Intelligent plankton collecting net system

Abstract

The application discloses an intelligent phytoplankton collecting net system, which comprises a control unit, and is connected with an execution module, a parameter setting module, a real-time environment detection module and an optimization module on the control unit; the execution module is used for collecting phytoplankton; the parameter setting module is used for setting and changing the sampling depth, sampling time, sampling frequency and sampling amount in the early and late stages; the real-time environment detection module is used for monitoring the water environment parameters in real time after starting the system and transmitting the data to the control unit; and the optimization module is integrated in the control unit, is used for processing and analyzing the real-time environment data through its own algorithm, and optimizes the collecting strategy according to the preset condition or real-time data; in the application, the automation, intelligence and sampling efficiency are significantly improved, the environment can be automatically monitored, the phytoplankton samples can be automatically collected and stored, the real-time monitoring of the environment parameters, the intelligent optimization of the sampling strategy and the integration of the automatic and accurate sampling are realized, and the efficiency, accuracy and research value of the phytoplankton sample collection are significantly improved.

Description

Technical Field

[0001] This invention belongs to the field of plankton and automation technology, specifically relating to an intelligent plankton collection net system. Background Technology

[0002] Traditional plankton collection methods rely on manual operation, which suffers from low sampling efficiency, high cost, and susceptibility to human factors. While automation and intelligent technologies are widely used in various fields, a complete intelligent collection system is still lacking in the field of plankton collection. Summary of the Invention

[0003] The purpose of this invention is to provide an intelligent plankton collection network system that can automatically monitor environmental parameters, intelligently select sampling locations, and automatically collect and store plankton samples, thereby solving the problems mentioned in the background art.

[0004] To achieve the above objectives, the present invention provides the following technical solution: an intelligent plankton collection net system, comprising a control unit, wherein the control unit is connected to:

[0005] The execution module is used to collect plankton;

[0006] The parameter setting module allows for the setting and modification of sampling depth, sampling time, sampling frequency, and sampling volume before and after sampling.

[0007] The real-time environmental monitoring module monitors aquatic environmental parameters in real time after the system is started and transmits the data to the control unit.

[0008] The optimization module, integrated within the control unit, processes and analyzes real-time environmental data through its own algorithms, and optimizes the acquisition strategy based on preset conditions or real-time data. Specifically, this includes selecting the optimal sampling location and adjusting the sampling mesh size.

[0009] The sampling unit receives data from the optimization module and selects the sampling method. Both the sampling unit and the execution module are controlled by the control unit, which controls the execution mechanism to perform automatic sampling operations.

[0010] The sample processing module is used to automatically shut down the sampling net after sampling is completed and transfer the collected planktonic samples to the storage unit;

[0011] Storage unit for storing plankton and preserving their biological characteristics.

[0012] As a preferred technical solution of the present invention, the sampling unit includes

[0013] The automatic sampling module, based on the optimized sampling strategy, sends instructions to the actuator to drive the sampling net to sink to the target depth and automatically activate the sampling net to collect plankton samples.

[0014] The data logging module is used to record sampling data in real time during the sampling process and store the data in internal storage or the cloud.

[0015] As a preferred technical solution of the present invention, the storage unit is provided with a temperature control module with temperature and humidity control functions. The temperature control module is used to ensure that the planktonic samples maintain their biological characteristics and research value during long-term storage.

[0016] As a preferred technical solution of the present invention, a communication module is also connected to the control unit, and a remote monitoring module is connected to the communication module, which transmits the sampling data and status information in real time. The remote monitoring module provides a user login window, enabling the user to remotely access, view real-time data, sampling results and system status, and perform necessary operations and controls.

[0017] As a preferred technical solution of the present invention, the storage unit is further provided with an addition module, which is used to add a fixative to the collected planktonic samples to maintain the freshness and stability of the samples.

[0018] As a preferred technical solution of the present invention, the algorithm used by the optimization module includes:

[0019] Sliding window method:

[0020] Divide the data into fixed-size windows, for example, process the 100 most recent data points each time, calculate the statistics of the data within the window, and dynamically adjust the sampling frequency or strategy based on these statistics.

[0021] Adaptive sampling method:

[0022] The sampling frequency is adjusted according to changes in real-time data, and indicators such as rate of change and data fluctuation are used to determine whether to sample and the sampling frequency.

[0023] Event-driven approach:

[0024] Monitor the occurrence of specific events, such as emergencies or abnormal events, and determine the sampling strategy based on the occurrence of the event.

[0025] As a preferred technical solution of the present invention, the data recording module includes recording sampling time, sampling depth, sampling amount, and environmental parameters.

[0026] As a preferred technical solution of the present invention, the execution module includes a sampling net, a motor, and a propeller connected to the motor; the real-time environment detection module consists of a variety of sensors for detecting water depth, water flow speed, light intensity, and temperature.

[0027] Compared with the prior art, the beneficial effects of the present invention are:

[0028] This invention exhibits significant advantages in automation, intelligence, and sampling efficiency. It can automatically monitor the environment, automatically collect and store planktonic samples, and realize the integration of real-time monitoring of environmental parameters, intelligent optimization of sampling strategies, and automatic and accurate sampling, which significantly improves the efficiency, accuracy, and scientific research value of planktonic sample collection. Attached Figure Description

[0029] Figure 1 This is a system diagram of the present invention. Detailed Implementation

[0030] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0031] Please see Figure 1 This invention provides a technical solution: an intelligent plankton collection net system, including a control unit, on which are connected:

[0032] The execution module is used to collect plankton;

[0033] The parameter setting module allows for the setting and modification of sampling depth, sampling time, sampling frequency, and sampling volume before and after sampling.

