Intelligent landscape stone table for indoor landscaping

Abstract

The invention relates to the field of indoor landscaping, and discloses an indoor landscaping intelligent landscape stone table which comprises a landscape stone table body, a stone scene is arranged at the top of the landscape stone table body, an adjusting structure is installed at the top of the stone scene, and an intelligent control module is arranged on one side of the landscape stone table body. The intelligent control module comprises a multi-scale sensing unit, a multi-scale modeling unit, a control execution unit and an interactive operation and maintenance unit; the multi-scale sensing unit is used for collecting plant physiology and environment parameters on the landscape stone table in real time to form multi-source data, and a multi-physics coupling theory is adopted to construct a cross-scale mathematical model and quantitatively describe plant physiology and environment parameter evolution. Multi-source data are formed by collecting plant physiology and environmental parameters on a landscape stone table in real time, a cross-scale mathematical model is constructed based on the multi-source data, and the plant growth state and the environmental evolution trend are quantitatively predicted, including dynamic changes of safety risks, fusion of the evolution trend and real-time data, to generate a control strategy.

Description

Technical Field

[0001] This invention relates to the field of indoor landscaping technology, specifically to an intelligent landscape stone platform for indoor landscaping. Background Technology

[0002] In interior space design, interior landscaping technology is dedicated to integrating plant cultivation, landscape aesthetics and intelligent control to meet people's needs for an ecological and intelligent living environment.

[0003] Traditional landscape stone platforms often employ a structure design that combines static stone features with open water features. If people are too close to the water features, especially when children are playing nearby, they may accidentally fall into the water due to carelessness or excessive movement. This increases the safety risk and limits the practicality of landscape stone platforms in terms of safety protection. Summary of the Invention

[0004] In view of the shortcomings of the existing technology, the present invention provides an intelligent landscape stone platform for indoor landscaping, which solves the problem of the low practicality of traditional landscape stone platforms in terms of safety protection.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solution: an indoor landscaping intelligent landscape stone platform, comprising a landscape stone platform, a stone landscape set on the top of the landscape stone platform, an adjustment structure installed on the top of the stone landscape, and an intelligent control module set on one side of the landscape stone platform, the intelligent control module comprising a multi-scale perception unit, a multi-scale modeling unit, a control execution unit, and an interactive operation and maintenance unit;

[0006] The multi-scale sensing unit is used to collect plant physiological and environmental parameters on the landscape stone platform in real time, forming multi-source data;

[0007] The multi-scale modeling unit is used to construct a cross-scale mathematical model based on multi-source data and multi-physics coupling theory, and to quantitatively describe the evolution of plant physiological and environmental parameters to obtain evolutionary trends. The evolutionary trends include plant growth status prediction and environmental evolution trends.

[0008] The control execution unit is used to generate a control strategy by using a nonlinear optimization algorithm, integrating evolutionary trends and real-time multi-source data, and to perform plant growth environment adjustment, rockery height adjustment and safety warning according to the control strategy.

[0009] The interactive communication unit is used to transmit various data and perform interactive operations.

[0010] By adopting the above technical solution, real-time collection of plant physiological and environmental parameters on the landscape stone platform generates multi-source data. Based on this multi-source data, a cross-scale mathematical model is constructed to quantitatively predict plant growth status and environmental evolution trends, including dynamic changes in safety risks. By integrating evolution trends and real-time data, a control strategy is generated. While regulating the plant growth environment, the height of the stone platform is adjusted to optimize the safety distance and trigger safety warnings. Interactive communication units ensure data transmission and interactive operations, enabling real-time perception, risk prediction, proactive control, and timely warning of the safety status of the landscape stone platform. This improves the practicality of the landscape stone platform and solves the problem of low practicality of traditional landscape stone platforms in terms of safety protection.

[0011] Preferably, the adjustment structure includes a floor slab, a mounting frame is fixedly connected to the top of the floor slab, a motor is fixedly installed on the top of the mounting frame, a take-up roller is fixedly provided at the output end of the motor, a lug is rotatably connected to one end of the take-up roller, and the bottom of the lug is fixedly connected to the top of the mounting frame.

[0012] Preferably, through holes are evenly provided on one side of the floor slab, decorative sleeves are provided at the bottom of the through holes of the floor slab, and pulleys are evenly fixedly installed on one side of the floor slab.

[0013] Preferably, a second connecting rope is provided on one side of the take-up roller, and a first connecting rope is uniformly and fixedly connected to one end of the second connecting rope. One end of the first connecting rope is fixedly connected to the top of the rockery, and the first connecting rope is located inside the decorative sleeve.

[0014] Preferably, a connecting rope three is fixedly connected to the bottom of the rockery, and an iron plate is fixedly connected to one end of the connecting rope three. A permanent magnet is provided at the bottom of the iron plate, and the bottom of the permanent magnet is installed inside the landscape stone platform.

[0015] Preferably, a groove is provided on one side of the landscape stone platform, an airbag is provided in the groove of the landscape stone platform, and the permanent magnet is located in the groove of the landscape stone platform.

[0016] Preferably, the multi-scale sensing unit includes a microscopic detection subunit, a mesoscopic monitoring subunit, a macroscopic environment subunit, and a fusion processing subunit. The microscopic detection subunit is used to collect leaf physiological parameters and soil micro-moisture data on the landscape stone platform in real time using a spectrometer and fiber optic sensors to obtain microscopic detection data. The mesoscopic monitoring subunit is used to acquire soil parameter distribution and root structure data on the landscape stone platform in real time through a soil sensor array and a root scanning module to obtain mesoscopic monitoring data. The macroscopic environment subunit is used to collect environmental parameters on the landscape stone platform in real time through acquisition devices to obtain macroscopic environment data. The acquisition devices include temperature and humidity sensors, light sensors, CO2 sensors, infrared ranging sensors, electrode-type water immersion sensors, and cameras. The fusion processing subunit is used to perform spatiotemporal alignment and outlier removal on the microscopic detection data, mesoscopic monitoring data, and macroscopic environment data using a federated Kalman filter algorithm to obtain multi-source data.

