Fish tank water temperature intelligent control method and system based on multiple probes

Abstract

The invention relates to the technical field of aquatic organism breeding, and discloses a fish tank water temperature intelligent control method and system based on multiple probes, and the method comprises the steps: constructing a multi-probe temperature control network of a fish tank, and outputting a global water temperature change thermodynamic diagram of the fish tank; according to the global water temperature change thermodynamic diagram and the partition water temperature real-time data, generating a partition temperature equalization mode of the fish tank; setting a multi-parameter linkage control threshold value of the fish tank so as to configure a global water temperature cooperative controller of the fish tank; the local water temperature sudden change value of the fish tank and the response delay time of the global water temperature cooperative controller are monitored in real time, so that the cooperative control efficiency index of the global water temperature cooperative controller is calculated, and a self-adaptive temperature control instruction of the fish tank is generated; and outputting a water temperature intelligent control scheme of the fish tank in combination with a partition temperature equalization mode, a global water temperature cooperative controller and a self-adaptive temperature control instruction. The accuracy of fish tank water temperature control can be improved.

Description

Technical Field

[0001] This invention relates to a method and system for intelligent control of aquarium water temperature based on multiple probes, belonging to the field of aquatic organism breeding technology. Background Technology

[0002] Intelligent aquarium water temperature control refers to the process of intelligently regulating the aquarium water temperature by integrating temperature sensors, automatic regulators, and early warning modules. This allows for real-time monitoring of water temperature changes, fluctuation frequencies, and the impact of ambient temperature, aiming to improve the accuracy and convenience of aquarium water temperature regulation and ensure a stable living environment for aquatic organisms.

[0003] However, traditional intelligent aquarium water temperature control mainly adopts a single-sensor constant temperature control method. This method adjusts the water temperature by collecting temperature data from a single location and using a fixed water temperature threshold standard. Although it can achieve basic water temperature monitoring and simple start / stop control of heating / cooling equipment, it is difficult to cope with sudden changes in local water temperature, such as local high temperatures caused by heater failure or local low temperatures caused by water changes, resulting in insufficient accuracy of aquarium water temperature control.

[0004] Therefore, there is an urgent need for a solution to improve the accuracy of aquarium water temperature control. Summary of the Invention

[0005] This invention provides a method and system for intelligent control of aquarium water temperature based on multiple probes, the main purpose of which is to improve the accuracy of aquarium water temperature control.

[0006] To achieve the above objectives, the present invention provides a method for intelligent control of aquarium water temperature based on multiple probes, comprising: The system acquires real-time water temperature data and aquatic organism activity trajectory data for different zones within the aquarium, and identifies the water temperature conduction characteristics of different functional areas within the aquarium to construct a multi-probe temperature control network for the aquarium. Collect water temperature fluctuation data under the multi-probe temperature control network, establish a global water temperature change heat map of the aquarium based on the water temperature fluctuation data, and generate a zone temperature balancing method for the aquarium based on the global water temperature change heat map and the real-time zone water temperature data. The suitable water temperature range and biological tolerance threshold of different aquatic organisms in the aquarium are analyzed, and the compatibility water temperature range of different aquatic organisms in the aquarium is determined based on the suitable water temperature range and the biological tolerance threshold. Based on the aforementioned compatible water temperature range, set the multi-parameter linkage control threshold for the aquarium, and configure the global water temperature collaborative controller for the aquarium based on the aforementioned multi-parameter linkage control threshold. The system monitors the local water temperature fluctuations in the aquarium and the response delay of the global water temperature co-controller in real time to calculate the co-control efficiency index of the global water temperature co-controller. Based on the co-control efficiency index, it generates an adaptive temperature control command for the aquarium. Combining the zoned temperature balancing method, the global water temperature collaborative controller, and the adaptive temperature control command, an intelligent water temperature control scheme for the fish tank is output.

[0007] Optionally, the step of generating a zoned temperature balancing method for the aquarium based on the overall water temperature change heatmap and the real-time zoned water temperature data includes: Based on the global water temperature change heat map, the temperature imbalance area of ​​the fish tank was identified; Analyze the temperature distribution pattern of the global water temperature change heatmap and extract the dynamic water temperature fluctuation characteristics of the real-time water temperature data of the zones. Based on the temperature distribution pattern and the dynamic water temperature fluctuation characteristics, determine the temperature control medium type of the fish tank; Construct a dynamic balance strategy matrix for the temperature control medium regulation type in different temperature imbalance regions; Based on the real-time water temperature data of the partition, locate the media control linkage node of the fish tank; Based on the medium regulation linkage node, determine the equalization trigger threshold corresponding to the temperature control medium regulation type; Based on the dynamic balancing strategy matrix and the balancing trigger threshold, adaptive balancing control commands are generated for different zones within the fish tank. The adaptive balancing control command generates a zoned temperature balancing method for the fish tank.

[0008] Optionally, locating the media control linkage node of the fish tank based on the real-time water temperature data of the partition includes: Identify the temperature control medium of the fish tank and its corresponding temperature control device, and obtain the zone sensor corresponding to the real-time water temperature data of the zone; Check the signal transmission ports of the temperature control device and the zone sensor; Based on the signal transmission port, the communication protocol specification between the temperature control device and the partition sensor is analyzed. Using the aforementioned communication standard protocol, the communication link relationship between the temperature control device and the partition sensor is analyzed; Based on the communication link relationship, establish a node association map between the temperature control device and the zone sensor; The media control linkage node of the fish tank can be located by using the node association map.

[0009] Optionally, configuring the global water temperature co-controller of the fish tank based on the multi-parameter linkage control threshold includes: By utilizing the parameter correlation characteristics of the multi-parameter linkage control threshold, the zone control channels and data interaction nodes of the fish tank are determined; Based on the partition control channel and the data interaction node, a multi-zone water temperature balancing module for the fish tank is set up. Identify the control precision requirements corresponding to the multi-parameter linkage control threshold, so as to set the adjustable response rate range of the partition control channel; The dynamic power adjustment module of the fish tank is deployed according to the adjustable response rate range; Define the range switching conditions and the recovery time for the control failure of the multi-parameter linkage control threshold to set up the intelligent emergency module of the fish tank; Query the device communication protocol associated with the multi-parameter linkage control threshold to deploy the multi-device compatible communication module of the fish tank; The multi-zone water temperature equalization module, the dynamic power adjustment module, the intelligent emergency module, and the multi-device compatible communication module are integrated to form the global water temperature collaborative controller of the fish tank.

[0010] Optionally, the real-time monitoring of local water temperature fluctuations in the fish tank and the response delay time of the global water temperature co-controller, to calculate the co-control efficiency index of the global water temperature co-controller, includes: Based on the local water temperature abrupt change value, the ecological sensitivity coefficient and water temperature fluctuation gradient in the fish tank are determined; Obtain the device response baseline value corresponding to the response delay time of the global water temperature collaborative controller; Retrieve the historical mutation dataset associated with the local water temperature mutation value to calculate the mutation diffusion coefficient of the fish tank; Combining the ecological sensitivity coefficient, the water temperature fluctuation gradient, the equipment response baseline value, and the mutation diffusion coefficient, the collaborative control efficiency index of the global water temperature collaborative controller is calculated using the following formula: ; in, Indicates the collaborative control effectiveness index. Indicates the ecological sensitivity coefficient. Indicates the water temperature fluctuation gradient. Indicates the device response baseline value. Indicates the historical minimum mutation rate. This represents the response delay time, and k represents the calibration coefficient. This represents the mutation diffusion coefficient.

[0011] Optionally, the step of acquiring real-time water temperature data and aquatic organism activity trajectory data of different zones within the aquarium, and identifying the water temperature conduction characteristics of different functional areas within the aquarium to construct a multi-probe temperature control network for the aquarium, includes: Based on the real-time water temperature data of the partition, the aquarium is divided into temperature-sensitive areas and temperature-uniform areas. Based on the temperature-sensitive area and the temperature-uniform area, a three-dimensional temperature control hierarchy structure for the fish tank is set up. The spatial distribution characteristics of aquatic organisms corresponding to the activity trajectory data of the aquatic organisms are analyzed to generate a distribution map of biological aggregation hotspots in the aquarium. Based on the biological hotspot distribution map, deploy the temperature probe combination of the three-dimensional temperature control hierarchical structure; The optimal temperature range for the aquarium's organisms is determined by using historical water temperature regulation data from the aquarium. By combining the optimal temperature zone of the organism with the real-time water temperature data of the zone, the water temperature deviation coefficient of each area of ​​the aquarium is calculated; Based on the aforementioned water temperature conduction characteristics, the temperature control response priority of each area of ​​the fish tank is set; Based on the water temperature deviation coefficient and the temperature control response priority, a multi-level temperature control response rule for the fish tank is formulated. Configure the linkage communication link between the three-dimensional temperature control hierarchy structure and the temperature probe combination; By integrating the multi-level temperature control response rules, the three-dimensional temperature control hierarchy, the temperature probe combination, and the linkage communication link, a multi-probe temperature control network for the aquarium is constructed.

[0012] Optionally, setting the multi-parameter linkage control threshold of the fish tank according to the compatible water temperature range includes: The core parameter set of the aquarium is analyzed and the corresponding ecological features are extracted. The core parameter set includes water temperature acquisition parameters, equipment operation parameters and environmental correlation parameters. Based on the aforementioned compatible water temperature range, the aquarium's water temperature safety fluctuation sub-range is divided; Based on the water temperature safety fluctuation sub-interval and the ecological correlation characteristics, the coordinated regulation requirements of the core parameter group are identified, and the ecological adaptability index of the core parameter group is determined. Based on the aforementioned coordinated control requirements, the linkage control unit of the core parameter group is set up; Define the response priority weights of the linkage control unit; The multi-parameter linkage control threshold of the fish tank is set using the ecological adaptability index and the response priority weight.

[0013] Optionally, generating the adaptive temperature control command for the fish tank based on the collaborative control efficiency index includes: Based on the collaborative control efficiency index, the ecologically specific sensitive parameters of the fish tank are selected. Define the controller dynamic performance threshold corresponding to the collaborative control performance index; Based on the controller's dynamic performance threshold and the ecologically specific sensitive parameters, the multi-dimensional temperature adjustment range of the fish tank is set. Retrieve a library of preset temperature control parameter combinations that match the multi-dimensional temperature adjustment range; Analyze the dynamic adaptation conditions of each parameter combination in the preset temperature control parameter combination library; Based on the dynamic adaptation conditions, an adaptive temperature control command for the fish tank is generated.

[0014] Optionally, determining the compatibility temperature range for different aquatic organisms in the aquarium based on the suitable water temperature range and the biological tolerance threshold includes: Identify the different ecological function types of the aquatic organisms in the aquarium, and determine the temperature interaction coefficients corresponding to the ecological function types; Based on the ecological function type and the temperature interaction coefficient, a temperature adaptation priority partitioning for the suitable water temperature range is established. Based on the temperature adaptation priority partitioning, identify the interval constraint boundaries of the biological tolerance threshold; Based on the temperature adaptation priority partitioning and the interval constraint boundary, a stratified water temperature adaptation rule is constructed for different aquatic organisms in the fish tank. Based on the stratified water temperature adaptation rules, the compatible water temperature ranges for different aquatic organisms in the fish tank are determined.

