An oil spill monitoring tracking buoy and control method, computer and storage medium

Abstract

The application discloses an oil spill monitoring and tracking buoy, a control method, a computer and a storage medium, wherein the information acquisition module is used for acquiring monitoring data by using a plurality of sensors arranged on the oil spill monitoring and tracking buoy; the first information processing module is used for screening one type of data in the monitoring data and performing data processing on the one type of data to obtain one type of result data; the information transmission module is used for transmitting the monitoring data and the one type of result data to a remote terminal; and the second data processing module is used for performing data processing on other monitoring data to obtain two types of result data, and combining the one type of result data to obtain an oil spill judgment result. The application collects and processes a plurality of types of information on the water surface by using the oil spill monitoring and tracking buoy, analyzes the oil spill condition on the water surface, accurately judges whether the oil spill condition exists, timely and accurately completes the monitoring of the oil spill condition on the water surface at a low cost, and avoids further harm caused by the oil spill.

Description

Technical Field

[0001] This invention relates to the field of marine environmental monitoring, and in particular to an oil spill monitoring and tracking buoy, control method, computer, and storage medium. Background Technology

[0002] With the continuous increase in oil consumption, the volume of oil transported by sea has also increased. However, oil spills frequently occur during production and transportation, posing a serious threat to the ecological environment. Existing oil spill monitoring technologies mainly rely on satellite remote sensing, aerial observation, and fixed alarm equipment, which suffer from problems such as poor real-time performance, high costs, and significant environmental constraints.

[0003] While buoy technology is an important monitoring method with relatively low cost, current buoy types, such as the ARGO buoy, typically only monitor temperature, salinity, depth, and dissolved oxygen levels. Their ability to detect oil spills is insufficient, failing to accurately obtain relevant information for timely monitoring. Inaccurate monitoring or delayed confirmation can lead to late detection of oil spills, significantly increasing the damage caused and resulting in greater environmental harm, as well as greatly increasing the difficulty and cost of subsequent cleanup. Therefore, there is an urgent need for a low-cost, highly accurate, and timely monitoring method for oil spills. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides an oil spill monitoring and tracking buoy, a corresponding oil spill monitoring and tracking buoy control method, a computer, and a computer storage medium.

[0005] According to one aspect of the present invention, an oil spill monitoring and tracking buoy is provided, comprising: an information acquisition module, a first information processing module, an information transmission module, and a second data processing module; wherein,

[0006] The information acquisition module is used to collect monitoring data using various sensors installed on the oil spill monitoring and tracking buoy;

[0007] The first information processing module is used to filter a type of data from the monitoring data and process the data to obtain a type of result data;

[0008] The information transmission module is used to transmit monitoring data and a type of result data to a remote terminal;

[0009] The second data processing module is used to process the second type of data other than the first type of data in the screened monitoring data to obtain the second type of result data, and combine it with the first type of result data to obtain the oil spill judgment result.

[0010] In the above scheme, the information acquisition module includes at least: an oil spill monitoring unit and a location monitoring unit; wherein,

[0011] The oil spill monitoring unit is used to determine whether there is an oil spill at the location;

[0012] The location monitoring unit is used to acquire the location information of the oil spill monitoring and tracking buoy.

[0013] In the above scheme, the oil spill monitoring unit further includes: a capacitance monitoring subunit, an ultraviolet fluorescence monitoring subunit, an infrared remote sensing monitoring subunit, an optical monitoring subunit, a temperature sensing monitoring subunit, a contact analysis subunit, an image monitoring subunit, and / or a radar monitoring subunit; wherein

[0014] The capacitance monitoring subunit is used to detect capacitance data at the water surface;

[0015] The ultraviolet fluorescence monitoring subunit is used to emit ultraviolet light towards the water surface by utilizing the excitation and fluorescence spectral characteristics of oils, to obtain the reflected light and determine the wavelength data of the reflected light.

