CN118525738A - Intelligent water conservancy monitoring and irrigation system based on computer - Google Patents

Abstract

The invention provides an intelligent water conservancy monitoring and irrigation system based on a computer, which comprises a sensor module, an intelligent control module, a network acquisition module, a data transmission module, a cloud computing platform and a user interface, wherein the sensor module is used for acquiring data of the intelligent water conservancy monitoring and irrigation system; the data transmission module collects data information through the sensor module and the network acquisition module, and sends data to the intelligent control module for control, the cloud computing platform performs data interaction with the data transmission module, and the user interface performs data interaction with the cloud computing platform. The invention has the advantages that: the irrigation efficiency is improved: through precise irrigation and water-saving optimization, the irrigation cost is reduced, and the water resource utilization efficiency is improved; improving the quality and yield of crops: through a reasonable irrigation strategy, the crops are ensured to obtain sufficient water supply, and the quality and the yield of the crops are improved; the burden of farmers is reduced: through automatic and intelligent management, the labor intensity of farmers is reduced, and the agricultural production efficiency is improved; promoting sustainable development.

Description

A computer-based intelligent water conservancy monitoring and irrigation system

Technical Field

The present invention relates to the field of smart agricultural water conservancy, and in particular to a computer-based smart water conservancy monitoring and irrigation system.

Background Art

Traditional agricultural irrigation generally adopts the method of flooding the fields, which has extremely low water efficiency and is easy to soak crops. With the development of Internet of Things technology, agricultural irrigation facilities are also equipped with Internet of Things to realize intelligent water and fertilizer irrigation. During irrigation, it can automatically detect, adjust and supply water according to the water and fertilizer requirements of different crops, as well as the soil moisture content and environmental conditions. It is mainly composed of valve control system, soil moisture monitoring system, water pump control system, communication network and monitoring service center. The communication between the monitoring service center and each monitoring system is realized by the field controller equipment of each system through GPRS/4G network, and each subsystem completes the monitoring and management control through valve control, sensors and field controllers. The existing intelligent irrigation system has general irrigation precision and cannot realize personalized irrigation.

Current farm irrigation systems face challenges in achieving water conservation and water and fertilizer utilization. Traditional irrigation methods are usually not intelligent enough, and the irrigation efficiency is low, often resulting in a waste of water resources and fertilizers. Therefore, a smarter system is needed to improve the efficiency of farm irrigation and reduce resource waste. Traditional farm irrigation systems usually rely on predetermined schedules and experience, and fail to make dynamic adjustments based on actual needs. This leads to a waste of water resources, especially in arid areas, where water resources become more precious. In addition, excessive fertilizer use may also lead to environmental problems and waste of resources.

Water-saving irrigation projects are to achieve effective use of farmland irrigation water by adopting advanced and applicable water-saving technologies, equipment and processes. In order to achieve the goal of scientific and precise irrigation, it is necessary to vigorously develop water-saving industries and technologies, promote agricultural water conservation, implement water-saving actions throughout society, and promote the transformation of water use from extensive to economical and intensive.

Summary of the invention

The present invention proposes a computer-based intelligent water conservancy monitoring and irrigation system, which can realize comprehensive monitoring and intelligent control of water conservancy facilities and irrigation processes, and help to improve water resource utilization efficiency, reduce irrigation costs, and reduce water resource waste.

The technical solution of the present invention is implemented as follows: a computer-based intelligent water conservancy monitoring and irrigation system, the system includes a sensor module, an intelligent control module, a network acquisition module, a data transmission module, a cloud computing platform and a user interface;

The data transmission module collects data information through the sensor module and the network acquisition module, and sends data to the intelligent control module for control. The cloud computing platform interacts with the data transmission module, and the user interface interacts with the cloud computing platform.