[0015] To address the aforementioned problems, this invention also provides a multi-probe-based intelligent aquarium water temperature control system, the system comprising: The temperature control module is used to acquire real-time water temperature data of different zones in the aquarium and aquatic organism activity trajectory data, and to identify the water temperature conduction characteristics of different functional areas in the aquarium in order to construct a multi-probe temperature control network for the aquarium. The strategy balancing module is used to collect water temperature fluctuation data under the multi-probe temperature control network, establish a global water temperature change heat map of the aquarium based on the water temperature fluctuation data, and generate a zone temperature balancing method for the aquarium based on the global water temperature change heat map and the real-time zone water temperature data. The water temperature adaptation module is used to analyze the suitable water temperature range and biological tolerance threshold of different aquatic organisms in the aquarium, and to determine the compatible water temperature range of different aquatic organisms in the aquarium based on the suitable water temperature range and the biological tolerance threshold. The collaborative control module is used to set the multi-parameter linkage control threshold of the aquarium according to the compatible water temperature range, and to configure the global water temperature collaborative controller of the aquarium based on the multi-parameter linkage control threshold. The collaborative performance evaluation module is used to monitor the local water temperature change value of the fish tank and the response delay time of the global water temperature collaborative controller in real time, so as to calculate the collaborative control performance index of the global water temperature collaborative controller, and generate the adaptive temperature control command of the fish tank based on the collaborative control performance index. The solution output module is used to combine the partitioned temperature balancing method, the global water temperature collaborative controller, and the adaptive temperature control command to output the intelligent water temperature control solution for the fish tank.

[0016] Compared to the problems described in the background art, the embodiments of the present invention acquire real-time water temperature data and aquatic organism activity trajectory data of the aquarium zones, and identify the water temperature conduction characteristics of different functional areas within the aquarium to construct a multi-probe temperature control network for the aquarium. This integrates discrete zone water temperature information and dynamic biological activity data to form a multi-regional, interconnected temperature control sensing system. This provides a structured framework for real-time capture of the adaptation relationship between changes in aquarium water temperature distribution and biological activity needs, ensuring comprehensive control over the complex water temperature environment of the aquarium and improving the intelligent adjustment accuracy and ecological adaptability of the multi-probe temperature control network for aquarium water temperature. Furthermore, the embodiments of the present invention, based on the water temperature wave... By using dynamic data to establish a heat map of the overall water temperature change in the aquarium, the dynamic fluctuations and spatial distribution differences of water temperature in different functional areas of the aquarium can be accurately correlated, ensuring real-time detection of the risk of overall water temperature imbalance. This embodiment of the invention generates a zoned temperature balancing method for the aquarium based on the overall water temperature change heat map and the real-time zoned water temperature data. This improves the ability to perceive the balance state of the complex water temperature environment in the aquarium, and lays the foundation for subsequent accurate location of temperature imbalance areas and optimization of multi-probe control strategies, enhancing the accuracy and dynamic adaptability of the multi-probe temperature control network for the balanced control of aquarium water temperature. This embodiment of the invention also extracts suitable water temperatures for different aquatic organisms in the aquarium. By defining the appropriate temperature range and biological tolerance threshold, a generalized temperature control mode can be upgraded to a biologically adapted control mechanism, precisely matching the survival needs of different species and strengthening the dynamic balance of the aquarium water environment and the full-cycle maintenance of biological health. Furthermore, this embodiment of the invention determines the compatible water temperature range for different aquatic organisms in the aquarium based on the suitable water temperature range and the biological tolerance threshold. This allows the multi-probe aquarium water temperature intelligent control system to dynamically adjust the zoned temperature control strategy according to biological characteristics, shifting from single-species temperature control to multi-biological collaborative regulation. This enhances the ability and stability of water temperature control to ensure the aquatic ecological balance and creates a safe and compatible water temperature environment for various organisms in the aquarium. This invention, by setting a multi-parameter linkage control threshold for the aquarium based on the aforementioned compatible water temperature range, can achieve precise and coordinated output of multi-probe water temperature regulation, improve the responsiveness to micro-fluctuations in the aquarium water temperature, and enhance the ecological adaptability of water temperature control in multi-species mixed-species scenarios. Furthermore, by configuring a global water temperature collaborative controller for the aquarium based on the aforementioned multi-parameter linkage control threshold, this invention can adapt to the water temperature fluctuation characteristics of different areas of the aquarium, forming a precise and collaborative global water temperature regulation system. This ensures efficient correction of complex water temperature fluctuations in multi-species mixed-species scenarios, and improves the stability and ecological adaptability of intelligent water temperature control in multi-probe aquariums.This invention, through real-time monitoring of local water temperature fluctuations in the aquarium and the response delay of the global water temperature co-controller, calculates the co-control efficiency index of the global water temperature co-controller. This integrates local water temperature anomaly fluctuation information acquired by multi-probe monitoring with the controller's real-time response time information into a unified efficiency evaluation dimension, accurately quantifying the controller's co-control capability in responding to local water temperature fluctuations. Furthermore, based on the co-control efficiency index, this invention generates adaptive temperature control commands for the aquarium, allowing the multi-probe aquarium water temperature intelligent control system to dynamically adjust its zone control strategy according to the efficiency index. This improves the control accuracy for complex water temperature fluctuations, shifting from passive response to active adaptation and enhancing parameter adjustment during aquarium water temperature control. The timely and stable operation of the system is improved. Finally, this embodiment of the invention, by combining the partitioned temperature balancing method, the global water temperature collaborative controller, and the adaptive temperature control command, outputs an intelligent water temperature control scheme for the aquarium. This scheme replaces single-location temperature control with partitioned monitoring and adjustment. The global water temperature collaborative controller responds in real-time to sudden changes in local water temperature to dynamically coordinate the operating status of heating / cooling equipment in each area, avoiding the problem of insufficient water temperature control accuracy caused by single-sensor acquisition and fixed threshold standards. Simultaneously, the adaptive temperature control command matches the real-time water temperature changes in different areas of the aquarium, reducing the impact of local high or low temperatures on aquatic organisms and the risk of erroneous equipment start-up and shutdown. This achieves a precise balance between control safety and water temperature stability under different abnormal water temperature scenarios. Therefore, the intelligent aquarium water temperature control method and system based on multiple probes provided by this embodiment of the invention can improve the accuracy of aquarium water temperature control. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating an intelligent aquarium water temperature control method based on multiple probes, as provided in an embodiment of the present invention. Figure 2 This is a schematic diagram of the internal temperature control principle of a global water temperature collaborative controller for a multi-probe-based intelligent control method for aquarium water temperature, provided in an embodiment of the present invention. Figure 3 This is a functional block diagram illustrating an embodiment of the present invention for implementing a multi-probe-based intelligent aquarium water temperature control system.

[0018] The objectives, features, and advantages of this invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0019] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0020] This application provides a method for intelligent control of aquarium water temperature based on multiple probes. The executing entity of this method includes, but is not limited to, at least one electronic device that can be configured to execute the method provided in this application, such as a server or a terminal. In other words, the method can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster.

[0021] Reference Figure 1 The diagram shown is a flowchart illustrating a multi-probe-based intelligent aquarium water temperature control method according to an embodiment of the present invention. In this embodiment, the multi-probe-based intelligent aquarium water temperature control method includes: S1. Acquire real-time water temperature data and aquatic organism activity trajectory data of the aquarium zones, and identify the water temperature conduction characteristics of different functional areas within the aquarium to construct a multi-probe temperature control network for the aquarium.

[0022] This invention acquires real-time water temperature data and aquatic organism activity trajectory data of different zones within an aquarium, and identifies the water temperature conduction characteristics of different functional areas within the aquarium. This allows for the construction of a multi-probe temperature control network for the aquarium. This network integrates discrete zone water temperature information with dynamic biological activity data, forming a multi-regional, interconnected temperature control sensing system. It provides a structured framework for real-time capture of the adaptation relationship between changes in aquarium water temperature distribution and biological activity needs, ensuring comprehensive control over the complex water temperature environment of the aquarium and improving the intelligent adjustment accuracy and ecological adaptability of the multi-probe temperature control network for aquarium water temperature.

[0023] The fish tank refers to a closed or semi-closed container used for artificially raising aquatic organisms (including but not limited to fish, crustaceans, mollusks, aquatic plants, etc.); the real-time water temperature data refers to the water temperature values ​​and temperature change trends of each area continuously acquired by temperature sensing devices (such as high-precision thermocouple sensors, NTC thermistor sensors, etc., with a measurement accuracy of not less than ±0.1℃) deployed in different functional areas of the fish tank within a preset acquisition period (the acquisition period can be set from 1 second / time to 5 minutes / time according to temperature control requirements); the aquatic organism activity trajectory data refers to structured data formed by continuous monitoring of the spatial location, movement path, dwell time, and activity frequency of target aquatic organisms in the fish tank through image acquisition equipment (such as high-definition cameras) or biological positioning sensors (such as miniature RFID tags suitable for small aquatic organisms, optical positioning modules, etc.), and data processing (including image recognition, coordinate transformation, trajectory fitting, etc.); the different functional areas refer to the water areas within the fish tank according to their functions. The layout of equipment and the survival needs of aquatic organisms are considered when dividing the internal space of an aquarium into independent or related areas with specific purposes, including a habitat area, a filtration area, a water circulation area, and a special organism area. The water temperature conduction characteristics refer to the patterns and characteristics of water temperature changes between or within different functional areas of the aquarium due to heat transfer (including heat conduction, heat convection, and heat radiation). These characteristics are jointly determined by the physical structure of the area (e.g., area volume, boundary material), water flow state (e.g., flow velocity, flow direction), heat dissipation / heat generation of surrounding equipment (e.g., heater power, filtration equipment operating temperature), and environmental interference factors (e.g., fluctuations in ambient room temperature). The multi-probe temperature control network refers to an integrated temperature control system based on the water temperature conduction characteristics of different functional areas of the aquarium. This system deploys multiple temperature probes in key areas (e.g., areas with weak water temperature conduction, areas with dense organisms, and areas surrounding equipment), and combines them with a data processing module, a control decision module, and temperature control execution devices (e.g., heaters, coolers, temperature-regulating water pumps).

[0024] As an embodiment of the present invention, the step of acquiring real-time water temperature data and aquatic organism activity trajectory data of different zones in the aquarium, and identifying the water temperature conduction characteristics of different functional areas within the aquarium to construct a multi-probe temperature control network for the aquarium includes: Based on the real-time water temperature data of the partition, the aquarium is divided into temperature-sensitive areas and temperature-uniform areas. Based on the temperature-sensitive area and the temperature-uniform area, a three-dimensional temperature control hierarchy structure for the fish tank is set up. The spatial distribution characteristics of aquatic organisms corresponding to the activity trajectory data of the aquatic organisms are analyzed to generate a distribution map of biological aggregation hotspots in the aquarium. Based on the biological hotspot distribution map, deploy the temperature probe combination of the three-dimensional temperature control hierarchical structure; The optimal temperature range for the aquarium's organisms is determined by using historical water temperature regulation data from the aquarium. By combining the optimal temperature zone of the organism with the real-time water temperature data of the zone, the water temperature deviation coefficient of each area of ​​the aquarium is calculated; Based on the aforementioned water temperature conduction characteristics, the temperature control response priority of each area of ​​the fish tank is set; Based on the water temperature deviation coefficient and the temperature control response priority, a multi-level temperature control response rule for the fish tank is formulated. Configure the linkage communication link between the three-dimensional temperature control hierarchy structure and the temperature probe combination; By integrating the multi-level temperature control response rules, the three-dimensional temperature control hierarchy, the temperature probe combination, and the linkage communication link, a multi-probe temperature control network for the aquarium is constructed.

