Intelligent irrigation method and system for landscaping, controller and spray head

Abstract

The invention relates to the field of landscaping management automation, and discloses an intelligent irrigation method and system for landscaping, a controller and a sprayer. Constructing a soil moisture dynamic equation and a plant growth model according to the plant information and the environment information; based on the dynamic equation and the growth model, nozzle opening time is calculated; controlling the nozzle to open and close according to the opening time; and dynamically adjusting the opening time of the nozzle based on the environment information after the nozzle is opened. According to the invention, the soil moisture dynamic equation is constructed based on the soil humidity and weather change, and the nozzle opening time is calculated 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, water resource waste caused by fixed-period watering is effectively avoided, meanwhile, the accuracy and timeliness of water supply are ensured, the modern requirements for water saving and precise maintenance are met, and remarkable environmental and economic benefits are achieved.

Description

Technical Field

[0001] The present invention relates to the field of garden greening management automation, and in particular to a garden greening intelligent watering method, system, controller and sprinkler. Background Art

[0002] With the rapid development of smart cities, landscaping management is becoming increasingly intelligent. Traditional landscaping watering methods rely primarily on manual or timed irrigation. While these methods meet basic needs, with the increasing demand for water conservation and precise maintenance, they are no longer able to adapt to the efficiency and refinement required by modern landscaping management. Intelligent irrigation systems are becoming an integral part of modern landscaping management, aiming to reduce water waste while ensuring healthy plant growth through more precise data collection and control.

[0003] Currently, the most common automated irrigation systems on the market are those based on fixed time settings. These systems use a pre-set schedule to control irrigation cycles, ensuring consistent irrigation regardless of changing weather conditions. These systems offer a degree of automation, reducing manual operation and management costs.

[0004] However, existing automatic watering systems cannot respond to environmental changes in real time, particularly shifts in weather conditions and soil moisture. This prevents the system from flexibly adjusting watering volume and timing, leading to water waste. In severe weather or when soil moisture fluctuates significantly, the system may over- or under-water, impacting plant growth and health. Summary of the Invention

[0005] In response to the shortcomings of the existing technology, the present invention provides a method, system, controller and sprinkler for intelligent landscaping irrigation, which solves the problems that the existing timed automatic irrigation system cannot respond to environmental changes in real time, cannot flexibly adjust the watering amount and time, resulting in water resource waste and uneven plant growth.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: A landscaping intelligent watering method, comprising the following steps: Collect environmental information; Construct soil moisture dynamic equations and plant growth models based on plant and environmental information; Calculate the nozzle opening time based on the dynamic equation and growth model; Control the nozzle to switch on and off according to the opening time; Dynamically adjust the nozzle opening time based on the environmental information after the nozzle is turned on.

[0007] 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.

[0008] Preferably, the soil moisture dynamic equation is used to calculate the change of soil temperature and humidity over time, soil evapotranspiration loss, precipitation and watering flow.

[0009] The calculation of the nozzle opening time is obtained by the water demand of the plant, soil temperature and humidity, environmental evapotranspiration, the total area of the irrigation area, future precipitation and the plant growth stage coefficient.

[0010] Preferably, the dynamic adjustment is based on real-time monitoring data of soil temperature and humidity, meteorological information and plant growth status, and the irrigation amount is dynamically corrected to maintain soil moisture.

[0011] A landscaping intelligent watering system, comprising: Acquisition module, used to monitor soil temperature and humidity in real time and transmit 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 sprinkler; used to receive and execute instructions and adjust its own working status.

[0012] Preferably, the acquisition module includes a plurality of soil temperature and humidity sensors, which are distributed in the greening area and used to monitor the soil temperature and humidity in the greening area in real time.

[0013] Preferably, the central controller includes a weather forecast interface module for acquiring real-time meteorological data within the green area.

[0014] A landscaping intelligent irrigation controller, comprising: A data receiving unit, used for receiving data from soil temperature and humidity sensors; Weather forecast unit, used to obtain real-time meteorological data within the green area; A data processing unit for performing data filtering, anomaly detection, and analysis on soil temperature and humidity sensor data and real-time meteorological data within the greening area; An optimal control calculation unit, configured to calculate an optimal irrigation strategy based on output data from the data processing unit, and dynamically adjust the optimal irrigation strategy based on feedback information from the electric sprinkler; The wireless communication unit is used to send watering instructions to the electric sprinkler based on the optimal watering strategy and receive feedback information.

[0015] An intelligent landscaping watering nozzle, which uses an electric nozzle and includes: Spraying component, used to dynamically adjust spraying flow and angle according to watering instructions; An actuator, including a solenoid valve, is used to adjust the opening time of the electric sprinkler according to the watering instruction from the central controller; The monitoring unit is used to detect the water pressure and flow rate of the sprinkler nozzle and feed the data back to the central controller.

[0016] The present invention provides a landscaping intelligent irrigation method, system, controller and sprinkler, which have the following beneficial effects: 1. This invention achieves efficient and intelligent irrigation control by constructing a dynamic soil moisture equation based on soil moisture and weather changes. This dynamic equation and growth model are then used to calculate the nozzle opening time. Compared to existing timed automatic irrigation systems, this invention effectively avoids the water waste caused by fixed-cycle watering while ensuring the accuracy and timeliness of water supply. This meets the needs of modern water conservation and precision maintenance, and offers significant environmental and economic benefits.

