A multi-source data fusion-based intelligent linkage control method and system for aquaculture equipment

Abstract

The application discloses a kind of based on multi-source data fusion's aquaculture equipment intelligent linkage control method and system, it is applied to by host computer, vice machine and comprehensive water quality monitoring terminal networking aquaculture system.The method fuses the accurate data of monitoring terminal and the operation data of each equipment, and forms perception dataset;System automatically generates linkage instruction according to preset strategy, and according to the change trend of dissolved oxygen, dynamically call aerator, mechanical oxygenation, liquid oxygen gas supply until chemical oxygenation equipment for gradient emergency.At the same time, it has the functions of safe stopping material, linkage unit management, manual intervention priority and equipment fault linkage compensation, etc.The present application realizes the holographic perception of multi-source data in aquaculture farm and the intelligent collaborative scheduling across devices, has the characteristics of fast response, strategy optimization, high reliability and low cost, and is suitable for large-scale, multi-pond mouth intelligent aquaculture farm.

Description

Technical Field

[0001] This invention relates to the field of smart aquaculture technology, specifically to a linkage control method and system that can integrate multi-source sensor data to achieve intelligent collaborative operation of aquaculture equipment across ponds. Background Technology

[0002] In aquaculture, key water parameters such as dissolved oxygen and pH levels change rapidly. Especially under adverse weather conditions such as high temperatures and rain, dissolved oxygen can drop sharply in a short period of time, leaving farmers with very little time to manually address the issue. If not addressed promptly, it can lead to widespread oxygen depletion, fish surfacing, or even death, resulting in significant economic losses. Currently, although aquaculture farms are equipped with various devices such as aerators, feeders, spraying systems, and liquid oxygen supply devices, most of these devices operate independently, lacking unified data collection and intelligent linkage capabilities. When dissolved oxygen levels drop, farmers need to rely on personal experience to judge and manually activate different devices sequentially, resulting in slow response times and a high risk of errors due to panic. More importantly, the species, density, and growth stages of aquaculture vary from pond to pond, requiring different linkage strategies. Existing technologies cannot achieve refined linkage management at the pond or unit level. Therefore, there is an urgent need for a control method that can integrate data from multiple sensor sources, automatically sense the situation of each pond, and generate and execute precise linkage strategies accordingly. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to provide a linkage control method and system that can integrate multi-source data, situational awareness and realize cross-device intelligent collaboration. To address the aforementioned technical problems, this invention discloses a multi-source data fusion-based linkage control method for aquaculture equipment. Its core lies in: using an intelligent control module to fuse and cross-verify high-precision data from a comprehensive water quality monitoring terminal with sensor data from each auxiliary unit in real time, forming a "sensory dataset." Subsequently, based on this sensing dataset, combined with multi-level anomaly thresholds and aquaculture stage strategy templates, the system dynamically matches and distributes the optimal linkage control strategy to the corresponding execution equipment, and monitors the execution status in real time, forming a closed-loop control system. The linkage control strategy includes: a gradient oxygenation strategy—prioritizing the use of aerators, activating mechanical aerators when insufficient, and activating liquid oxygen supply devices when still insufficient; a chemical oxygenation emergency strategy—automatically administering chemical oxygenators for emergency treatment when all physical oxygenation methods are exhausted but dissolved oxygen remains at a dangerous threshold; and a safe shutdown strategy—automatically stopping feeding when dissolved oxygen falls below a safe level. In addition, it includes functions such as linkage unit management, priority for manual intervention, and equipment failure linkage compensation. Compared with the prior art, the beneficial effects of the present invention are as follows: 1. Holographic perception and intelligent decision-making: Integrate multi-source sensor data to accurately judge the real situation of the pond, avoiding wrong decisions caused by misjudgment of a single data source. 2. Dynamic strategy and precise execution: The linkage strategy is dynamically generated according to data trends to ensure that the most effective measures are taken in the first place. 3. Extreme cost and high reliability: Preferentially use low-cost aeration solutions and call high-cost equipment step by step as needed, which can save both lives and money. 4. Unitized management and fine control: Divide the linkage units according to the ponds, without interference with each other, and achieve refined management of large-scale aquaculture. 5. Transparent management and data assetization: All data, decision-making, and execution records are traceable, and can be mastered in real time through the App, helping users achieve refined management and build digital assets. BRIEF DESCRIPTION OF THE DRAWINGS

