Dispatching management system and method applied to deep-sea organism monitoring buoy

Abstract

The invention discloses a dispatching management system and method applied to a deep-sea organism monitoring buoy, and relates to the field of deep-sea organism monitoring, and the system comprises a data collection subsystem which collects the data of the deep-sea organism monitoring buoy; the data processing subsystem is used for determining the electric quantity state according to the electric quantity of the battery, screening underwater sound signals based on the sound signal state, screening water surface images based on the water surface object state and then uploading the electric quantity state and the water surface image to the intelligent scheduling subsystem; the meteorological data, the water quality data and the position data are analyzed and uploaded to the intelligent scheduling subsystem; and the intelligent scheduling subsystem selects one mode from a watching mode, a monitoring mode, an ending mode and a sleep mode as a current mode by combining a preset start-stop strategy, generates an instruction and respectively issues the instruction to the data acquisition subsystem and the data processing subsystem so as to control start-stop of data acquisition and start-stop of data reporting. The long-term stable operation capability and the energy use efficiency of the buoy are improved.

Description

Technical Field

[0001] This application relates to the field of deep-sea biological surveillance, and in particular to a scheduling management system and method for deep-sea biological surveillance buoys. Background Technology

[0002] As flagship species of marine ecosystems, cetaceans' distribution, behavior, and population dynamics are significant indicators of marine ecological health. In recent years, passive acoustic and optical observation methods, with their advantages of non-invasiveness and long-term continuous observation, have been widely applied in marine mammal research. Buoys, as multi-mission observation platforms integrating acoustic, optical, water quality, and position sensors with communication modules, have become important technological carriers for marine environmental monitoring and biological behavior research.

[0003] In practical applications, buoy platforms not only need to simultaneously undertake multiple tasks such as acoustic monitoring, water parameter acquisition, image recording, and positioning and navigation, but also need to ensure long-term stable operation in environments far from shore, with limited communication and unstable energy supply. Traditional buoy monitoring systems typically rely on solar power and perform functions such as environmental data acquisition and wireless transmission. However, in variable natural environments (such as cloudy days or continuous rainfall), unstable power supply can easily lead to system power depletion, causing data loss, system crashes, and other problems. Existing embedded systems lack flexible task scheduling mechanisms, often performing non-critical tasks even when the power is low, resulting in energy waste. Although some systems have low-power modes, they cannot flexibly switch operating modes in dynamic environments and lack effective task priority management and energy consumption prediction capabilities. Furthermore, in abnormal system conditions, such as a single task occupying CPU resources for an extended period, system response often becomes sluggish or even deadlocked, and traditional designs rarely incorporate independent monitoring modules to intervene in or recover from system behavior. Summary of the Invention

[0004] The purpose of this application is to provide a scheduling and management system and method for deep-sea biological monitoring buoys, which can improve the long-term stable operation capability and energy efficiency of the buoys.

[0005] To achieve the above objectives, this application provides the following solution: In a first aspect, this application provides a scheduling and management system for deep-sea biological monitoring buoys, comprising: The data acquisition subsystem is used to collect data on the battery level of the deep-sea organism monitoring buoy, meteorological data of the surrounding environment, water quality data, surface images, location data, and underwater acoustic signals. A data processing subsystem, connected to the data acquisition subsystem, is used for: determining the battery status based on the battery level and uploading it to the intelligent scheduling subsystem; determining the acoustic signal status based on the underwater acoustic signal, filtering the underwater acoustic signal based on the acoustic signal status, and uploading it to the intelligent scheduling subsystem; determining the state of objects on the water surface based on the water surface image, filtering the water surface image based on the state of objects on the water surface, and uploading it to the intelligent scheduling subsystem; and parsing the meteorological data, the water quality data, and the location data and uploading them to the intelligent scheduling subsystem. The intelligent scheduling subsystem is used to: set a watchdog mode, a monitoring mode, a termination mode, and a sleep mode; select one mode from the watchdog mode, the monitoring mode, the termination mode, and the sleep mode as the current mode based on the power status and the sound signal status, combined with a preset start / stop strategy; generate a first instruction and a second instruction based on the current mode; send the first instruction to the data acquisition subsystem to control the start / stop of data acquisition; and send the second instruction to the data processing subsystem to control the start / stop of data reporting.