[0017] 2. The soil temperature, humidity and environmental meteorological data of the present invention control the sprinkler nozzles to switch according to the opening time, so that the present invention can intelligently respond to climate changes and soil moisture fluctuations, avoid the negative effects of over-watering or under-watering on plant growth, ensure that plants grow healthily under optimal moisture conditions, and greatly improve irrigation efficiency and plant maintenance quality.

[0018] 3. The present invention dynamically adjusts the nozzle opening time based on environmental information after the nozzle is turned on, thereby achieving the purpose of intelligent feedback, real-time monitoring and evaluation of irrigation effects, and automatic adjustment of watering strategies. Unlike static control systems in the prior art, the present invention can continuously receive real-time data feedback, thereby ensuring that each irrigation achieves the optimal effect, further improving irrigation efficiency and healthy plant growth. This efficient feedback mechanism ensures the accuracy of irrigation operations, avoids uneven watering caused by human error or environmental changes, and reflects the high degree of intelligence and automation of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 Schematic diagram of the method flow of the present invention; Figure 2 Schematic diagram of the system architecture of the present invention; Figure 3 A schematic diagram of a controller of the present invention; Figure 4 Schematic diagram of the electric nozzle of the present invention. DETAILED DESCRIPTION

[0020] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the specification of the present invention. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0021] In order to better understand the present invention, the above contents are described in detail below in conjunction with specific embodiments.

[0022] Please see the attached Figure 1 The embodiment of the present invention provides a landscaping intelligent watering method, comprising the following steps: Collect environmental information; In this embodiment, collecting environmental information is a fundamental step in implementing an intelligent irrigation system. Real-time collection of environmental information provides the necessary data support for the subsequent calculation of soil moisture dynamic equations and the construction of plant growth models. This step is a crucial component of the entire intelligent irrigation method. By collecting environmental parameters such as soil temperature and humidity, and meteorological data, the system ensures that it can promptly and accurately reflect the current greening environment conditions and serve as a basis for adjusting irrigation strategies.

[0023] 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 area, with the collected data transmitted to a central controller in real time. Meteorological data, including parameters such as temperature, humidity, wind speed, air pressure, and precipitation, can be obtained through weather stations or weather service interfaces and provided to the system for further processing.

[0024] In one possible implementation, soil temperature and humidity sensors are deployed at various locations throughout the green space 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) are used to ensure accurate soil moisture monitoring. These sensors enable the system to detect changes in soil moisture and adjust irrigation strategies accordingly.

[0025] Alternatively, 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, and more. This data can help further predict weather changes in the coming hours or days, thereby optimizing irrigation decisions.

[0026] To ensure accurate and timely information collection, wireless transmission technology can be used to transmit collected soil temperature, humidity, and meteorological data to a central controller. Based on this real-time data, the central controller combines it with previously constructed soil moisture dynamics equations and plant growth models to calculate the appropriate irrigation timing and amount.

[0027] 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 temperature, relative humidity, and wind speed, thereby reflecting the plant's water needs. Through this dynamic calculation, the intelligent irrigation system can make more accurate irrigation decisions.

[0028] Typically, after collected environmental information is transmitted to a central controller via sensors, the system processes the data to eliminate noise and outliers, ensuring accuracy. These processing steps effectively ensure that the environmental data used is reliable and free of interference.

[0029] Alternatively, if future weather data predicts heavy rainfall, the system will adjust the irrigation schedule accordingly, reducing watering to avoid wasting water. This allows the system to dynamically adjust irrigation volume and timing based on external weather data and real-time soil moisture conditions in response to future weather changes, maximizing plant growth efficiency while conserving water resources.

[0030] Specifically, by collecting precise environmental information, the intelligent irrigation system can monitor changes in soil moisture in real time, respond promptly to plant water needs, and reduce errors during irrigation. For example, if sensors detect low soil moisture and the weather forecast indicates insufficient rainfall in the coming days, the system can increase irrigation to replenish soil moisture.

[0031] Therefore, by accurately collecting environmental information, the system can assess soil moisture conditions 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.

[0032] Construct soil moisture dynamic equations and plant growth models based on plant and environmental information; In this embodiment, soil moisture changes and their impact on plant growth are core elements of intelligent irrigation strategies. By combining plant and environmental information, constructing a soil moisture dynamic equation, and establishing a plant growth model, we can accurately predict soil moisture and formulate an optimal irrigation strategy accordingly. This step not only provides a scientific calculation basis but also improves irrigation accuracy and water resource utilization efficiency through quantitative analysis of plant needs.

[0033] Specifically, the soil moisture dynamic equation is used to describe the change of soil moisture content over time, mainly considering factors such as evapotranspiration loss, precipitation replenishment, and irrigation input. The equation can be expressed as follows: Where θ(t) represents the volumetric water content of the soil; ET(t) is the evapotranspiration rate at time t; P(t) is the precipitation; I(t) is the irrigation input flow; t represents time; It represents the rate of change of soil moisture content over time.

[0034] Specifically, the evapotranspiration rate ET(t) can be calculated using the Penman-Monteith model, which calculates the water evapotranspiration demand of plants based on meteorological parameters such as air temperature, humidity, wind speed, and solar radiation. The calculation formula is as follows: Where ET is the evapotranspiration rate, which represents the water released by plants through evaporation and transpiration; Δ is the slope of the saturated water vapor pressure curve, which is the effect of temperature on saturated vapor pressure; R n is the net radiation, which represents the radiation energy received by the ground minus the energy reflected by the ground; G is the soil heat flux, which represents the heat flow of the soil layer; γ is the humidity constant, which represents the relationship between water vapor and temperature in the air; T is the air temperature; u2 is the wind speed, which describes the wind speed, which has an impact on the evaporation of water; e s is the saturated water vapor pressure; e a is the actual water vapor pressure, the actual water vapor pressure in the air.

