the roots of plants, minimizing water waste.
And (3) self-adaptive control: and automatically adjusting irrigation water flow rate and irrigation period according to the real-time sensor data and the decision model by using an adaptive control system. The optimization algorithm of the controller can ensure that the irrigation effect is optimal under different meteorological conditions.
The fertilization optimization strategy comprises the following steps:
soil analysis: analyzing a soil sample, determining nutrient content and pH value in the soil, and making a fertilization plan to meet the nutrient requirements of plants based on an analysis result;
plant requirements: considering the growth stages and nutrient requirements of different crops, the fertilization plan should be adjusted according to the requirements of specific crops. For example, more nitrogen fertilizer is typically required during early anagen phase;
quantitative fertilization: applying a specific amount of fertilizer according to a plan using accurate fertilizer application equipment, which can avoid the problem of over-fertilization or under-fertilization;
topdressing strategies: and according to the growth condition of plants and the nutrient concentration of soil, adopting an additional fertilizer strategy to adjust a fertilizer application plan in time so as to adapt to the demands of the plants.
Environmental protection: and the environment-friendly fertilizer is selected, so that the pollution risk to soil and water is reduced. Meanwhile, the fertilization strategy is optimized to reduce the loss of nitrogen and phosphorus.
A remote sensing technology module;
the remote sensing technology module comprises satellite remote sensing and unmanned aerial vehicle technology, and multispectral sensors are arranged through the satellite remote sensing and the unmanned aerial vehicle, so that farmland data of vegetation health, soil quality and moisture content can be obtained.
An adaptive control system module;
the self-adaptive control system module comprises a controller, the self-adaptive control algorithm is used for dynamically adjusting irrigation and fertilization parameters based on sensor data, model prediction and remote sensing data, the water flow rate of the water source supply system and the fertilization amount of the fertilizer supply system are automatically adjusted according to the decision model, and the controller integrates a sensor feedback loop.
A water resource management module;
the water resource management module comprises a plurality of groups of water quality sensors for monitoring water quality in real time, and the water resource management module formulates a water resource supply strategy based on water quality monitoring data and farmland requirements;
a remote monitoring and automatic alarm module;
a user interface is provided that allows a user to remotely monitor system status and real-time data and to set an automatic alarm mechanism to notify the user when the system is abnormal.
A water-saving technical module;
the water-saving technology module comprises a plurality of groups of drip irrigation pipes and micro-spraying equipment which are used for water saving technology, and water is directly conveyed to plant roots by using drip irrigation and micro-spraying technology.
Intelligent agriculture liquid manure integrative integrated irrigation system includes following steps:
s1, data acquisition and processing are carried out, farmland environment parameters are monitored in real time through a sensor network, and data are transmitted to a data acquisition unit;
in this embodiment, S1 specifically includes:
the system comprises an acquisition sensor, a soil humidity sensor, a temperature sensor, a weather station and a plant health sensor, wherein the acquisition sensor is arranged in a farmland and is used for monitoring soil and environmental parameters;
data transmission, wherein sensor data is transmitted to a data acquisition unit through a wired or wireless network;
and (3) data processing: the data acquisition unit receives the sensor data and performs real-time processing including data filtering, calibration and format conversion to ensure data quality.
S2, data analysis and model learning, and then combining sensor data with historical data through a data acquisition unit to perform deep learning and data mining analysis to generate a decision model;
in this embodiment, S2 specifically includes:
data storage, namely establishing a database to store historical data, including soil characteristics, plant growth records and meteorological data;
model training, training a deep learning model using a machine learning algorithm to analyze historical data and generate a decision model;
and (3) real-time analysis, wherein real-time sensor data are combined with the decision model to generate an irrigation and fertilization plan.