[0006] Secondly, this application provides a scheduling and management method for deep-sea biological monitoring buoys, including: Collect battery power, meteorological data, water quality data, surface images, location data, and underwater acoustic signals of the deep-sea organism monitoring buoy; The system determines the battery status based on the battery level; it determines the acoustic signal status based on the underwater acoustic signal, and uploads the underwater acoustic signal after filtering based on the acoustic signal status; it determines the status of objects on the water surface based on the water surface image, and uploads the water surface image after filtering based on the status of objects on the water surface; and it parses the meteorological data, the water quality data, and the location data. Based on the battery status and the sound signal status, and combined with a preset start / stop strategy, select one mode from the following modes as the current mode: the watchdog mode, the monitoring mode, the closing mode, and the sleep mode; generate a first instruction and a second instruction based on the current mode to control the start / stop of data acquisition and the start / stop of data reporting.

[0007] According to the specific embodiments provided in this application, the following technical effects are disclosed: This application collects multiple required data through a data acquisition subsystem, which then processes the data. Based on the processed data, the intelligent scheduling subsystem, in conjunction with a preset start / stop strategy, selects one mode from the following—listening mode, monitoring mode, tailing mode, and hibernation mode—as the current mode and generates an instruction. This instruction is then sent to the data acquisition subsystem to control the start and stop of data acquisition. Through the aforementioned mode switching, this application can automatically and dynamically change the tasks performed by the system, effectively control energy consumption, improve energy efficiency, and ensure the long-term stable operation of the buoy. Attached Figure Description

[0008] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0009] Figure 1 This is a schematic diagram of a scheduling and management system applied to deep-sea biological monitoring buoys in one embodiment of this application.

[0010] Figure 2 This is a schematic diagram illustrating the switching between the listening mode, monitoring mode, termination mode, and sleep mode in one embodiment of this application.

[0011] Figure 3 This is a schematic diagram of the listening mode in one embodiment of this application.

[0012] Figure 4 This is a schematic diagram of the monitoring mode in one embodiment of this application.

[0013] Figure 5 This is a schematic diagram of the closing mode in one embodiment of this application.

[0014] Figure 6 This is a schematic diagram of the hibernation mode in one embodiment of this application. Detailed Implementation

[0015] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0016] This application relates to a power management scheme and low-power intelligent task scheduling for drifting buoys, which is particularly suitable for deep-sea biological monitoring buoys in energy-constrained environments, and can improve the long-term stable operation capability and energy efficiency of the buoys.

[0017] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0018] In one exemplary embodiment, such as Figure 1As shown, a scheduling and management system for deep-sea biological monitoring buoys is provided, the system including a data acquisition subsystem, a data processing subsystem and an intelligent scheduling subsystem.

[0019] (i) The data acquisition subsystem is used to collect data on the battery level of the deep-sea organism monitoring buoy, meteorological data of its environment, water quality data, surface images, location data, and underwater acoustic signals. In a specific application, the data acquisition subsystem includes: a power management module, a meteorological sensor, a water quality sensor, an image acquisition module, a satellite communication module, and a hydrophone. The image acquisition module can be a camera.

[0020] The power management module is used to monitor the battery level of the deep-sea organism monitoring buoy and interacts with the data processing subsystem through the GPIO interface.

[0021] The meteorological sensor is used to monitor meteorological data of the environment in which the deep-sea organism monitoring buoy is located, and interacts with the data processing subsystem through USART; the meteorological data includes temperature, humidity and wind speed data.

[0022] The water quality sensor is used to monitor water quality data of the environment in which the deep-sea organism monitoring buoy is located, and interacts with the data processing subsystem via USART; the water quality data includes water temperature and salinity data.

[0023] The image acquisition module is used to monitor surface images of the environment in which the deep-sea organism monitoring buoy is located, and interacts with the data processing subsystem via Ethernet.

