A landscaping intelligent irrigation method, system, controller and sprinkler

Abstract

The application relates to the field of garden greening management automation, and discloses a garden greening intelligent irrigation method, system, controller and spray head, the method comprising: collecting environmental information; constructing a soil moisture dynamic equation and a plant growth model according to plant information and environmental information; calculating a spray head opening time based on the dynamic equation and the growth model; controlling the spray head to open and close according to the opening time; and dynamically adjusting the spray head opening time based on the environmental information after the spray head is opened. The application constructs a soil moisture dynamic equation based on soil humidity and weather changes, and calculates a spray head opening time based on the dynamic equation and the growth model, so that efficient and intelligent irrigation control is realized. Compared with an existing timing automatic irrigation system, the application effectively avoids water resource waste caused by fixed cycle watering, while ensuring the accuracy and timeliness of water supply, meets the needs of modern water saving and accurate maintenance, and has remarkable environmental and economic benefits.

Description

Technical Field

[0001] This invention relates to the field of automated management of landscaping and greening, specifically to an intelligent irrigation method, system, controller, and sprinkler head for landscaping and greening. Background Technology

[0002] With the rapid development of smart cities, landscape management is gradually becoming more intelligent. Traditional landscape irrigation methods mainly rely on manual or timed watering. While these methods can meet basic needs, they are no longer adequate for the high efficiency and precision requirements of modern landscape management, given the increasing demands for water conservation and precise maintenance. Intelligent irrigation systems are gradually becoming an indispensable part of modern landscape management, aiming to reduce water waste while ensuring healthy plant growth through more precise data collection and control.

[0003] Currently, the most commonly used systems on the market are automatic irrigation systems based on fixed time settings. These systems control the irrigation cycle through a preset schedule, irrigating according to the set times regardless of weather conditions. These systems offer a degree of automation, reducing manual operation and management costs.

[0004] However, existing automatic irrigation systems cannot respond to environmental changes in real time, especially changes in weather conditions and real-time soil moisture. This makes it impossible for the system to flexibly adjust the irrigation amount and timing, leading to water waste. In severe weather or when soil moisture fluctuates significantly, the system may over- or under-water, thereby affecting plant growth and health. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides an intelligent irrigation method, system, controller, and sprinkler for landscaping, which solves the problems of existing timed automatic irrigation systems being unable to respond to environmental changes in real time, unable to flexibly adjust the amount and timing of watering, resulting in water waste and uneven plant growth.

[0006] To achieve the above objectives, the present invention provides the following technical solution: an intelligent irrigation method for landscaping, comprising the following steps:

[0007] Collect environmental information;

[0008] Soil moisture dynamic equations and plant growth models were constructed based on plant and environmental information.

[0009] The nozzle opening time is calculated based on dynamic equations and growth models.

[0010] Control the nozzles to turn on and off according to the opening time;

[0011] The nozzle opening time is dynamically adjusted based on environmental information after the nozzle is turned on.

[0012] Preferably, the environmental information includes soil temperature and humidity and environmental meteorological data, and the plant information includes plant height, leaf area and plant growth stage.

[0013] Preferably, the soil moisture dynamic equation is used to calculate the changes in soil temperature and humidity over time, soil evapotranspiration loss, precipitation, and irrigation flow rate.

[0014] The calculation of the sprinkler opening time is derived from the plant's water requirement, soil temperature and humidity, environmental evapotranspiration, total irrigated area, future precipitation, and plant growth stage coefficient.

[0015] Preferably, the dynamic adjustment is based on real-time monitoring data of soil temperature and humidity, meteorological information and plant growth status, to dynamically correct the irrigation amount and maintain soil moisture.

[0016] A smart irrigation system for landscaping includes:

[0017] The data acquisition module is used to monitor soil temperature and humidity in real time and transmit the data to the central controller;

[0018] The central controller receives real-time meteorological data and soil temperature and humidity data, analyzes and calculates irrigation needs, and sends irrigation instructions to the electric sprinklers.

[0019] Electric nozzles; used to receive and execute instructions and adjust their own working status.

[0020] Preferably, the acquisition module includes several soil temperature and humidity sensors, which are distributed in the green area to monitor the soil temperature and humidity in the green area in real time.

[0021] Preferably, the central controller includes a weather forecast interface module for acquiring real-time meteorological data within the green area.

[0022] A smart irrigation controller for landscaping, the controller comprising:

[0023] The data receiving unit is used to receive data from the soil temperature and humidity sensor.

[0024] The weather forecasting unit is used to acquire real-time meteorological data within the green area.

[0025] The data processing unit is used to perform data filtering, anomaly detection, and analysis on soil temperature and humidity sensor data and real-time meteorological data within the green area;

[0026] The optimal control calculation unit is used to calculate the optimal irrigation strategy based on the output data of the data processing unit, and to dynamically adjust the optimal irrigation strategy based on the feedback information of the electric sprinkler head.

[0027] The wireless communication unit is used to send irrigation commands to the electric sprinkler head based on the optimal irrigation strategy and to receive feedback information.

[0028] A smart irrigation sprinkler head for landscaping, the sprinkler head being an electric sprinkler head, comprising:

[0029] Spraying components are used to dynamically adjust the spray flow rate and angle according to irrigation instructions;

[0030] The actuator, including a solenoid valve, is used to adjust the opening time of the electric sprinkler head according to the irrigation command from the central controller;

[0031] The monitoring unit is used to detect the water pressure and flow rate of the sprinkler head and feed the data back to the central controller.

[0032] This invention provides an intelligent irrigation method, system, controller, and sprinkler head for landscaping. It offers the following advantages:

[0033] 1. This invention constructs a dynamic equation for soil moisture based on soil humidity and weather changes, and calculates the sprinkler head opening time based on the dynamic equation and growth model, thus achieving efficient and intelligent irrigation control. Compared with existing timed automatic irrigation systems, this invention effectively avoids water waste caused by fixed-cycle watering, while ensuring the accuracy and timeliness of water supply, meeting the needs of modern water conservation and precision maintenance, and has significant environmental and economic benefits.

[0034] 2. The present invention controls the opening and closing of the sprinkler head based on the soil temperature and humidity and environmental meteorological data, enabling the invention to intelligently respond to climate change and soil moisture fluctuations, avoid the negative impact of over-watering or under-watering on plant growth, ensure that plants grow healthily under optimal water conditions, and greatly improve irrigation efficiency and plant maintenance quality.