[0017] Preferably, the multi-scale modeling unit includes a microphysiological model subunit, a mesoscopic coupling model subunit, and a macroscopic field model subunit. The microphysiological model subunit is used to model and analyze microscopic detection data from multi-source data based on fluid dynamics theory, construct a leaf cell water transport model, and obtain cell physiological state parameters. The mesoscopic coupling model subunit is used to combine fractal theory and soil hydrodynamics principles, integrate cell physiological state parameters with mesoscopic monitoring data from multi-source data, construct a root-soil water coupling model, and obtain the relationship between root water absorption characteristics and soil parameter evolution. The macroscopic field model subunit is used to adopt multi-physics field coupling theory, integrate the relationship between root water absorption characteristics and soil parameter evolution with macroscopic environmental data from multi-source data, construct a cross-scale mathematical model, and output plant growth status prediction and environmental evolution trend.

[0018] Preferably, the control execution unit includes an optimization solution subunit, a disturbance compensation subunit, and an execution control subunit. The optimization solution subunit is used to fuse evolutionary trends and real-time multi-source data using a nonlinear optimization algorithm to obtain an initial control quantity. The disturbance compensation subunit is used to estimate random environmental disturbances through an extended state observer and correct the initial control quantity to obtain a control strategy. The execution control subunit is used to adjust the plant growth environment, adjust the height of the rockery, and provide safety warnings through execution devices according to the control strategy. The execution devices include irrigation equipment, lighting equipment, audible and visual alarms, and adjustment structures. The safety warnings include voice prompts when personnel approach a preset value, audible and visual alarms when water is detected, and APP push notifications.

[0019] Preferably, the interactive communication unit includes a communication subunit and an interaction subunit. The communication subunit is used to transmit various data through a communication device, which includes a wireless module, an Ethernet interface, an RS485 interface, and a USB interface. The interaction subunit is used to perform interactive operations through an interaction device, which includes a touch screen and a voice module.

[0020] This invention provides an intelligent landscape stone platform for indoor landscaping. It has the following beneficial effects:

[0021] 1. This invention collects real-time physiological and environmental parameters of plants on landscape stone platforms to form multi-source data. Based on this multi-source data, a cross-scale mathematical model is constructed to quantitatively predict plant growth status and environmental evolution trends, including dynamic changes in safety risks. By integrating evolution trends and real-time data, a control strategy is generated. While regulating the plant growth environment, the height of the stone platform is adjusted to optimize the safety distance and trigger safety warnings. Through an interactive communication unit, data transmission and interactive operations are ensured. This invention achieves real-time perception, risk prediction, proactive control, and timely warning of the safety status of the landscape stone platform, improving its practicality and solving the problem of low practicality of traditional landscape stone platforms in terms of safety protection.

[0022] 2. This invention uses a motor to wind up the second connecting rope, which in turn drives the first connecting rope to move up and down through the through hole and pulley. This, in turn, moves the rockery up and down above the landscape platform, allowing the height of the rockery to be adjusted within a certain range. When the multi-scale sensing unit detects that someone has fallen into the landscape platform, it continuously lifts the rockery, which then uses the third connecting rope to move the iron plate upward, overcoming the attraction of the permanent magnet. This releases the restriction on the airbag in the groove, allowing the airbag to unfold and float on the water surface using elasticity and buoyancy, providing a gripping support for the person who has fallen into the water and enabling emergency rescue. This enhances the practicality of the structure and takes into account both landscape layering and safety protection.

[0023] 3. This invention collects multi-source data through a multi-scale sensing unit, constructs a cross-scale mathematical model through a multi-scale modeling unit, quantitatively describes the dynamic relationship between plant physiology and environment, and integrates model prediction and real-time data generation optimization strategies through a control execution unit to adjust environmental factors such as irrigation and light, thereby dynamically adapting to the needs of different growth stages of plants, avoiding problems such as over-irrigation or insufficient light, and improving plant survival rate and growth quality.

[0024] 4. This invention dynamically adjusts the height of the rockery according to the strategy of the control execution unit by adjusting the structure. During the vigorous growth period of plants, the rockery is raised to expand the vertical landscape layer. When people are detected approaching, the rockery is lowered to reduce the safety distance. Under normal conditions, it maintains an aesthetic height that is suitable for the indoor space. This allows the rockery to not only meet the visual needs of indoor landscaping, but also respond to the functional requirements of safety protection and plant growth, thus achieving an organic unity of landscape aesthetics, spatial adaptation and safety and practicality. Attached Figure Description

[0025] Figure 1 This is a three-dimensional structural diagram of the present invention;

[0026] Figure 2 This is a partial structural diagram of the connecting rope of the present invention;

[0027] Figure 3 This is a schematic diagram of the internal structure of the landscape stone platform of the present invention;

[0028] Figure 4 This is a partial structural diagram of the iron plate of the present invention;

[0029] Figure 5 This is a schematic diagram of the intelligent control module architecture of the present invention.

[0030] Among them, 1. Landscape stone platform; 2. Stone landscape; 3. Intelligent control module; 4. Iron plate; 5. Decorative sleeve; 6. Connecting rope one; 7. Floor slab; 8. Mounting frame; 9. Motor; 10. Winding roller; 11. Pulley; 12. Connecting rope two; 13. Connecting rope three; 14. Lug; 15. Through hole; 16. Permanent magnet; 17. Airbag; 18. Groove. Detailed Implementation

[0031] The technical solution of the present invention will now be clearly and completely described 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.

[0032] Please see the appendix Figure 1 -Appendix Figure 5 This invention provides an intelligent landscape stone platform for indoor landscaping, including a landscape stone platform 1, a stone landscape 2 on the top of the landscape stone platform 1, an adjustment structure on the top of the stone landscape 2, and an intelligent control module 3 on one side of the landscape stone platform 1. The intelligent control module 3 includes a multi-scale perception unit, a multi-scale modeling unit, a control execution unit, and an interactive operation and maintenance unit.

