Intelligent irrigation management system for landscape architecture

Abstract

The invention belongs to the technical field of garden irrigation, and particularly discloses a garden landscape intelligent irrigation management system which comprises a sensing layer, a transmission layer, a platform layer and an execution layer. The sensing layer is used for collecting garden environment and plant related data; the transmission layer is used for transmitting the data acquired by the sensing layer to the platform layer; the platform layer is used for realizing data visualization, intelligent decision generation and equipment control; the execution layer executes irrigation operation according to an instruction of the platform layer; according to the system, through accurate monitoring and intelligent control, water resource waste and irrigation cost are effectively reduced. Manual inspection and operation workloads are reduced through automatic operation, one administrator can manage thousands of mu of gardens, and the management efficiency is improved. The risk of plant diseases and insect pests can be reduced through on-demand irrigation, and the stability and attractiveness of the garden landscape effect are kept. The environment, irrigation and plant growth data accumulated by the system provides a scientific decision basis for garden maintenance, and is convenient for long-term planning and management strategy optimization.

Description

Technical Field

[0001] This invention relates to the field of garden irrigation technology, specifically to a smart irrigation management system for garden landscapes. Background Technology

[0002] Traditional garden irrigation often relies on manual control or timed irrigation methods, resulting in significant water waste, low irrigation efficiency, and an inability to precisely irrigate according to the actual environment and plant water requirements. With the continuous expansion of garden landscapes and the increasing demands for water and energy conservation, there is an urgent need for a management system capable of real-time monitoring of environmental and plant conditions and achieving automated, precise irrigation. Currently, some existing irrigation systems are insufficient in terms of the comprehensiveness of data collection, the intelligence of decision-making, and system compatibility, making it difficult to meet the diverse and refined irrigation needs of modern gardens. Summary of the Invention

[0003] The purpose of this invention is to provide a smart irrigation management system for garden landscapes. By integrating multi-source data acquisition, intelligent decision-making, and automated control technologies, it achieves precise, intelligent, and efficient garden irrigation, solving problems such as water waste and low management efficiency in traditional irrigation methods.

[0004] To achieve the above objectives, the present invention provides the following technical solution: a smart irrigation management system for garden landscapes, comprising a perception layer, a transmission layer, a platform layer, and an execution layer.

[0005] The sensing layer is used to collect data related to the garden environment and plants.

[0006] The transmission layer is used to transmit the data collected by the perception layer to the platform layer.

[0007] The platform layer is used to realize data visualization, intelligent decision generation, and equipment control.

[0008] The execution layer performs irrigation operations according to the instructions of the platform layer.

[0009] In a preferred embodiment of the present invention, the sensing layer includes a soil moisture sensor, an environmental weather station, and a plant physiological sensor; the soil moisture sensor is deployed in the soil of various areas of the garden to monitor soil moisture, temperature, pH value, and nutrient content in real time; the environmental weather station is installed in open areas of the garden to collect environmental data such as light intensity, air temperature and humidity, wind speed, and rainfall; and the plant physiological sensor is installed on specific plants to monitor physiological indicators such as stem flow and leaf water potential.

[0010] As a preferred embodiment of the present invention, the transmission layer adopts a combination of wireless and wired communication; for large-area garden scenarios, LoRa / NB-IoT technology is used for low-power, long-distance wireless data transmission; in areas with good network signals and high transmission speed requirements, 4G or 5G wireless communication is used; for short-distance transmission within the park with high stability requirements, fiber optic or RS485 bus wired communication is used.

[0011] In a preferred embodiment of the present invention, the platform layer includes a cloud platform management system and edge computing nodes; the cloud platform management system has a data visualization module, an intelligent decision engine module, and a remote control module; the data visualization module displays real-time monitoring data, irrigation history records, and equipment status through a web interface or mobile APP; the intelligent decision engine module generates irrigation plans based on a rule engine or AI algorithm; the remote control module supports manual or automatic mode switching to perform timed and zoned control of irrigation equipment in the execution layer; and the edge computing nodes perform localized preliminary processing of the data collected by the perception layer to reduce cloud computing pressure and data transmission latency.