[0035] 3. This invention dynamically adjusts the sprinkler opening time based on environmental information after the sprinkler is turned on, thus achieving intelligent feedback, real-time monitoring and evaluation of irrigation effects, and automatic adjustment of watering strategies. Unlike static control systems in existing technologies, this invention can continuously receive real-time data feedback, ensuring optimal results for each irrigation, further improving irrigation efficiency and plant health. This efficient feedback mechanism ensures the precision of irrigation operations, avoiding uneven watering caused by human error or environmental changes, demonstrating the system's high level of intelligence and automation. Attached Figure Description

[0036] Figure 1 This is a schematic diagram of the method flow of the present invention;

[0037] Figure 2 This is a schematic diagram of the system architecture of the present invention;

[0038] Figure 3 This is a schematic diagram of the controller of the present invention;

[0039] Figure 4 This is a schematic diagram of the electric nozzle of the present invention. Detailed Implementation

[0040] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0041] To better understand the present invention, the above content will be described in detail below with reference to specific embodiments.

[0042] Please see the appendix Figure 1 This invention provides an intelligent irrigation method for landscaping, comprising the following steps:

[0043] Collect environmental information;

[0044] In this embodiment, collecting environmental information is one of the fundamental steps in realizing an intelligent irrigation system. Real-time collection of environmental information provides necessary data support for subsequent calculations of soil moisture dynamic equations and the construction of plant growth models. This step is a crucial link in the entire intelligent irrigation method. By collecting environmental parameters such as soil temperature and humidity, and meteorological data, the system ensures that it can reflect the current greening environment status in a timely and accurate manner, serving as a basis for adjusting irrigation strategies.

[0045] Specifically, environmental information includes soil temperature and humidity, as well as meteorological data. Soil temperature and humidity are primarily collected using soil temperature and humidity sensors distributed throughout the green areas, and the collected data is transmitted to the central controller in real time. Meteorological data includes parameters such as temperature, humidity, wind speed, air pressure, and precipitation. This information can be obtained through weather stations or meteorological service interfaces and provided to the system for further processing.

[0046] In one possible implementation, soil temperature and humidity sensors are deployed at different locations within the green area to ensure real-time monitoring of soil moisture changes in different areas. For example, resistive, frequency-response, or other types of sensors with high accuracy (e.g., ±1% RH or higher) can be used to ensure accurate monitoring of soil moisture. Through these sensors, the system can sense changes in soil moisture and adjust irrigation strategies accordingly.

[0047] In another implementation, meteorological data can be collected by connecting to an external meteorological service interface to obtain real-time weather data. The collected meteorological data includes temperature, humidity, precipitation, wind speed, etc., which helps to further predict weather changes in the next few hours or days, thereby optimizing irrigation decisions.

[0048] To ensure the accuracy and real-time nature of information collection, wireless transmission technology can be used to transmit the collected soil temperature and humidity data, as well as meteorological data, to the central controller in a timely manner. Based on this real-time data, combined with the previously established soil moisture dynamic equation and plant growth model, the central controller calculates the appropriate irrigation timing and water volume.

[0049] In some embodiments, the evapotranspiration rate in the soil moisture dynamics equation can be calculated using a model based on the Penman-Monteith formula. This formula estimates the evapotranspiration rate based on factors such as air temperature, relative humidity, and wind speed, thereby reflecting the plant's water requirements. Through this dynamic calculation, the intelligent irrigation system can make more precise irrigation decisions.

[0050] Typically, after the collected environmental information is transmitted to the central controller via sensors, the system processes the data, eliminating noise and outliers to ensure accuracy. These processing steps effectively guarantee the reliability of the environmental data used and prevent interference.

[0051] As an alternative, if future weather data predicts heavy rainfall, the system will adjust the irrigation plan accordingly, reducing the amount of water used to avoid wasting water resources. In this way, when responding to future weather changes, the system can dynamically adjust irrigation volume and timing based on external weather data and real-time soil moisture conditions, maximizing plant growth efficiency while conserving water resources.

[0052] Specifically, by collecting precise environmental information, the intelligent irrigation system can monitor changes in soil moisture in real time, respond promptly to the water needs of plants, and reduce errors during irrigation. For example, when the sensor detects low soil moisture and the weather forecast indicates insufficient rainfall in the next few days, the system can increase the irrigation amount to replenish soil moisture.

[0053] Therefore, by accurately collecting environmental information, the system can assess soil moisture levels and plant needs in real time, thereby rationally allocating water resources and achieving efficient intelligent irrigation. This not only ensures healthy plant growth but also effectively conserves water resources and avoids over-irrigation.

[0054] Soil moisture dynamic equations and plant growth models were constructed based on plant and environmental information.

[0055] In this embodiment, changes in soil moisture and their impact on plant growth are the core elements of the intelligent irrigation strategy. By combining plant and environmental information, a dynamic equation for soil moisture is constructed, and a plant growth model is established, enabling accurate prediction of soil moisture and the formulation of optimal irrigation strategies. This step not only provides a scientific computational basis but also improves the accuracy of irrigation and the efficiency of water resource utilization through quantitative analysis of plant needs.

[0056] Specifically, the soil moisture dynamics equation describes the change of soil moisture content over time, mainly considering factors such as evapotranspiration loss, precipitation recharge, and irrigation input. The equation can be expressed as follows:

[0057]

[0058] Where θ(t) represents soil volumetric water content; ET(t) is the evapotranspiration rate at time t; P(t) is precipitation; I(t) is irrigation input flow rate; and t represents time. This indicates the rate of change of soil moisture content over time.

[0059] Specifically, the evapotranspiration rate ET(t) can be calculated using the Penman-Monteith model, which calculates the plant's water evapotranspiration requirement based on meteorological parameters such as air temperature, humidity, wind speed, and solar radiation. The calculation formula is as follows:

[0060]

[0061] Where ET is the evapotranspiration rate, representing the water released by plants through evaporation and transpiration; Δ is the slope of the saturated vapor pressure curve, representing the effect of temperature on saturated vapor pressure; R n Net radiation represents the radiant energy received by the ground, minus the energy reflected by the ground; G is the soil heat flux, representing the heat flow of the soil layer; γ is the humidity constant, representing the relationship between water vapor in the air and temperature; T is the air temperature; u2 is the wind speed, describing the wind velocity, which affects the evapotranspiration of moisture; e s e is the saturated water vapor pressure; a This is the actual water vapor pressure, the pressure of water vapor that actually exists in the air.