[0033] The multi-scale sensing unit is used to collect plant physiological and environmental parameters on the landscape stone platform 1 in real time, forming multi-source data;

[0034] The multi-scale modeling unit is used to construct cross-scale mathematical models based on multi-source data and multi-physics coupling theory, and to quantitatively describe the evolution of plant physiological and environmental parameters, thereby obtaining evolutionary trends, including plant growth status prediction and environmental evolution trends.

[0035] The control execution unit is used to generate a control strategy by employing a nonlinear optimization algorithm, integrating evolutionary trends and real-time multi-source data, and then adjusting the plant growth environment, adjusting the height of the rockery 2, and providing safety warnings based on the control strategy.

[0036] The interactive communication unit is used to transmit various data and perform interactive operations.

[0037] Specifically, by setting up landscape stone platform 1 and stone landscape 2, a physical carrier for indoor landscaping is constructed, providing space for plant growth and landscape display. The adjustable structure at the top of stone landscape 2 allows for height adjustment as needed. Real-time collection of leaf physiological parameters, root structure parameters, and environmental parameters such as temperature, humidity, light, personnel distance, and water immersion status of plants on landscape stone platform 1 generates multi-source data, providing comprehensive input data for subsequent model construction. A cross-scale mathematical model is constructed based on multi-physics coupling theory using multi-source data to quantify the dynamic correlation and evolution of plant physiological and environmental parameters, obtaining plant growth status predictions and environmental evolution trends. This transforms discrete multi-source data into continuous evolutionary patterns, providing theoretical guidance for the generation of control strategies and enabling forward-looking predictions of plant growth and environmental changes. In one embodiment, plant physiological parameters include cell water transport and root water absorption characteristics; plant environmental parameters include temperature and humidity field and light field evolution; plant growth status predictions include growth rate and leaf unfolding degree; and environmental evolution trends include temperature and humidity changes and safety risk evolution.

[0038] By employing a nonlinear optimization algorithm to integrate evolutionary trends with real-time multi-source data, a control strategy is generated that balances plant growth optimization, energy consumption control, and safety protection. This strategy drives irrigation equipment to regulate water levels, lighting equipment to control the light environment, and structural adjustments to change the height of the rockery. It also triggers safety warning actions such as audible and visual alarms and app push notifications. This transforms the theoretical model into actual control commands, enabling dynamic adaptation to the plant growth environment, intelligent adjustment of the rockery's spatial morphology, and proactive response to safety risks. By transmitting and interacting with various data sources, the system ensures coordinated operation between units while supporting user monitoring and intervention, achieving a unity of intelligent control and user-friendly interaction.

[0039] Through the synergistic effect of the aforementioned structures and units, multi-source data is generated by collecting real-time physiological and environmental parameters of plants on the landscape stone platform. Based on this multi-source data, a cross-scale mathematical model is constructed to quantitatively predict plant growth status and environmental evolution trends, including dynamic changes in safety risks. By integrating evolutionary trends and real-time data, a control strategy is generated. While regulating the plant growth environment, the height of the stone platform is adjusted by modifying the structure to optimize the safety distance and trigger safety warnings. Interactive communication units ensure data transmission and interactive operations, enabling real-time perception, risk prediction, proactive control, and timely warning of the safety status of the landscape stone platform. This improves the practicality of the landscape stone platform and solves the problem of low practicality of traditional landscape stone platforms in terms of safety protection.

[0040] The adjustment structure includes a floor slab 7, with a mounting frame 8 fixedly connected to the top of the floor slab 7. A motor 9 is fixedly mounted on the top of the mounting frame 8, and a take-up roller 10 is fixedly mounted at the output end of the motor 9. One end of the take-up roller 10 is rotatably connected to a lug 14, the bottom of which is fixedly connected to the top of the mounting frame 8. Through holes 15 are evenly spaced on one side of the floor slab 7, and decorative sleeves 5 are provided at the bottom of the through holes 15. Pulleys 11 are evenly fixedly mounted on one side of the floor slab 7. A second connecting rope 12 is provided on one side of the take-up roller 10, and a first connecting rope 6 is evenly fixedly connected to one end of the second connecting rope 12. One end of the first connecting rope 6 is fixedly connected to the top of the rockery 2, and the first connecting rope 6 is located inside the decorative sleeve 5. A third connecting rope 13 is fixedly connected to the bottom of the rockery 2, and an iron plate 4 is fixedly connected to one end of the third connecting rope 13. A permanent magnet 16 is provided at the bottom of the iron plate 4, and the bottom of the permanent magnet 16 is installed inside the landscape stone platform 1. A groove 18 is provided on one side of the landscape stone platform 1. An airbag 17 is installed in the groove 18 of the landscape stone platform 1, and a permanent magnet 16 is located in the groove 18 of the landscape stone platform 1.

[0041] Specifically, the adjustment structure is installed via floor slab 7. Mounting frame 8 is welded to the top of floor slab 7, providing support for motor 9 and take-up roller 10. Motor 9 is preferably a servo motor, its output shaft coaxially connected to take-up roller 10 via a key. One end of take-up roller 10 is rotatably connected to lug 14 via a bearing. The bottom of lug 14 is bolted to mounting frame 8, forming a rotational support for take-up roller 10. Connecting rope 2 12 is wound circumferentially around take-up roller 10. The end of connecting rope 2 12 is branched into multiple connecting ropes 1 6 via a rope splitter, typically 3-4 ropes, to ensure balanced force distribution on rockery 2. Through holes 15 are opened at corresponding positions on floor slab 7, with decorative sleeves 5 nested inside to partially conceal connecting ropes 1 6 and create a scenic effect, enhancing aesthetics. Connecting ropes 1 6 pass through decorative sleeves 5 and through holes 15, with the ends fixed to the top suspension point of rockery 2 via hanging rings. A pulley 11 is installed at the bottom of the floor slab 7 to guide the connecting rope 6 and prevent the rope from directly rubbing against the floor slab 7. The lug 14 is attracted by the permanent magnet 16, which limits the airbag 17 to the groove 18 of the landscape stone platform 1.