[0025] The temperature-sensitive area refers to a specific spatial region within the aquarium where the water temperature fluctuates beyond a preset threshold due to external disturbances (such as heat / cold sources, water flow changes) or inherent characteristics (such as poor local water flow). The temperature-uniform region refers to a spatial region within the aquarium where the water temperature is minimally affected by disturbances, water flow is balanced, and temperature fluctuations are below the preset threshold. The three-dimensional temperature control hierarchy refers to a multi-dimensional temperature control management system constructed based on the spatial distribution of the temperature-sensitive and temperature-uniform regions within the aquarium, combined with a three-dimensional aquatic environment (horizontal zoning + vertical stratification). Specifically, A 1.2m × 0.5m × 0.6m aquarium can be divided into 3 horizontal zones (left equipment zone, middle biological zone, right static zone) and 2 vertical layers (upper layer 10cm below the water surface, lower layer 10cm above the tank bottom), forming 6 three-dimensional levels. The "middle biological zone - lower layer" (temperature sensitive + bio-aggregate) is designated as the first level (probe density 1 / 0.2㎡, sampling frequency 1 time / 2 seconds), and the "right static zone - upper layer" (uniform temperature + no bio-aggregate) is designated as the third level (probe density 1 / 1㎡, sampling frequency 1 time / 30 seconds). "Sexual behavior" refers to the quantitative description of the spatial behavioral characteristics of aquatic organisms in an aquarium, including their location, activity range, and aggregation frequency at different times and under different environmental conditions (such as light, water temperature, and food distribution). For example, tropical fish tend to concentrate in the lower middle layer of the aquarium between 9:00-11:00 and 16:00-18:00 (70% of their time spent there), while they disperse at the upper edge of the aquarium between 22:00 and 6:00 at night (60% of their time spent there). The biological aggregation hotspot distribution map refers to marking areas with high-frequency biological residence and activity based on the spatial distribution characteristics of aquatic organisms. The term "hotspot" is used to visually represent the spatial distribution of these hotspots in a heatmap format. The temperature probe combination refers to temperature probes of varying precision and sampling frequencies configured within a three-dimensional temperature control hierarchy based on the distribution map of biological aggregation hotspots. For example, four high-precision NTC probes (error ≤ ±0.1℃, sampling frequency 1 time / 2 seconds) are deployed in the primary hotspot area (biological aggregation + temperature sensitivity); two conventional NTC probes (error ≤ ±0.2℃, sampling frequency 1 time / 5 seconds) are deployed in the secondary hotspot area; and two low-cost thermistor probes (error ≤ ±0.2℃, sampling frequency 1 time / 5 seconds) are deployed in the non-hotspot area.The system uses one probe at 3℃ (sampling frequency 1 time / 30 seconds), forming a combined configuration of 7 probes. The historical water temperature regulation data refers to the collection of data from the aquarium temperature control system over the past 3 months, including water temperature monitoring records, equipment adjustment commands (such as heater power and water circulation speed), and biological status feedback (such as swimming frequency, food intake, and mortality rate). The optimal temperature range for aquatic organisms refers to the water temperature range corresponding to the optimal survival status (such as activity level, food intake, and health) of aquatic organisms, based on historical water temperature regulation data. For example, historical data shows that goldfish maintain a stable food intake of 4-5g / day, a swimming frequency of 45-55 times / minute, and no mortality records when the water temperature is 20-24℃; therefore, 20-24℃ is determined to be the optimal temperature range for aquatic organisms. The optimal temperature zone for the organism; the water temperature deviation coefficient is a dimensionless index that quantifies the degree of deviation between the real-time water temperature of each area of ​​the aquarium and the optimal temperature zone for the organism, used to judge the degree of abnormality in the water temperature of a region; the temperature control response priority refers to the order in which temperature control processing is set for each area of ​​the aquarium, combining water temperature conduction characteristics (such as heat diffusion rate, temperature regulation lag) and the water temperature deviation coefficient; the multi-level temperature control response rule refers to the differentiated temperature control operation strategy formulated based on the coupling result of the water temperature deviation coefficient and the temperature control response priority; the linkage communication link refers to the bidirectional data transmission channel connecting the temperature probe combination, the core control unit, and the temperature control execution devices (heating rod, water circulation pump, cooling plate) in the three-dimensional temperature control hierarchy structure.

[0026] Optionally, the temperature-sensitive area and temperature-uniform area of ​​the aquarium can be divided by the coefficient of variation method; the distribution map of biological aggregation hotspots in the aquarium can be generated by the kernel density estimation algorithm; the three-dimensional temperature control hierarchy structure of the aquarium can be set by the spatial grid modeling method; and the water temperature deviation coefficient of each area of ​​the aquarium can be calculated by the Euclidean distance algorithm.

[0027] S2. Collect water temperature fluctuation data under the multi-probe temperature control network, establish a global water temperature change heat map of the aquarium based on the water temperature fluctuation data, and generate a zone temperature balancing method for the aquarium based on the global water temperature change heat map and the real-time zone water temperature data.

[0028] This invention, through collecting water temperature fluctuation data from the multi-probe temperature control network, can capture the dynamic changes and frequency of water temperature in different functional areas (such as the biological habitat area and the filtration area) within the aquarium in real time, providing data support for accurately determining the priority of temperature control needs in each area.

[0029] The water temperature fluctuation data refers to the water temperature values ​​of each functional area continuously collected and recorded by temperature detection probes deployed in different functional areas of the aquarium (such as biological habitat area, filtration area, water circulation area, etc.) during the operation of the multi-probe temperature control network, within a preset collection period (the collection period can be set from 1 second / time to 5 minutes / time according to temperature control requirements).

[0030] Furthermore, by establishing a global water temperature change heatmap of the fish tank based on the water temperature fluctuation data, this embodiment of the invention can accurately correlate the dynamic fluctuations and spatial distribution differences of water temperature in different functional areas of the fish tank, ensuring real-time capture of the risk of global water temperature imbalance.

[0031] The aforementioned global water temperature change heat map refers to a graphical data carrier that uses water temperature fluctuation data collected by the multi-probe temperature control network as its core foundation, and processes it through spatial coordinate mapping and temperature gradient visualization algorithms. This data carrier can intuitively reflect the dynamic changes in water temperature and regional distribution differences within the entire space of the aquarium.

[0032] As an embodiment of the present invention, the step of establishing a global water temperature change heatmap of the fish tank based on the water temperature fluctuation data includes: Based on the water temperature fluctuation data, construct the regional temperature difference feature matrix of the fish tank; The time-series temperature data of each functional area of ​​the fish tank are separated from the water temperature fluctuation data; Identify the extreme points and fluctuation period characteristics of regional water temperature fluctuations in the temperature time series data; Based on the extreme points of water temperature fluctuation in the region, temperature difference slices for the corresponding time period are extracted from the temperature difference feature matrix of the region. The three-dimensional spatial coordinate data of the fish tank is obtained, and combined with the temperature difference slice, the regional temperature gradient layout of the fish tank is generated. Based on the regional temperature gradient layout and the preset temperature color matching rules, the color mapping parameters of the fish tank are defined; Using the aforementioned fluctuation periodicity characteristics, an adaptive sampling frequency for the fish tank is set; Based on the color mapping parameters and the adaptive sampling frequency, a heat map of the global water temperature change in the fish tank is established.

[0033] The regional temperature difference feature matrix refers to a two-dimensional structured data matrix that stores the water temperature difference between different functional areas at the same time, using each functional area of ​​the aquarium as its row / column dimension and timestamps as its index. This matrix is ​​used to quantify the differences in water temperature distribution between areas. The temperature time series data refers to a sequence of water temperature data collected continuously in chronological order for a single functional area of ​​the aquarium. The regional water temperature fluctuation extreme points refer to the maximum or minimum water temperature points within a certain time period in the temperature time series data. The fluctuation periodicity feature refers to the periodic change pattern of water temperature over time in the temperature time series data. The temperature difference slice refers to the extraction of water temperature slices from the regional temperature difference feature matrix. A subset of temperature difference data within a specific time period corresponding to the "regional extreme point of water temperature fluctuation" is selected, containing temperature difference records for all functional area pairs within that time period, used to focus on regional difference analysis during periods of abnormal water temperature changes; the three-dimensional spatial coordinate data refers to three-dimensional coordinate system data used to describe the physical spatial location inside the aquarium, including the origin of the coordinate system, the direction of the coordinate axes, and the coordinate range of each functional area. The actual dimensions of the aquarium (length L, width W, height H) and the boundary positions of each functional area (such as the X, Y, and Z ranges of the biological habitat area) can be measured using a ruler or laser rangefinder; the regional temperature gradient layout refers to combining the three-dimensional spatial coordinate data with the temperature difference. After slicing and interpolating to complete the temperature data of the entire aquarium space, a grid layout reflecting the correspondence between "temperature and spatial location" is formed. This grid layout includes the temperature values ​​and coordinates of all grid cells, visually representing the gradient trend of temperature change in space. The preset temperature color matching rules refer to standardized rules pre-defined to quantify the correspondence between temperature values ​​and visual colors, including temperature range divisions and the corresponding color system (e.g., RGB value range) for each range. The color mapping parameters refer to the correspondence parameters of "aquarium grid cell coordinates - temperature value - RGB color value" calculated according to the preset temperature color matching rules, used to map the regional temperature... Temperature data in the gradient layout is converted into visual colors; the adaptive sampling frequency refers to the dynamic adjustment of the aquarium water temperature data acquisition frequency based on the water temperature fluctuation cycle characteristics of each functional area of ​​the aquarium. The adaptive sampling frequency (times / minute) = 60 / (fluctuation cycle duration (minutes) × sampling coefficient k), where the sampling coefficient k is a dynamically adjusted parameter (value range 0.1-0.5). For example, when the real-time temperature time series data shows that the water temperature is close to the extreme point of fluctuation (such as time ≤ T / 10 from the extreme point, where T is the fluctuation cycle), k is 0.1 (high frequency acquisition); when the water temperature is in a stable stage within the cycle, k is 0.5 (low frequency acquisition).

[0034] Optionally, the regional temperature difference feature matrix of the fish tank can be constructed using a matrix filling algorithm (such as zero-filling) through Python's NumPy library; the extreme points of regional water temperature fluctuations in the temperature time series data can be identified using a sliding window extreme value detection algorithm; and the fluctuation periodic features in the temperature time series data can be identified using a Fourier transform algorithm.

[0035] Furthermore, by generating a zoned temperature balancing method for the aquarium based on the global water temperature change heat map and the real-time zoned water temperature data, this embodiment of the invention can improve the ability to perceive the balanced state of the complex water temperature environment of the aquarium. At the same time, it lays the foundation for subsequent accurate location of temperature imbalance areas and optimization of multi-probe control strategies, and enhances the accuracy and dynamic adaptability of the multi-probe temperature control network for the balanced control of aquarium water temperature.

[0036] The aforementioned zoned temperature balancing method refers to a specific implementation plan or strategy formulated based on the overall water temperature distribution pattern of the aquarium and real-time water temperature data of each area to make the water temperature in different zones of the aquarium tend to be stable and uniform.