[0034] The real-time environmental monitoring module monitors aquatic environmental parameters in real time after the system is started and transmits the data to the control unit.

[0035] The optimization module, integrated within the control unit, processes and analyzes real-time environmental data through its own algorithms, and optimizes the acquisition strategy based on preset conditions or real-time data. Specifically, this includes selecting the optimal sampling location and adjusting the sampling mesh size.

[0036] The sampling unit receives data from the optimization module and selects the sampling method. Both the sampling unit and the execution module are controlled by the control unit, which controls the execution mechanism to perform automatic sampling operations.

[0037] The sample processing module is used to automatically shut down the sampling net after sampling is completed and transfer the collected planktonic samples to the storage unit;

[0038] Storage unit for storing plankton and preserving their biological characteristics.

[0039] In this embodiment, the sampling unit includes

[0040] The automatic sampling module, based on the optimized sampling strategy, sends instructions to the actuator to drive the sampling net to sink to the target depth and automatically activate the sampling net to collect plankton samples.

[0041] The data logging module is used to record sampling data in real time during the sampling process and store the data in internal storage or the cloud.

[0042] In this embodiment, the storage unit is equipped with a temperature control module that controls temperature and humidity. This temperature control module is used to ensure that the planktonic samples maintain their biological characteristics and research value during long-term storage.

[0043] In this embodiment, a communication module is also connected to the control unit, and a remote monitoring module is connected to the communication module. The remote monitoring module transmits the sampling data and status information in real time. The remote monitoring module provides a login window for users, allowing users to remotely access and view real-time data, sampling results and system status, and perform necessary operations and controls.

[0044] In this embodiment, the storage unit is also provided with an addition module, which is used to add a fixative to the collected planktonic samples to maintain the freshness and stability of the samples.

[0045] In this embodiment, the algorithm used by the optimization module includes:

[0046] Sliding window method:

[0047] Divide the data into fixed-size windows, for example, process the 100 most recent data points each time, calculate the statistics of the data within the window, and dynamically adjust the sampling frequency or strategy based on these statistics.

[0048] Adaptive sampling method:

[0049] The sampling frequency is adjusted according to changes in real-time data, and indicators such as rate of change and data fluctuation are used to determine whether to sample and the sampling frequency.

[0050] Event-driven approach:

[0051] Monitor the occurrence of specific events, such as emergencies or abnormal events, and determine the sampling strategy based on the occurrence of the event.

[0052] In this embodiment, the data recording module includes recording sampling time, sampling depth, sampling volume, and environmental parameters.

[0053] In this embodiment, the execution module includes a sampling net, a motor, and a propeller connected to the motor; the real-time environmental detection module consists of a variety of sensors used to detect water depth, water flow speed, light intensity, and temperature.

[0054] Although embodiments of the invention have been shown and described (see the detailed description above), it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. An intelligent plankton collection net system, comprising a control unit, characterized in that: The control unit is connected to: The execution module is used to collect plankton; The parameter setting module allows for the setting and modification of sampling depth, sampling time, sampling frequency, and sampling volume before and after sampling. The real-time environmental monitoring module monitors aquatic environmental parameters in real time after the system is started and transmits the data to the control unit. The optimization module, integrated within the control unit, processes and analyzes real-time environmental data through its own algorithms, and optimizes the acquisition strategy based on preset conditions or real-time data. The sampling unit receives data from the optimization module and selects the sampling method. Both the sampling unit and the execution module are controlled by the control unit, which controls the execution mechanism to perform automatic sampling operations. The sample processing module is used to automatically shut down the sampling net after sampling is completed and transfer the collected planktonic samples to the storage unit; Storage unit for storing plankton and preserving their biological characteristics; The sampling unit includes The automatic sampling module, based on the optimized sampling strategy, sends instructions to the actuator to drive the sampling net to sink to the target depth and automatically activate the sampling net to collect plankton samples. The data recording module is used to record sampling data in real time during the sampling process and store the data in internal storage or the cloud. The storage unit is equipped with a temperature control module that has temperature and humidity control functions. This temperature control module is used to ensure that the planktonic samples maintain their biological characteristics and research value during long-term storage. A communication module is also connected to the control unit, and a remote monitoring module is connected to the communication module. The remote monitoring module transmits the sampling data and status information in real time. The remote monitoring module provides a login window for users, allowing them to remotely access the system, view real-time data, sampling results and system status, and perform necessary operations and controls. The storage unit is also equipped with an addition module, which is used to add fixative to the collected planktonic samples to maintain the freshness and stability of the samples. The algorithms used by the optimization module include: Sliding window method: The data is divided into fixed-size windows, the statistics of the data within the windows are calculated, and the sampling frequency or strategy is dynamically adjusted based on these statistics. Adaptive sampling method: The sampling frequency is adjusted according to changes in real-time data, and the rate of change and data fluctuation indicators are used to determine whether to sample and the sampling frequency. Event-driven approach: Monitor the occurrence of specific events and determine the sampling strategy based on the occurrence of the events; The data recording module includes recording sampling time, sampling depth, sampling volume, and environmental parameters; The execution module includes a sampling net, a motor, and a propeller connected to the motor; the real-time environmental detection module consists of various sensors used to detect water depth, water flow speed, light intensity, and temperature.

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