[0042] Specifically, the operation of motor 9 drives the winding roller 10 to rotate on lug 14, thereby winding up connecting rope 2 12. This causes connecting rope 1 6 to move up and down through through hole 15 and pulley 11, which in turn causes the rockery 2 to move up and down on the upper part of the landscape platform 1. This allows for adjustment of the height of the rockery 2 within a certain range, taking into account both landscape layering and safety protection. When the multi-scale sensing unit detects that someone has fallen into the landscape platform 1, the operation of motor 9 continuously lifts the rockery 2. This causes connecting rope 3 13 to drive iron plate 4 to overcome the attraction of permanent magnet 16, causing iron plate 4 to move upward. This releases the restriction on airbag 17 in groove 18, allowing airbag 17 to unfold and float on the water surface using elasticity and buoyancy, providing grip and support for the person who has fallen into the water. Combined with sound and light alarms and APP push notifications, emergency rescue can be achieved, thereby enhancing the practicality of this structure.

[0043] In some embodiments, the connecting rope 6 is made of high-strength nylon rope with a waterproof coating, and the pulley 11 has a V-shaped groove design to accommodate the rope diameter and prevent slippage. A Hall displacement sensor is added at the through hole 15 to monitor the displacement of the connecting rope 6 in real time and feed it back to the control execution unit, forming a closed-loop control of the height of the rockery 2 to ensure adjustment accuracy.

[0044] The multi-scale sensing unit includes a microscopic detection subunit, a mesoscopic monitoring subunit, a macroscopic environment subunit, and a fusion processing subunit. The microscopic detection subunit is used to collect leaf physiological parameters and soil micro-moisture data on the landscape stone platform 1 in real time using a spectrometer and fiber optic sensors to obtain microscopic detection data. The mesoscopic monitoring subunit is used to acquire soil parameter distribution and root structure data on the landscape stone platform 1 in real time through a soil sensor array and a root scanning module to obtain mesoscopic monitoring data. The macroscopic environment subunit is used to collect environmental parameters on the landscape stone platform 1 in real time through acquisition devices, including temperature and humidity sensors, light sensors, CO2 sensors, infrared ranging sensors, electrode-type water immersion sensors, and cameras. The fusion processing subunit is used to perform spatiotemporal alignment and outlier removal on the microscopic detection data, mesoscopic monitoring data, and macroscopic environment data using a federated Kalman filter algorithm to obtain multi-source data.

[0045] Specifically, the multi-scale sensing unit achieves comprehensive perception of the physiological and environmental parameters of plants on the landscape stone platform through a hierarchical sub-unit design.

[0046] Typically, the spectrometer configured in the microscopic detection subunit is installed at a predetermined position on the top of the landscape stone platform. It can collect the reflectance spectrum information of the leaves in real time and obtain physiological parameters such as leaf chlorophyll content and leaf water content by analyzing the spectral characteristics. As an alternative, fiber optic sensors are implanted, with their probes buried in the soil around the plant roots. They use the principle of optical time-domain reflectometry to sense the distribution of microscopic soil moisture, thereby obtaining local dynamic changes in soil moisture. In some embodiments, the sampling frequency of the microscopic detection subunit can be adjusted according to the plant's growth status. During the vigorous growth period of the plant, the sampling frequency can be appropriately increased to obtain more refined microscopic detection data.

[0047] The mesoscopic monitoring subunit is used to acquire the spatial distribution of soil parameters and the structural characteristics of plant roots. Specifically, a soil sensor array is distributed in a preset matrix form within the planting area of ​​the landscape stone platform, typically containing multiple detection nodes. Each node can simultaneously collect parameters such as soil moisture and electrical conductivity, and the data from multiple nodes is combined to form two-dimensional distribution information of soil parameters. Alternatively, a root scanning module is usually installed at the bottom of the landscape stone platform. It uses structured light scanning technology to periodically scan the plant roots, acquiring three-dimensional morphological data of the roots, and then analyzing the fractal structural characteristics of the roots. In one possible implementation, the mesoscopic monitoring subunit will initially correlate the collected soil parameter distribution data with the root structure data, providing a foundation for subsequent modeling and analysis.

[0048] The macro-environment subunit is responsible for collecting macro-environmental parameters around the landscape stone platform. Typically, temperature and humidity sensors are installed at different heights on the platform to obtain temperature and humidity data for different spatial locations; light sensors are usually oriented towards the light source to collect ambient light intensity and spectral distribution information; and CO2 sensors are deployed near the plant canopy to monitor the surrounding CO2 concentration in real time. In some embodiments, infrared ranging sensors are installed on the side of the platform closer to the water feature to sense the distance between people and the water feature; electrode-type water immersion sensors are embedded in the bottom edge of the water feature to detect any water spillage; and cameras are fixed above the platform to collect image information of the surrounding scene. These acquisition devices work together to form a macro-environmental data acquisition network.

[0049] The fusion processing subunit employs a federated Kalman filter algorithm to construct a distributed fusion architecture that addresses the heterogeneity of microscopic detection data, mesoscopic monitoring data, and macroscopic environmental data, thereby achieving accurate data integration.

[0050] Specifically, the algorithm first establishes state-space models for each of the three sub-units. For the microscopic detection sub-unit, its state equation can be expressed as: ,in, for The time-matter microstate vector includes parameters such as leaf chlorophyll content and soil micromoisture. This is the state transition matrix, reflecting the evolution of microscopic parameters over time. This represents process noise, which follows a zero-mean Gaussian distribution. Its observation equation is: ,in, These are the observations from the spectrometer and fiber optic sensor; The observation matrix maps the microscopic state to the observation space; The variance of the noise is preset based on the sensor accuracy.

[0051] For the mesoscopic monitoring subunit, the state equation is: ,in, It includes mesoscopic parameters such as soil moisture distribution and root fractal dimension; To characterize the spatiotemporal evolution of mesoscopic parameters, such as the diffusion characteristics of soil moisture. The observation equation is: ,in, This is the output data of the soil sensor array and root scanning module; It reflects the mapping relationship between the mesoscopic state and the observed values.