[0037] As an embodiment of the present invention, the step of generating a zoned temperature balancing method for the fish tank based on the global water temperature change heat map and the real-time zoned water temperature data includes: Based on the global water temperature change heat map, the temperature imbalance area of ​​the fish tank was identified; Analyze the temperature distribution pattern of the global water temperature change heatmap and extract the dynamic water temperature fluctuation characteristics of the real-time water temperature data of the zones. Based on the temperature distribution pattern and the dynamic water temperature fluctuation characteristics, determine the temperature control medium type of the fish tank; Construct a dynamic balance strategy matrix for the temperature control medium regulation type in different temperature imbalance regions; Based on the real-time water temperature data of the partition, locate the media control linkage node of the fish tank; Based on the medium regulation linkage node, determine the equalization trigger threshold corresponding to the temperature control medium regulation type; Based on the dynamic balancing strategy matrix and the balancing trigger threshold, adaptive balancing control commands are generated for different zones within the fish tank. The adaptive balancing control command generates a zoned temperature balancing method for the fish tank.

[0038] The temperature imbalance area refers to a localized area in the aquarium where the water temperature deviates from the preset target temperature range (e.g., 25±1℃), or the temperature difference between adjacent areas exceeds a set threshold (e.g., ≥2℃), resulting in damage to the stability of the aquatic environment. The temperature distribution pattern refers to the spatial distribution characteristics of water temperature presented in the overall water temperature change heatmap, including the location, range, and shape of high-temperature / low-temperature zones, as well as the direction and steepness of temperature gradients. The dynamic water temperature fluctuation characteristics refer to the amplitude, frequency, trend, and abrupt changes in the water temperature of each zone over time in the real-time data of zoned water temperatures. The temperature control medium adjustment type... The term "type" refers to the classification of operating modes of physical media used to regulate water temperature (such as heaters, cooling pads, circulating water pumps, etc.), including combinations of adjustable attributes such as media type, intensity of action, and operating parameters. The "dynamic balance strategy matrix" refers to a two-dimensional matrix with temperature imbalance regions as rows and temperature control media regulation types as columns, where each element represents the "dynamic correspondence between media regulation parameters and regional temperature differences." The "media regulation linkage node" refers to the physical connection or logical interaction interface between different temperature control media (such as heaters, water pumps) and zone monitoring points in the aquarium temperature control system. The "equilibrium trigger threshold" refers to the critical temperature that triggers temperature control media regulation. The conditions are as follows: when the zone water temperature or the temperature difference between zones reaches a certain threshold, the corresponding dynamic balancing strategy is activated. For example, the "low temperature zone trigger threshold is T≤24℃" and the "adjacent zone temperature difference trigger threshold is ≥2℃". When the bottom zone water temperature drops to 23.8℃ or the temperature difference between zones A and B reaches 2.1℃, heating or water flow adjustment is automatically triggered. The different zones refer to sub-regions with independent water temperature monitoring and control capabilities, divided according to the physical structure of the aquarium (such as depth, spatial location) or functional requirements (such as feeding area, filtration area). For example, vertically divided into "surface zone (water depth 0-10cm)" and "middle zone (water depth 10cm)". The area is divided into two zones: "-30cm" and "bottom zone (water depth 30-50cm)". Horizontally, it is divided into "left feeding zone" and "right filtration zone". The adaptive balance control command refers to a control command generated for different zones based on a dynamic balance strategy matrix and balance trigger threshold. The command can automatically adjust parameters according to real-time water temperature changes. For example, "If the bottom zone water temperature is ≤24℃ and the fluctuation range σ=0.8℃, start low-power heating (200W) and check the water temperature after 10 minutes; if the water temperature rises to 24.5℃, then reduce to 100W heating; if the standard is not met within 10 minutes, switch to medium-power heating (500W)".

[0039] Optionally, the dynamic water temperature fluctuation characteristics of the real-time water temperature data of the partition can be extracted by a linear regression model; the equalization trigger threshold corresponding to the temperature control medium adjustment type can be determined by Monte Carlo simulation; and the adaptive equalization control commands for different partitions in the aquarium can be generated by a fuzzy control algorithm.

[0040] As another embodiment of the present invention, the step of locating the media control linkage node of the fish tank based on the real-time water temperature data of the partition includes: Identify the temperature control medium of the fish tank and its corresponding temperature control device, and obtain the zone sensor corresponding to the real-time water temperature data of the zone; Check the signal transmission ports of the temperature control device and the zone sensor; Based on the signal transmission port, the communication protocol specification between the temperature control device and the partition sensor is analyzed. Using the aforementioned communication standard protocol, the communication link relationship between the temperature control device and the partition sensor is analyzed; Based on the communication link relationship, establish a node association map between the temperature control device and the zone sensor; The media control linkage node of the fish tank can be located by using the node association map.

[0041] The temperature control medium refers to the physical carrier or energy form used to regulate the aquarium water temperature, changing the water temperature through heat transfer, energy conversion, etc., including refrigerants, electrical energy, circulating water, etc. The temperature control device refers to the hardware device that directly performs temperature control operations, converting the energy of the temperature control medium into a water temperature regulation effect, including heaters (converting electrical energy into heat energy), semiconductor cooling chips (cooling through refrigerants), variable frequency water pumps (driving circulating water to transfer heat), solenoid valves (controlling water flow to regulate heat exchange efficiency), etc. The zone sensors refer to sensing devices deployed in each zone of the aquarium for real-time acquisition of water temperature data in their respective areas. They are the core components for obtaining real-time zone water temperature data, such as the DS18B20 temperature sensor deployed in the surface zone (sampling accuracy ±0.5℃) and the SHT30 temperature and humidity integrated sensor deployed in the bottom zone (simultaneously monitoring water temperature and ambient humidity). The signal transmission port refers to the hardware port that enables physical connection or signal transmission between the temperature control device and the zone sensors, such as the GPIO interface between the heater and the zone sensors (used to transmit switch control signals), the water pump and... The sensor has an RS485 interface (for transmitting water temperature data and speed adjustment commands) and a USB interface (for power supply and data upload). The communication standard protocol refers to the standardized rules followed when the temperature control device and the zone sensor interact with each other, including data format, transmission timing, and verification methods, to ensure the accuracy and consistency of communication. The communication link relationship refers to the data flow direction, interaction logic, and dependency relationship formed between the temperature control device and the zone sensor based on the communication standard protocol. For example, a one-way data link where the sensor sends water temperature data to the controller, and the controller generates commands to drive the heater. The node association diagram is a topology diagram that graphically and intuitively displays the physical connections and communication link relationships between the temperature control device, the zone sensor, and the signal transmission port. In the node association diagram, circular nodes represent sensors (labeled "Z1-S"), square nodes represent temperature control devices (labeled "H1-Heater"), line segments indicate interface types (such as "RS485") and communication protocols (such as "MQTT"), and arrows indicate the data flow direction (such as Z1-S→H1).

[0042] Optionally, the communication protocol between the temperature control device and the partition sensor can be parsed using a packet capture tool, such as Wireshark; the communication link relationship between the temperature control device and the partition sensor can be analyzed using a directed graph model.

[0043] S3. Analyze the suitable water temperature range and biological tolerance threshold of different aquatic organisms in the aquarium, and determine the compatible water temperature range of different aquatic organisms in the aquarium based on the suitable water temperature range and the biological tolerance threshold.

[0044] This invention, by extracting the suitable water temperature range and biological tolerance threshold of different aquatic organisms in the aquarium, can upgrade the generalized temperature control mode into a biologically adapted regulation mechanism, accurately matching the survival needs of different species, and strengthening the dynamic balance of the aquarium water environment and the full-cycle maintenance of biological health.

[0045] The aquatic organisms referred to here are various aquatic organisms living in the aquarium environment, including fish, crustaceans, mollusks, and aquatic plants. The suitable water temperature range refers to the water temperature range that can meet the normal physiological activities (such as feeding, growth, and reproduction) of specific aquatic organisms. For example, the suitable water temperature range for guppies is 22-26℃, within which they are highly active and have a strong reproductive capacity. The suitable water temperature range for centipede grass is 20-28℃, within which photosynthetic efficiency is highest and growth is good. The biological tolerance threshold refers to the water temperature limit that aquatic organisms can withstand (including upper and lower thresholds). When the water temperature exceeds this threshold, the organism will exhibit physiological abnormalities (such as metabolic disorders and stress responses), and prolonged exposure may lead to death.

[0046] Optionally, the suitable water temperature range for different aquatic organisms in the aquarium can be analyzed using clustering analysis algorithms. For example, clustering analysis can be performed on known suitable water temperature data of aquatic organisms of the same family / genus, and transfer learning can be applied to closely related species to quickly determine their suitable range. The biological tolerance threshold for different aquatic organisms in the aquarium can be obtained using a Logistic regression model. The specific steps are as follows: statistically analyze the 24-hour survival rate of multiple samples (e.g., 30 goldfish) at different water temperatures; use a Logistic regression model to fit the relationship between survival probability and water temperature to obtain an S-shaped curve; based on the S-shaped curve, take the water temperature value corresponding to a survival probability of 5% (e.g., upper limit 30℃, lower limit 4℃) as the tolerance threshold.

[0047] Furthermore, by determining the compatible water temperature range for different aquatic organisms in the aquarium based on the suitable water temperature range and the biological tolerance threshold, the embodiments of the present invention enable the multi-probe aquarium water temperature intelligent control system to dynamically adjust the zoned temperature control strategy according to the biological characteristics, shifting from single-species temperature control to multi-biological collaborative regulation, enhancing the water temperature control's ability to ensure the ecological balance and stability of the aquarium, and creating a safe and compatible water temperature environment for various organisms in the aquarium.

[0048] The compatible water temperature range refers to the water temperature range in an aquarium where multiple aquatic organisms are kept together, which simultaneously meets the suitable water temperature range for all organisms and does not exceed the tolerance threshold of any one organism. For example, if guppies (suitable water temperature 22-26℃, tolerance threshold 18-30℃), cherry shrimp (suitable water temperature 20-26℃, tolerance threshold 15-28℃), and centipede grass (suitable water temperature 20-28℃, tolerance threshold 10-32℃) are kept together in the aquarium, then the compatible water temperature range for the three is 22-26℃.

[0049] As an embodiment of the present invention, determining the compatibility water temperature range for different aquatic organisms in the fish tank based on the suitable water temperature range and the biological tolerance threshold includes: Identify the different ecological function types of the aquatic organisms in the aquarium, and determine the temperature interaction coefficients corresponding to the ecological function types; Based on the ecological function type and the temperature interaction coefficient, a temperature adaptation priority partitioning for the suitable water temperature range is established. Based on the temperature adaptation priority partitioning, identify the interval constraint boundaries of the biological tolerance threshold; Based on the temperature adaptation priority partitioning and the interval constraint boundary, a stratified water temperature adaptation rule is constructed for different aquatic organisms in the fish tank. Based on the stratified water temperature adaptation rules, the compatible water temperature ranges for different aquatic organisms in the fish tank are determined.