S3, acquiring remote sensing data, and simultaneously periodically acquiring farmland data including vegetation health, soil quality and the like by using satellite remote sensing and unmanned aerial vehicle technology;
in this embodiment, S3 specifically includes:
satellite remote sensing, subscribing satellite data service, acquiring satellite images, and monitoring vegetation health and soil humidity of farmlands;
unmanned aerial vehicle technique uses many rotor unmanned aerial vehicle to be equipped with multispectral sensor, flies in the low altitude, acquires high-resolution farmland image, monitors soil quality and moisture content.
S4, self-adaptive control is performed, and then a control system uses a self-adaptive control algorithm to adjust irrigation and fertilization parameters according to sensor data, model prediction and remote sensing data, wherein an efficient water-saving technology is used for irrigation, so that water resource waste is minimized;
in this embodiment, S4 specifically includes:
a controller design, using a Programmable Logic Controller (PLC) or microcontroller, for automatically controlling the irrigation and fertigation system;
executing the decision, and automatically adjusting the water flow rate of the water source supply system and the fertilizing amount of the fertilizer supply system by the controller according to the decision model;
and a feedback loop, an integrated sensor feedback loop, ensures that the actual operation is consistent with the plan.
In this embodiment, the controller design specifically includes:
the irrigation water flow rate is controlled by using a PID (proportional-integral-derivative) controller, and the control signal is calculated by the following method:
control signal = Kp ×e+ki ×jedt+kd ×de/dt
Wherein:
kp, ki and Kd are the tuning parameters of the controller;
e is the error between the current measured value and the target value (set value-current value);
let e dt denote the integral of the error, the accumulation of historical error;
de/dt represents the derivative of the error, indicating the speed of the error change.
In addition, the water saving technology specifically comprises:
and the irrigation technology adopts drip irrigation and micro-spray irrigation technologies, and water is directly conveyed to the roots of plants, so that the waste of water resources is minimized.
S5, water resource management, namely monitoring the water quality and availability of a water source in real time, and making a water resource supply strategy;
in this embodiment, S5 specifically includes:
water quality monitoring, namely installing a water quality sensor to monitor the water quality of a water source, wherein the water quality comprises parameters such as pH value, dissolved oxygen and the like;
and (3) a water resource supply strategy, which is based on the water quality monitoring data and farmland requirements, and comprises water pump control and irrigation plan.
S6, remote monitoring and automatic alarming, farmers can monitor the system state remotely through a user interface, and the system can automatically alarm to inform the user of system abnormality.
In this embodiment, S6 specifically includes:
user interface development, web interface development and mobile applications, allowing users to monitor system status and real-time data remotely,
and the alarm system is provided with an automatic alarm mechanism, including a short message, an email or an application notification, so as to notify a user when the system is abnormal.
Those of ordinary skill in the art will appreciate that implementing all or part of the processes of the above embodiments may be accomplished by computer programs instructing the relevant hardware, wherein the hardware specifically includes soil moisture sensors, temperature sensors, humidity sensors, wind speed and wind direction sensors, weather stations, multispectral sensors, positioning systems (GPS), controllers, drip irrigation devices, fertilizer supply devices, drones, satellite communication devices, computing servers or cloud servers, smart phones or computer interfaces, power devices, and wherein the software includes data analysis tools, such as Python, R, MATLAB; a neural network (CNN) and Recurrent Neural Network (RNN) based machine learning framework; remote sensing image processing tools such as ENVI, ERDAS imaging; PLC programming software; SCADA (Supervisory Control and Data Acquisition) software; GIS tools; communication software; database systems, such as MySQL, postgreSQL; the software and the system are based on Windows operating system to realize server operation and control equipment.
The foregoing is only a preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art, who is within the scope of the present invention, should make equivalent substitutions or modifications according to the technical scheme of the present invention and the inventive concept thereof, and should be covered by the scope of the present invention.