[0062] In one possible implementation, a plant growth model is used to describe the growth status of plants under different water supply conditions, and combined with soil moisture dynamics equations, to predict plant water requirements. Plant growth status can be characterized by parameters such as plant height and leaf area, and water requirements can be dynamically adjusted based on growth stages.

[0063] In some embodiments, the plant growth model can employ a photosynthetic kinetics-based model, which comprehensively considers photosynthetically active radiation, carbon dioxide concentration, and water supply to predict the plant's growth rate. Its basic expression is:

[0064] G = Φ·PAR·f(W);

[0065] Where G represents the plant growth rate; Φ is the photosynthetic efficiency; PAR is the photosynthetically active radiation; and f(W) is the water regulation factor, which describes the effect of soil water supply on plant growth.

[0066] Generally, the soil moisture regulating factor f(W) depends on the relationship between soil moisture θ and plant water requirement, and can be represented by an exponential model or a piecewise linear model, for example:

[0067]

[0068] Where, θ opt θ represents the optimal soil moisture content for plant growth. w This represents the water content at the plant's wilting point. This model is used to describe the impact of soil moisture on plant growth and provides a basis for subsequent irrigation strategies.

[0069] As an alternative, historical data can be incorporated into the model calibration when constructing soil moisture dynamics equations and plant growth models. For example, through long-term environmental monitoring and the accumulation of plant growth data, data-driven methods (such as machine learning) can be used to adjust model parameters and improve prediction accuracy.

[0070] In another implementation, the model's calculations can be dynamically adjusted by incorporating real-time meteorological data. For example, during periods of high temperature and drought, the evapotranspiration rate increases significantly. In such cases, the system can dynamically adjust the evapotranspiration parameters in the soil moisture equation based on environmental conditions to optimize irrigation strategies.

[0071] Specifically, by constructing a soil moisture dynamic equation and a plant growth model, the system can dynamically monitor and predict soil moisture, ensuring that plants can obtain the water they need under optimal growth conditions. At the same time, this model provides theoretical support for intelligent irrigation systems, enabling them to make precise irrigation decisions based on environmental changes and plant needs.

[0072] Therefore, in this invention, the mathematical model constructed based on environmental information and plant growth status can effectively improve the rationality and intelligence of irrigation strategies. It can not only meet the needs of plant growth, but also optimize water resource utilization to the greatest extent, avoid over- or under-irrigation, and achieve precise and efficient intelligent irrigation control.

[0073] The nozzle opening time is calculated based on dynamic equations and growth models.

[0074] In this invention, the sprinkler head opening time is a crucial control parameter of the intelligent irrigation system, directly affecting soil moisture content and plant growth status. By combining the soil moisture dynamic equation and the plant growth model, the sprinkler head opening time can be scientifically calculated to meet the optimal water requirements for plant growth. Furthermore, the irrigation strategy can be dynamically adjusted under different environmental conditions, ensuring healthy plant growth while optimizing water resource utilization efficiency.

[0075] In this embodiment, the sprinkler activation time is determined by the plant's water requirement, soil moisture status, and environmental evapotranspiration. First, the target soil moisture replenishment amount Δθ needs to be calculated to meet the plant's current growth needs: Δθ = θ opt -θ(t);

[0076] Where, θ opt θ(t) represents the optimal soil moisture content for plant growth; θ(t) represents the current soil moisture content.

[0077] Specifically, the irrigation amount I needs to satisfy the requirement that the soil moisture content increases from θ(t) to the optimal soil moisture content θ for plant growth. opt ,Right now:

[0078] I=Δθ·Z r ·ρ w ;

[0079] Among them, Z r The effective absorption depth of plant roots; ρ w Let be the volume density of water. This formula is used to calculate the total amount of water required to maintain optimal plant growth.

[0080] In one possible implementation, the nozzle opening time T s The calculation formula depends on the sprinkler flow rate Q and the irrigation volume I.

[0081]

[0082] In some embodiments, if there are multiple sprinklers in the irrigation area, the sprinkler density and coverage area need to be considered for correction. The calculation formula is as follows:

[0083]

[0084] Among them, D s Q represents the number of nozzles per unit area; Q represents the coverage area of ​​a single nozzle.

[0085] Generally, the evapotranspiration rate (ET) also needs to be included in the calculation to compensate for water loss and ensure that soil moisture is maintained at an appropriate level. The corrected sprinkler opening time calculation is as follows:

[0086]

[0087] Where A is the total area of ​​the irrigated area; ET is calculated by the Penman-Monteith equation and reflects the amount of water loss due to plant transpiration and environmental evaporation.

[0088] In another implementation, if weather forecasts indicate rainfall in the near future, the sprinkler activation time can be adjusted to reduce over-irrigation. The corrected formula is as follows:

[0089]

[0090] Among them, P f This is the future precipitation estimate; this calculation method can avoid unnecessary waste of water resources.

[0091] Specifically, soil moisture requirements change dynamically depending on the plant's growth stage. For example, seedlings require higher soil moisture, while mature plants may tolerate a certain range of moisture fluctuations. Therefore, the sprinkler activation time must also be adjusted according to the plant's growth cycle, as expressed in the following formula:

[0092]

[0093] Among them, f stage This is a coefficient representing the plant growth stage; appropriate adjustment factors are set according to different stages to ensure that water supply matches growth needs.

[0094] Alternatively, the system can dynamically adjust the sprinkler head opening time by incorporating data from real-time soil moisture sensors. For example, if the actual soil moisture is detected to be higher than expected, the sprinkler head opening time can be appropriately shortened to achieve precision irrigation.

[0095] Therefore, in this invention, the sprinkler opening time calculation method based on the soil moisture dynamic equation and plant growth model can achieve scientific control of irrigation, avoid water waste, ensure that plants grow under suitable moisture conditions, and improve the intelligence level of the irrigation system.