[0050] The ecological function type refers to the functional category of aquarium organisms based on their role and function in the ecosystem, including core producers, core consumers, decomposers / cleaners, etc. The temperature interaction coefficient is a numerical indicator that quantifies the degree of mutual influence between organisms of different ecological function types due to water temperature changes. Its value range is typically [-1, 1]. A positive temperature interaction coefficient indicates synergistic water temperature adaptability (a suitable water temperature for one organism is beneficial to the other), while a negative temperature interaction coefficient indicates conflicting water temperature adaptability (a suitable water temperature for one organism is detrimental to the other). A larger absolute value indicates a stronger interaction. The Pearson correlation coefficient can be used to calculate the interaction between the two types of organisms and the water temperature. The correlation between temperature and temperature is normalized to the [-1, 1] interval, which is the temperature interaction coefficient between the two. The temperature adaptation priority zoning refers to the hierarchical allocation of temperature control resources based on the ecological function type and temperature interaction coefficient of organisms. For example, the suitable water temperature range for core consumers (guppies) is 22-26℃, and because these organisms are the core of aquaculture and their temperature interaction coefficients are mostly positive (beneficial to other organisms), they have the highest priority. The suitable water temperature range for core producers (aquatic plants) is 20-28℃, and because aquatic plants provide basic ecological support for other organisms, they have the second highest priority. The suitable water temperature range for cleaners (cherry shrimp) is 20-26℃, and because cleaners have strong adaptability to water temperature, they have the lowest priority. The aforementioned temperature range constraint boundary refers to the critical boundary that cannot be breached in the compatible water temperature range, determined based on temperature adaptation priority zoning and the biological tolerance thresholds (upper and lower thresholds) of organisms in each ecological function type. For example, the tolerance threshold for a first-priority zone (guppies, suitable for 22-26℃) is 18-30℃, so the "core constraint boundary" of the compatible water temperature range is 22-26℃ (must fall entirely within this range). The tolerance threshold for a second-priority zone (aquatic plants, suitable for 20-28℃) is 10-32℃, so the "extended constraint boundary" of the compatible water temperature range is 20-28℃ (must cover the core constraint boundary and not exceed this range). The third-priority zone... The tolerance threshold for the zone (cherry shrimp, suitable for 20-26℃) is 15-28℃. Therefore, the "final constraint boundary" of the compatibility water temperature range is 20-26℃ (which must simultaneously meet the core and extended constraint boundaries and not exceed this range). The stratified water temperature adaptation rule refers to the differentiated water temperature control strategy formulated for organisms of different ecological function types based on the temperature adaptation priority zoning and interval constraint boundaries. For example, the compatibility water temperature range must completely cover the suitable water temperature range of 22-26℃ for core consumers, and the fluctuation range shall not exceed ±0.5℃. The compatibility water temperature range must have an overlap rate of ≥70% with the suitable water temperature range of 20-26℃ for cleaners, and not exceed their tolerance threshold of 15-28℃.

[0051] Optionally, the temperature adaptation priority partitioning of the suitable water temperature range can be established using the Analytic Hierarchy Process (AHP); the interval constraint boundary of the biological tolerance threshold can be identified using the boundary intersection operation model; and the stratified water temperature adaptation rules of aquatic organisms in the aquarium can be constructed using a rule reasoning engine (RRE).

[0052] S4. Based on the compatibility water temperature range, set the multi-parameter linkage control threshold of the fish tank, and configure the global water temperature collaborative controller of the fish tank based on the multi-parameter linkage control threshold.

[0053] This invention, by setting the multi-parameter linkage control threshold of the aquarium according to the compatible water temperature range, can achieve precise and coordinated output of multi-probe water temperature regulation, improve the fineness of response to micro-fluctuations in water temperature in the aquarium, and enhance the ecological adaptability of water temperature control in multi-species mixed-species scenarios.

[0054] The multi-parameter linkage control threshold refers to the critical boundary value with collaborative response logic set in the multi-probe aquarium water temperature intelligent control system, based on the compatible water temperature range where multiple aquatic organisms coexist in the aquarium. This threshold is set for multiple key control parameters (including water temperature directly related parameters and ecological support parameters) that affect water temperature stability and ecological adaptability.

[0055] As an embodiment of the present invention, setting the multi-parameter linkage control threshold of the fish tank according to the compatible water temperature range includes: The core parameter set of the aquarium is analyzed and the corresponding ecological features are extracted. The core parameter set includes water temperature acquisition parameters, equipment operation parameters and environmental correlation parameters. Based on the aforementioned compatible water temperature range, the aquarium's water temperature safety fluctuation sub-range is divided; Based on the water temperature safety fluctuation sub-interval and the ecological correlation characteristics, the coordinated regulation requirements of the core parameter group are identified, and the ecological adaptability index of the core parameter group is determined. Based on the aforementioned coordinated control requirements, the linkage control unit of the core parameter group is set up; Define the response priority weights of the linkage control unit; The multi-parameter linkage control threshold of the fish tank is set using the ecological adaptability index and the response priority weight.

[0056] The core parameter set refers to the set of key parameters in the aquarium water temperature intelligent control system that directly or indirectly affect water temperature stability and the survival status of organisms in the tank, and need to be incorporated into a multi-parameter linkage control system. These parameters include water temperature acquisition parameters, equipment operating parameters, and environmental parameters. Specifically, the water temperature acquisition parameters include real-time water temperature values ​​(unit: °C), water temperature change rate (unit: °C / min), and water temperature fluctuation amplitude (unit: °C) collected by multiple probes in different areas of the tank (e.g., upper water layer, middle water layer, bottom water layer, coral / aquatic plant attachment area) from which temperatures change. The equipment operating parameters include the real-time power (unit: W), operating time (unit: min), and start / stop frequency (unit: times / h) of the heater, and the cooling capacity (unit: W) of the chiller. The system is defined as follows: Operating status (standby / working), water flow rate of the circulating water pump (unit: L / h); Environmental parameters include room temperature (unit: ℃), air humidity (unit: %RH), ambient light duration (unit: h / d), and rate of change of ambient temperature (unit: ℃ / h); Ecological characteristics refer to the mapping relationship between the changing states of each parameter in the core parameter group and the physiological activities, survival adaptability, and ecosystem balance of organisms in the aquarium (such as fish, corals, and aquatic plants). For example, if the heater's single start-stop interval is <10 min, and the local water temperature difference in the tank is ≥1.5℃, it will increase the yellowing rate of aquatic plant leaves (such as centipede grass) by 20%; The water temperature safety fluctuation sub-range refers to the compatibility water temperature range (i.e., the tank temperature range). The aquarium is divided into sub-ranges with different safety levels and control requirements, based on the suitable water temperature range for all organisms and the organisms' tolerance limits to water temperature fluctuations. The coordinated control requirement refers to the specific control targets and behavioral requirements for adjusting multiple parameters in coordination when the water temperature deviates from the core safety zone, or when a parameter in the core parameter group fluctuates abnormally, in order to bring the water temperature back to the compatible water temperature range and ensure the survival needs of the organisms. For example, if the water temperature enters the critical intervention zone (e.g., 25.2℃, lower than the core safety zone of 26℃) and the ambient room temperature continues to decrease (at a rate of 0.3℃ / h), the coordinated control requirement is: "Increase the heater power to 80% (from 50%), increase the circulating water pump speed by 20% (to accelerate the uniform diffusion of water temperature), and turn off the aquarium top." Cover the ventilation openings (to reduce heat loss); the ecological adaptability index refers to a dimensionless index that quantifies the adaptability of the core parameter group linkage control scheme to the aquarium ecosystem (biological survival, environmental balance), with a value range of [0,1]. The closer the index value is to 1, the more the control scheme meets the needs of biological survival and ecological balance; the linkage control unit refers to a functional module in the aquarium multi-parameter linkage control system that is responsible for executing specific parameter control tasks and has independent control logic and hardware support, including a zoned temperature control unit, a water flow adjustment unit, and an environmental adaptation unit; the response priority weight refers to the weight coefficient assigned to each unit based on the importance of the linkage control unit to water temperature stability and ecosystem balance, with a value range of [0,1].

[0057] For example, assuming the compatible water temperature range is 25-28℃ (for tropical fish + aquatic plant mixed breeding scenario), the water temperature safety fluctuation sub-ranges are divided as follows: Core safety zone: 26-27℃, within this range the water temperature fluctuation range is ≤0.3℃, the organisms have no stress response, and no active control needs to be initiated; Warning buffer zone: 25.5-25.9℃, 27.1-27.5℃, within this range the water temperature fluctuation range is 0.3-0.5℃, the organisms show slight stress (such as a slight decrease in activity), and mild linkage control needs to be initiated (such as fine-tuning the heater power); Critical intervention zone: 25-25.4℃, 27.6-28℃, within this range the water temperature fluctuation range is >0.5℃, the organisms show obvious stress (such as stopping feeding), and emergency linkage control needs to be initiated (such as the heater running at full power + adjusting the circulating water flow).

[0058] Optionally, the ecological adaptability index of the core parameter group can be determined using a weighted summation model based on the analytic hierarchy process (AHP); the response priority weight of the linkage control unit can be defined using the entropy weight method.

[0059] Furthermore, by configuring the global water temperature collaborative controller of the aquarium based on the multi-parameter linkage control threshold, the embodiments of the present invention can adapt to the water temperature fluctuation characteristics of different areas of the aquarium, forming a precise and collaborative global water temperature regulation system, ensuring efficient correction of complex water temperature fluctuations in multi-species mixed-species scenarios, and improving the stability and ecological adaptability of intelligent water temperature control in multi-probe aquariums.

[0060] The aforementioned global water temperature coordinating controller refers to an integrated control unit that integrates four core functional modules—multi-region water temperature balancing, dynamic power adjustment, intelligent emergency response, and multi-device compatible communication—based on multi-parameter linkage control thresholds. It achieves precise and coordinated control of the entire aquarium water temperature through zoned control channels and data interaction nodes.

[0061] As an embodiment of the present invention, configuring the global water temperature co-controller of the fish tank based on the multi-parameter linkage control threshold includes: By utilizing the parameter correlation characteristics of the multi-parameter linkage control threshold, the zone control channels and data interaction nodes of the fish tank are determined; Based on the partition control channel and the data interaction node, a multi-zone water temperature balancing module for the fish tank is set up. Identify the control precision requirements corresponding to the multi-parameter linkage control threshold, so as to set the adjustable response rate range of the partition control channel; The dynamic power adjustment module of the fish tank is deployed according to the adjustable response rate range; Define the range switching conditions and the recovery time for the control failure of the multi-parameter linkage control threshold to set up the intelligent emergency module of the fish tank; Query the device communication protocol associated with the multi-parameter linkage control threshold to deploy the multi-device compatible communication module of the fish tank; The multi-zone water temperature equalization module, the dynamic power adjustment module, the intelligent emergency module, and the multi-device compatible communication module are integrated to form the global water temperature collaborative controller of the fish tank.

[0062] To intuitively demonstrate the hardware execution logic of the global water temperature collaborative controller based on multi-parameter linkage control threshold configuration, please refer to [link / reference]. Figure 2 The diagram shown is an internal temperature control principle diagram of a global water temperature collaborative controller based on a multi-probe intelligent control method for aquarium water temperature according to an embodiment of the present invention. The diagram uses a fuzzy PID controller and a PLC as the core control architecture to illustrate that the multi-zone water temperature equalization module uses zoned control channels (such as relay combinations, heating / cooling modules, etc.) and data interaction nodes (sensors, controller data interaction points) to utilize temperature sensor feedback and cooperate with 3D flat panel heating to accurately achieve the collaborative control of aquarium water temperature.