[0024] The satellite communication module is used to monitor the location data of the deep-sea organism monitoring buoy and report the data monitored by other sensors via satellite.

[0025] The hydrophone is used to listen to underwater acoustic signals in the environment of the deep-sea organism monitoring buoy and interacts with the data processing subsystem via SPI.

[0026] (ii) A data processing subsystem, connected to the data acquisition subsystem, is used for: determining the battery status based on the battery power and uploading it to the intelligent scheduling subsystem; determining the acoustic signal status based on the underwater acoustic signal, filtering the underwater acoustic signal based on the acoustic signal status, and uploading it to the intelligent scheduling subsystem; determining the state of objects on the water surface based on the water surface image, filtering the water surface image based on the state of objects on the water surface, and uploading it to the intelligent scheduling subsystem; and parsing the meteorological data, the water quality data, and the location data and uploading them to the intelligent scheduling subsystem.

[0027] In a specific application, the data processing subsystem includes: a power consumption judgment module, an audio data processing module, a video data processing module, a data parsing module, and a data reporting module.

[0028] The battery level determination module determines the battery status based on a first preset battery level value and a second preset battery level value, and transmits this information to the intelligent scheduling subsystem. Specifically, when the battery level is below the first preset battery level value, the battery status is determined to be low; when the battery level exceeds the first preset battery level value but not the second preset battery level value, the battery status is determined to be medium; and when the battery level exceeds the second preset battery level value, the battery status is determined to be high. In practical applications, the first preset battery level value can be set to 20%, and the second preset battery level value can be set to 30%, as needed. This application uses the battery level determination module to determine the relationship between the current battery level and a threshold, and then switches modes based on the determination result.

[0029] The audio data processing module is used to process the underwater acoustic signal using an audio detection algorithm to obtain the acoustic signal status. If the acoustic signal status indicates the presence of a target acoustic signal, the underwater acoustic signal is transmitted to the intelligent scheduling subsystem. Additionally, the audio data processing module can also store the underwater acoustic signal.

[0030] The video data processing module uses image detection algorithms to process the water surface image to determine the state of objects on the water surface. If the state indicates the presence of a target organism, the water surface image is transmitted to the intelligent scheduling subsystem. Additionally, the video data processing module also stores the water surface image.

[0031] The data parsing module is used to parse water quality data, meteorological data, and location data collected by water quality sensors, meteorological sensors, and satellite communication modules, and transmit them to the intelligent scheduling subsystem.

[0032] In practical applications, water surface images need to be compressed before being uploaded.

[0033] The data reporting module is used to upload the power status, meteorological data, water quality data, location data, underwater acoustic signals, and water surface images to the satellite communication module according to the instructions of the intelligent scheduling subsystem.

[0034] (III) The intelligent scheduling subsystem is used to: set a watchdog mode, a monitoring mode, a closing mode, and a sleep mode; select one mode from the watchdog mode, the monitoring mode, the closing mode, and the sleep mode as the current mode based on the power status and the sound signal status, combined with a preset start / stop strategy; generate a first instruction and a second instruction based on the current mode; send the first instruction to the data acquisition subsystem to control the start / stop of data acquisition; and send the second instruction to the data processing subsystem to control the start / stop of data reporting.

[0035] The intelligent scheduling subsystem is connected to the data processing subsystem to realize task scheduling and power management. Four modes are used in the scheduling and management process: monitor mode, tracking mode, wrap-up mode, and hibernation mode.

[0036] The monitoring mode involves: activating the power management module, the meteorological sensor, the water quality sensor, the hydrophone, and the satellite communication module, while deactivating the image acquisition module; and uploading the meteorological data, the water quality data, the underwater acoustic signal, and the location data to a remote terminal via the satellite communication module.

[0037] In short, this mode requires the hydrophone to receive underwater sound signals and run a sound detection algorithm to determine whether to enter monitoring mode. It also requires monitoring and determining battery level to decide whether to enter monitoring mode or sleep mode. Location data, meteorological data, and water quality data need to be read and uploaded periodically; for example, location data should be read every six hours, and meteorological and water quality data every three hours. Furthermore, the RTC clock is corrected when reading location data via GPS. If the system also has a split beam and router configured in the application, these must be disabled in monitoring mode.