[0052] The state equation of the macroscopic environment sub-unit is: ,in, Includes macroscopic parameters such as temperature, humidity, light intensity, and CO2 concentration; It reflects the dynamic changes in the macroscopic environment, such as the fluctuation of temperature with light intensity. The observation equation is: ,in, This refers to observational data from macroscopic data acquisition devices such as temperature and humidity sensors and light sensors.

[0053] During the data fusion phase, each sub-unit first performs local estimation. The local estimated values ​​of the microscopic detection sub-unit are shown below. and error covariance The solution is obtained through the prediction-update step of Kalman filtering; the mesoscopic monitoring subunit and the macroscopic environment subunit are solved similarly, respectively. and During global fusion, the fusion processing subunit performs weighted integration of local estimates: In the formula, These are weighting coefficients, taken into account the low noise characteristic of microscopic detection data. It can be set to a larger value; when macroeconomic data fluctuates significantly, Reduce the size appropriately to ensure fusion accuracy.

[0054] In some embodiments, a time synchronization factor is introduced into the algorithm to achieve spatiotemporal alignment. The sampling times of different sub-units are calibrated so that... Unified to the same time base; and simultaneously through spatial transformation matrix Transform the spatial coordinates of each sub-unit, such as mapping the two-dimensional distribution of mesoscopic soil parameters to the coordinate system of the macroscopic environment, to ensure spatial consistency of the data.

[0055] As an alternative, outlier removal is achieved through residual testing, by calculating the observed residuals. ,when When the value exceeds the preset threshold, it is identified as an outlier and removed. The final output is multi-source data that has undergone spatiotemporal alignment and outlier processing, providing reliable input for multi-scale modeling units.

[0056] The multi-scale modeling unit includes a microphysiological model subunit, a mesoscopic coupling model subunit, and a macroscopic field model subunit. The microphysiological model subunit is used to model and analyze microscopic detection data from multi-source data based on fluid dynamics theory, construct a leaf cell water transport model, and obtain cell physiological state parameters. The mesoscopic coupling model subunit is used to combine fractal theory and soil hydrodynamics principles, integrate cell physiological state parameters with mesoscopic monitoring data from multi-source data, construct a root-soil water coupling model, and obtain the relationship between root water absorption characteristics and soil parameter evolution. The macroscopic field model subunit is used to adopt multi-physics field coupling theory, integrate the relationship between root water absorption characteristics and soil parameter evolution with macroscopic environmental data from multi-source data, construct a cross-scale mathematical model, and output plant growth status prediction and environmental evolution trend.

[0057] Specifically, the multi-scale modeling unit constructs cross-scale mathematical models to quantitatively describe the dynamic relationship between plant physiology and the environment by transforming multi-source data into evolutionary trends that can be used for control decisions.

[0058] Generally, the microscopic physiological model subunit uses microscopic detection data from multi-source datasets as input and analyzes the water transport process in leaf cells based on fluid dynamics theory. Specifically, the leaf cell water transport model it constructs adopts the following approach: ,in, The dynamic viscosity of the cell sap reflects its flow characteristics. This is the velocity vector of the cell sap, describing the direction and speed of water flow within the cell; This refers to the pressure distribution within the cell; The density of the cell sap; The volume forces acting on the cell sap are primarily considered, taking into account the forces generated by the osmotic pressure gradient. Specifically, by inputting leaf moisture content data obtained from a spectrometer and soil micro-moisture data obtained from a fiber optic sensor, numerical solutions can be used to obtain cell physiological state parameters such as intracellular pressure distribution and water flux. These parameters can reflect the real-time physiological activity of leaf cells.

[0059] The mesoscopic coupling model subunit receives cellular physiological state parameters output from the microscopic physiological model subunit and integrates mesoscopic monitoring data from multiple sources. It then constructs a root-soil water coupling model by combining fractal theory and soil hydrodynamic principles. Alternatively, this model can employ a fractal-corrected water movement equation: ,in, Soil volumetric water content, taken from mesoscopic monitoring data of a soil sensor array; For time; Soil hydraulic conductivity considering root fractal characteristics, The root fractal dimension is calculated from the root structure data obtained by the root scanning module. Soil water potential; The root water absorption rate is related to the root fractal dimension. and soil moisture content Correspondingly, the larger the fractal dimension, the more developed the root system, and the higher the water absorption rate. By solving this equation, the relationship between root water absorption characteristics and soil parameter evolution can be obtained, such as the water consumption rate and the distribution of root water absorption efficiency in different soil regions.

[0060] The macroscopic field model sub-unit, as the output of the multi-scale modeling unit, integrates the root water absorption characteristics and soil parameter evolution relationships output by the mesoscopic coupling model sub-unit, along with macroscopic environmental data from multiple sources, using multiphysics coupling theory to construct a cross-scale mathematical model. Typically, this model includes equations describing the coupled evolution of light, temperature, and CO2 concentration, for example:

[0061]

[0062]

[0063]

[0064] in, The light intensity is taken from the light sensor data of the macroscopic environment subunit. The ambient temperature is obtained from a temperature and humidity sensor. CO2 concentration, from a CO2 sensor; These are model parameters that reflect the strength of interactions between various environmental factors. Reference temperature; The ambient background temperature; External CO2 concentration; The function representing the effect of soil moisture content on light absorption is derived from the evolution relationship of soil parameters; This is a function representing the effect of root water absorption rate on temperature. This is a function of the effect of plant photosynthesis on CO2 concentration, which is related to the chlorophyll content in leaves.