[0063] The parameter correlation feature refers to the logical correlation and numerical dependency between different control parameters (such as water temperature deviation threshold, probe temperature difference threshold, equipment start-stop threshold, etc.) in the multi-parameter linkage control threshold. For example, when the "water temperature deviation threshold (±0.5℃)" is triggered (e.g., bottom water temperature 23.4℃ < compatibility range 24-26℃ lower limit 0.6℃), it will inevitably be linked to the "heater start-stop threshold (<24℃ start)," forming a direct "device response" correlation. The zonal control channel refers to the dedicated control path constructed in the global water temperature collaborative controller for different physical areas of the aquarium (e.g., upper water body, bottom water body, biological habitat exclusive area, equipment surrounding influence area). For example, the upper control channel's acquisition end is a water temperature probe 10cm below the aquarium water surface, and the execution end is... The upper water body features a miniature chiller responsible for monitoring and correcting upper water temperature deviations (such as excessively high upper water temperature due to summer sunlight). The bottom water control channel uses a water temperature probe located 5cm above the aquarium substrate as its acquisition end and a localized heater in the bottom water body as its execution end, responsible for monitoring and correcting bottom water temperature deviations (such as excessively low bottom water temperature due to distance from the main heater). The data interaction node refers to the hardware interface or network node connecting the zone control channels and the central controller, responsible for real-time transmission of sensor data, control commands, and status feedback information, supporting multi-channel collaborative communication. The multi-zone water temperature balancing module is a control logic unit used to coordinate the operating status of each zone control channel. By analyzing the regional temperature differences transmitted by the data interaction node, it dynamically adjusts the output power of each channel to achieve overall water temperature gradient control within a preset threshold (such as ≤±0).The control precision requirement refers to the quantitative requirement for the water temperature control error range based on the survival characteristics of the aquarium organisms (such as tropical fish, corals, etc.), usually expressed as ±ΔT (°C); the adjustable response rate range refers to the time interval (e.g., 5-30 seconds) from receiving the control command to the water temperature reaching the target value, which can be dynamically adjusted according to the control precision requirement. The higher the precision requirement, the narrower the response rate range; the dynamic power adjustment module refers to the execution unit that automatically adjusts the output power (e.g., 0-1000W) of the heating / cooling elements based on the adjustable response rate range and real-time water temperature deviation, supporting pulse width modulation (PWM) or continuous power adjustment; the interval switching condition refers to the critical condition in the multi-parameter linkage control threshold that triggers the control strategy to switch from one parameter interval to another, such as when the water temperature exceeds 28°C. At a certain temperature (℃), the high-temperature protection mode is activated. The aforementioned control failure recovery time refers to the maximum permissible delay (e.g., ≤30 seconds) for activating emergency measures when the control system fails (e.g., sensor malfunction, heater damage). The intelligent emergency module refers to a control unit that automatically activates preset remedial measures (e.g., backup heater switching, audible and visual alarms, remote notifications) when the interval switching condition is met or control failure occurs. The device communication protocol refers to the data interaction rules between the multi-device compatible communication module and internal / external aquarium devices (e.g., sensors, heaters, mobile APP), including data format, transmission rate, and verification method (e.g., MQTT, Modbus protocols). The multi-device compatible communication module refers to a hardware / software unit that supports the conversion and adaptation of multiple device communication protocols, enabling interconnection between the central controller and devices of different brands and types.

[0064] Optionally, the zoned control channels of the fish tank can be determined by the K-means clustering algorithm; the interval switching conditions of the multi-parameter linkage control threshold can be generated using the ID3 algorithm; and the control failure recovery time of the multi-parameter linkage control threshold can be defined based on the Failure Mode and Effects Analysis (FMEA) algorithm.

[0065] S5. Monitor the local water temperature fluctuation value of the fish tank and the response delay time of the global water temperature co-controller in real time, so as to calculate the co-control efficiency index of the global water temperature co-controller, and generate the adaptive temperature control command of the fish tank based on the co-control efficiency index.

[0066] This invention, through real-time monitoring of local water temperature fluctuations in the aquarium and the response delay of the global water temperature co-controller, calculates the co-control performance index of the global water temperature co-controller. This integrates the local water temperature anomaly fluctuation information obtained from multi-probe monitoring with the controller's real-time response time information into a unified performance evaluation dimension, accurately quantifying the controller's co-control capability in responding to local water temperature fluctuations.

[0067] The local water temperature mutation value refers to the maximum difference between the water temperature of a certain zone in the aquarium and the historical average water temperature of that zone within a preset time window (e.g., 10 seconds). For example, if the water temperature in zone A (monitored by probe 2) suddenly rises from 26℃ to 28.3℃ within 10 seconds, while the historical average water temperature is 26.1℃, then the local water temperature mutation value is 28.3-26.1=2.2℃ (exceeding the normal threshold of ±0.5℃, and is judged as a mutation). The response delay time refers to the time interval between receiving the local water temperature mutation signal and initiating the corresponding control command by the global water temperature co-control controller. For example, if probe 3 detects a water temperature mutation value of 1.8℃ in zone B at the 10th second and sends a signal, and the controller initiates the power adjustment command at the 12.5th second, then the response delay time is 2.5 seconds. The co-control efficiency index is a dimensionless index calculated based on the local water temperature mutation value and the response delay time, used to comprehensively evaluate the control efficiency of the global water temperature co-control controller in responding to local water temperature anomalies.

[0068] As an embodiment of the present invention, the real-time monitoring of the local water temperature fluctuation value of the fish tank and the response delay time of the global water temperature co-controller, in order to calculate the co-control efficiency index of the global water temperature co-controller, includes: Based on the local water temperature abrupt change value, the ecological sensitivity coefficient and water temperature fluctuation gradient in the fish tank are determined; Obtain the device response baseline value corresponding to the response delay time of the global water temperature collaborative controller; Retrieve the historical mutation dataset associated with the local water temperature mutation value to calculate the mutation diffusion coefficient of the fish tank; The collaborative control efficiency index of the global water temperature collaborative controller is calculated by combining the ecological sensitivity coefficient, the water temperature fluctuation gradient, the equipment response benchmark value, and the mutation diffusion coefficient.

[0069] The ecological sensitivity coefficient refers to the tolerance of organisms in the aquarium to sudden changes in water temperature, and its unit is [ ]. The ecological sensitivity coefficient can usually be calibrated experimentally, for example, by observing the stress response of fish under specific temperature abrupt changes (such as decreased activity, changes in respiratory rate, etc.) and fitting a sensitivity curve. A larger value indicates a more sensitive ecosystem to temperature changes (e.g., tropical fish are sensitive to small temperature differences); a smaller value indicates stronger adaptability (e.g., eurythermal fish). The water temperature fluctuation gradient refers to the rate of change of local water temperature per unit time, with units of [K·K]. [Kelvin per second], local water temperature data can be collected in real time by a high-precision temperature sensor, and the time derivative is calculated to determine the value; the device response reference value refers to the theoretical response speed of the global water temperature co-controller under ideal conditions, with units of [s]. -1The response time (per second) can reflect the upper limit of the controller's hardware performance; for example, a device response baseline of 0.5 seconds. -1 When the value is specified, it indicates that the controller can correct a maximum of 0.5 times the water temperature deviation per second. The device response baseline value can be measured using a step response test. The historical mutation dataset refers to a collection of water temperature mutation events recorded in the aquarium in the past, including the mutation amplitude and occurrence time, with units of [K]. The mutation diffusion coefficient describes the diffusion rate of water temperature mutations within the aquarium, with units of [s]. -1 The mutation diffusion coefficient can be obtained by experimentally measuring the time constant of mutation propagation from local to global.

[0070] As another embodiment of the present invention, the collaborative control efficiency index of the global water temperature collaborative controller is calculated by the following formula: ; in, Indicates the collaborative control effectiveness index. Indicates the ecological sensitivity coefficient. Indicates the water temperature fluctuation gradient. Indicates the device response baseline value. Indicates the historical minimum mutation rate. This represents the response delay time, and k represents the calibration coefficient. This represents the mutation diffusion coefficient.

[0071] It should be explained that in this application, the formula Used to characterize the ecological threat intensity of current mutations (unit [s]). -1 The higher the value, the higher the ecological risk faced by the system (such as sensitive corals encountering rapid warming). This is used to correct the device's response to changes in abrupt changes and avoid insufficient response to abnormal changes. It is particularly important to note that this is achieved by introducing the historical minimum mutation rate. This allows for reference to the system's past handling of extreme mutations, making the calculation results more dynamically adaptable. This is used to mitigate performance degradation under extreme latency, preventing the controller from being prematurely deemed a failure. Furthermore, it utilizes the mutation diffusion coefficient... and response latency By incorporating the dynamic process of controller response delay and mutation diffusion into the calculation, the performance differences under different delays and different mutation diffusion trends can be reflected, such as the diffusion rate decreasing after the water temperature tends to be uniform.

[0072] Furthermore, in this embodiment of the invention, by generating adaptive temperature control commands for the aquarium based on the collaborative control efficiency index, the multi-probe aquarium water temperature intelligent control system can dynamically adjust the zonal control strategy according to the efficiency index, improve the control accuracy of complex water temperature fluctuations, shift from passive response to active adaptation, and enhance the timeliness and stability of parameter adjustment during aquarium water temperature control.

[0073] The adaptive temperature control command refers to a set of differentiated temperature adjustment commands dynamically generated for each zone's control channel based on the real-time value of the collaborative control efficiency index. It includes elements such as power adjustment parameters, response rate parameters, and regional collaborative logic. For example, when the collaborative control efficiency index is 85 (high level), the adaptive temperature control command generated by the system may be: "Maintain 90% of the current value for heating power in zone A, and maintain a response rate of 5 seconds; activate the pre-adjustment mode in zone B, and reduce the power by 5% in advance to suppress potential sudden changes; maintain a data interaction frequency of 1 second / time for each zone."

[0074] As an embodiment of the present invention, generating the adaptive temperature control command for the fish tank based on the cooperative control efficiency index includes: Based on the collaborative control efficiency index, the ecologically specific sensitive parameters of the fish tank are selected. Define the controller dynamic performance threshold corresponding to the collaborative control performance index; Based on the controller's dynamic performance threshold and the ecologically specific sensitive parameters, the multi-dimensional temperature adjustment range of the fish tank is set. Retrieve a library of preset temperature control parameter combinations that match the multi-dimensional temperature adjustment range; Analyze the dynamic adaptation conditions of each parameter combination in the preset temperature control parameter combination library; Based on the dynamic adaptation conditions, an adaptive temperature control command for the fish tank is generated.