[0035] In one possible implementation, a plant growth model describes plant growth under varying water supply conditions and, combined with soil moisture dynamics equations, predicts plant water requirements. Plant growth can be characterized by parameters such as plant height and leaf area, and water requirements can be dynamically adjusted based on the growth stage.

[0036] In some embodiments, the plant growth model may use a photosynthesis-based growth kinetics model that comprehensively considers photosynthetically active radiation, carbon dioxide concentration, and water supply to predict plant growth rate. The basic expression 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 the water regulation factor, which describes the effect of soil water supply on plant growth.

[0037] In general, the soil moisture control factor f(W) depends on the relationship between soil moisture θ and plant water demand, and can be expressed using an exponential model or a piecewise linear model, for example: Among them, θ opt represents the optimal soil moisture content for plant growth; θ w is the water content at the plant's wilting point. This model is used to describe the impact of soil moisture on plant growth and provide a basis for subsequent irrigation strategies.

[0038] Alternatively, historical data can be incorporated into the soil moisture dynamics equation and plant growth model for model correction. For example, through long-term environmental monitoring and plant growth data accumulation, data-driven methods (such as machine learning) can be used to adjust model parameters and improve prediction accuracy.

[0039] In another implementation, the model's calculations can be dynamically adjusted based on real-time meteorological data. For example, during hot and dry weather, evapotranspiration rates increase significantly. In this case, the system can dynamically adjust the evapotranspiration parameters in the soil moisture equation based on environmental conditions, optimizing irrigation strategies.

[0040] Specifically, by constructing a soil moisture dynamics equation and a plant growth model, the system can dynamically monitor and predict soil moisture, ensuring that plants receive the required water for optimal growth. This model also provides theoretical support for intelligent irrigation systems, enabling them to make precise irrigation decisions based on environmental changes and plant needs.

[0041] Therefore, in the present invention, the mathematical model constructed based on environmental information and plant growth status can effectively improve the rationality and intelligence of the irrigation strategy, which can not only meet the growth needs of plants, but also optimize the utilization of water resources to the greatest extent, avoid excessive or insufficient irrigation, and realize accurate and efficient intelligent irrigation control.

[0042] Calculate the nozzle opening time based on the dynamic equation and growth model; In this invention, the nozzle opening time is a key control parameter of the intelligent irrigation system, directly affecting soil moisture content and plant growth. Combining soil moisture dynamic equations with plant growth models allows for scientific calculation of nozzle opening times to meet optimal plant water requirements. This allows for dynamic adjustment of irrigation strategies under varying environmental conditions, ensuring healthy plant growth while optimizing water resource utilization efficiency.

[0043] In this embodiment, the opening time of the nozzle is determined by the water demand of the plant, the moisture state of the soil, and the evaporation rate of the environment. First, the target soil moisture replenishment amount Δθ needs to be calculated to meet the current growth needs of the plant: Δθ = θ opt -θ(t); Among them, θ optrepresents the optimal soil moisture content for plant growth; θ(t) is the current soil moisture content.

[0044] Specifically, the irrigation amount I needs to satisfy the soil moisture content from θ(t) to the optimal soil moisture content for plant growth θ opt ,Right now: I=Δθ·Z r ·ρ w ; Among them, Z r is the effective absorption depth of plant roots; ρ w is the volume density of water. The total amount of water required to maintain optimal plant growth is calculated using this formula.

[0045] In one possible implementation, the opening time of the nozzle is T s It depends on the flow rate Q of the sprinkler and the irrigation volume I. The calculation formula is: In some embodiments, if there are multiple sprinklers in the irrigation area, the sprinkler density and coverage must be considered for correction. The calculation formula is as follows: Among them, D s It represents the number of nozzles per unit area; Q represents the coverage area of a single nozzle.

[0046] In general, the evapotranspiration rate (ET) must also be included in the calculation to compensate for water loss and ensure that the soil moisture is maintained at an appropriate level. The corrected sprinkler opening time is calculated as follows: Where A is the total area of the irrigation area; ET is calculated by the Penman-Monteith equation, reflecting the water loss due to plant transpiration and environmental evaporation.

[0047] In another implementation, if the weather forecast indicates that there will be precipitation in the near future, the sprinkler opening time can be adjusted to reduce over-irrigation. The correction formula is as follows: Among them, P f is the amount of precipitation in the future; this calculation method can avoid unnecessary waste of water resources.

[0048] Specifically, the soil moisture requirements of plants at different growth stages vary dynamically. For example, the seedling stage requires maintaining high soil moisture, while the mature stage may allow for a certain range of dryness and wetness fluctuations. Therefore, the nozzle opening time also needs to be adjusted according to the plant growth cycle, as expressed by: Among them, fstage It is the plant growth stage coefficient; set appropriate adjustment factors according to different stages to ensure that water supply matches growth needs.

[0049] Alternatively, the system can incorporate data from real-time soil moisture sensors to dynamically adjust sprinkler opening times. For example, if actual soil moisture is higher than expected, the sprinkler opening time can be shortened to achieve precise irrigation.