The sensor module includes sensors deployed in the farmland, which are used to monitor and collect real-time data in the farmland in real time and upload it to the data transmission module;

The intelligent control module receives control instructions sent from the cloud computing platform through the data transmission module, executes irrigation tasks, and realizes automatic and intelligent control;

The network collection module collects recent weather forecast information through the Internet and uploads it to the cloud computing platform through the data transmission module;

The data transmission module is responsible for transmitting the data collected by the sensor module and the network acquisition module to the cloud computing platform to achieve real-time data transmission;

The cloud computing platform is responsible for data storage, processing and analysis. The platform uses big data analysis technology to mine and predict the collected data to provide a scientific basis for irrigation decision-making;

The user interface provides an operation interface for users to view data and perform operations.

Preferably, the sensor module includes sensors deployed in the farmland, including water level sensors, soil moisture sensors, meteorological sensors, and crop growth sensors, for real-time monitoring of soil moisture, temperature, wind speed, and crop growth status information.

Preferably, the intelligent control module includes intelligent valves, irrigation pumps, and sprinklers for performing irrigation tasks, and also includes multiple fertilizer storage tanks and metering valves connected to the irrigation pumps. These devices can receive control instructions from the cloud computing platform to achieve automated and intelligent control.

Preferably, the network collection module collects recent weather forecast information through the Internet, including sunshine duration, rainfall, evaporation, and temperature range data.

Preferably, the data transmission module is responsible for transmitting the data collected by the sensor to the cloud computing platform, and the data transmission module adopts wireless communication technology to realize real-time transmission of data.

Preferably, the user interface provides an operation interface for users, including a mobile phone APP and a web page, which facilitates users to view real-time data, set irrigation parameters, and receive early warning information.

Preferably, the cloud computing platform automatically adjusts the irrigation strategy according to the growth requirements of different crops, soil conditions and meteorological factors.

Preferably, the existing water volume is added with the predicted precipitation and subtracted with the predicted evaporation to obtain the predicted remaining water volume, which is then compared with the actual water demand of the crops in the area to replenish water or drain the farmland.

As a preferred method, the calculation formula of the actual crop water requirement (CWR) is:

CWR=SWHC*[1-(EP/PET)]*CorrectionFactor

CWR: actual crop water requirement, based on crop type, growth stage and climatic conditions;

SWHC: soil water holding capacity, which depends on soil type, texture and structural properties;

EP: Expected precipitation, which is the precipitation in the future period obtained according to the weather forecast;

PET: Potential Evaporation, which is the potential for water evaporation calculated based on meteorological conditions.

Compared with the prior art, the advantages of the present invention are:

1. Improve irrigation efficiency: reduce irrigation costs and improve water resource utilization efficiency through precision irrigation and water-saving optimization;

2. Improve crop quality and yield: Through reasonable irrigation strategies, ensure that crops receive sufficient water supply and improve crop quality and yield;

3. Reduce the burden on farmers: Through automation and intelligent management, reduce the labor intensity of farmers and improve agricultural production efficiency;

4. Promote sustainable development: Through water-saving irrigation and environmental management, reduce the negative impact on the environment and promote sustainable agricultural development.

BRIEF DESCRIPTION OF THE DRAWINGS

Fig. 1 is a schematic diagram of a module of the present invention;

FIG2 is a schematic diagram of a sensor module of the present invention;

FIG. 3 is a schematic diagram of the workflow of the present invention.

DETAILED DESCRIPTION

The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

Embodiment: See Figure 1, Figure 2 and Figure 3,

A computer-based intelligent water conservancy monitoring and irrigation system is a new water conservancy management model that integrates advanced information technology and control methods, aiming to achieve intelligent management and efficient use of water resources. The system integrates key technologies such as sensor technology, data transmission and storage technology, data analysis and mining technology, and decision support system technology to achieve comprehensive monitoring and intelligent control of water conservancy facilities and irrigation processes.