[0038] like Figure 3 As shown, in a specific application, after entering the monitor mode, the timer first counts for 1 hour. After 1 hour, the timer flag is triggered, the SPI buffer and algorithm cache are cleared, and then the 6H counter is incremented by 1 and the 3H timer count is incremented by 1. Next, GPS (i.e., location data) is read and recorded. When the 3H count is greater than or equal to 3 (i.e., three hours have been worked), meteorological and water quality (i.e., meteorological data and water quality data) are read and recorded. Then, it is determined whether the 6H count is greater than or equal to 6. If it is (i.e., six hours have been worked), the status and received parameters (if any) are reported through the satellite communication module, and then the 6H count is cleared. Thus, six hours of work are completed. If not (i.e., three hours have been worked, but not six hours), the 3H count is cleared, and the battery level is checked. When the 3H count is less than 3, the battery level is also checked. When the battery level is less than 20%, the system enters sleep mode. When the battery level is greater than 30%, the system returns to the step of the timer counting for 1 hour and performs data monitoring in monitor mode again. If the timer flag is not triggered, read SPI data and execute the biological audio detection algorithm. If a target is found at this time, enter the monitoring mode; if no target is found, return to the step of determining whether the timer flag has been triggered.

[0039] The monitoring mode is as follows: turn on the meteorological sensor, the water quality sensor, and the satellite communication module, and turn them off after data is detected; turn on the image acquisition module, and use an image detection algorithm to process the water surface image to obtain the state of objects on the water surface; turn off the hydrophone and the power management module.

[0040] In short, this mode immediately activates or wakes up all necessary sensors upon entry, then immediately reads and records location, meteorological, and water quality data. Furthermore, the RTC clock is corrected when reading location data via GPS. If the system also uses a split beam and router, both must be enabled in monitoring mode.

[0041] like Figure 4 As shown, in a specific application, after entering the monitoring mode, the hydrophone is turned off, and the camera, split beam and router power are turned on. At the same time, UDP listening is performed to wait for the relevant peripherals to start successfully, and water quality, weather and GPS information are read once. Then, after the timer is reloaded for 10 minutes, it is determined whether the cache is full. If so, the cache is cleared, the timer is waited for to be interrupted, and then the end mode is entered; if not, the timer is waited for to be interrupted directly, and then the end mode is entered.

[0042] The closing mode involves: activating the power management module to monitor the battery level; keeping the meteorological sensor, water quality sensor, and hydrophone switched off; uploading the meteorological data, water quality data, location data, and water surface image to a remote terminal via the satellite communication module; and then shutting down the image acquisition module and satellite communication module after the upload is complete. This closing mode follows the monitoring mode to perform final processing on the monitored data.

[0043] Specifically, in this mode, it checks whether the ARM has stored images (reading cyclically). If images are stored, the satellite is activated to transmit the images stored by the ARM. If the system also has split beams and routers configured in the application, then in the tailing mode, the split beams and routers also need to be turned off.

[0044] like Figure 5As shown, in a specific application, after entering the end-of-life mode, on the one hand, UDP queries for images. When an image (i.e., a water surface image) is found, JSON (meteorological data, water quality data, and location data corresponding to the water surface image) is read and stored in SDRAM, retaining confidence information, etc. Then, all information in SDRAM is read, sorted by time, and a data compression algorithm is executed, waiting for data transmission. On the other hand, the satellite communication module is started and waits for power-on, polling the connection status. If the connection is established, the compressed data is transmitted. If the connection to the satellite network cannot be established, the data is sent to the buffer, the timer is reloaded for 5 minutes, and the data is waited for transmission. After the data is transmitted, the transmission result is cleared, the buffer is written to the log, and finally, the battery level is used to determine whether to enter sleep mode or monitor mode.

[0045] The sleep mode is as follows: the power management module is turned on to monitor the battery level; the battery level and location data are uploaded to the remote terminal via the satellite communication module; and then the satellite communication module, the meteorological sensor, the water quality sensor, the image acquisition module, and the hydrophone are turned off.