[0012] As a preferred embodiment of the present invention, the execution layer includes intelligent valves, sprinklers, and an integrated water and fertilizer device; the intelligent valves are installed in the irrigation network to realize the on / off control of different irrigation areas; the sprinklers are selected according to the type and layout of garden plants, such as rotating sprinklers and drip irrigation tapes; the integrated water and fertilizer device automatically mixes fertilizers according to the soil nutrient data analyzed by the platform layer and applies fertilizers synchronously through the irrigation system.

[0013] As a preferred embodiment of the present invention, the rule engine of the intelligent decision engine module includes a soil moisture threshold setting unit, a threshold triggering unit, and a time constraint unit.

[0014] The soil moisture threshold setting unit is used to set different soil moisture threshold ranges for different plant types and growth stages.

[0015] The threshold triggering unit generates an irrigation start command when the real-time monitored soil moisture value is lower than the lower limit of the threshold range; and generates an irrigation stop command when the upper limit of the threshold range is reached.

[0016] The time constraint unit is used to set the time window for irrigation execution, avoiding irrigation during high-temperature periods or when the probability of rainfall exceeds a preset value.

[0017] As a preferred embodiment of the present invention, the AI ​​algorithm of the intelligent decision engine module includes a historical data training unit, an environmental parameter fusion unit, and a dynamic adjustment unit.

[0018] Historical data training unit: LSTM time series prediction model is built based on at least 12 months of historical irrigation data, meteorological data and plant growth data.

[0019] The environmental parameter fusion unit takes real-time soil moisture, meteorological data, and plant physiological indicators as input features, and outputs the predicted water demand for the next 72 hours through the prediction model.

[0020] The dynamic adjustment unit updates the model parameters quarterly based on the deviation between the actual irrigation effect and the predicted value, thereby improving the prediction accuracy.

[0021] As a preferred embodiment of the present invention, the cloud platform management system of the platform layer further includes an anomaly monitoring module, a multi-level alarm module, and a data analysis module.

[0022] The anomaly monitoring module identifies faults such as water leakage, power failure, and sensor drift by comparing sensor data with preset thresholds.

[0023] The multi-level alarm module sends three levels of alarm information—SMS, APP push, and email—for different fault types, and includes a heat map of the fault location and a link to the maintenance manual.

[0024] The data analysis module generates monthly water usage reports, equipment failure rate reports, and plant growth trend analysis reports based on historical irrigation data.

[0025] As a preferred embodiment of the present invention, the intelligent valve configuration of the execution layer adopts a pulse-powered solenoid valve. The solenoid valve is powered by DC24V pulse and has a flow regulation function. It achieves a flow regulation accuracy of 0-100% through PWM control signal. The execution layer also includes a valve status feedback unit, which uploads valve opening and closing position and water flow pressure data to the platform layer in real time.

[0026] As a preferred embodiment of the present invention, the intelligent decision engine module of the cloud platform management system combines weather forecast data collected by the environmental meteorological station, specifically including a precipitation probability analysis unit, an evapotranspiration calculation unit, and an extreme weather response unit.

[0027] The precipitation probability analysis unit automatically suspends the irrigation plan when the probability of precipitation in the next 24 hours exceeds 60%.

[0028] The evapotranspiration calculation unit calculates the reference crop evapotranspiration based on the Penman-Monteith formula and adjusts the irrigation amount in conjunction with the crop coefficient Kc.

[0029] The extreme weather response unit automatically shuts down all outdoor irrigation equipment and enters flood prevention mode when typhoon or rainstorm warnings are issued.

[0030] Compared with the prior art, the beneficial effects of the present invention are:

[0031] This system effectively reduces water waste and irrigation costs through precise monitoring and intelligent control. Automated operation reduces the workload of manual inspections and operations, allowing one administrator to manage thousands of acres of gardens, thus improving management efficiency. On-demand irrigation reduces the risk of plant diseases and pests, maintaining the stability and aesthetics of the garden landscape. The environmental, irrigation, and plant growth data accumulated by the system provide a scientific basis for garden maintenance decisions, facilitating long-term planning and optimization of management strategies. Attached Figure Description

[0032] Figure 1 This is a schematic diagram of the system of the present invention. Detailed Implementation

[0033] The technical solutions of 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.

[0034] Please see Figure 1 The present invention provides a technical solution: a smart irrigation management system for garden landscapes, comprising a perception layer, a transmission layer, a platform layer and an execution layer.