In terms of smart water conservancy monitoring, the system deploys sensors such as water level sensors, flow sensors, and water quality sensors to achieve real-time monitoring of key parameters such as water level, flow, and water quality of water conservancy facilities such as reservoirs, rivers, and channels. The data collected by the sensors is transmitted to the data center via wireless or wired means for storage and analysis. The system uses cloud computing and big data technologies to process, analyze, and mine the collected data in real time to provide decision support and early warning functions.

In terms of irrigation systems, the smart water monitoring and irrigation system can realize automatic control and intelligent scheduling of irrigation equipment based on real-time monitoring of soil moisture, meteorological conditions, and crop growth status information through intelligent algorithms and optimization models. The system can accurately calculate the irrigation water volume and irrigation time according to the water demand of crops and soil moisture conditions, and realize precise irrigation and water-saving irrigation. At the same time, the system can also realize real-time monitoring and fault warning of the operating status of irrigation equipment through remote monitoring and intelligent control, thereby improving the operating efficiency and reliability of the equipment.

In addition, the smart water conservancy monitoring and irrigation system can also be combined with geographic information system (GS) technology to achieve the spatial distribution and visualization of water conservancy facilities and irrigation areas, helping decision makers to better understand water resources and irrigation conditions and formulate more scientific and reasonable management strategies.

In general, the computer-based smart water conservancy monitoring and irrigation system integrates advanced information technology and control methods to achieve comprehensive monitoring and intelligent control of water conservancy facilities and irrigation processes, which helps to improve water resource utilization efficiency, reduce irrigation costs, reduce water resource waste, and promote the sustainable development of the water conservancy industry.

This application designs a new smart water irrigation system. We will make full use of cutting-edge technologies such as modern computer technology, Internet of Things technology, big data analysis, and artificial intelligence to achieve more efficient, smarter, and more environmentally friendly irrigation management. The following is a detailed design plan for the system:

System Overview

The new smart water conservancy irrigation system takes "intelligence, precision and water conservation" as its core design concept. By integrating multiple sensors, intelligent control equipment and cloud computing platforms, it can realize real-time monitoring and intelligent control of the entire irrigation process. The system can automatically adjust the irrigation strategy according to the growth needs of different crops, soil conditions and meteorological factors to achieve precise irrigation and water-saving irrigation.

System Architecture

The system is mainly composed of sensor module, network acquisition module, intelligent control module, data transmission module, cloud computing platform and user interface.

Sensor module: Sensors deployed in farmland, including soil moisture sensors, meteorological sensors, crop growth sensors, etc., are used to monitor soil moisture, temperature, wind speed, and crop growth status information in real time. Sensors also include soil temperature sensors, soil pH sensors, flow sensors, and crop growth sensors. Soil moisture sensors are mainly dryland soil moisture sensors, and paddy fields are paddy field water level sensors.

The network collection module collects recent weather forecast information through the Internet, including sunshine duration, rainfall, evaporation, and temperature range data.

The intelligent control module includes intelligent valves, irrigation pumps, and sprinklers for performing irrigation tasks. It also includes multiple fertilizer storage tanks and their connected metering valves, which are connected to the irrigation pumps. These devices can receive control instructions from the cloud computing platform to achieve automated and intelligent control.

According to the growth needs of plants, the cloud computing platform configures the fertilizer ratio, and each fertilizer storage tank provides fertilizer to the metering valve. The metering valve measures and evenly discharges and mixes according to the instructions, and finally discharges it to the irrigation pump, which flows to each farmland together with the irrigation water source to supplement nutrients.

Data transmission module: responsible for transmitting the data collected by the sensor to the cloud computing platform. Wireless communication technologies such as Wi-Fi, 4G/5G, etc. can be used to achieve real-time data transmission.

Cloud computing platform: As the core of the system, it is responsible for data storage, processing and analysis. The platform uses big data analysis technology to mine and predict the collected data to provide a scientific basis for irrigation decision-making.