[0004] Figure 1 It is a flowchart of the linkage control method of the present invention. Figure 2 It is a schematic diagram of the architecture of the linkage control system of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0005] The preferred embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Embodiment 1: Control method process As Figure 1 shown, this embodiment provides a linkage control method for aquaculture equipment based on multi-source data fusion. The host obtains and fuses the first water quality data of the comprehensive water quality monitoring terminal in real time through the intelligent control module, as well as the second water quality data and equipment operation status data of auxiliary machines such as aerators and liquid oxygen, to form a perception data set. When it is detected that the dissolved oxygen in a certain pond begins to decline, the host first fully opens all aerators in that pond; if the dissolved oxygen still continues to decline, the mechanical aeration device is automatically started for supplementary aeration; if the downward trend still remains unchanged, the liquid oxygen supply device is started for full-scale oxygen supply; when all physical aeration means are exhausted but the dissolved oxygen is still at a dangerous threshold, the host automatically sends an instruction to the spraying system in that pond to put in chemical oxygenating agents for first aid. At the same time, when the dissolved oxygen is lower than the safe value, the host automatically sends a stop feeding instruction to the feeding machine in that pond to prevent feed residues from aggravating the oxygen debt. During the entire linkage process, different ponds are divided into different linkage units, and the equipment within the same unit shares the linkage strategy, without interference between different units. If the operator issues a manual control instruction through the App or the remote control, the manual instruction is preferentially executed. If a certain device suddenly fails and goes offline, the host automatically calls available devices with the same or similar functions in the same pond to take over the work. Embodiment 2: Linkage control system architecture like Figure 2 As shown, this embodiment provides a linkage control system for implementing the above method. The entire system is networked through intelligent control modules. The integrated water quality monitoring terminal is responsible for collecting water quality data at fixed points and continuously; each auxiliary device is responsible for performing aquaculture operations such as oxygenation and feeding; the main unit, as the core brain, is responsible for integrating data from multiple sources, analyzing the situation, and issuing precise linkage control commands. It should be noted that the above embodiments are merely preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any equivalent method modifications or system architecture modifications made based on the concept of the present invention are included within the scope of protection of the present invention.

Claims

1. A multi-source data fusion-based aquaculture equipment linkage control method applied to an aquaculture system comprising a host computer, multiple slave computers and at least one comprehensive water quality monitoring terminal, wherein the host computer, each slave computer and the comprehensive water quality monitoring terminal are in data communication through an intelligent control module, characterized in that, include: S1. Data Fusion and Situation Awareness: The host computer receives and fuses the first water quality data from the integrated water quality monitoring terminal, the second water quality data from the sensors on each auxiliary unit, and / or the equipment operation status data in real time through the intelligent control module, forming a perception dataset that reflects the current comprehensive situation of each aquaculture pond. S2. Anomaly detection and strategy matching: The host computer determines the current risk level of each pond based on the sensing dataset, combined with preset multi-level anomaly thresholds and aquaculture stage strategy templates, and automatically matches the corresponding linkage control strategy. S3. Generation and issuance of linkage instructions: When it is determined that a certain pond has triggered the linkage condition, the host generates an encrypted control instruction according to the matched linkage control strategy and issues it to one or more corresponding auxiliary devices in the pond. S4. Linked Execution and Feedback: The slave device that receives the instruction executes the corresponding action and feeds back the execution result and the latest status of the device to the host through the intelligent control module, forming a closed-loop control.

2. The method of claim 1, wherein, The sensing dataset in S1 includes at least dissolved oxygen, water temperature, pH value, and equipment online status; the host compares and verifies similar sensor data from different devices, and combines dissimilar sensor data for comprehensive judgment to determine whether the linkage triggering conditions are met.

3. The method of claim 1, wherein, The linkage control strategy in S2 includes a gradient oxygenation strategy: when the dissolved oxygen in a pond is detected to be lower than the preset value, the main unit will prioritize turning on all aerators in that pond; if the dissolved oxygen continues to drop, the mechanical aerator will be automatically started. If the oxygen level continues to drop, activate the liquid oxygen supply system to provide full oxygen supply.

4. The method of claim 3, wherein, The linkage control strategy also includes emergency linkage for chemical oxygenation: when all mechanical oxygenation devices and liquid oxygen supply devices in the pond are operating at full capacity, but the dissolved oxygen value is still lower than the preset danger threshold within a preset time, the host automatically sends an instruction to the spraying system or equipment with dispensing function in the pond to dispense chemical oxygenating agent for emergency rescue.

5. The method of claim 1, wherein, The linkage control strategy in S2 includes a safe feeding stop strategy: when the dissolved oxygen in a certain pond is detected to be lower than the preset safety value, the host automatically sends a stop feeding command to the feeder in that pond.

6. The method of claim 1, wherein, It also includes linkage unit management: different aquaculture ponds are divided into different linkage units, equipment within the same linkage unit shares the same linkage strategy, and the linkage logic between different linkage units is independent of each other; when a linkage unit triggers an emergency linkage, it does not affect the normal operation of other linkage units.

7. The method of claim 1, wherein, It also includes prioritizing human intervention: during the automatic linkage process, if the host receives a legitimate human control command from the App or remote control, the human command will be executed first. After the human command is executed, the automatic linkage logic will be re-evaluated and restored based on the latest perception dataset.

8. The method of claim 1, wherein, It also includes equipment failure linkage compensation: when a device that is executing a linkage command suddenly fails and goes offline, the host automatically calls on an available device with the same or similar function from the same pond to take over its work; If there is no available equipment in the same pond, reduce the priority of oxygen supply demand for that pond and report the fault information.

9. The method of claim 1, wherein, The integrated water quality monitoring terminal can simultaneously monitor the water quality data of multiple adjacent ponds and share the monitoring data with the host computer of the corresponding pond through the intelligent control module.

10. A system for implementing the method of any one of claims 1 to 9, characterized in that, include: At least one integrated water quality monitoring terminal is used to collect primary water quality data from aquaculture ponds; Multiple auxiliary machines are used to perform specific aquaculture operations; A host computer, which communicates with the integrated water quality monitoring terminal and each auxiliary device through a network of intelligent control modules, is configured to execute the control logic of data fusion, situational awareness, strategy matching, and command issuance.

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