[0096] Control the nozzles to turn on and off according to the opening time;

[0097] In this embodiment, the sprinkler head switching control is based on calculated on-time to ensure that the irrigation process matches the plant's water requirements. By combining soil moisture dynamics equations and plant growth models, the sprinkler head operating time can be rationally determined, and the on / off state of the sprinklers can be dynamically adjusted according to environmental changes to ensure that soil moisture content is maintained within a suitable range. The sprinkler head switching not only needs to be controlled according to predetermined times but also requires feedback adjustments based on real-time monitoring data to optimize water resource utilization efficiency.

[0098] Specifically, the sprinkler head activation time is determined based on the time parameters calculated in the preceding steps, combined with soil moisture conditions. First, according to the aforementioned calculation method, the required sprinkler head activation time is determined, and the sprinkler head is activated when the soil moisture content falls below a set threshold. After the sprinkler head is activated, the system continuously tracks moisture changes in the irrigated area and shuts off the sprinkler head when the target moisture content is reached to prevent over-irrigation or water waste.

[0099] Specifically, sprinkler head operation is significantly affected by environmental factors, thus requiring dynamic adjustments during control. For example, under conditions of high temperature or strong winds, the rate of water evaporation is high, and the sprinkler head operating time may need to be appropriately extended to compensate for additional water loss. Conversely, under conditions of low temperature and high humidity, soil moisture evaporation is slower, and the sprinkler head operating time can be appropriately shortened to prevent excessive soil moisture. Furthermore, when rainfall is imminent, one irrigation session can be reduced or skipped, thereby optimizing water resource utilization.

[0100] In one possible implementation, the sprinkler head's on / off state can be adjusted in real time based on soil moisture monitoring results. If, during sprinkler operation, soil moisture fails to increase as expected (potentially due to low permeability or abnormal flow), the sprinkler head's operating time can be appropriately extended until irrigation needs are met. Conversely, if a rapid increase in soil moisture is detected and it approaches the set optimal value, the sprinkler head can be shut off prematurely to prevent soil oversaturation.

[0101] In another approach, sprinkler control can be optimized based on the plant's growth stage. For example, in the early stages of plant growth, when the root system is shallow and more sensitive to water requirements, the sprinkler operation time needs to be shorter but the frequency higher to keep the topsoil moist. During the mature stage, when the root system penetrates deeper into the soil, allowing for longer wet-dry cycles, the sprinkler operation time can be appropriately extended and the irrigation frequency reduced to adapt to the plant's physiological characteristics and improve water use efficiency.

[0102] Normally, the sprinkler head's on / off control uses a set operating cycle, which is fine-tuned based on real-time environmental data within that cycle. If environmental conditions change abruptly during sprinkler operation, such as a sudden downpour or a sudden increase in humidity, the sprinkler head can automatically stop operating to adapt to sudden weather changes. In the event of a prolonged drought, the sprinkler head's operating time can be increased to ensure sufficient soil moisture supply.

[0103] As an alternative, sprinkler control can be adjusted in conjunction with remote monitoring. For example, by periodically analyzing historical data, the operating time of the sprinklers can be adjusted to adapt to different seasons and soil conditions. If long-term monitoring reveals that the soil in a certain area has weak water retention capacity, the operating time of the sprinklers can be appropriately increased or the irrigation frequency can be increased to compensate for water loss.

[0104] Therefore, in this invention, the on / off control of the sprinkler heads is based on calculated irrigation time and optimized in conjunction with environmental feedback to achieve precision irrigation. This method can adapt to different climatic conditions, plant growth stages, and soil characteristics, ensuring that plants receive adequate water while avoiding unnecessary water waste and improving the intelligence and efficiency of irrigation.

[0105] The nozzle opening time is dynamically adjusted based on environmental information after the nozzle is turned on.

[0106] In this embodiment, the sprinkler head activation time not only depends on the preset calculated value but also needs to be dynamically adjusted based on real-time environmental information after the sprinkler head is activated. Since external environmental factors (such as temperature, humidity, wind speed, and precipitation) affect soil moisture evaporation rate and plant water absorption efficiency, relying solely on the initially calculated sprinkler head activation time may lead to insufficient or excessive irrigation. By introducing an environmental feedback mechanism, soil moisture, evapotranspiration rate, and meteorological changes are dynamically monitored during sprinkler operation, and the sprinkler head activation time is corrected in real time to ensure that the irrigation amount accurately matches the plant's needs and optimizes water resource utilization to the greatest extent.

[0107] Specifically, after the sprinkler heads are turned on, the system acquires real-time environmental data through soil moisture sensors, meteorological monitoring equipment, and flow meters, and dynamically adjusts the sprinkler head operating time based on the changing trends. If the soil moisture quickly reaches or exceeds the target value during the sprinkler head operation, the sprinkler head can be turned off early to avoid excessive moisture. If a high evaporation rate or high wind speed is detected, resulting in a rapid recovery of soil moisture, the system can appropriately extend the sprinkler head operating time to compensate for moisture loss.

[0108] Specifically, the system assesses whether the current irrigation efficiency meets expectations by calculating the rate of change in soil moisture after the sprinklers are turned on. For example, if the increase in soil moisture content is less than a set threshold within a certain time interval, it may indicate that water infiltration is too rapid or that plants are absorbing too much water. In this case, the system will appropriately extend the sprinkler opening time to ensure that the soil moisture content reaches the set range. In addition, if rainfall is detected in a short period of time, the sprinkler opening time can be shortened accordingly to avoid over-irrigation.

[0109] In one possible implementation, environmental feedback data after the sprinkler heads are turned on can be used to adjust the parameters of the irrigation model. For example, if a low soil moisture recovery rate is detected during sprinkler operation, it may indicate poor water retention capacity or leakage problems in the soil of that area. In this case, the system can adjust the upper limit of the target soil moisture to ensure sufficient water supply. Conversely, if a fast moisture recovery rate is detected and the soil moisture exceeds the set upper limit, the system can appropriately reduce the sprinkler head operating time to optimize water resource utilization.

[0110] In another implementation, the sprinkler head activation time can be adaptively adjusted based on short-term weather forecast information. For example, if the system detects a rapid rise in temperature and a quick drop in humidity shortly after the sprinkler head is activated, which may lead to increased water evaporation, the sprinkler head operation time can be appropriately extended to compensate for the additional water loss. Furthermore, if precipitation is detected during sprinkler operation, irrigation can be immediately stopped, or the subsequent sprinkler head activation time can be reduced to minimize water waste.