[0046] Specifically, in this mode, it is necessary to maintain the power management module interface level, maintain the RTC real-time clock, and attempt to report the system status and read commands every 6 hours. If the system also has a split beam and router configured in the application, then the split beam and router also need to be turned off in sleep mode.

[0047] like Figure 6 As shown, in a specific application, after entering sleep mode, the satellite communication module is activated to send logs, battery level, and GPS information to the remote terminal. At this time, all peripherals are turned off, and the RTC real-time clock reloads and wakes up after 12 hours (the specific timing duration can be set by relevant technical personnel as needed, and is not limited to 6 hours, 12 hours, etc.). If waiting for the RTC wake-up interrupt, the battery level monitored by the power management module is judged. If the battery level is higher than 30%, the satellite communication module is activated to send battery level information, the hydrophone is powered on, and the monitor mode is entered. If the battery level is lower than 30%, the satellite communication module is activated to send logs, battery level, and GPS information, and then the process returns to the step of reloading the RTC real-time clock for 12 hours.

[0048] In practical applications, after the system powers on, the current mode defaults to the monitor mode. Based on this, such as... Figure 2 As shown, the preset start / stop strategy is: When the current mode is the monitor mode, it simultaneously monitors changes in battery power and underwater acoustic signals. If the battery power is low (less than 20%), the monitor mode is switched to sleep mode, in which case the microcontroller and a small portion of the satellite communication functions can be retained.

[0049] If the battery status is high (battery level greater than 30%) when the current mode is sleep mode, the sleep mode will be switched to monitor mode.

[0050] When the current mode is the monitoring mode, if the sound signal status indicates the presence of a target sound signal and the battery status is medium or high (battery power greater than 20%), then the monitoring mode is switched to the surveillance mode, and the required multiple sensors are turned on.

[0051] When the current mode is monitoring mode, it will automatically switch to closing mode after a preset duration.

[0052] When the current mode is the cleanup mode, if the battery status is high after the cleanup process is completed, the cleanup mode is switched to the watchdog mode to wait for the next signal trigger. In the application, after the cleanup process is completed, the local cache needs to be cleared and the battery level needs to be checked.

[0053] When the current mode is the finishing mode, if the battery status is low or medium (battery power less than 30%) after the finishing process corresponding to the finishing mode is completed, then the finishing mode will be adjusted to the sleep mode.

[0054] In one exemplary application, this application introduces a low-power watchdog monitoring module that can proactively interrupt the current task and restart the module when it detects abnormal CPU time consumption or abnormal response of a task, ensuring system recovery and avoiding a stuck state.

[0055] In one exemplary application, this application integrates a high-capacity dedicated battery and an energy redundancy storage unit to achieve a multi-day power supply redundancy design, support energy capture and delayed distribution, and improve battery life in extreme environments.

[0056] In one exemplary application, this application sets up a low power protection and self-recovery mechanism: when the power drops to a critical value, the system will automatically save key data, switch to sleep mode, and periodically wake up to detect the power supply recovery status. Once energy is available, the original task execution will be automatically resumed.

[0057] Based on the same inventive concept, this application also provides a method for implementing the system described above. The solution provided by this method is similar to the implementation scheme described in the system above; therefore, the specific limitations in one or more method embodiments provided below can be found in the system limitations above, and will not be repeated here.

[0058] In one exemplary embodiment, a scheduling and management method for deep-sea biological monitoring buoys is provided, comprising: (1) Collect battery power, meteorological data of the environment, water quality data, water surface images, location data and underwater acoustic signals of the deep-sea biological monitoring buoy.

[0059] (2) Determine the power status based on the battery power; determine the sound signal status based on the underwater sound signal, and upload the underwater sound signal after filtering based on the sound signal status; determine the water surface object status based on the water surface image, and upload the water surface image after filtering based on the water surface object status; parse the meteorological data, the water quality data and the location data.

[0060] (3) Based on the power status and the sound signal status, and in conjunction with the preset start-stop strategy, select one mode from the listening mode, monitoring mode, closing mode and sleep mode as the current mode; generate a first instruction and a second instruction based on the current mode to control the start and stop of data acquisition and the start and stop of data reporting.