[0035] The sensing layer is used to collect data related to the garden environment and plants.

[0036] The sensing layer includes a soil moisture sensor, an environmental weather station, and a plant physiological sensor. The soil moisture sensor is deployed in the soil of various areas of the garden to monitor soil moisture, temperature, pH value, and nutrient content in real time. The environmental weather station is installed in open areas of the garden to collect environmental data such as light intensity, air temperature and humidity, wind speed, and rainfall. The plant physiological sensor is installed on specific plants to monitor physiological indicators such as stem flow and leaf water potential.

[0037] The transmission layer is used to transmit the data collected by the perception layer to the platform layer.

[0038] The transmission layer employs a combination of wireless and wired communication. For large-area garden scenarios, LoRa / NB-IoT technology is used for low-power, long-distance wireless data transmission. In areas with good network signals and high transmission speed requirements, 4G or 5G wireless communication is used. For short-distance transmission within the park with high stability requirements, fiber optic or RS485 bus wired communication is used.

[0039] The platform layer is the core control part of the system, used to realize data visualization, intelligent decision generation and equipment control.

[0040] The platform layer includes a cloud platform management system and edge computing nodes. The cloud platform management system has a data visualization module, an intelligent decision engine module, and a remote control module. The data visualization module displays real-time monitoring data, irrigation history records, and equipment status through a web interface or mobile APP. The intelligent decision engine module generates irrigation plans based on a rule engine or AI algorithm. The remote control module supports manual or automatic mode switching and performs timed and zoned control of irrigation equipment in the execution layer. The edge computing nodes perform localized preliminary processing on the data collected by the perception layer to reduce cloud computing pressure and data transmission latency.

[0041] The rule engine of the intelligent decision engine module includes a soil moisture threshold setting unit, a threshold triggering unit, and a time constraint unit.

[0042] The soil moisture threshold setting unit is used to set different soil moisture threshold ranges for different plant types and growth stages.

[0043] The threshold triggering unit generates an irrigation start command when the real-time monitored soil moisture value is lower than the lower limit of the threshold range; and generates an irrigation stop command when the upper limit of the threshold range is reached.

[0044] The time constraint unit is used to set the time window for irrigation execution, avoiding irrigation during high-temperature periods or when the probability of rainfall exceeds a preset value.

[0045] The AI ​​algorithm of the intelligent decision engine module includes a historical data training unit, an environmental parameter fusion unit, and a dynamic adjustment unit.

[0046] Historical data training unit: LSTM time series prediction model is built based on at least 12 months of historical irrigation data, meteorological data and plant growth data.

[0047] The environmental parameter fusion unit takes real-time soil moisture, meteorological data, and plant physiological indicators as input features, and outputs the predicted water demand for the next 72 hours through the prediction model.

[0048] The dynamic adjustment unit updates the model parameters quarterly based on the deviation between the actual irrigation effect and the predicted value, thereby improving the prediction accuracy.

[0049] The cloud platform management system of the platform layer also includes an anomaly monitoring module, a multi-level alarm module, and a data analysis module.

[0050] The anomaly monitoring module identifies faults such as water leakage, power failure, and sensor drift by comparing sensor data with preset thresholds.

[0051] The multi-level alarm module sends three levels of alarm information—SMS, APP push, and email—for different fault types, and includes a heat map of the fault location and a link to the maintenance manual.

[0052] The data analysis module generates monthly water usage reports, equipment failure rate reports, and plant growth trend analysis reports based on historical irrigation data.

[0053] The intelligent decision engine module of the cloud platform management system combines weather forecast data collected by the environmental meteorological station and specifically includes a precipitation probability analysis unit, an evapotranspiration calculation unit, and an extreme weather response unit.

[0054] The precipitation probability analysis unit automatically suspends the irrigation plan when the probability of precipitation in the next 24 hours exceeds 60%.

[0055] The evapotranspiration calculation unit calculates the reference crop evapotranspiration based on the Penman-Monteith formula and adjusts the irrigation amount in conjunction with the crop coefficient Kc.

[0056] The extreme weather response unit automatically shuts down all outdoor irrigation equipment and enters flood prevention mode when typhoon or rainstorm warnings are issued.

[0057] The execution layer performs irrigation operations according to the instructions of the platform layer.