[0065] Specifically, in the process of linking mesoscopic soil moisture and root water uptake data with macroscopic environmental parameters through the aforementioned equations, the macroscopic field model subunit simultaneously integrates infrared ranging information and electrode-type water immersion sensor information from the macroscopic environmental data. This allows the model output to not only include plant growth status predictions and environmental evolution trends but also provide a basis for safety early warning. Generally, the model uses the distance parameters between people and water features collected by the infrared ranging sensor as input variables, combined with the spatial dynamic characteristics in the environmental evolution trend, to construct a distance change prediction model. When the predicted distance is less than a preset safety threshold, a proximity warning trigger condition is generated. For the water feature status data collected by the electrode-type water immersion sensor, the model incorporates it as a sudden state variable into the macroscopic field coupling equation. When an abnormal change in the water immersion signal is detected, it is determined to be a potential water-falling situation, forming a basis for a water-falling warning.

[0066] Through numerical simulation, while obtaining predictions of plant growth status and environmental evolution trends, the model can simultaneously output monitoring results for personnel approach risk levels and water-related status. Plant growth status predictions include growth rate and leaf unfolding degree, while environmental evolution trends include temperature and humidity changes over the next 12 hours. Alternatively, the model can appropriately adjust the sensitivity of the approach warning based on changes in light intensity within the environmental evolution trend, improving response speed during periods of high personnel activity. In some embodiments, the macroscopic field model subunit combines scene images captured by cameras to assist in identifying personnel position and posture, correcting distance prediction biases, and making the judgments of approach and water-related warnings more accurate. This also ensures coordinated operation with the plant growth regulation model, without affecting the normal output of plant growth status and environmental evolution trends.

[0067] As an alternative, during the model solving process, the output of the microscopic physiological model subunit provides boundary conditions for the mesoscopic coupling model subunit. For example, leaf water potential in cell physiological state parameters can serve as a driving term for the root water uptake model; while the soil moisture distribution obtained from the mesoscopic coupling model subunit serves as the initial condition for the macroscopic environmental field model, ensuring the coherence of the cross-scale model. In one possible implementation, the model parameters of each subunit are adjusted according to the plant species. For succulents, the sensitivity coefficient of root water uptake to soil moisture content can be appropriately increased to adapt to their drought-tolerant characteristics.

[0068] Through the modeling process of the above three-level sub-units, the multi-scale modeling unit realizes a full-scale quantitative description from microscopic cell physiology to macroscopic environmental evolution. Its output of plant growth status prediction and environmental evolution trend provides a theoretical basis for the control execution unit to generate precise control strategies.

[0069] The control execution unit includes an optimization solution subunit, a disturbance compensation subunit, and an execution control subunit. The optimization solution subunit is used to fuse evolutionary trends and real-time multi-source data using a nonlinear optimization algorithm to obtain the initial control quantity. The disturbance compensation subunit is used to estimate random environmental disturbances through an extended state observer and correct the initial control quantity to obtain the control strategy. The execution control subunit is used to regulate the plant growth environment, adjust the height of the rockery 2, and provide safety warnings through execution equipment according to the control strategy. The execution equipment includes irrigation equipment, lighting equipment, audible and visual alarms, and adjustment structures. The safety warnings include voice prompts when personnel approach a preset value, audible and visual alarms when water is detected, and APP push notifications.

[0070] Specifically, the control execution unit transforms evolutionary trends into specific regulatory actions through the coordinated operation of three levels of sub-units, thereby controlling the plant growth environment, rockery height, and safety status.

[0071] Generally, the optimization solution sub-unit takes the evolution trend output by the multi-scale modeling unit and the real-time parameters from multi-source data as input, and uses a nonlinear optimization algorithm to construct the objective function to solve for the initial control quantity. Specifically, the objective function can be expressed as: ,in, This represents the deviation vector between plant growth status and environmental parameters. This is a plant growth deviation function that reflects the difference between the actual state and the ideal state. This is a control vector that includes irrigation volume, light intensity, and rise / fall rates, etc. This is an energy consumption function that characterizes the energy consumption of equipment during operation. This is a safety state vector, which includes information such as personnel distance and water immersion status. This is a safety risk function; the higher the risk, the larger the function value. These are weighting coefficients, generally speaking. Larger values ​​are chosen to prioritize safety. By solving this objective function, initial control variables that balance plant growth, energy consumption control, and safety can be obtained, such as the flow rate setpoint for irrigation equipment, the power parameters of lighting equipment, the speed command for rockery lifting and lowering, and the trigger threshold for safety warnings.

[0072] The disturbance compensation subunit receives the initial control input from the optimization solution subunit, estimates the random disturbances in the environment using an extended state observer, and corrects the initial control input. Specifically, the equation of the extended state observer can be expressed as:

[0073]

[0074] in, The estimated value output by the system corresponds to the measured value of plant growth environment parameters, rockery height, or safety status. This is an estimate of the system state; This is an estimate of the total disturbance, including unmodeled disturbances such as sudden changes in ambient temperature and sudden approach of people; The observer gain is set using the pole placement method; For control coefficients; This is the initial control input. After obtaining the disturbance estimate through this observer, the corrected control strategy is as follows: ,in, The revised control strategy, As a compensation coefficient, generally, when a strong disturbance such as a person rapidly approaching is detected, The value is increased to enhance the compensation effect.

[0075] The execution control subunit takes the modified control strategy as input and drives the execution equipment to achieve specific control actions. Specifically, for plant growth environment regulation, it drives irrigation equipment according to the irrigation parameters in the control strategy, such as controlling the pulse width of the piezoelectric micropump to adjust the drip irrigation flow, or controlling the on / off state of the solenoid valve to start the spray mode; for light regulation, it adjusts the PWM duty cycle of the three-primary-color LED array to change the light quality ratio and light intensity to meet the needs of different growth stages of plants.

[0076] As an option, the height of the rockery is adjusted by controlling the operation of the motor in the adjustment structure. According to the height command in the control strategy, the winding roller is driven to rotate forward or reverse to wind up or unwind the connecting rope. At the same time, the feedback signal from the height positioning unit ensures the adjustment accuracy. Under normal circumstances, when a person is detected approaching, the motor will be driven first to lower the rockery to the preset safe height.