User interface: Provide users with a friendly operation interface, including mobile APP and web page, so that users can view real-time data, set irrigation parameters, receive early warning information, etc.

The sensor module is used to obtain various data in the farmland, including soil temperature data, soil moisture and water level data, soil pH data, crop growth data, and water flow data in pipes and ditches. Then, the cloud computing module is used to correct, fuse, and preprocess the farmland data, and combine the crops planted in each farmland to generate the recent water demand of each farmland. The next step is to use the network acquisition module to collect recent weather forecast information through the Internet, combine the weather forecast information, derive precipitation, evaporation and other data, and calculate the actual water supply of regional farmland. Finally, the user interface is operated to carry out targeted irrigation and drip irrigation for each farmland through the intelligent control module. In order to automatically adjust the irrigation strategy based on the growth needs of different crops, soil conditions, and meteorological factors, combined with precipitation and evaporation, we need to first identify the key factors and consider their impact on the irrigation amount, and formulate a simplified formula to approximate this strategy.

Here is a basic formula that calculates irrigation amount (IA) based on crop water requirement (CWR), soil water holding capacity (SWHC), expected precipitation (EP), and potential evapotranspiration (PET):

IA=CWR+PET-SWHC-EP

Irrigation amount (IA), which is equal to crop water requirement (CWR) plus potential evaporation (PET), minus water held by soil moisture (SWHC), minus expected precipitation (EP);

CWR=SWHC*[1-(EP/PET)]*CorrectionFactor

CWR: actual crop water requirement, based on crop type, growth stage and climatic conditions

SWHC: Soil Water Holding Capacity, which depends on soil type, texture and structural properties

EP: Expected precipitation, which is the amount of precipitation in the future according to the weather forecast

PET: Potential Evaporation, which is the potential for water evaporation calculated based on meteorological conditions such as temperature, humidity, wind speed and solar radiation.

CorrectionFactor: Correction factor, which ranges from 0.9 to 1.1. This value is used to adjust the irrigation amount according to actual monitoring data and empirical values, taking into account factors such as actual evapotranspiration, changes in crop growth status, and changes in soil moisture. This formula is a simplified model that assumes that the soil moisture retention capacity is a constant value, but in fact it may change with changes in soil temperature. At the same time, expected precipitation is an uncertain variable that depends on the accuracy of weather forecasts. Potential evaporation is a relatively stable value, but it will also be affected by changes in meteorological conditions.

In actual applications, this formula may need to be further customized and optimized based on the meteorological, soil and crop data of the specific region. Usually, the determination of this irrigation strategy requires precise adjustment based on real-time environmental monitoring data, historical meteorological data and crop growth models. Moreover, automated irrigation systems usually combine sensor technology, the Internet of Things and artificial intelligence algorithms to adjust irrigation strategies in real time to achieve the goals of water saving, high efficiency and environmental protection.

Suppose there is a piece of farmland in a certain area, mainly growing wheat and corn. The soil conditions, climate conditions and crop growth cycles in the area are different. In order to achieve the irrigation goals of water saving, high efficiency and environmental protection, it is decided to introduce a smart water irrigation system.

System composition and working principle:

1. Perception layer: Soil moisture sensors, weather stations, and evaporation monitoring equipment are deployed in farmland. These sensors collect data such as soil moisture, precipitation, temperature, humidity, wind speed, and solar radiation in real time, and transmit them to the data center through wireless communication technology;

2. Data processing and analysis layer: After receiving the data, the data center uses cloud computing and big data technology to process and analyze the data. The system first determines the actual crop water requirement (CWR) and soil water retention capacity (SWHC) based on crop type, growth stage and soil conditions. Then, it combines real-time meteorological data and historical data to predict precipitation (EP) and potential evaporation (PET) in the future.