[0058] The execution layer includes intelligent valves, sprinklers, and an integrated water and fertilizer device; the intelligent valves are installed in the irrigation network to realize the on / off control of different irrigation areas; the sprinklers are selected according to the type and layout of garden plants, such as rotating sprinklers and drip irrigation tapes; the integrated water and fertilizer device automatically mixes fertilizers according to the soil nutrient data analyzed by the platform layer and applies fertilizers synchronously through the irrigation system.

[0059] The intelligent valve configuration of the execution layer adopts a pulse-powered solenoid valve. The solenoid valve is powered by DC24V pulse and has a flow regulation function. It achieves a flow regulation accuracy of 0-100% through PWM control signal. The execution layer also includes a valve status feedback unit, which uploads valve opening and closing position and water flow pressure data to the platform layer in real time.

[0060] In summary, various sensors in the perception layer collect data at preset frequencies; for example, the soil moisture sensor collects data every 10 minutes. The collected data is then sent to the platform layer via the transmission layer. Edge computing nodes in the platform layer perform preliminary data processing before uploading it to the cloud platform management system. The cloud platform management system compares and analyzes real-time data with historical data and plant growth models. If soil moisture falls below a set threshold (e.g., 40%), or if weather forecasts predict no future rainfall and the plants require water, the intelligent decision engine generates an irrigation command, which is sent to the execution layer via the remote control module. The execution layer's intelligent valves open, and the sprinklers irrigate according to the set mode. Simultaneously, if soil nutrients are insufficient, the integrated water and fertilizer device automatically initiates fertilization. During irrigation, the system continuously monitors data, shutting down the irrigation equipment when soil moisture reaches the set upper limit or the irrigation plan is completed. Administrators can monitor the equipment's operating status in real time through the cloud platform management system's web interface or mobile app, receive alarms for leaks, power outages, sensor malfunctions, etc., and query historical data for irrigation effect analysis.

[0061] System Deployment: Based on the actual layout of the garden and the distribution of plants, soil moisture sensors, environmental weather stations, and plant physiological sensors are reasonably installed in different areas; irrigation pipelines are laid, and smart valves and sprinklers are installed; edge computing nodes and communication equipment are deployed to ensure stable data transmission; a cloud platform management system server is built, and the system software is installed and configured.

[0062] Parameter settings: In the cloud platform management system, set parameters such as soil moisture threshold, irrigation time, and fertilizer ratio according to different plant types and growth stages; configure sensor acquisition frequency and data transmission rules.

[0063] Operation and monitoring: After the system is put into operation, the administrator can view the monitoring data and equipment status in real time through the web interface or mobile APP; when the system triggers irrigation commands or issues abnormal alarms, timely handling and maintenance are carried out; the system data is analyzed regularly to optimize irrigation strategies and equipment operating parameters.

[0064] It is worth noting that the entire device is controlled by a master control button. Since the device matched with the control button is a common device and belongs to existing mature technology, its electrical connection relationship and specific circuit structure will not be described in detail here.

[0065] 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 management system for garden landscapes, characterized in that: It includes the perception layer, transmission layer, platform layer, and execution layer; The sensing layer is used to collect data related to the garden environment and plants; The transmission layer is used to transmit the data collected by the perception layer to the platform layer; The platform layer is used to realize data visualization, intelligent decision generation, and equipment control; The execution layer performs irrigation operations according to the instructions of the platform layer.

2. The intelligent irrigation management system for garden landscapes according to claim 1, characterized in that: The sensing layer includes a soil moisture sensor, an environmental weather station, and a plant physiological sensor. The soil moisture sensors are deployed in the soil of various areas of the garden to monitor soil moisture, temperature, pH value and nutrient content in real time. The environmental meteorological station is installed in an open area of ​​the garden and is used to collect environmental data such as light intensity, air temperature and humidity, wind speed, and rainfall. The plant physiological sensor is installed on a specific plant to monitor physiological indicators such as stem flow and leaf water potential.

3. The intelligent irrigation management system for garden landscapes according to claim 1, characterized in that: The transmission layer employs a combination of wireless and wired communication. For large-area garden scenarios, LoRa / NB-IoT technology is used for low-power, long-distance wireless data transmission. In areas with good network signals and high transmission speed requirements, 4G or 5G wireless communication is used. For short-distance transmission within the park with high stability requirements, fiber optic or RS485 bus wired communication is used.