[0050] Therefore, in the present invention, the nozzle opening time calculation method based on the soil moisture dynamic equation and plant growth model can achieve scientific control of irrigation, avoid waste of water resources, and at the same time ensure that plants grow under suitable moisture conditions, thereby improving the intelligence level of the irrigation system.

[0051] Control the nozzle to switch on and off according to the opening time; In this embodiment, sprinkler on / off control is based on a calculated on / off time, ensuring that the irrigation process matches the plant's water needs. By combining soil moisture dynamics equations with plant growth models, the sprinkler's operating time can be rationally determined, and the sprinkler's on / off state can be dynamically adjusted based on environmental changes to ensure that soil moisture content remains within an appropriate range. Sprinkler on / off control must not only be controlled according to a predetermined timeframe but also require feedback adjustments based on real-time monitoring data to optimize water resource utilization efficiency.

[0052] Specifically, the sprinkler activation time is determined based on the time parameters calculated in the previous steps, combined with soil moisture conditions. First, the system determines how long the sprinkler should be on, using the aforementioned calculation method. The system activates the sprinkler when soil moisture falls below a set threshold. Once the sprinkler is on, the system continuously tracks moisture changes in the irrigation area and shuts off when the target moisture content is reached, preventing over-irrigation and water waste.

[0053] Specifically, the on / off switching of sprinklers is significantly affected by environmental factors, necessitating dynamic adjustments during the control process. For example, under high temperatures or strong winds, the evaporation rate is high, and the sprinkler on / off time may need to be extended to compensate for the additional water loss. Conversely, under low temperatures and high humidity, soil moisture evaporates more slowly, and the sprinkler on / off time can be shortened to prevent excess soil moisture. Furthermore, if precipitation is imminent, irrigation can be reduced or even skipped, optimizing water resource utilization.

[0054] In one possible implementation, sprinkler activation can be adjusted in real time based on soil moisture monitoring results. If, during sprinkler operation, soil moisture levels fail to increase as expected, perhaps due to low permeability or abnormal flow rates, the sprinkler activation time can be extended until irrigation demand is met. Conversely, if soil moisture levels are detected to be rapidly rising and approaching the set optimal value, the sprinkler can be shut off prematurely to prevent soil oversaturation.

[0055] In another implementation, 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, sprinkler activation times need to be shorter but more frequent to keep the surface soil moist. In mature stages, however, when the root system penetrates deeper into the soil, allowing for longer wet-dry cycles, sprinkler activation times can be extended and irrigation frequency reduced to accommodate plant physiological characteristics and improve water use efficiency.

[0056] Typically, sprinkler on / off control follows a set operating cycle, with fine-tuning within that cycle based on real-time environmental data. If environmental conditions suddenly change while a sprinkler is on, such as a sudden downpour or a surge in humidity, the sprinkler can automatically stop to accommodate the sudden change. In the event of persistent drought, the sprinkler's operating time can be increased to ensure adequate soil moisture.

[0057] Alternatively, sprinkler control can be adjusted in conjunction with remote monitoring. For example, by regularly analyzing historical data, sprinkler operation duration can be adjusted to suit different seasons and soil conditions. If long-term monitoring reveals that the soil in a particular area has low water retention, the sprinkler's operating time can be increased or the watering frequency can be increased to compensate for the water loss.

[0058] Therefore, in this invention, sprinkler on / off control is based on calculated irrigation times and optimized with environmental feedback to achieve precise irrigation. This method can adapt to different climate conditions, plant growth stages, and soil characteristics, ensuring that plants receive the appropriate amount of water while avoiding unnecessary water waste, thereby improving the intelligence and efficiency of irrigation.

[0059] Dynamically adjust the nozzle opening time based on the environmental information after the nozzle is turned on.

[0060] In this embodiment, the opening time of the sprinkler nozzle not only depends on the preset calculated value, but also needs to be dynamically adjusted in combination with the real-time environmental information after the sprinkler nozzle is turned on. Since external environmental factors (such as temperature, humidity, wind speed, precipitation, etc.) affect the soil moisture evaporation rate and plant water absorption efficiency, relying solely on the sprinkler nozzle opening time obtained by the initial calculation may lead to insufficient or excessive irrigation. By introducing an environmental feedback mechanism, the soil moisture, evaporation rate and meteorological changes are dynamically monitored during the operation of the sprinkler nozzle, and the opening time of the sprinkler nozzle is corrected in real time to ensure that the irrigation amount accurately matches the needs of the plants and optimizes the use of water resources to the greatest extent.

[0061] Specifically, after the sprinklers are turned on, the system collects real-time environmental data from soil moisture sensors, meteorological monitoring equipment, and flow meters, and dynamically adjusts the sprinkler operating time based on these trends. If soil moisture quickly reaches or exceeds the target value while the sprinklers are on, the sprinklers can be shut off prematurely to prevent excess moisture. If the system detects a rapid recovery of soil moisture due to factors such as high evaporation rates or high wind speeds, the system can appropriately extend the sprinkler operating time to compensate for moisture loss.

[0062] Specifically, the system evaluates whether current irrigation efficiency is meeting expectations by calculating the rate of change in soil moisture after the sprinklers are turned on. For example, if the increase in soil moisture falls below a set threshold within a certain time interval, this may indicate rapid water infiltration or excessive plant uptake. In this case, the system will appropriately extend the sprinkler's on time to ensure that the soil moisture content remains within the set range. Furthermore, if rainfall is detected within a short period of time, the sprinkler's on time can be shortened to avoid over-irrigation.