3. Decision-making and control layer: Based on the above data and analysis results, the system uses the above formula or similar algorithms to calculate the irrigation amount (IA). At the same time, the system also considers factors such as actual evapotranspiration, changes in crop growth status, and changes in soil moisture, and fine-tunes the irrigation amount through correction factors;

4. Execution layer: Once the irrigation strategy is determined, the system will implement it through automated irrigation equipment (such as sprinklers, drip irrigation systems, etc.). These devices can accurately control the water supply and irrigation amount according to the system instructions to ensure that the crops get the right amount of water.

In the smart water conservancy irrigation system, the formula WHC*(1-(EP/PET))*CorrectionFactor is usually used to calculate the actual irrigation water demand of crops, where: WHC represents the water holding capacity of crops, that is, the amount of water required by crops in a certain period of time, EP represents the actual evaporation, that is, the amount of water actually lost by crops through transpiration, and PET represents the potential evaporation, that is, the maximum amount of water that crops may lose under ideal conditions. CorrectionFactor: represents the correction factor, which is used to adjust the irrigation amount according to factors such as soil, crop type, and atmosphere. The following are two specific cases implemented according to this formula:

Example 1: Smart irrigation of corn fields

WHC=80mm (daily water requirement of corn)

EP=50mm (According to soil moisture monitoring, the actual evaporation of corn fields on that day)

PET=70 mm (potential evaporation on the day based on meteorological data)

CorrectionFactor=1.1 (taking into account the effect of soil texture and local wind speed on evaporation)

calculate:

Actual irrigation water requirement = 80mm*(1-(50mm/70mm)*1.1

=80mm*(1-0.714)*1.1

=22.88mm≈23mm

Implementation: Based on the calculation results, the system will start the irrigation equipment to provide about 23 mm of irrigation water to the corn field.

Example 2: Intelligent lawn irrigation

data:

WHC=40mm (daily lawn water requirement)

EP=30mm (According to soil moisture monitoring, the actual evaporation of the lawn on that day)

PET=50mm (potential evaporation on the day based on meteorological data)

CorrectionFactor = 0.9 (taking into account the effect of lawn soil water retention capacity and local humidity on evaporation)

calculate:

Actual irrigation water requirement = 40mm*(1-(30mm/50 mm)*0.9

=40mm*(1-0.6)*09=40 mm*0.4*0.9

=14.4mm (rounded to 14mm)

Implementation: Based on the calculation results, the system will start the irrigation equipment to provide about 14 mm of irrigation water to the lawn;

These two cases demonstrate how the Zhicao Water Conservancy Irrigation System calculates and implements irrigation based on crop water requirement coefficient, actual base yield, potential evaporation and correction factor, thereby ensuring that crops receive an appropriate amount of water supply while avoiding waste of water resources.

In smart water irrigation systems, the determination of the Correction Factor is usually based on experience, experimental data or expert advice, and it is not a value directly calculated. This factor takes into account a variety of factors, such as soil texture, crop type, local climate conditions (such as wind speed, humidity, temperature), irrigation methods (such as drip irrigation, sprinkler irrigation, etc.), etc., to fine-tune the irrigation water demand.

For CorrectionFactor = 1.1 in Case 1 and CorrectionFactor = 0.9 in Case 2, these two values may be based on the following considerations:

1. Soil texture: Different soil textures have different water retention capabilities. If the soil has a poor water retention capacity, a higher correction factor may be needed to compensate for the rapid loss of water.

2. Crop type: Different crops have different water requirements and absorption efficiencies. Some crops may require more water to achieve optimal growth, which may require adjustment of the correction factor.

3. Local climate conditions: Wind speed, humidity, temperature, etc. will affect the evaporation rate of water. If the climate conditions make the water evaporate faster, it may be necessary to increase the correction factor to ensure that the crop gets enough water.

4. Irrigation method: Different irrigation methods such as drip irrigation and sprinkler irrigation have different efficiencies, which will also affect the determination of the correction factor.

5. Historical data and expert advice: Based on historical irrigation data and expert advice, appropriate correction factors can be estimated.