[0111] Generally, dynamic adjustment strategies for sprinklers need to be combined with historical irrigation data to optimize control logic. For example, through long-term data analysis, a correlation model between environmental parameters and sprinkler activation time can be established, enabling the system to automatically adjust sprinkler operation strategies based on past environmental trends. For instance, in high-evaporation environments, the system may pre-set longer activation times, while in low-evaporation environments, it may reduce sprinkler operation time to improve irrigation efficiency.

[0112] Alternatively, the system can employ a self-learning algorithm to automatically optimize the sprinkler operation strategy based on environmental changes after the sprinkler is turned on. For example, a machine learning model can be built based on historical soil moisture variation data to predict moisture changes after the sprinkler is turned on, and the opening time can be dynamically adjusted accordingly. This approach improves the system's adaptability, enabling precise control of the sprinkler's operation under different environmental conditions.

[0113] In summary, the dynamic adjustment of sprinkler head opening time in this invention is based on environmental feedback information after sprinkler head operation, enabling the irrigation system to achieve adaptive regulation under different environmental conditions. By real-time monitoring of soil moisture, evapotranspiration rate, and meteorological factors, and combining historical data to optimize control strategies, this method can effectively improve irrigation accuracy, reduce water waste, ensure plant growth under optimal water supply conditions, and enhance the overall intelligence level of irrigation management.

[0114] Please see the appendix Figure 2 This invention provides an intelligent irrigation system for landscaping, comprising:

[0115] The data acquisition module is used to monitor soil temperature and humidity in real time and transmit the data to the central controller;

[0116] The central controller receives real-time meteorological data and soil temperature and humidity data, analyzes and calculates irrigation needs, and sends irrigation instructions to the electric sprinklers.

[0117] Electric nozzles; used to receive and execute instructions and adjust their own working status.

[0118] In this embodiment, the system includes the following key components: a data acquisition module, a central controller, and electric sprinklers. Each component works together to achieve intelligent management of the irrigation process, ensuring that plants receive the water they need and maximizing water resource utilization efficiency.

[0119] Data Acquisition Module:

[0120] The data acquisition module is responsible for real-time monitoring of soil temperature and humidity, ensuring continuous understanding of the soil environment. This module uses a set of soil temperature and humidity sensors distributed throughout the irrigation area to collect temperature and humidity data from different soil layers. These sensors can be resistive, frequency-response, or capacitive, accurately measuring soil moisture and temperature and transmitting this data to the central controller in real time. The role of the data acquisition module is to provide the central controller with a reliable foundation of soil data, enabling the central controller to analyze and calculate irrigation needs based on accurate environmental data.

[0121] Central controller:

[0122] The central controller, acting as the system's brain, receives real-time soil temperature and humidity data from the acquisition modules and analyzes it in conjunction with real-time meteorological data (such as air temperature, humidity, wind speed, and precipitation) provided by external meteorological services. Using the collected data and meteorological information, the central controller applies advanced water dynamics models and plant growth models to calculate the gap between the current soil moisture level and plant needs, thereby determining the appropriate irrigation requirements. The calculation process may include predictions of future weather changes and optimization of soil moisture prediction models.

[0123] The central controller uses a pre-set algorithm to determine in real time whether the irrigation system needs to be activated. For example, if the system detects that the soil moisture is below a preset threshold and the weather forecast indicates no rainfall in the short term, the central controller will send an activation command to the electric sprinklers. If the calculation shows that the soil moisture is sufficient for plant needs, the system will postpone or stop irrigation. Furthermore, the central controller can dynamically adjust the irrigation volume and frequency based on system demand and environmental feedback, ensuring water conservation while meeting the plant's growth requirements.

[0124] Electric nozzles:

[0125] After receiving an irrigation command from the central controller, the electric sprinkler head adjusts its operating status accordingly. Upon receiving an activation command, the electric sprinkler head performs irrigation operations by adjusting parameters such as spray volume, spraying method, or coverage of the sprayed area. The operating status of the electric sprinkler head can be adjusted as needed, for example, by changing the sprinkler flow rate or controlling the spray angle to ensure uniform water distribution in the irrigation area. The electric sprinkler head not only responds to activation commands from the central controller but also provides feedback on its own operating status (such as whether the sprinkler head is operating normally, whether the water flow is blocked, etc.), allowing the central controller to monitor and adjust the system in real time.

[0126] Specifically, once the electric sprinkler head receives a command from the central controller, it begins irrigating according to a predetermined flow rate and duration. During this process, the sprinkler head can continue operating until the predetermined soil moisture calculated by the central controller is reached, or it automatically stops upon receiving a signal from other sensors (such as when the soil moisture reaches a set target). In the event of a system malfunction or other abnormal situation, the electric sprinkler head can also notify the central controller through a feedback mechanism, thereby activating a fault alarm or other emergency response measures.

[0127] Alternatively, the data acquisition module, central controller, and electric sprinklers are connected via wireless or wired networks to ensure real-time and stable data transmission. All data is transmitted wirelessly to the central controller, giving the entire irrigation system high flexibility and remote control capabilities. Administrators can view the irrigation system's operating status via a remote platform and make manual adjustments as needed.

[0128] Therefore, this system can effectively and intelligently adjust the irrigation process based on real-time environmental data, soil moisture, plant needs, and meteorological conditions, not only optimizing water resource use but also ensuring that plants grow under optimal moisture conditions. Furthermore, through an integrated feedback mechanism and dynamic adjustment capabilities, the system can adaptively adjust to external changes, improving the intelligence and stability of irrigation management.

[0129] As an alternative, suppose a park has a large green area distributed across several different blocks, and each block is equipped with several soil moisture sensors. Each sensor monitors the soil moisture in its area in real time, ensuring the data's timeliness and accuracy. When the central controller receives data from the soil moisture sensors, it analyzes the soil moisture status of each block and decides whether to irrigate or adjust the existing irrigation plan based on the actual situation.