[0077] In terms of safety warnings, the control subunit triggers corresponding actions based on the safety instructions in the control strategy: when the infrared ranging sensor detects that the distance to a person is less than the preset value, it drives the audible and visual alarm to issue a voice prompt, such as "Please pay attention to the safety of the water feature edge"; when the electrode-type water immersion sensor detects a water-falling signal, it immediately activates a high-decibel buzzer and flashes a red warning light, and pushes the warning information to the user's APP through the interactive communication unit, while simultaneously linking the irrigation equipment to suspend water feature-related functions to reduce safety risks.

[0078] Through the coordinated operation of the above three-level sub-units, the control execution unit realizes a complete closed loop from optimization solution to disturbance compensation and then to specific execution. This not only ensures the precise control of the plant growth environment, but also takes into account the flexible adjustment of the rockery height and the real-time management of the safety status, enabling the entire landscape rockery system to have intelligent and automated operation capabilities.

[0079] The interactive communication unit includes a communication subunit and an interaction subunit. The communication subunit is used to transmit various data through communication devices, which include a wireless module, an Ethernet interface, an RS485 interface, and a USB interface. The interaction subunit is used to perform interactive operations through interactive devices, which include a touch screen and a voice module.

[0080] Specifically, the interactive communication unit achieves the connection between data transmission and interactive operations through the collaboration of the communication subunit and the interactive subunit.

[0081] Generally, the communication subunit undertakes data transmission tasks between the system's internal and external systems, with its various communication devices working together according to different transmission scenarios. Specifically, the ZigBee module in the wireless module is mainly used for short-range data interaction between units within the intelligent control module, such as transmitting multi-source data collected by the multi-scale sensing unit to the multi-scale modeling unit, or sending instructions from the control execution unit to the execution device; its low-power characteristics are suitable for continuous data exchange. The 4G module is responsible for remote data transmission, sending system operating status, early warning information, etc., to the cloud platform, while receiving remote control instructions from the cloud. As an alternative, the Ethernet interface is often used for large data volume transmission, such as transmitting scene images collected by cameras to the edge computing unit, or backing up historical data to the local server. The RS485 interface mainly connects sensors and actuators, using a bus topology to achieve serial communication between multiple devices, such as connecting the soil sensor array and the multi-scale sensing unit, or exchanging instructions between the motor drive module and the control execution unit. The USB interface is used for local data export and device debugging, such as backing up system logs via USB flash drive or connecting debugging tools for parameter configuration.

[0082] The interactive subunit enables direct interaction between the user and the system through interactive devices, meeting the user's needs for system monitoring and operation. Typically, a touchscreen is installed on the side or near the control panel of the landscape rockery. Its interface displays the system's real-time status, including plant growth parameters, environmental parameters, equipment operating status, and safety warning information. Users can adjust parameters via touch, such as adjusting the target humidity for plant growth, setting the distance threshold for safety warnings, or controlling the height of the rockery. Alternatively, the voice module supports voice command recognition and feedback. Users can issue operation commands via voice, such as "Start irrigation" or "Raise the rockery," and the system will announce the current status via voice, such as "Irrigation has started" or "The rockery is adjusting to a safe height," providing a convenient interaction method in scenarios where hands are limited.

[0083] In some embodiments, the communication subunit employs a data encryption mechanism to ensure transmission security, encrypting sensitive data such as user instructions and warning information to prevent information leakage during transmission; the interaction subunit has access control functions, verifying user identity through touch screen or voice commands, with different permissions allowing users to operate different functions, ensuring the security of system operation.

[0084] In one possible implementation, the communication subunit and the interaction subunit interact with each other. User instructions received by the interaction subunit are transmitted to the control execution unit through the communication subunit. For example, irrigation time parameters set by the user through the touch screen are sent to the optimization solution subunit of the control execution unit through the communication subunit as constraints of the objective function. At the same time, the real-time status data of the system is transmitted to the interaction subunit through the communication subunit and displayed on the touch screen or broadcast through the voice module, so that the user can keep abreast of the system's operation.

[0085] Through the coordinated operation of the communication subunit and the interaction subunit, the interactive communication unit realizes data flow and user interaction inside and outside the system, providing a data transmission channel and operation interface for the intelligent operation of the entire landscape stone platform system, ensuring that the system can operate independently and automatically, and also respond to the personalized needs of users.

[0086] Multi-scale sensing units collect real-time safety-related parameters and plant physiological and environmental parameters on the landscape rockery, forming multi-source data to provide a comprehensive sensing foundation for safety protection. Multi-scale modeling units employ multi-physics coupling theory to incorporate safety and environmental parameters into a cross-scale mathematical model, quantifying the environmental evolution patterns such as personnel approach trends and the risk of falling into water, thus obtaining an evolutionary trend that includes dynamic changes in safety risks and enabling proactive prediction of safety hazards. Control execution units use nonlinear optimization algorithms to integrate evolutionary trends and real-time multi-source data, generating a control strategy that balances plant growth regulation and safety protection. When a person is detected approaching a preset safe distance, the adjustment structure is driven to adjust the height of the rockery to reduce the risk. It features a short safety distance and triggers voice prompts simultaneously. When a water-falling condition is detected, it immediately activates an audible and visual alarm and pushes warning information to the user terminal via the interactive communication unit, forming a tiered response safety protection mechanism. The interactive communication unit enables real-time transmission of safety data and user interaction, supporting remote monitoring of safety status and intervention control strategies to ensure the timeliness and operability of safety protection. It achieves dynamic monitoring of the safety status of landscape stone platforms, early risk warnings, proactive structural adjustments, and multi-channel alarms, solving the problem that traditional landscape stone platforms, lacking safety parameter perception, risk prediction capabilities, and proactive control mechanisms, cannot promptly detect safety hazards, effectively warn and intervene, resulting in low practicality in safety protection.