6. Experimental data: Through field experiments, crop growth and water use efficiency under different conditions can be measured to determine a more accurate correction factor. It should be noted that the Correction Factor is a dynamic factor that may be adjusted with changes in seasons, years, and local conditions. Therefore, in actual applications, this factor needs to be regularly checked and updated to ensure the accuracy and efficiency of irrigation.

Since CorrectionFactor is not directly calculated, there is no specific Python code to calculate it. In practical applications, the value of this factor is usually set based on actual conditions and expert advice.

Implementation effect: Through the application of the smart water conservancy irrigation system, the irrigation efficiency of farmland in the region has been significantly improved. The system can automatically adjust the irrigation strategy according to actual needs and conditions, avoiding the problem of over-irrigation or under-irrigation. At the same time, the system can also monitor the farmland environment and crop growth status in real time, provide decision support for farmers, and help them better manage farmland.

In addition, the smart water conservancy irrigation system also has the advantages of water saving, environmental protection and reduced production costs. By accurately controlling the irrigation amount and irrigation time, the system effectively reduces the waste of water resources. At the same time, a reasonable irrigation strategy can also help improve the soil environment and increase crop yield and quality.

In short, the smart water conservancy and irrigation system optimizes irrigation strategies by combining real-time data and algorithms. In the future, with the continuous advancement of technology and the expansion of its application scope, the smart water conservancy and irrigation system will play a more important role in the agricultural field.

Features:

1. Real-time monitoring and early warning: The sensor network monitors farmland environmental parameters and crop growth status in real time. Once an abnormality is found, the system immediately issues an early warning notification to remind users to take corresponding measures.

2. Precision irrigation: According to the water demand of crops and soil moisture conditions, the system automatically calculates the irrigation water volume and irrigation time to achieve precise irrigation and avoid waste of water resources.

3. Water-saving optimization: Optimize and analyze irrigation data through intelligent algorithms to find the best irrigation strategy, reduce irrigation costs, and improve water resource utilization efficiency.

4. Remote control and automation: Users can remotely set irrigation parameters, control the switches of irrigation equipment, etc. through the user interface to achieve automated management of the irrigation process.

5. Data visualization and report generation: The system provides rich data visualization functions, which can display monitoring data to users in the form of charts, so that users can intuitively understand the farmland conditions. At the same time, the system can also generate irrigation reports to facilitate data analysis and management.

When implementing a new smart water conservancy irrigation system, it is necessary to fully consider the actual situation and needs of the farmland and formulate a reasonable implementation plan. The system can be applied to various types of farmland, including rice fields, orchards, vegetable fields, etc., providing strong technical support for agricultural production.

By applying the new smart water irrigation system, the following goals can be achieved:

1. Improve irrigation efficiency: Reduce irrigation costs and improve water resource utilization efficiency through precision irrigation and water-saving optimization.

2. Improve crop quality and yield: Through reasonable irrigation strategies, ensure that crops receive sufficient water supply and improve crop quality and yield.

3. Reduce the burden on farmers: Through automation and intelligent management, reduce the labor intensity of farmers and improve agricultural production efficiency.

4. Promote sustainable development: Through water-saving irrigation and environmental management, reduce the negative impact on the environment and promote sustainable agricultural development.

In short, the new smart water conservancy irrigation system uses modern scientific and technological means to realize intelligent and precise management of the entire irrigation process, provides strong technical support for agricultural production, and helps promote agricultural modernization and sustainable development.

By setting up a rainfall detection and surrounding environmental meteorological monitoring device composed of an agricultural meteorological monitor and a rain gauge, the rainfall amount and the weather around the water management monitoring platform device in the next few days can be monitored, thereby providing data support for the water management department to do a good job in water control and improve the efficiency of water control.