[0063] In one possible implementation, environmental feedback data from sprinkler activation can be used to adjust irrigation model parameters. For example, if a slow soil moisture recovery rate is detected during sprinkler operation, this may indicate poor soil water retention or leakage. In this case, the system can adjust the upper limit of the target soil moisture to ensure adequate water supply. Conversely, if a rapid recovery rate is detected and the soil moisture exceeds the set upper limit, the system can appropriately reduce the sprinkler's operating time to optimize water use.

[0064] In another implementation, the sprinkler's on-time can be adaptively adjusted based on short-term weather forecasts. For example, if the system detects a rapid rise in temperature and a drop in humidity shortly after a sprinkler is turned on, potentially leading to increased evaporation, the sprinkler's operating time can be appropriately extended to compensate for the additional water loss. Furthermore, if the sprinkler detects impending precipitation while operating, irrigation can be terminated immediately or the subsequent sprinkler on-time can be reduced to minimize water waste.

[0065] Typically, dynamic sprinkler adjustment strategies require integration with historical irrigation data to optimize control logic. For example, through long-term data analysis, a correlation model between environmental parameters and sprinkler activation times can be established, enabling the system to automatically adjust sprinkler operation strategies based on historical environmental trends. For example, in high-evaporation environments, the system might pre-set a longer activation time, while in low-evaporation environments, the sprinkler operating time might be reduced to improve irrigation efficiency.

[0066] Alternatively, the system can employ a self-learning algorithm to automatically optimize sprinkler operation strategies based on environmental changes after the sprinklers are activated. For example, a machine learning model based on historical soil moisture data can be used to predict moisture changes after a sprinkler is activated and dynamically adjust the activation time accordingly. This approach improves system adaptability, enabling precise control of sprinkler operation under varying environmental conditions.

[0067] In summary, the present invention dynamically adjusts the nozzle opening time based on environmental feedback from nozzle operation, enabling the irrigation system to achieve adaptive control under varying environmental conditions. By real-time monitoring of soil moisture, evapotranspiration rate, and meteorological factors, and optimizing control strategies based on historical data, this method can effectively improve irrigation accuracy, reduce water waste, ensure plant growth with optimal water supply, and enhance the overall intelligence of irrigation management.

[0068] Please see the attached Figure 2 The embodiment of the present invention provides a landscaping intelligent irrigation system, comprising: Acquisition module, used to monitor soil temperature and humidity in real time and transmit 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 sprinkler; used to receive and execute instructions and adjust its own working status.

[0069] In this embodiment, the system includes the following key components: a data collection module, a central controller, and electric sprinklers. These components work together to achieve intelligent management of the irrigation process, ensuring that plants receive the water they need and maximizing water resource utilization efficiency.

[0070] Acquisition module: The 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 within the area. These sensors can be resistive, frequency response, or capacitive, and can accurately measure soil moisture and temperature, transmitting this data in real time to the central controller. The acquisition module provides the central controller with a reliable soil data foundation, enabling it to analyze and calculate irrigation needs based on accurate environmental data.

[0071] Central controller: The central controller, the brain of the system, receives real-time soil temperature and humidity data from the acquisition module and analyzes it in conjunction with real-time meteorological data (such as temperature, humidity, wind speed, and precipitation) provided by external meteorological services. Using this collected data and meteorological information, the central controller applies advanced water dynamics and plant growth models to calculate the gap between current soil moisture levels and plant needs, thereby determining appropriate watering requirements. This calculation process may include forecasting future weather changes and optimizing soil moisture prediction models.

[0072] The central controller uses a pre-programmed algorithm to determine in real time whether the irrigation system needs to be activated. For example, if the system detects that soil moisture is below a preset threshold and the forecast shows no precipitation in the near future, the central controller sends an activation command to the electric sprinklers. If the calculation results indicate that the soil moisture meets the plant's needs, the system delays or stops watering. Furthermore, the central controller dynamically adjusts irrigation volume and frequency based on system requirements and environmental feedback, ensuring water conservation and meeting plant growth requirements.

[0073] Electric nozzle: After receiving the irrigation command from the central controller, the electric sprinkler adjusts its working state according to the signal. After receiving the start command, the electric sprinkler performs irrigation operations by adjusting parameters such as the spray volume, spraying pattern, or coverage of the spraying area. The working state of the electric sprinkler can be adjusted as needed, for example, by changing the flow rate of the sprinkler or controlling the spray angle to ensure uniform distribution of water in the irrigation area. The electric sprinkler can not only respond to the start command issued by the central controller, but also provide feedback on its own working status (such as whether the sprinkler is operating normally, whether the water flow is blocked, etc.), so that the central controller can monitor and adjust the system in real time.

[0074] Specifically, when the electric sprinkler receives instructions from the central controller, it begins irrigating at a predetermined flow rate and duration. During this process, the sprinkler can continue to operate until the predetermined soil moisture calculated by the central controller is reached, or automatically stop in response to feedback from other sensors (such as when the soil moisture reaches the set target). In the event of a system failure or other abnormal situation, the electric sprinkler can also notify the central controller through a feedback mechanism, thereby initiating a fault alarm or other emergency response measures.

[0075] Alternatively, the data acquisition module, central controller, and electric sprinklers can be connected via a wireless or wired network to ensure real-time and stable data transmission. All data is transmitted to the central controller via wireless communication, making the entire irrigation system highly flexible and remotely controllable. Managers can monitor the system's operating status through the remote platform and make manual adjustments as needed.