[0130] In this embodiment, the central controller performs intelligent analysis and decision-making by comprehensively considering soil moisture data, meteorological data (such as temperature, humidity, and precipitation), and future weather forecasts for each area. For example, in some areas, if sensor data shows that the soil moisture is below a set minimum moisture threshold, and meteorological data predicts no rainfall in the near future, the central controller will automatically calculate the additional irrigation demand for that area. This calculation takes into account the current soil moisture, the soil's water-holding capacity, and future weather conditions to ensure accurate water supply.

[0131] Based on the calculations, the central controller sends instructions to the electric sprinklers in the relevant areas, requesting extended irrigation time or increased water flow to ensure soil moisture reaches the level required for optimal plant growth. For example, if the soil moisture in a certain area is 20% lower than the predetermined target, the central controller will increase the irrigation time or increase the sprinkler water flow to compensate for the insufficient moisture. The extended irrigation time can be dynamically adjusted according to the sprinkler flow and spray range to ensure that water penetrates evenly into the soil layer, meeting the needs of the plants.

[0132] Conversely, when rain is expected, the central controller will make adjustments based on weather forecasts, even if soil moisture is low in some areas. For example, if weather forecasts indicate impending rainfall, the system will reduce or cancel irrigation plans for certain areas to avoid over-irrigation. The central controller adjusts irrigation plans based on rainfall forecasts, potentially reducing the planned irrigation amount or canceling irrigation for certain areas entirely. Through these adjustments, the system avoids water waste and ensures the soil is not over-saturated.

[0133] During implementation, the system also monitors soil moisture changes in each block in real time and dynamically adjusts the irrigation strategy. If the soil moisture in a certain area does not reach the expected level shortly after irrigation, or if the rainfall forecast changes, the central controller will issue instructions again based on real-time data to adjust the irrigation strategy. For example, if the rainfall is less than expected, the sprinkler head operating time may be extended as needed; if the rainfall is greater than expected, the irrigation amount will be further reduced.

[0134] Specifically, soil moisture sensors in each block transmit data to a central controller via wireless or wired networks. The controller then generates irrigation instructions based on the analysis results. These instructions are transmitted in real time to the motorized sprinklers in the corresponding blocks via wireless networks or other communication methods. Upon receiving the instructions, the motorized sprinklers automatically adjust their on / off state, flow rate, and spraying time according to system requirements, thereby ensuring optimal irrigation results for each block.

[0135] In addition, to ensure irrigation effectiveness in each area, the system regularly performs data analysis and self-optimization. Through long-term data accumulation, the system can more accurately predict irrigation needs under different seasons and weather conditions, and automatically adjust the irrigation strategy for each block. Managers can view the soil moisture and irrigation effect of each block in real time through the visual interface of the central control system, and intervene manually when necessary to further optimize the irrigation plan.

[0136] In this embodiment, by combining real-time soil moisture data, meteorological information, and plant needs, the system achieves precise irrigation control. The system dynamically adjusts the irrigation strategy for each block according to environmental changes, avoiding over-irrigation or water waste while ensuring healthy and efficient plant growth. This intelligent irrigation system not only improves water resource utilization efficiency but also significantly reduces maintenance costs, making it widely applicable, especially suitable for large green spaces, parks, and farmland.

[0137] In this embodiment, the system accesses an authoritative meteorological data service platform, such as the meteorological data interface of the China Meteorological Administration, to obtain comprehensive regional meteorological data. Through this platform, the system can obtain real-time data on key meteorological parameters such as temperature, humidity, wind speed, precipitation, and air pressure. Relying on authoritative meteorological data services ensures the accuracy and reliability of the data source, guaranteeing that the central controller can make accurate decisions based on high-quality input when processing meteorological data.

[0138] In addition, to better address changes in local microclimates, the system will also install small weather stations around the irrigation area. These small weather stations can supplement local meteorological data, particularly for accurately monitoring changes in temperature and humidity caused by microclimate variations. Compared to traditional weather stations, small weather stations offer greater flexibility and accuracy, reflecting real-time dynamic changes in local climate, such as differences in humidity, temperature, and wind speed.

[0139] Small weather stations are equipped with high-precision sensors, including rain gauges, temperature sensors, humidity sensors, and wind speed sensors, enabling continuous monitoring and real-time collection of meteorological data. Rain gauges monitor short-term precipitation, temperature and humidity sensors accurately detect changes in air temperature and humidity, and wind speed sensors help understand the impact of wind on evapotranspiration rates. This collected data is transmitted wirelessly to a central controller, providing the system with real-time meteorological information.

[0140] Data transmission and processing:

[0141] For data transmission, this system employs wireless communication technologies such as 4G and NB-IoT to ensure real-time transmission of meteorological data from the weather station to the central controller. The application of wireless communication technology makes data transmission more convenient and efficient, while avoiding the challenges of long-distance cabling. 4G technology offers faster data transmission rates, suitable for high-frequency data updates and large-volume data transmission; while NB-IoT is suitable for long-distance, low-power, and long-term continuous monitoring applications, ensuring stable data transmission over a wider area.

[0142] To ensure data security during data transmission, all transmitted data is encrypted. Encryption technology prevents data leakage or tampering during transmission, ensuring the confidentiality and integrity of meteorological data. This encryption measure effectively prevents malicious actors from interfering with the normal operation of the irrigation system by stealing or tampering with meteorological data, ensuring that the system makes optimal decisions based on accurate and reliable meteorological data.

[0143] Data reception and processing:

[0144] After receiving data from the meteorological service platform and small weather stations, the central controller performs real-time analysis and preprocessing. During preprocessing, the system cleans the received data, removing outliers and noise to ensure the accuracy of the analysis. For example, if erroneous data is detected due to equipment failure or communication problems, the system will mark it as an outlier and remove it.

[0145] Based on time series analysis, the central controller also performs trend analysis on meteorological data. By analyzing the data change trends over a period of time, the system can predict trends such as rainfall, temperature, and humidity changes in the next few hours or days. For example, if a large amount of rainfall is predicted in the next few hours, the system will adjust the irrigation plan according to the expected precipitation to avoid over-irrigation; if the weather forecast indicates that drought is imminent, the system will increase the irrigation amount accordingly.

[0146] Comprehensive Management and Optimization:

[0147] Through this integrated meteorological data acquisition and processing method, the automatic irrigation system can dynamically adjust its irrigation strategy based on real-time meteorological data. Timely data transmission and real-time processing enable the system to adjust irrigation plans based on accurate weather forecasts and real-time data, optimize water resource utilization, avoid over-irrigation or water shortage, and ensure that plants maintain healthy growth under different climatic conditions.