The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims (9)

1. Intelligent water conservancy monitoring and irrigation system based on computer, its characterized in that: the system comprises a sensor module, an intelligent control module, a network acquisition module, a data transmission module, a cloud computing platform and a user interface;

The data transmission module collects data information through the sensor module and the network acquisition module, sends data to the intelligent control module for control, the cloud computing platform performs data interaction with the data transmission module, and the user interface performs data interaction with the cloud computing platform;

the sensor module comprises sensors deployed in farmlands, is used for monitoring and collecting real-time data in the farmlands in real time and uploading the real-time data to the data transmission module;

The intelligent control module receives a control instruction sent by the cloud computing platform through the data transmission module, executes an irrigation task and realizes automatic and intelligent control;

The network acquisition module acquires recent weather forecast information through the Internet and uploads the information to the cloud computing platform through the data transmission module;

The data transmission module is responsible for transmitting the data acquired by the sensor module and the network acquisition module to the cloud computing platform so as to realize real-time data transmission;

The cloud computing platform is responsible for data storage, processing and analysis, and adopts a big data analysis technology to excavate and predict the collected data so as to provide scientific basis for irrigation decision;

the user interface provides an operation interface for a user to view data and execute operations.

2. The computer-based intelligent water conservancy monitoring and irrigation system as set forth in claim 1, wherein: the sensor module comprises sensors deployed in farmlands, including a water level sensor, a soil humidity sensor, a meteorological sensor and a crop growth sensor, and is used for monitoring soil humidity, temperature, wind speed and crop growth state information in real time.

3. The computer-based intelligent water conservancy monitoring and irrigation system as set forth in claim 1, wherein: the intelligent control module comprises an intelligent valve, an irrigation pump and a sprinkler, and is used for executing irrigation tasks, and further comprises a plurality of chemical fertilizer storage tanks and metering valves connected with the chemical fertilizer storage tanks, wherein the metering valves are connected with the irrigation pump, and the devices can receive control instructions from the cloud computing platform to realize automation and intelligent control.

4. The computer-based intelligent water conservancy monitoring and irrigation system as set forth in claim 1, wherein: the network acquisition module acquires recent weather forecast information including sunshine duration, rainfall, evaporation and temperature range data through the Internet.

5. The computer-based intelligent water conservancy monitoring and irrigation system as set forth in claim 1, wherein: the data transmission module is responsible for transmitting data acquired by the sensor to the cloud computing platform, and the data transmission module adopts a wireless communication technology to realize real-time data transmission.

6. The computer-based intelligent water conservancy monitoring and irrigation system as set forth in claim 1, wherein: the user interface provides an operation interface for a user, and comprises a mobile phone APP and a webpage end, so that the user can conveniently view real-time data, set irrigation parameters and receive early warning information.

7. A computer-based intelligent water conservancy monitoring and irrigation system according to any of claims 1-6 and wherein: the cloud computing platform automatically adjusts irrigation strategies according to the growth requirements, soil conditions and meteorological factors of different crops.

8. The computer-based intelligent water conservancy monitoring and irrigation system as set forth in claim 7, wherein: the predicted evaporation capacity is subtracted from the existing water quantity plus the predicted precipitation capacity to obtain the predicted residual water quantity, and then the predicted residual water quantity is compared with the actual water demand of crops in the farmland in the area to carry out water supplementing or water draining work on the farmland.

9. The computer-based intelligent water conservancy monitoring and irrigation system as set forth in claim 8, wherein: calculation formula of actual water demand (Crop Water Requirement, CWR) of crops

CWR=SWHC*[1-(EP/PET)]*CorrectionFactor

CWR: the actual water demand of crops is determined based on the types of crops, the growth stage and climate condition factors;

SWHC: soil moisture retention capacity, depending on soil type, texture and structural characteristics;

EP: expected precipitation, which is precipitation over a period of time in the future, derived from weather forecast;

PET: potential evaporation, which is the calculated moisture evaporation potential from meteorological conditions;

CorrectionFactor: correction coefficients.