[0076] This system effectively and intelligently adjusts irrigation processes based on real-time environmental data, soil moisture, plant needs, and meteorological conditions. This not only optimizes water use but also ensures that plants grow in optimal moisture conditions. Furthermore, through integrated feedback mechanisms and dynamic adjustment capabilities, the system can adaptively adjust to external changes, enhancing the intelligence and stability of irrigation management.

[0077] As an alternative, consider a large park green space spread across several distinct zones, each equipped with several soil moisture sensors. Each sensor monitors the soil moisture in its area in real time, ensuring real-time and accurate data. Upon receiving data from the sensors, a central controller analyzes the soil moisture conditions in each zone and, based on the actual conditions, decides whether to irrigate or adjust the existing irrigation plan.

[0078] In this embodiment, the central controller performs intelligent analysis and decision-making by comprehensively considering soil moisture data for each zone, meteorological data (such as temperature, humidity, and precipitation), and future weather forecasts. For example, in certain zones, if sensor data indicates that soil moisture is below a set minimum moisture threshold and meteorological data predicts no rainfall in the near future, the central controller automatically calculates the additional irrigation requirements for that zone. This calculation takes into account current soil moisture, soil water-holding capacity, and future weather conditions to ensure precise water supply.

[0079] Based on the calculations, the central controller instructs the electric sprinklers in the relevant zones to extend watering time or increase water flow to ensure soil moisture reaches the level required for optimal plant growth. For example, if soil moisture in a particular zone falls 20% below the target, the central controller will increase watering time or increase sprinkler flow to compensate. The extended watering time can be dynamically adjusted based on the sprinkler flow rate and spraying range to ensure even water penetration into the soil and meet plant needs.

[0080] Conversely, if rain is predicted, even if soil moisture in some areas is low, the central controller will make appropriate adjustments based on the weather forecast. For example, if the weather forecast indicates impending precipitation, the system will reduce or cancel irrigation plans for certain areas to avoid over-irrigation. The central controller will adjust the irrigation plan based on the predicted precipitation, potentially reducing the original irrigation amount or completely eliminating irrigation for certain areas. In this way, through appropriate adjustments, the system can avoid water waste and ensure that the soil is not over-wetted.

[0081] During implementation, the system also monitors soil moisture changes in each zone in real time and dynamically adjusts irrigation strategies. If soil moisture in a particular area fails to reach the expected level within a short period of time after irrigation, or if the precipitation forecast changes, the central controller will issue instructions based on real-time data to adjust the irrigation strategy. For example, if precipitation is less than expected, the sprinkler operating time may be extended as needed; if precipitation is greater than expected, irrigation will be further reduced.

[0082] Specifically, soil moisture sensors in each plot transmit data via wireless or wired networks to a central controller, which generates irrigation instructions based on the analysis results. These instructions are then transmitted in real time to the electric sprinklers in the corresponding plot via wireless networks or other communication methods. Upon receiving the instructions, the electric sprinklers automatically adjust their on / off function, flow rate, and spraying time based on the system's requirements, ensuring optimal irrigation results for each plot.

[0083] Furthermore, to ensure irrigation effectiveness in each area, the system regularly conducts data analysis and self-optimization. Through long-term data accumulation, the system can more accurately predict irrigation needs in different seasons and weather conditions and automatically adjust irrigation strategies for each area. Through the central control system's visual interface, managers can view soil moisture conditions and irrigation effectiveness in each area in real time, and intervene manually when necessary to further optimize irrigation plans.

[0084] In this embodiment, the system achieves precise irrigation control by combining real-time soil moisture data, meteorological information, and plant needs. The system dynamically adjusts the irrigation strategy for each zone based on environmental changes, avoiding over-irrigation and 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. It has broad application prospects, particularly in large green spaces, parks, and farmland.

[0085] In this embodiment, the system also accesses comprehensive regional meteorological data by connecting to authoritative meteorological data service platforms, such as the China Meteorological Administration's meteorological data interface. Through this platform, the system can obtain timely, 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 data sources, ensuring that the central controller can make precise decisions based on high-quality input when processing meteorological data.

[0086] In addition, to better respond to local microclimate variations, the system also installs small weather stations around irrigation areas. These stations can supplement the collection of local meteorological data, specifically 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 dynamic changes in the local climate in real time, such as humidity, temperature variations, and wind speed.

[0087] Small weather stations are equipped with high-precision sensors, including rain sensors, temperature sensors, humidity sensors, and wind speed sensors, enabling continuous monitoring and real-time collection of meteorological data. Rain sensors can be used to monitor short-term precipitation, while temperature and humidity sensors can accurately detect changes in air temperature and humidity. Wind speed sensors help understand the impact of wind on evaporation rates. This data is collected and transmitted to a central controller via wireless communication technology, providing the system with real-time meteorological information.

[0088] Data transmission and processing: For data transmission, this system uses wireless communication technologies such as 4G and NB-IoT to ensure real-time transmission of meteorological data from weather stations to the central controller. The application of wireless communication technologies makes data transmission more convenient and efficient while also avoiding the challenges of long-distance cabling. 4G technology offers faster data transmission rates, making it suitable for frequent data updates and large-scale data transmission. NB-IoT, on the other hand, is suitable for long-distance, low-power, and continuous monitoring scenarios, ensuring stable data transmission over a wider area.