[0075] The ecologically specific sensitive parameters refer to specific sensitive parameters strongly correlated with the aquarium's ecological state extracted from the collaborative control efficiency index. These include the uniform water temperature deviation (reflecting the impact of regional temperature differences on organisms; for example, the index drops sharply when the temperature difference between the upper and lower layers is >0.8℃), the biological stress response coefficient (quantifying changes in biological state caused by water temperature fluctuations; for example, the index decreases by 0.15 for every 10% decrease in the activity rate of tropical fish), and the equipment collaborative wear rate (reflecting the balance between energy consumption and lifespan of the control equipment; for example, the index is below 0.7 when the heater's start-stop frequency is >12 times / h). The controller dynamic efficiency threshold refers to the threshold that is dynamically adjusted in real time according to the collaborative control efficiency index and used to determine temperature control. The control device's operating efficiency meets the critical threshold required by the aquarium ecosystem. For example, when the collaborative control efficiency index is high (indicating good ecosystem stability), the controller's dynamic efficiency threshold can be set to ±0.5℃ (i.e., temperature fluctuations within this range indicate that efficiency is met); when the collaborative control efficiency index is low (indicating poor ecosystem stability), the threshold can be adjusted to ±0.2℃ to improve control accuracy. The multi-dimensional temperature regulation range refers to the set of allowable water temperature regulation ranges defined by comprehensively considering multiple dimensions such as different areas within the aquarium (e.g., upper, middle, and lower water layers), different microenvironments of different organisms, and different time periods (e.g., day and night, seasons). For example, for polyculture of upper-level fish... For aquariums housing guppies and bottom-dwelling shellfish (such as freshwater clams), multi-dimensional temperature regulation ranges can include: 24-26℃ for the upper water layer during the day and 22-24℃ at night; and 23-25℃ for the bottom water layer during the day and 21-23℃ at night, to accommodate the habitat needs of different organisms. The preset temperature control parameter combination library refers to a pre-stored set of several effective parameters related to temperature control (such as heating power, cooling intensity, regulation frequency, and water circulation speed). The parameter combination refers to a set of interrelated control parameters selected from the preset temperature control parameter combination library to achieve a specific temperature regulation target; for example, parameters for rapidly raising the aquarium water temperature. The parameter combination may include: 100% heating power, high-speed water circulation, and temperature monitoring frequency every 5 minutes. Among these, heating power determines the temperature rise intensity, water circulation speed affects heat diffusion efficiency, and monitoring frequency ensures timely control. The dynamic adaptation conditions refer to the real-time constraints that the parameter combination must meet to be effectively applied to the current aquarium temperature control scenario. For example, the dynamic adaptation conditions of a parameter combination can be set as "current aquarium water temperature is more than 2°C lower than the target temperature, dissolved oxygen content in the water is ≥5mg / L, and external ambient temperature is ≤25°C". The parameter combination will only be activated when these three conditions are met simultaneously to ensure that the control process will not have a negative impact on the ecosystem.

[0076] Optionally, the controller dynamic performance threshold corresponding to the collaborative control performance index can be defined by the gradient boosting tree algorithm (XGBoost); the dynamic adaptation conditions of each parameter combination in the preset temperature control parameter combination library can be analyzed by the particle swarm optimization algorithm.

[0077] S6. Combining the zoned temperature balancing method, the global water temperature collaborative controller, and the adaptive temperature control command, output the intelligent water temperature control scheme for the fish tank.

[0078] This invention combines the zonal temperature balancing method, the global water temperature coordinating controller, and the adaptive temperature control command to output an intelligent water temperature control scheme for the aquarium. It replaces single-location temperature control with zonal monitoring and adjustment. The global water temperature coordinating controller responds in real-time to sudden changes in local water temperature, dynamically coordinating the operating status of heating / cooling equipment in each area. This avoids the problem of insufficient water temperature control accuracy caused by single-sensor data acquisition and fixed threshold standards. Simultaneously, the adaptive temperature control command matches the real-time water temperature changes in different areas of the aquarium, reducing the impact of localized high or low temperatures on aquatic organisms and the risk of erroneous equipment start-up and shutdown. This achieves a precise balance between control safety and water temperature stability under different abnormal water temperature scenarios.

[0079] The aforementioned intelligent water temperature control scheme refers to a complete and dynamically adjustable aquarium water temperature regulation and execution strategy formed through the coordinated adaptation of zoned temperature balancing, a global water temperature collaborative controller, and adaptive temperature control commands. The zoned temperature balancing method provides a framework for water temperature monitoring and basic regulation, clarifying the key directions of temperature control, the priority of abnormal handling, and the water temperature balancing criteria in different water areas (such as prioritizing the stability of water temperature in the core habitat area of ​​aquatic organisms, and then regulating the water temperature in the peripheral areas). The global water temperature collaborative controller provides the core basis for equipment linkage and decision control, defining the basic operating modes and collaborative relationships of each temperature control device (heater, cooling element, circulating water pump) (such as the linkage between the heater and the circulating water pump to regulate the water temperature in the low-temperature zone), ensuring the efficiency and coordination of the water temperature regulation process. The adaptive temperature control command gives the solution real-time optimization capabilities, dynamically optimizing equipment operating parameters (such as heating power and water pump speed) based on the abnormal deviation of water temperature (such as the difference between the actual water temperature and the target threshold), ensuring that the aquarium water temperature always meets the survival standards of aquatic organisms, and avoiding the risk of local high / low temperature stress or aquatic organism survival crisis caused by equipment failure or environmental changes.

[0080] Compared to the problems described in the background art, the embodiments of the present invention acquire real-time water temperature data and aquatic organism activity trajectory data of the aquarium zones, and identify the water temperature conduction characteristics of different functional areas within the aquarium to construct a multi-probe temperature control network for the aquarium. This integrates discrete zone water temperature information and dynamic biological activity data to form a multi-regional, interconnected temperature control sensing system. This provides a structured framework for real-time capture of the adaptation relationship between changes in aquarium water temperature distribution and biological activity needs, ensuring comprehensive control over the complex water temperature environment of the aquarium and improving the intelligent adjustment accuracy and ecological adaptability of the multi-probe temperature control network for aquarium water temperature. Furthermore, the embodiments of the present invention, based on the water temperature wave... By using dynamic data to establish a heat map of the overall water temperature change in the aquarium, the dynamic fluctuations and spatial distribution differences of water temperature in different functional areas of the aquarium can be accurately correlated, ensuring real-time detection of the risk of overall water temperature imbalance. This embodiment of the invention generates a zoned temperature balancing method for the aquarium based on the overall water temperature change heat map and the real-time zoned water temperature data. This improves the ability to perceive the balance state of the complex water temperature environment in the aquarium, and lays the foundation for subsequent accurate location of temperature imbalance areas and optimization of multi-probe control strategies, enhancing the accuracy and dynamic adaptability of the multi-probe temperature control network for the balanced control of aquarium water temperature. This embodiment of the invention also extracts suitable water temperatures for different aquatic organisms in the aquarium. By defining the appropriate temperature range and biological tolerance threshold, a generalized temperature control mode can be upgraded to a biologically adapted control mechanism, precisely matching the survival needs of different species and strengthening the dynamic balance of the aquarium water environment and the full-cycle maintenance of biological health. Furthermore, this embodiment of the invention determines the compatible water temperature range for different aquatic organisms in the aquarium based on the suitable water temperature range and the biological tolerance threshold. This allows the multi-probe aquarium water temperature intelligent control system to dynamically adjust the zoned temperature control strategy according to biological characteristics, shifting from single-species temperature control to multi-biological collaborative regulation. This enhances the ability and stability of water temperature control to ensure the aquatic ecological balance and creates a safe and compatible water temperature environment for various organisms in the aquarium. This invention, by setting a multi-parameter linkage control threshold for the aquarium based on the aforementioned compatible water temperature range, can achieve precise and coordinated output of multi-probe water temperature regulation, improve the responsiveness to micro-fluctuations in the aquarium water temperature, and enhance the ecological adaptability of water temperature control in multi-species mixed-species scenarios. Furthermore, by configuring a global water temperature collaborative controller for the aquarium based on the aforementioned multi-parameter linkage control threshold, this invention can adapt to the water temperature fluctuation characteristics of different areas of the aquarium, forming a precise and collaborative global water temperature regulation system. This ensures efficient correction of complex water temperature fluctuations in multi-species mixed-species scenarios, and improves the stability and ecological adaptability of intelligent water temperature control in multi-probe aquariums.This invention, through real-time monitoring of local water temperature fluctuations in the aquarium and the response delay of the global water temperature co-controller, calculates the co-control efficiency index of the global water temperature co-controller. This integrates local water temperature anomaly fluctuation information acquired by multi-probe monitoring with the controller's real-time response time information into a unified efficiency evaluation dimension, accurately quantifying the controller's co-control capability in responding to local water temperature fluctuations. Furthermore, based on the co-control efficiency index, this invention generates adaptive temperature control commands for the aquarium, allowing the multi-probe aquarium water temperature intelligent control system to dynamically adjust its zone control strategy according to the efficiency index. This improves the control accuracy for complex water temperature fluctuations, shifting from passive response to active adaptation and enhancing parameter adjustment during aquarium water temperature control. The timely and stable operation of the system is improved. Finally, this embodiment of the invention, by combining the partitioned temperature balancing method, the global water temperature collaborative controller, and the adaptive temperature control command, outputs an intelligent water temperature control scheme for the aquarium. This scheme replaces single-location temperature control with partitioned monitoring and adjustment. The global water temperature collaborative controller responds in real-time to sudden changes in local water temperature to dynamically coordinate the operating status of heating / cooling equipment in each area, avoiding the problem of insufficient water temperature control accuracy caused by single-sensor acquisition and fixed threshold standards. Simultaneously, the adaptive temperature control command matches the real-time water temperature changes in different areas of the aquarium, reducing the impact of local high or low temperatures on aquatic organisms and the risk of erroneous equipment start-up and shutdown. This achieves a precise balance between control safety and water temperature stability under different abnormal water temperature scenarios. Therefore, the intelligent aquarium water temperature control method and system based on multiple probes provided by this embodiment of the invention can improve the accuracy of aquarium water temperature control.

[0081] like Figure 3 The diagram shown is a functional block diagram of an intelligent aquarium water temperature control system based on multiple probes according to the present invention.

[0082] The multi-probe-based intelligent aquarium water temperature control system 200 described in this invention can be installed in an electronic device. Depending on the functions implemented, the multi-probe-based intelligent aquarium water temperature control system may include a temperature control module 201, a strategy balancing module 202, a water temperature adaptation module 203, a collaborative control module 204, a collaborative performance evaluation module 205, and a scheme output module 206. The modules described in this invention can also be referred to as units, which are a series of computer program segments that can be executed by the processor of an electronic device and perform a fixed function, stored in the memory of the electronic device.

[0083] In this embodiment of the invention, the functions of each module / unit are as follows: The temperature control module 201 is used to acquire real-time water temperature data of different zones in the aquarium and aquatic organism activity trajectory data, and to identify the water temperature conduction characteristics of different functional areas in the aquarium in order to construct a multi-probe temperature control network for the aquarium. The strategy balancing module 202 is used to collect water temperature fluctuation data under the multi-probe temperature control network, establish a global water temperature change heat map of the aquarium based on the water temperature fluctuation data, and generate a zone temperature balancing method for the aquarium based on the global water temperature change heat map and the real-time zone water temperature data. The water temperature adaptation module 203 is used to analyze the suitable water temperature range and biological tolerance threshold of different aquatic organisms in the fish tank, and to determine the compatible water temperature range of different aquatic organisms in the fish tank based on the suitable water temperature range and the biological tolerance threshold. The collaborative control module 204 is used to set the multi-parameter linkage control threshold of the aquarium according to the compatible water temperature range, and to configure the global water temperature collaborative controller of the aquarium based on the multi-parameter linkage control threshold. The collaborative performance evaluation module 205 is used to monitor the local water temperature change value of the fish tank and the response delay time of the global water temperature collaborative controller in real time, so as to calculate the collaborative control performance index of the global water temperature collaborative controller, and generate the adaptive temperature control command of the fish tank based on the collaborative control performance index. The solution output module 206 is used to combine the partitioned temperature balancing method, the global water temperature collaborative controller and the adaptive temperature control command to output the intelligent water temperature control solution for the fish tank.