[0148] Furthermore, the system can pre-calculate and adjust future irrigation needs based on meteorological data. For example, if heavy rainfall is forecast for the next two days, the system will reduce irrigation in advance to avoid unnecessary water waste. Conversely, if the weather forecast indicates a prolonged drought, the system will increase irrigation in advance based on historical data and plant water requirement models to meet the plants' water needs.

[0149] In summary, by connecting to an authoritative meteorological service platform and combining local data collection from small weather stations, along with real-time data transmission and encryption processing, the automatic irrigation system can flexibly adjust irrigation strategies based on changes in global and local meteorological information, ensuring that the irrigation process is intelligent, precise, and efficient.

[0150] Please see the appendix Figure 3 This invention provides an intelligent irrigation controller for landscaping, the controller comprising:

[0151] The data receiving unit is used to receive data from the soil temperature and humidity sensor.

[0152] The weather forecasting unit is used to acquire real-time meteorological data within the green area.

[0153] The data processing unit is used to perform data filtering, anomaly detection, and analysis on soil temperature and humidity sensor data and real-time meteorological data within the green area;

[0154] The optimal control calculation unit is used to calculate the optimal irrigation strategy based on the output data of the data processing unit, and to dynamically adjust the optimal irrigation strategy based on the feedback information of the electric sprinkler head.

[0155] The wireless communication unit is used to send irrigation commands to the electric sprinkler head based on the optimal irrigation strategy and to receive feedback information.

[0156] In this embodiment, the controller includes the following key functional units: a data receiving unit, a weather forecasting unit, a data processing unit, an optimal control calculation unit, and a wireless communication unit. The collaboration of each unit enables the entire system to dynamically adjust the irrigation plan based on real-time data and feedback information, ensuring a precise supply of water to the plants.

[0157] Data receiving unit:

[0158] The data receiving unit is responsible for receiving data from soil temperature and humidity sensors within the landscaping area. Soil humidity sensors monitor real-time changes in soil moisture, providing fundamental data for irrigation decisions. Temperature sensors help monitor soil temperature, further assessing changes in evapotranspiration rates. The core task of the data receiving unit is to ensure the accuracy and real-time nature of the sensor data, transmitting this data to the subsequent processing unit for analysis.

[0159] Weather forecast unit:

[0160] The weather forecasting unit's function is to acquire real-time meteorological data within the green area, including temperature, humidity, wind speed, precipitation, and air pressure. This information is crucial for irrigation decisions because it helps the central controller predict weather changes over the next few hours or days, allowing for dynamic adjustments to irrigation strategies. To obtain real-time meteorological data, the weather forecasting unit can connect to a public meteorological service platform, such as the China Meteorological Administration's interface, or supplement local data through small weather stations around the park.

[0161] Data processing unit:

[0162] The data processing unit receives data from soil temperature and humidity sensors and weather forecasting units, and performs data filtering, anomaly detection, and analysis. The data filtering step removes noise and inaccurate data from the sensors and meteorological data, ensuring that subsequent calculations are based on accurate and high-quality data. Anomaly detection uses algorithms to identify outliers (such as errors caused by equipment malfunctions or environmental interference) and discards them to ensure computational stability. The analysis step then conducts in-depth analysis of the processed data to identify the gap between current soil moisture and plant needs, and assesses the impact of future weather conditions on irrigation strategies.

[0163] Optimal control calculation unit:

[0164] The optimal control calculation unit is responsible for calculating the optimal irrigation strategy based on the filtered and anomaly-detected data output from the data processing unit. This strategy considers factors such as current soil moisture, plant water requirements, meteorological data, and future weather forecasts. By using optimization algorithms and models, the system can calculate the optimal irrigation time and water volume for each area to ensure that plants can grow under optimal moisture conditions. The optimal control calculation unit also dynamically adjusts the irrigation strategy based on feedback information from the electric sprinklers. For example, if the sprinklers detect abnormal water flow or soil moisture fails to meet the set standard, the system will recalculate the irrigation volume or time to ensure that the irrigation target is achieved.

[0165] Wireless communication unit:

[0166] The wireless communication unit sends irrigation commands to the electric sprinklers based on the optimal irrigation strategy and receives feedback information from the sprinklers. The wireless communication unit supports multiple communication protocols, such as Wi-Fi, 4G, and NB-IoT, ensuring timely and stable data transmission. Through these commands, the controller can precisely control the opening and closing of each sprinkler and adjust its flow rate. Feedback information includes the sprinkler's operating status, water flow rate, and soil moisture, helping the controller understand the irrigation effect and adjust its strategy in real time.

[0167] For example, during irrigation, if the system receives feedback from the sprinkler heads that the soil moisture is still too low, the controller will extend the irrigation time or increase the water flow based on the feedback information until the set target is reached.

[0168] Please see the appendix Figure 4 This invention provides an intelligent irrigation sprinkler head for landscaping, which is an electric sprinkler head and includes:

[0169] Spraying components are used to dynamically adjust the spray flow rate and angle according to irrigation instructions;

[0170] The actuator, including a solenoid valve, is used to adjust the opening time of the electric sprinkler head according to the irrigation command from the central controller;

[0171] The monitoring unit is used to detect the water pressure and flow rate of the sprinkler head and feed the data back to the central controller.

[0172] In this embodiment, the spray angle adjustment function can be flexibly set according to the needs of different garden areas, adapting to complex terrain and plant arrangements. By dynamically adjusting the spray angle and water flow, the sprinkler head can achieve precise localized irrigation, avoiding excessive water distribution to areas that do not need irrigation, thereby improving irrigation efficiency and accuracy.

[0173] Implementing agency:

[0174] The actuator mainly consists of a solenoid valve and an electric control unit. The solenoid valve is used to precisely adjust the opening time and duration of the electric sprinkler head according to the irrigation instructions from the central controller. The solenoid valve can quickly respond to changes in the control signal and accurately control the opening and closing of the water flow. Through precise electromagnetic control, the actuator can perform efficient and reliable irrigation operations within the set time range.