[0061] Compared with the prior art, this application has the following advantages: (1) Power sensing and mode switching mechanism: This application can monitor the remaining power in real time and automatically select to enter multiple working modes such as data acquisition, transmission, sleep or ultra-low power consumption according to the battery power level and load requirements, so as to effectively control energy consumption.

[0062] (2) Dynamic scheduling and adaptive management: This application has an intelligent scheduling algorithm that can dynamically allocate task priorities based on external environment (such as climate, task urgency) and internal status (such as power consumption, CPU usage) and reasonably delay the execution of non-critical tasks.

[0063] (3) By switching between the various modes in this application, data protection and minimum power consumption maintenance can be achieved in extreme environments: In the case of no charging input for a long time (such as continuous cloudy days), it can automatically enter the ultra-low power consumption mode of <1mA level, shut down all non-critical modules, and retain only the basic data retention and wake-up logic.

[0064] (4) Signal monitoring and integrated control logic: Under the control of the core scheduling system, this application can continuously monitor environmental signals (such as radar and sensor triggers) and dynamically start response tasks according to the set strategy to achieve true "on-demand wake-up".

[0065] This application achieves intelligent power management and task scheduling in unstable energy environments through software and hardware co-design, significantly improving the system stability, energy efficiency ratio and data integrity of self-powered devices such as buoys.

[0066] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0067] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A dispatch management system applied to a deep-sea biological monitoring buoy, characterized in that, The system comprises: a data acquisition subsystem for acquiring battery power of a deep-sea biological monitoring buoy, meteorological data of an environment where the deep-sea biological monitoring buoy is located, water quality data, water surface images, position data and underwater acoustic signals; a data processing subsystem connected with the data acquisition subsystem, configured to determine a power state according to the battery power and upload the power state to an intelligent scheduling subsystem; determine an acoustic signal state according to the underwater acoustic signals, and upload the underwater acoustic signals to the intelligent scheduling subsystem after screening the underwater acoustic signals based on the acoustic signal state; determine a water surface object state according to the water surface images, and upload the water surface images to the intelligent scheduling subsystem after screening the water surface images based on the water surface object state; analyze the meteorological data, the water quality data and the position data and upload the data to the intelligent scheduling subsystem; the intelligent scheduling subsystem is configured to set a listening mode, a monitoring mode, a tail mode and a hibernation mode; select one mode from the listening mode, the monitoring mode, the tail mode and the hibernation mode as a current mode according to the power state and the acoustic signal state in combination with a preset start-stop strategy; generate a first instruction and a second instruction according to the current mode; send the first instruction to the data acquisition subsystem to control start and stop of data acquisition; and send the second instruction to the data processing subsystem to control start and stop of data uploading.

2. The dispatch management system applied to the deep-sea biological monitoring buoy according to claim 1, characterized in that, The data acquisition subsystem comprises: a power management module for monitoring battery power of the deep-sea biological monitoring buoy; a meteorological sensor for monitoring meteorological data of an environment where the deep-sea biological monitoring buoy is located; a water quality sensor for monitoring water quality data of an environment where the deep-sea biological monitoring buoy is located; an image acquisition module for monitoring water surface images of an environment where the deep-sea biological monitoring buoy is located; a satellite communication module for monitoring position data of an environment where the deep-sea biological monitoring buoy is located and communicating with a satellite; a hydrophone for listening to underwater acoustic signals of an environment where the deep-sea biological monitoring buoy is located.

3. The dispatch management system applied to the deep-sea biological monitoring buoy according to claim 2, characterized in that, The data processing subsystem comprises: a power judgment module for determining a power state of the battery power according to a first preset power value and a second preset power value and transmitting the power state to an intelligent scheduling subsystem; an audio data processing module for processing the underwater acoustic signals by using an audio detection algorithm to obtain an acoustic signal state; if the acoustic signal state is that a target acoustic signal exists, transmitting the underwater acoustic signals to the intelligent scheduling subsystem; a video data processing module for processing the water surface images by using an image detection algorithm to obtain a water surface object state; if the water surface object state is that a target biological object exists, transmitting the water surface images to the intelligent scheduling subsystem; a data analysis module for analyzing the meteorological data, the water quality data and the position data and transmitting the data to the intelligent scheduling subsystem; the data uploading module is configured to upload the power state, the meteorological data, the water quality data, the position data, the underwater acoustic signals and the water surface images to the satellite communication module according to the second instruction of the intelligent scheduling subsystem.