4. The intelligent irrigation management system for garden landscapes according to claim 1, characterized in that: The platform layer includes a cloud platform management system and edge computing nodes; The cloud platform management system has a data visualization module, an intelligent decision engine module, and a remote control module; The data visualization module displays real-time monitoring data, irrigation history records, and equipment status through a web interface or mobile APP. The intelligent decision engine module generates irrigation plans based on a rule engine or AI algorithm. The remote control module supports manual or automatic mode switching to perform timed and zoned control of the irrigation equipment in the execution layer. The edge computing nodes perform localized preliminary processing on the data collected by the perception layer, reducing cloud computing pressure and data transmission latency.

5. The intelligent irrigation management system for garden landscapes according to claim 4, characterized in that: The rule engine of the intelligent decision engine module includes a soil moisture threshold setting unit, a threshold triggering unit, and a time constraint unit; The soil moisture threshold setting unit is used to set different soil moisture threshold ranges for different plant types and growth stages; The threshold triggering unit generates an irrigation start command when the real-time monitored soil moisture value is lower than the lower limit of the threshold range; and generates an irrigation stop command when the upper limit of the threshold range is reached. The time constraint unit is used to set the time window for irrigation execution, avoiding irrigation during high-temperature periods or when the probability of rainfall exceeds a preset value.

6. The intelligent irrigation management system for garden landscapes according to claim 4, characterized in that: The AI ​​algorithm of the intelligent decision engine module includes a historical data training unit, an environmental parameter fusion unit, and a dynamic adjustment unit; Historical data training unit: LSTM time series prediction model is built based on at least 12 months of historical irrigation data, meteorological data and plant growth data. The environmental parameter fusion unit takes real-time soil moisture, meteorological data, and plant physiological indicators as input features, and outputs the water demand prediction value for the next 72 hours through the prediction model. The dynamic adjustment unit updates the model parameters quarterly based on the deviation between the actual irrigation effect and the predicted value, thereby improving the prediction accuracy.

7. The intelligent irrigation management system for garden landscapes according to claim 4, characterized in that: The cloud platform management system of the platform layer also includes an anomaly monitoring module, a multi-level alarm module, and a data analysis module; The anomaly monitoring module identifies faults such as water leakage, power failure, and sensor drift by comparing sensor data with preset thresholds. The multi-level alarm module sends three levels of alarm information—SMS, APP push, and email—for different fault types, and includes a heat map of the fault location and a link to the maintenance manual. The data analysis module generates monthly water usage reports, equipment failure rate reports, and plant growth trend analysis reports based on historical irrigation data.

8. The intelligent irrigation management system for garden landscapes according to claim 1, characterized in that: The intelligent decision engine module of the cloud platform management system combines weather forecast data collected by the environmental meteorological station, and specifically includes a precipitation probability analysis unit, an evapotranspiration calculation unit, and an extreme weather response unit. The precipitation probability analysis unit automatically suspends the irrigation plan when the probability of precipitation in the next 24 hours exceeds 60%. The evapotranspiration calculation unit calculates the reference crop evapotranspiration based on the Penman-Monteith formula and adjusts the irrigation amount in combination with the crop coefficient Kc. The extreme weather response unit automatically shuts down all outdoor irrigation equipment and enters flood prevention mode when typhoon or rainstorm warnings are issued.

9. A smart irrigation management system for garden landscapes according to claim 1, characterized in that: The execution layer includes intelligent valves, nozzles, and integrated water and fertilizer devices; The intelligent valve is installed in the irrigation pipeline network to enable on / off control of different irrigation areas; The sprinklers are selected from rotating sprinklers and drip irrigation tapes according to the type and layout of garden plants; The integrated water and fertilizer device automatically mixes fertilizers based on soil nutrient data analyzed by the platform layer and applies the fertilizers simultaneously through the irrigation system.

10. A smart irrigation management system for garden landscapes according to claim 9, characterized in that: The intelligent valve in the execution layer is a pulse-powered solenoid valve, which is powered by DC24V pulses. The solenoid valve has a flow regulation function and achieves a flow regulation accuracy of 0-100% through PWM control signals. The execution layer also includes a valve status feedback unit, which uploads valve opening and closing position and water flow pressure data to the platform layer in real time.

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