[0175] The electric control unit works in conjunction with the solenoid valve to ensure the real-time execution of irrigation commands. The controller dynamically adjusts the timing and duration of each spray based on data such as current soil moisture and weather forecasts. For example, when soil moisture is too low, the controller will extend the operating time of the electric sprinklers; conversely, when moisture is suitable, the operating time will be shortened accordingly.

[0176] Monitoring Unit:

[0177] The monitoring unit includes pressure and flow sensors, responsible for real-time monitoring of the pressure and flow rate of water from the sprinkler heads and feeding the data back to the central controller. By monitoring the sprinkler head pressure and flow rate in real time, the system can identify potential anomalies, such as sprinkler head blockage or malfunction. This feedback data provides the central controller with a real-time assessment of the irrigation effect, helping it determine whether the current irrigation meets expectations and make necessary adjustments.

[0178] For example, if the system detects that the sprinkler head pressure is too low or the flow rate is abnormal, it may mean that the sprinkler head is clogged or there is a problem with the water supply. In this case, the monitoring unit will report this information to the central controller, and the system can immediately adjust the operation of other sprinkler heads or issue maintenance instructions to notify the user to check.

[0179] Furthermore, this invention can incorporate a solar power supply control system, which makes the entire intelligent irrigation system for landscaping more independent, environmentally friendly, and efficient. The solar power supply system converts solar energy into electrical energy, providing a continuous power supply to sensors, controllers, electric sprinklers, and other equipment, avoiding dependence on the traditional power grid. This makes it particularly suitable for applications in areas with unstable power supply or remote locations.

[0180] Furthermore, the solar power system is equipped with high-efficiency solar panels and an intelligent charging controller, which can automatically adjust the charging process according to the intensity of solar radiation and the battery's charge level, ensuring that the system's batteries are always in optimal charging condition. In addition, the system can intelligently adjust the power supply according to weather changes and sunshine conditions, ensuring that it charges via solar energy during the day and uses the battery's stored power to maintain equipment operation at night or on cloudy days.

[0181] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A smart irrigation method for landscaping, characterized in that, Includes the following steps: Collect environmental information; Soil moisture dynamic equations and plant growth models were constructed based on plant and environmental information. The soil moisture dynamic equation is as follows: Where θ(t) represents soil volumetric water content; ET(t) is the evapotranspiration rate at time t; P(t) is precipitation; I(t) is irrigation input flow rate; and t represents time. This indicates the rate of change of soil moisture content over time. The plant growth model is: G = Φ·PAR·f(W), where G represents the plant growth rate; Φ is the photosynthetic efficiency; PAR is the photosynthetically active radiation; and f(W) is a water regulation factor that describes the effect of soil water supply on plant growth. The nozzle opening time is calculated based on dynamic equations and growth models. The formula for calculating the nozzle opening time is: Among them, f stage P is the coefficient for plant growth stages. f For future precipitation, D s I represents the number of sprinklers per unit area, and Q represents the coverage area of ​​a single sprinkler head; I = Δθ·Z r ·ρ w Z r ρ represents the effective absorption depth of plant roots. w Let Δθ be the volume density of water, and θ = θ opt -θ(t), θ opt θ(t) represents the optimal soil moisture content for plant growth, and A represents the current soil moisture content. ET is calculated by the Penman-Monteith equation and reflects the amount of water lost through plant transpiration and environmental evaporation. The nozzle opening time is dynamically adjusted based on environmental information after the nozzle is turned on.

2. The intelligent irrigation method for landscaping according to claim 1, characterized in that, The environmental information includes soil temperature and humidity and environmental meteorological data, and the plant information includes plant height, leaf area and plant growth stage.

3. The intelligent irrigation method for landscaping according to claim 2, characterized in that, The soil moisture dynamic equation is used to calculate the changes in soil temperature and humidity over time, soil evapotranspiration loss, precipitation, and irrigation flow.

4. The intelligent irrigation method for landscaping according to claim 2, characterized in that, The calculation of the sprinkler opening time is derived from the plant's water requirement, soil temperature and humidity, environmental evapotranspiration, total irrigated area, future precipitation, and plant growth stage coefficient.

5. The intelligent irrigation method for landscaping according to claim 2, characterized in that, The dynamic adjustment is based on real-time monitoring data of soil temperature and humidity, meteorological information and plant growth status, and dynamically corrects the irrigation amount to maintain soil moisture.

6. A smart irrigation system for landscaping, based on a smart irrigation method for landscaping according to any one of claims 1-5, characterized in that, include: The data acquisition module is used to monitor soil temperature and humidity in real time and transmit the data to the central controller; The central controller receives real-time meteorological data and soil temperature and humidity data, analyzes and calculates irrigation needs, and sends irrigation instructions to the electric sprinklers. Electric nozzles; used to receive and execute instructions and adjust their own working status.

7. The intelligent irrigation system for landscaping according to claim 6, characterized in that, The acquisition module includes several soil temperature and humidity sensors, which are distributed in the green area to monitor the soil temperature and humidity in the green area in real time.

8. The intelligent irrigation system for landscaping according to claim 7, characterized in that, The central controller includes a weather forecast interface module for acquiring real-time meteorological data within the green area.

9. A smart irrigation controller for landscaping, based on the smart irrigation system for landscaping as described in any one of claims 6-8, characterized in that, The controller includes: The data receiving unit is used to receive data from the soil temperature and humidity sensor. The weather forecasting unit is used to acquire real-time meteorological data within the green area. The data processing unit is used to perform data filtering, anomaly detection, and analysis on soil temperature and humidity sensor data and real-time meteorological data within the green area; The optimal control calculation unit is used to calculate the optimal irrigation strategy based on the output data of the data processing unit, and to dynamically adjust the optimal irrigation strategy based on the feedback information of the electric sprinkler head. The wireless communication unit is used to send irrigation commands to the electric sprinkler head based on the optimal irrigation strategy and to receive feedback information.

10. A smart irrigation sprinkler head for landscaping, based on the smart irrigation system for landscaping as described in any one of claims 6-8, characterized in that, The nozzle is an electrically powered nozzle, comprising: Spraying components are used to dynamically adjust the spray flow rate and angle according to irrigation instructions; The actuator, including a solenoid valve, is used to adjust the opening time of the electric sprinkler head according to the irrigation command from the central controller; The monitoring unit is used to detect the water pressure and flow rate of the sprinkler head and feed the data back to the central controller.

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