Claims (9)

1. The intelligent agricultural water and fertilizer integrated irrigation system is characterized by comprising a data acquisition and processing module, an artificial intelligence and big data analysis module, a remote sensing technology module, a self-adaptive control system module, a water resource management module, a remote monitoring and automatic alarm module and a water saving technology module;
the data acquisition and processing module comprises a plurality of groups of soil humidity sensors, temperature sensors, weather stations and plant health sensors, and the data acquisition unit receives the data of each sensor for real-time processing;
the artificial intelligence and big data analysis module stores soil characteristics, plant growth records and meteorological data, trains a deep learning model based on a machine learning algorithm, analyzes historical data and generates a decision model, and the decision model is combined with sensor data to generate an irrigation and fertilization plan;
the remote sensing technology module comprises satellite remote sensing and unmanned aerial vehicle technology, wherein the satellite remote sensing monitors vegetation health and soil humidity of a farmland, and the unmanned aerial vehicle is provided with a multispectral sensor;
the self-adaptive control system module comprises a controller, wherein the controller automatically adjusts the water flow rate of the water source supply system and the fertilizing amount of the fertilizer supply system according to a decision model, and the controller integrates a sensor feedback loop;
the water resource management module comprises a plurality of groups of water quality sensors for monitoring water quality, and the water resource management module formulates a water resource supply strategy based on water quality monitoring data and farmland requirements;
the remote monitoring and automatic alarming module allows a user to remotely monitor system state and real-time data and set an automatic alarming mechanism;
the water-saving technology module comprises a plurality of groups of drip irrigation pipes and micro-spraying equipment.
2. The intelligent agricultural water and fertilizer integrated irrigation system as claimed in claim 1, wherein: the data acquisition and processing module collects soil humidity, temperature and meteorological data information through the sensor, and the data are transmitted to the data acquisition unit for processing.
3. The intelligent agricultural water and fertilizer integrated irrigation system as claimed in claim 1, wherein: the artificial intelligence and big data analysis module uses deep learning and data mining techniques to analyze the sensor data and the historical data and generate a decision model including optimization strategies for irrigation and fertilization.
4. The intelligent agricultural water and fertilizer integrated irrigation system as claimed in claim 1, wherein: the remote sensing technology module acquires farmland data of vegetation health, soil quality and moisture content by utilizing satellite remote sensing and unmanned aerial vehicle technology.
5. The intelligent agricultural water and fertilizer integrated irrigation system as claimed in claim 1, wherein: the adaptive control system module dynamically adjusts irrigation and fertilization parameters based on sensor data, model prediction and remote sensing data using an adaptive control algorithm.
6. The intelligent agricultural water and fertilizer integrated irrigation system as claimed in claim 1, wherein: the water resource management module monitors the water quality and availability of a water source in real time, and establishes a water resource supply strategy according to the system requirements.
7. The intelligent agricultural water and fertilizer integrated irrigation system as claimed in claim 1, wherein: the remote monitoring and automatic alarm module provides a user interface allowing a user to remotely monitor the system status and set an automatic alarm function to notify the user when the system is abnormal.
8. The intelligent agricultural water and fertilizer integrated irrigation system as claimed in claim 1, wherein: the water-saving technology module integrates drip irrigation and micro-spray irrigation water-saving technologies, and the drip irrigation and micro-spray irrigation technologies are used for directly conveying water to plant roots.
9. The intelligent agricultural water and fertilizer integrated irrigation system of claim 1, comprising the steps of:
s1, data acquisition and processing are carried out, farmland environment parameters are monitored in real time through a sensor network, and data are transmitted to a data acquisition unit;
s2, data analysis and model learning, and then combining sensor data with historical data through a data acquisition unit to perform deep learning and data mining analysis to generate a decision model;
s3, acquiring remote sensing data, and simultaneously periodically acquiring farmland data including vegetation health, soil quality and the like by using satellite remote sensing and unmanned aerial vehicle technology;
s4, self-adaptive control is performed, and then a control system uses a self-adaptive control algorithm to adjust irrigation and fertilization parameters according to sensor data, model prediction and remote sensing data, wherein an efficient water-saving technology is used for irrigation, so that water resource waste is minimized;
s5, water resource management, namely monitoring the water quality and availability of a water source in real time, and making a water resource supply strategy;
s6, remote monitoring and automatic alarming, farmers can monitor the system state remotely through a user interface, and the system can automatically alarm to inform the user of system abnormality.
CN202311156316.5A 2023-09-08 2023-09-08 Intelligent agricultural water and fertilizer integrated irrigation system Withdrawn CN117016151A (en)

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CN117236650A (en) * 2023-11-13 2023-12-15 山东工泵电机有限公司 Intelligent fluid dynamic adjustment method based on deep learning

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117236650A (en) * 2023-11-13 2023-12-15 山东工泵电机有限公司 Intelligent fluid dynamic adjustment method based on deep learning
CN117236650B (en) * 2023-11-13 2024-03-01 山东工泵电机有限公司 Water-fertilizer integrated intelligent pump house control method

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