4. The dispatch management system applied to the deep-sea biological monitoring buoy according to claim 3, characterized in that, The power determination module determines the power state of the battery power according to the first preset power value and the second preset power value, and includes: When the battery power does not exceed the first preset power value, the battery power state is determined to be a low power state; When the battery power exceeds the first preset power value and does not exceed the second preset power value, the battery power state is determined to be a medium power state; When the battery power exceeds the second preset power value, the battery power state is determined to be a high power state.

5. The dispatch management system applied to the deep-sea biological monitoring buoy according to claim 1, characterized in that, The preset start-stop strategy is: When the current mode is a listening mode, if the power state is a low power state, the listening mode is adjusted to a sleep mode; When the current mode is a sleep mode, if the power state is a high power state, the sleep mode is adjusted to a listening mode; When the current mode is a listening mode, if the sound signal state is a target sound signal and the power state is a medium power state or a high power state, the listening mode is adjusted to a monitoring mode; When the current mode is a monitoring mode, it is automatically adjusted to a tail mode after a preset time; When the current mode is a tail mode, if the power state is a high power state after the corresponding tail processing of the tail mode is completed, the tail mode is adjusted to a listening mode; When the current mode is a tail mode, if the power state is a low power state or a medium power state after the corresponding tail processing of the tail mode is completed, the tail mode is adjusted to a sleep mode.

6. The dispatch management system applied to the deep-sea biological monitoring buoy according to claim 2, characterized in that, The listening mode is: The power management module, the weather sensor, the water quality sensor, the hydrophone and the satellite communication module are turned on, and the image acquisition module is turned off; The weather data, water quality data, underwater sound signal and position data are uploaded to a remote terminal through the satellite communication module.

7. The dispatch management system applied to the deep-sea biological monitoring buoy according to claim 2, characterized in that, The monitoring mode is: The weather sensor, the water quality sensor and the satellite communication module are turned on, and are turned off after monitoring data; the image acquisition module is turned on; the hydrophone and the power management module are turned off.

8. The dispatch management system applied to the deep-sea biological monitoring buoy according to claim 2, characterized in that, The tail mode is: The power management module is turned on to monitor the battery power; the weather sensor, the water quality sensor and the hydrophone are kept in an off state; The weather data, water quality data, position data and surface image are uploaded to a remote terminal through the satellite communication module, and the image acquisition module and the satellite communication module are turned off after uploading is completed.

9. The dispatch management system applied to the deep-sea biological monitoring buoy according to claim 2, characterized in that, The sleep mode is: The power management module is turned on to monitor the battery power; The battery power and the position data are uploaded to a remote terminal through the satellite communication module, and then the satellite communication module, the weather sensor, the water quality sensor, the image acquisition module and the hydrophone are turned off.

10. A dispatch management method applied to a deep-sea biological monitoring buoy, characterized by, The method includes: Collecting the battery power of the deep sea biological monitoring buoy, the weather data of the environment, the water quality data, the surface image, the position data and the underwater sound signal; determining a battery power state according to the battery power, determining an underwater acoustic signal state according to the underwater acoustic signal, and uploading the underwater acoustic signal after screening based on the underwater acoustic signal state; determining a water surface object state according to the water surface image, and uploading the water surface image after screening based on the water surface object state; analyzing the weather data, the water quality data, and the position data; selecting one mode from a listening mode, a monitoring mode, a finishing mode, and a hibernation mode as a current mode according to the battery power state and the underwater acoustic signal state in combination with a preset start-stop strategy; and generating a first instruction and a second instruction according to the current mode to control the start-stop of data collection and the start-stop of data uploading.

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