[0084] In detail, the modules in the multi-probe-based intelligent aquarium water temperature control system 200 described in this embodiment of the invention employ the same methods as described above. Figure 1 The method used is the same as the intelligent aquarium water temperature control method based on multiple probes described above, and can produce the same technical effect, so it will not be elaborated here.

[0085] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0086] Finally, it should be noted that in the above embodiments, each embodiment can be combined with each other or independent. Deleting any one of them will not affect the technical implementation of other embodiments. The above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A multi-probe based intelligent control method for water temperature in an aquarium, characterized in that, The method includes: The system acquires real-time water temperature data and aquatic organism activity trajectory data for different zones within the aquarium, and identifies the water temperature conduction characteristics of different functional areas within the aquarium to construct a multi-probe temperature control network for the aquarium. Collect water temperature fluctuation data under the multi-probe temperature control network, establish a global water temperature change heat map of the aquarium based on the water temperature fluctuation data, and generate a zone temperature balancing method for the aquarium based on the global water temperature change heat map and the real-time zone water temperature data. The suitable water temperature range and biological tolerance threshold of different aquatic organisms in the aquarium are analyzed, and the compatibility water temperature range of different aquatic organisms in the aquarium is determined based on the suitable water temperature range and the biological tolerance threshold. Based on the aforementioned compatible water temperature range, set the multi-parameter linkage control threshold for the aquarium, and configure the global water temperature collaborative controller for the aquarium based on the aforementioned multi-parameter linkage control threshold. The system monitors the local water temperature fluctuations in the aquarium and the response delay of the global water temperature co-controller in real time to calculate the co-control efficiency index of the global water temperature co-controller. Based on the co-control efficiency index, it generates an adaptive temperature control command for the aquarium. Combining the zoned temperature balancing method, the global water temperature collaborative controller, and the adaptive temperature control command, an intelligent water temperature control scheme for the fish tank is output.

2. The multi-probe based fish tank water temperature intelligent control method of claim 1, wherein, The method for generating a zoned temperature balancing mechanism for the aquarium based on the overall water temperature change heatmap and the real-time zoned water temperature data includes: Based on the global water temperature change heat map, the temperature imbalance area of ​​the fish tank was identified; Analyze the temperature distribution pattern of the global water temperature change heatmap and extract the dynamic water temperature fluctuation characteristics of the real-time water temperature data of the zones. Based on the temperature distribution pattern and the dynamic water temperature fluctuation characteristics, determine the temperature control medium type of the fish tank; Construct a dynamic balance strategy matrix for the temperature control medium regulation type in different temperature imbalance regions; Based on the real-time water temperature data of the partition, locate the media control linkage node of the fish tank; Based on the medium regulation linkage node, determine the equalization trigger threshold corresponding to the temperature control medium regulation type; Based on the dynamic balancing strategy matrix and the balancing trigger threshold, adaptive balancing control commands are generated for different zones within the fish tank. The adaptive balancing control command generates a zoned temperature balancing method for the fish tank.

3. The multi-probe based fish tank water temperature intelligent control method of claim 2, wherein, The step of locating the media control linkage node of the fish tank based on the real-time water temperature data of the partition includes: Identify the temperature control medium of the fish tank and its corresponding temperature control device, and obtain the zone sensor corresponding to the real-time water temperature data of the zone; Check the signal transmission ports of the temperature control device and the zone sensor; Based on the signal transmission port, the communication protocol specification between the temperature control device and the partition sensor is analyzed. Using the aforementioned communication standard protocol, the communication link relationship between the temperature control device and the partition sensor is analyzed; Based on the communication link relationship, establish a node association map between the temperature control device and the zone sensor; The media control linkage node of the fish tank can be located by using the node association map.

4. The multi-probe based fish tank water temperature intelligent control method of claim 1, wherein, The configuration of the global water temperature co-control controller for the fish tank based on the multi-parameter linkage control threshold includes: By utilizing the parameter correlation characteristics of the multi-parameter linkage control threshold, the zone control channels and data interaction nodes of the fish tank are determined; Based on the partition control channel and the data interaction node, a multi-zone water temperature balancing module for the fish tank is set up. Identify the control precision requirements corresponding to the multi-parameter linkage control threshold, so as to set the adjustable response rate range of the partition control channel; The dynamic power adjustment module of the fish tank is deployed according to the adjustable response rate range; Define the range switching conditions and the recovery time for the control failure of the multi-parameter linkage control threshold to set up the intelligent emergency module of the fish tank; Query the device communication protocol associated with the multi-parameter linkage control threshold to deploy the multi-device compatible communication module of the fish tank; The multi-zone water temperature equalization module, the dynamic power adjustment module, the intelligent emergency module, and the multi-device compatible communication module are integrated to form the global water temperature collaborative controller of the fish tank.

5. The multi-probe based fish tank water temperature intelligent control method of claim 1, wherein, The method of real-time monitoring of local water temperature fluctuations in the fish tank and the response delay time of the global water temperature co-control system to calculate the co-control efficiency index of the global water temperature co-control system includes: Based on the local water temperature abrupt change value, the ecological sensitivity coefficient and water temperature fluctuation gradient in the fish tank are determined; Obtain the device response baseline value corresponding to the response delay time of the global water temperature collaborative controller; Retrieve the historical mutation dataset associated with the local water temperature mutation value to calculate the mutation diffusion coefficient of the fish tank; Combining the ecological sensitivity coefficient, the water temperature fluctuation gradient, the equipment response baseline value, and the mutation diffusion coefficient, the collaborative control efficiency index of the global water temperature collaborative controller is calculated using the following formula: ； in, Indicates the collaborative control effectiveness index. Indicates the ecological sensitivity coefficient. Indicates the water temperature fluctuation gradient. Indicates the device response baseline value. Indicates the historical minimum mutation rate. This represents the response delay time, and k represents the calibration coefficient. This represents the mutation diffusion coefficient.

6. The multi-probe based fish tank water temperature intelligent control method of claim 1, wherein, The process of acquiring real-time water temperature data and aquatic organism activity trajectory data of different zones within the aquarium, and identifying the water temperature conduction characteristics of different functional areas within the aquarium to construct a multi-probe temperature control network for the aquarium, includes: Based on the real-time water temperature data of the partition, the aquarium is divided into temperature-sensitive areas and temperature-uniform areas. Based on the temperature-sensitive area and the temperature-uniform area, a three-dimensional temperature control hierarchy structure for the fish tank is set up. The spatial distribution characteristics of aquatic organisms corresponding to the activity trajectory data of the aquatic organisms are analyzed to generate a distribution map of biological aggregation hotspots in the aquarium. Based on the biological hotspot distribution map, deploy the temperature probe combination of the three-dimensional temperature control hierarchical structure; The optimal temperature range for the aquarium's organisms is determined by using historical water temperature regulation data from the aquarium. By combining the optimal temperature zone of the organism with the real-time water temperature data of the zone, the water temperature deviation coefficient of each area of ​​the aquarium is calculated; Based on the aforementioned water temperature conduction characteristics, the temperature control response priority of each area of ​​the fish tank is set; Based on the water temperature deviation coefficient and the temperature control response priority, a multi-level temperature control response rule for the fish tank is formulated. Configure the linkage communication link between the three-dimensional temperature control hierarchy structure and the temperature probe combination; By integrating the multi-level temperature control response rules, the three-dimensional temperature control hierarchy, the temperature probe combination, and the linkage communication link, a multi-probe temperature control network for the aquarium is constructed.

7. The multi-probe based fish tank water temperature intelligent control method of claim 1, wherein, The step of setting the multi-parameter linkage control threshold of the fish tank according to the compatible water temperature range includes: The core parameter set of the aquarium is analyzed and the corresponding ecological features are extracted. The core parameter set includes water temperature acquisition parameters, equipment operation parameters and environmental correlation parameters. Based on the aforementioned compatible water temperature range, the aquarium's water temperature safety fluctuation sub-range is divided; Based on the water temperature safety fluctuation sub-interval and the ecological correlation characteristics, the coordinated regulation requirements of the core parameter group are identified, and the ecological adaptability index of the core parameter group is determined. Based on the aforementioned coordinated control requirements, the linkage control unit of the core parameter group is set up; Define the response priority weights of the linkage control unit; The multi-parameter linkage control threshold of the fish tank is set using the ecological adaptability index and the response priority weight.

8. The intelligent aquarium water temperature control method based on multiple probes as described in claim 1, characterized in that, The step of generating adaptive temperature control commands for the fish tank based on the collaborative control efficiency index includes: Based on the collaborative control efficiency index, the ecologically specific sensitive parameters of the fish tank are selected. Define the controller dynamic performance threshold corresponding to the collaborative control performance index; Based on the controller's dynamic performance threshold and the ecologically specific sensitive parameters, the multi-dimensional temperature adjustment range of the fish tank is set. Retrieve a library of preset temperature control parameter combinations that match the multi-dimensional temperature adjustment range; Analyze the dynamic adaptation conditions of each parameter combination in the preset temperature control parameter combination library; Based on the dynamic adaptation conditions, an adaptive temperature control command for the fish tank is generated.

9. The intelligent aquarium water temperature control method based on multiple probes as described in claim 1, characterized in that, The determination of the compatibility temperature range for different aquatic organisms within the aquarium, based on the suitable water temperature range and the biological tolerance threshold, includes: Identify the different ecological function types of the aquatic organisms in the aquarium, and determine the temperature interaction coefficients corresponding to the ecological function types; Based on the ecological function type and the temperature interaction coefficient, a temperature adaptation priority partitioning for the suitable water temperature range is established. Based on the temperature adaptation priority partitioning, identify the interval constraint boundaries of the biological tolerance threshold; Based on the temperature adaptation priority partitioning and the interval constraint boundary, a stratified water temperature adaptation rule is constructed for different aquatic organisms in the fish tank. Based on the stratified water temperature adaptation rules, the compatible water temperature ranges for different aquatic organisms in the fish tank are determined.

10. A multi-probe based intelligent fish tank water temperature control system, characterized in that, The system includes: The temperature control module is used to acquire real-time water temperature data of different zones in the aquarium and aquatic organism activity trajectory data, and to identify the water temperature conduction characteristics of different functional areas in the aquarium in order to construct a multi-probe temperature control network for the aquarium. The strategy balancing module is used to collect water temperature fluctuation data under the multi-probe temperature control network, establish a global water temperature change heat map of the aquarium based on the water temperature fluctuation data, and generate a zone temperature balancing method for the aquarium based on the global water temperature change heat map and the real-time zone water temperature data. The water temperature adaptation module is used to analyze the suitable water temperature range and biological tolerance threshold of different aquatic organisms in the aquarium, and to determine the compatible water temperature range of different aquatic organisms in the aquarium based on the suitable water temperature range and the biological tolerance threshold. The collaborative control module is used to set the multi-parameter linkage control threshold of the aquarium according to the compatible water temperature range, and to configure the global water temperature collaborative controller of the aquarium based on the multi-parameter linkage control threshold. The collaborative performance evaluation module is used to monitor the local water temperature fluctuation values ​​of the fish tank and the response delay time of the global water temperature collaborative controller in real time, so as to calculate the collaborative control performance index of the global water temperature collaborative controller, and generate the adaptive temperature control command of the fish tank based on the collaborative control performance index; the scheme output module is used to combine the zone temperature balancing method, the global water temperature collaborative controller and the adaptive temperature control command to output the intelligent water temperature control scheme of the fish tank.

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