[0089] To ensure data security during transmission, all transmitted data is encrypted. This encryption technology prevents data leakage or tampering during transmission, ensuring the confidentiality and integrity of meteorological data. This encryption effectively prevents unauthorized individuals from disrupting 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 weather data.

[0090] Data reception and processing: The central controller receives data from the weather service platform and small weather stations and performs real-time analysis and preprocessing. During preprocessing, the system cleans the data, removing abnormal data and noise to ensure accurate analysis. For example, if erroneous data due to equipment failure or communication problems is detected, the system will mark it as an outlier and remove it.

[0091] Based on time series analysis, the central controller also performs trend analysis on meteorological data. By analyzing data trends over a period of time, the system can predict trends such as rainfall, temperature, and humidity over the next few hours or days. For example, if heavy rainfall is predicted within the next few hours, the system will adjust the irrigation schedule based on the expected precipitation to avoid over-irrigation. If the weather forecast indicates an impending drought, the system will increase irrigation accordingly.

[0092] Comprehensive management and optimization: Through this integrated approach to meteorological data collection and processing, the automatic watering system can dynamically adjust watering strategies based on real-time meteorological data. The timely transmission and real-time processing of data enable the system to adjust watering plans based on accurate weather forecasts and real-time data, optimizing water resource utilization, avoiding overwatering or water shortages, and ensuring consistent healthy plant growth under varying climate conditions.

[0093] The system can also pre-calculate and adjust future irrigation needs based on meteorological data. For example, if heavy rainfall is forecast over the next two days, the system will proactively reduce irrigation to avoid unnecessary water waste. Conversely, if the forecast indicates a prolonged drought, the system will proactively increase irrigation to meet plant water needs based on historical data and plant water requirement models.

[0094] In summary, by connecting to an authoritative meteorological service platform and combining local data collection from small meteorological stations, coupled 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 an intelligent, precise, and efficient irrigation process.

[0095] Please see the attached Figure 3The embodiment of the present invention provides a landscaping intelligent irrigation controller, the controller comprising: A data receiving unit, used for receiving data from soil temperature and humidity sensors; Weather forecast unit, used to obtain real-time meteorological data within the green area; A data processing unit for performing data filtering, anomaly detection, and analysis on soil temperature and humidity sensor data and real-time meteorological data within the greening area; An optimal control calculation unit, configured to calculate an optimal irrigation strategy based on output data from the data processing unit, and dynamically adjust the optimal irrigation strategy based on feedback information from the electric sprinkler; The wireless communication unit is used to send watering instructions to the electric sprinkler based on the optimal watering strategy and receive feedback information.

[0096] In this embodiment, the controller includes the following key functional units: a data receiving unit, a weather forecast unit, a data processing unit, an optimal control calculation unit, and a wireless communication unit. The collaboration of these units enables the entire system to dynamically adjust irrigation plans based on real-time data and feedback, ensuring the precise supply of water required by plants.

[0097] Data receiving unit: The data receiving unit is responsible for receiving data from soil temperature and humidity sensors within the landscaping area. Soil moisture sensors monitor soil moisture changes in real time, providing essential data for irrigation decisions. Temperature sensors monitor soil temperature and further assess changes in evapotranspiration rates. The core task of the data receiving unit is to ensure the accuracy and real-time nature of sensor data and transmit it to the subsequent processing unit for analysis.

[0098] Weather Forecast Unit: The weather forecast unit acquires real-time meteorological data within the green area, including temperature, humidity, wind speed, precipitation, and air pressure. This information is crucial for irrigation decision-making, as it helps the central controller predict weather changes over the next few hours or days and dynamically adjust irrigation strategies. To obtain real-time meteorological data, the weather forecast unit can access public meteorological service platforms, such as those provided by the China Meteorological Administration, or supplement local data with small weather stations located around the park.

[0099] Data processing unit: The data processing unit receives data from the soil temperature and humidity sensor and the weather forecast unit, and performs data filtering, anomaly detection and analysis. The data filtering step is used to remove noise and inaccurate data from the sensor and meteorological data to ensure that subsequent calculations are based on real and high-quality data. Anomaly detection uses algorithms to identify outliers (such as errors caused by equipment failure or environmental interference) and eliminates them to ensure the stability of the calculation. The analysis step conducts in-depth analysis of the processed data to identify the gap between current soil moisture and plant needs, and evaluate the impact of future meteorological conditions on irrigation strategies.

[0100] Optimal control calculation unit: The optimal control calculation unit is responsible for calculating the optimal watering strategy based on the filtered and anomaly-detected data output by the data processing unit. This strategy takes into account 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 watering time and amount for each area to ensure that plants can grow under optimal water conditions. The optimal control calculation unit also dynamically adjusts the watering strategy based on feedback information from the electric sprinklers. For example, if the sprinkler detects an abnormal water flow or the soil moisture fails to meet the set standard, the system will recalculate the watering amount or time to ensure that the irrigation target is achieved.

[0101] Wireless communication unit: The wireless communication unit sends watering instructions to the electric sprinklers based on the optimal watering strategy and receives feedback 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. Using these instructions, the controller can precisely control the opening and closing of each sprinkler, as well as flow rate adjustment. Feedback information includes sprinkler operating status, water flow, soil moisture, and other information, helping the controller understand irrigation effectiveness and adjust its strategy in real time.

[0102] For example, during the irrigation process, if the soil moisture received by the system from the sprinkler is still low, the controller will extend the irrigation time or increase the water flow rate based on the feedback information until the set target is reached.