[0087] 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. An intelligent landscape stone platform for indoor landscaping, comprising a landscape stone platform (1), characterized in that: The top of the landscape stone platform (1) is provided with a stone landscape (2), the top of the stone landscape (2) is equipped with an adjustment structure, and an intelligent control module (3) is provided on one side of the landscape stone platform (1). The intelligent control module (3) includes a multi-scale perception unit, a multi-scale modeling unit, a control execution unit and an interactive operation and maintenance unit. The multi-scale sensing unit is used to collect plant physiological and environmental parameters on the landscape stone platform (1) in real time to form multi-source data; The multi-scale modeling unit is used to construct a cross-scale mathematical model based on multi-source data and multi-physics coupling theory, and to quantitatively describe the evolution of plant physiological and environmental parameters to obtain evolutionary trends. The evolutionary trends include plant growth status prediction and environmental evolution trends. The control execution unit is used to generate a control strategy by using a nonlinear optimization algorithm, integrating evolutionary trends and real-time multi-source data, and to adjust the plant growth environment, adjust the height of the rockery (2), and provide safety warnings according to the control strategy. The interactive communication unit is used to transmit various data and perform interactive operations.

2. The intelligent landscape stone platform for indoor landscaping according to claim 1, characterized in that: The adjustment structure includes a floor slab (7), a mounting frame (8) is fixedly connected to the top of the floor slab (7), a motor (9) is fixedly installed on the top of the mounting frame (8), a take-up roller (10) is fixedly provided at the output end of the motor (9), a lug (14) is rotatably connected to one end of the take-up roller (10), and the bottom of the lug (14) is fixedly connected to the top of the mounting frame (8).

3. The intelligent landscape stone platform for indoor landscaping according to claim 2, characterized in that: The floor slab (7) has through holes (15) evenly distributed on one side, and decorative sleeves (5) are provided at the bottom of the through holes (15) of the floor slab (7). Pulleys (11) are evenly fixedly installed on one side of the floor slab (7).

4. The intelligent landscape stone platform for indoor landscaping according to claim 2, characterized in that: A connecting rope two (12) is provided on one side of the take-up roller (10). A connecting rope one (6) is evenly fixedly connected to one end of the connecting rope two (12). One end of the connecting rope one (6) is fixedly connected to the top of the rockery (2). The connecting rope one (6) is located inside the decorative sleeve (5).

5. The intelligent landscape stone platform for indoor landscaping according to claim 4, characterized in that: The bottom of the rockery (2) is fixedly connected to a connecting rope three (13), one end of which is fixedly connected to an iron plate (4). The bottom of the iron plate (4) is provided with a permanent magnet (16), and the bottom of the permanent magnet (16) is installed inside the landscape stone platform (1).

6. The intelligent landscape stone platform for indoor landscaping according to claim 5, characterized in that: A groove (18) is provided on one side of the landscape stone platform (1), and an airbag (17) is provided in the groove (18) of the landscape stone platform (1). The permanent magnet (16) is located in the groove (18) of the landscape stone platform (1).

7. The intelligent landscape stone platform for indoor landscaping according to claim 1, characterized in that: The multi-scale sensing unit includes a microscopic detection subunit, a mesoscopic monitoring subunit, a macroscopic environment subunit, and a fusion processing subunit. The microscopic detection subunit is used to collect leaf physiological parameters and soil micro-moisture data on the landscape stone platform (1) in real time using a spectrometer and fiber optic sensors to obtain microscopic detection data. The mesoscopic monitoring subunit is used to acquire soil parameter distribution and root structure data on the landscape stone platform (1) in real time through a soil sensor array and a root scanning module to obtain mesoscopic monitoring data. The macroscopic environment subunit is used to collect environmental parameters on the landscape stone platform (1) in real time through acquisition devices to obtain macroscopic environmental data. The acquisition devices include a temperature and humidity sensor, a light sensor, a CO2 sensor, an infrared ranging sensor, an electrode-type water immersion sensor, and a camera. The fusion processing subunit is used to perform spatiotemporal alignment and outlier removal on the microscopic detection data, mesoscopic monitoring data, and macroscopic environmental data using a federated Kalman filter algorithm to obtain multi-source data.

8. The intelligent landscape stone platform for indoor landscaping according to claim 1, characterized in that: The multi-scale modeling unit includes a microphysiological model subunit, a mesoscopic coupling model subunit, and a macroscopic field model subunit. The microphysiological model subunit is used to model and analyze microscopic detection data from multi-source data based on fluid dynamics theory, construct a leaf cell water transport model, and obtain cell physiological state parameters. The mesoscopic coupling model subunit is used to combine fractal theory and soil hydrodynamics principles, integrate cell physiological state parameters with mesoscopic monitoring data from multi-source data, construct a root-soil water coupling model, and obtain the relationship between root water absorption characteristics and soil parameter evolution. The macroscopic field model subunit is used to use multi-physics field coupling theory to integrate the relationship between root water absorption characteristics and soil parameter evolution with macroscopic environmental data from multi-source data, construct a cross-scale mathematical model, and output plant growth status prediction and environmental evolution trend.

9. The intelligent landscape stone platform for indoor landscaping according to claim 1, characterized in that: The control execution unit includes an optimization solution subunit, a disturbance compensation subunit, and an execution control subunit. The optimization solution subunit is used to fuse the evolution trend and real-time multi-source data using a nonlinear optimization algorithm to obtain the initial control quantity. The disturbance compensation subunit is used to estimate the random disturbance of the environment through an extended state observer and correct the initial control quantity to obtain the control strategy. The execution control subunit is used to adjust the plant growth environment, adjust the height of the rockery (2), and provide safety warnings through the execution equipment according to the control strategy. The execution equipment includes irrigation equipment, lighting equipment, sound and light alarms, and adjustment structures. The safety warnings include voice prompts when people approach a preset value, sound and light alarms when water is detected, and APP push notifications.

10. The intelligent landscape stone platform for indoor landscaping according to claim 1, characterized in that: The interactive communication unit includes a communication subunit and an interaction subunit. The communication subunit is used to transmit various data through a communication device, which includes a wireless module, an Ethernet interface, an RS485 interface, and a USB interface. The interaction subunit is used to perform interactive operations through an interaction device, which includes a touch screen and a voice module.

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