[0103] Please see the attached Figure 4 The embodiment of the present invention provides a smart garden irrigation nozzle, which uses an electric nozzle and includes: Spraying component, used to dynamically adjust spraying flow and angle according to watering instructions; An actuator, including a solenoid valve, is used to adjust the opening time of the electric sprinkler according to the watering instruction from the central controller; The monitoring unit is used to detect the water pressure and flow rate of the sprinkler nozzle and feed the data back to the central controller.

[0104] In this embodiment, the spray angle adjustment function can be flexibly set to meet the needs of different garden areas, adapting to complex terrain and plant arrangements. By dynamically adjusting the spray angle and water flow rate, the sprinkler can achieve precise localized irrigation, avoiding excessive water distribution to areas that do not need irrigation, thereby improving irrigation efficiency and accuracy.

[0105] Actuator: The actuator primarily consists of a solenoid valve and an electric control unit. The solenoid valve precisely adjusts the opening and closing times of the electric sprinklers based on irrigation commands from the central controller. The solenoid valve rapidly responds to changes in control signals, accurately turning the water flow on and off. Through precise electromagnetic control, the actuator delivers efficient and reliable irrigation within the set timeframe.

[0106] The electric control unit works in conjunction with the solenoid valve to ensure real-time execution of irrigation instructions. The controller dynamically adjusts the timing and duration of each spraying event based on current soil moisture, weather forecast, and other data. For example, if soil moisture is too low, the controller will extend the activation time of the electric sprinkler; if moisture is appropriate, the activation time will be shortened accordingly.

[0107] Monitoring unit: The monitoring unit, comprised of pressure and flow sensors, monitors the pressure and flow of water flowing out of the sprinklers in real time and transmits this data back to the central controller. By monitoring sprinkler pressure and flow in real time, the system can identify potential anomalies, such as blockage or malfunction. This feedback data provides the central controller with a real-time assessment of irrigation effectiveness, helping it determine whether irrigation is meeting expectations and make necessary adjustments.

[0108] For example, if the system detects low pressure or abnormal flow at a sprinkler head, it could indicate a blockage or water supply problem. The monitoring unit then feeds this information back to the central controller, allowing the system to immediately adjust the operation of other sprinklers or issue maintenance instructions to notify the user for inspection.

[0109] The present invention also incorporates a solar power control system, making the entire landscaping intelligent irrigation system more independent, environmentally friendly, and efficient. By converting solar energy into electricity, the solar power system provides a continuous power supply for sensors, controllers, electric sprinklers, and other equipment, eliminating reliance on the traditional power grid. This makes it particularly suitable for applications in remote areas with unstable power supplies.

[0110] The solar power system is equipped with efficient solar panels and an intelligent charge controller that automatically adjusts the charging process based on solar radiation intensity and battery charge status, ensuring the system's batteries are always optimally charged. Furthermore, the system intelligently adjusts power supply based on weather changes and sunshine conditions, ensuring solar charging during the day and battery power reserves to maintain equipment operation at night or on cloudy days.

[0111] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A landscaping intelligent watering method, characterized in that: The following steps are involved: Collect environmental information; Construct soil moisture dynamic equations and plant growth models based on plant and environmental information; Calculate the nozzle opening time based on the dynamic equation and growth model; Control the nozzle to switch on and off according to the opening time; Dynamically adjust the nozzle opening time based on the environmental information after the nozzle is turned on.

2. A landscaping intelligent watering method 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. A landscaping intelligent watering method 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 watering flow.

4. A landscaping intelligent watering method according to claim 2, characterized in that: The calculation of the nozzle opening time is obtained by the water demand of the plant, soil temperature and humidity, environmental evapotranspiration, the total area of the irrigation area, future precipitation and the plant growth stage coefficient.

5. The intelligent landscaping watering method 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 landscaping intelligent watering system, based on a landscaping intelligent watering method according to any one of claims 1 to 5, characterized in that: include: Acquisition module, used to monitor soil temperature and humidity in real time and transmit 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 sprinkler; used to receive and execute instructions and adjust its own working status.

7. The intelligent landscaping irrigation system according to claim 6, characterized in that: The acquisition module includes a plurality of soil temperature and humidity sensors, which are distributed in the greening area and used to monitor the soil temperature and humidity in the greening area in real time.

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

9. A garden greening intelligent irrigation controller, based on a garden greening intelligent irrigation system according to any one of claims 6 to 8, characterized in that: The controller includes: A data receiving unit, used for receiving data from soil temperature and humidity sensors; Weather forecast unit, used to obtain real-time meteorological data within the green area; A data processing unit for performing data filtering, anomaly detection, and analysis on soil temperature and humidity sensor data and real-time meteorological data within the greening area; An optimal control calculation unit, configured to calculate an optimal irrigation strategy based on output data from the data processing unit, and dynamically adjust the optimal irrigation strategy based on feedback information from the electric sprinkler; The wireless communication unit is used to send watering instructions to the electric sprinkler based on the optimal watering strategy and receive feedback information.

10. A garden greening intelligent irrigation nozzle, based on a garden greening intelligent irrigation system according to any one of claims 6 to 8, characterized in that: The spray nozzle uses an electric spray nozzle, including: Spraying component, used to dynamically adjust spraying flow and angle according to watering instructions; An actuator, including a solenoid valve, is used to adjust the opening time of the electric sprinkler according to the watering instruction from the central controller; The monitoring unit is used to detect the water pressure and flow rate of the sprinkler nozzle and feed the data back to the central controller.

Images