[0016] The infrared remote sensing monitoring subunit is used to acquire infrared radiation data from the water surface;

[0017] The optical monitoring subunit is used to emit light towards the water surface by utilizing the difference in refractive index of different liquids, and to collect light intensity data at the light acquisition point.

[0018] The image monitoring subunit is used to acquire water surface image data or water surface video data at the current moment;

[0019] The radar monitoring subunit is used to transmit radar waves to the water surface and acquire radar wave feedback data.

[0020] The temperature sensing monitoring subunit is used to acquire water surface temperature data and water body temperature data;

[0021] The contact analysis subunit is used to acquire material property data using a contact probe sensor.

[0022] In the above scheme, the first information processing module is further used for:

[0023] The monitoring data is filtered according to the preset type to obtain one type of data, and the obtained one type of data is processed to obtain another type of result data.

[0024] Based on the preset type, determine the type of data that needs to be processed locally;

[0025] The system filters and processes one type of data from the monitoring data. Specifically, it compares preset standard capacitance data with capacitance data at the water surface to obtain capacitance judgment data; compares the wavelength data of reflected light with preset wavelength data to obtain fluorescence judgment data; determines the presence of temperature difference boundaries in the infrared radiation image to obtain infrared judgment data; compares light intensity data with preset light intensity data when only water is present to obtain optical judgment data; determines the presence of temperature differences between water surface temperature data and water body temperature data to obtain temperature judgment data; and determines the presence of oily substances on the water surface based on material property data to obtain property judgment data.

[0026] The processed capacitance judgment data, fluorescence judgment data, infrared judgment data, optical judgment data, temperature judgment data and / or attribute judgment data sets are used to generate a type of result data.

[0027] In the above scheme, the information transmission module is further used for:

[0028] Monitoring data and a type of result data are transmitted to a remote terminal via wireless communication; wherein, the wireless communication includes at least mobile communication or satellite communication.

[0029] In the above scheme, the second data processing module is further used for:

[0030] Image analysis and judgment are performed on water surface image data or water surface video data to obtain image judgment data; image analysis and judgment on water surface image data or water surface video data includes: artificial intelligence analysis and judgment or video sequence motion analysis and judgment;

[0031] Based on radar wave feedback data, radar judgment data is obtained according to the difference in echo energy.

[0032] Two types of result data are generated by combining image judgment data and radar judgment data;

[0033] Based on location monitoring information, combined with Class I and Class II result data, it is determined whether there is an oil spill at the location of the oil spill monitoring and tracking buoy, and the oil spill judgment result is obtained.

[0034] In the above scheme, the second data processing module is further used for:

[0035] Based on the first type of result data and the second type of result data, corresponding weight values ​​are set for each judgment data contained therein;

[0036] The oil spill assessment ratio is calculated based on the various assessment data and their respective weight values.

[0037] The oil spill judgment ratio is compared with the preset judgment ratio. When the oil spill judgment ratio is greater than the preset ratio, the oil spill judgment result is that there is an oil spill. When the oil spill judgment ratio is not greater than the preset ratio, the oil spill judgment result is that there is no oil spill.

[0038] According to another aspect of the present invention, an oil spill monitoring and tracking buoy control method is provided, wherein the operation implemented by an oil spill monitoring and tracking buoy as described in any of the above embodiments includes:

[0039] Monitoring data is collected using multiple sensors installed on the oil spill monitoring and tracking buoy;

[0040] The monitoring data is filtered according to the preset type to obtain one type of data, and the obtained one type of data is processed to obtain another type of result data.

[0041] Transmit monitoring data and a type of result data to a remote terminal;

[0042] Data processing is performed on the second category of data other than the first category of data in the screening and monitoring data to obtain the second category of result data, and the oil spill judgment result is obtained by combining the first category of result data.

[0043] According to another aspect of the present invention, a computer is provided that employs the above-described oil spill monitoring and tracking buoy control method, comprising: a processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other through the communication bus;

[0044] The memory is used to store at least one executable instruction that causes the processor to perform operations as described above for an oil spill monitoring and tracking buoy.

[0045] According to another aspect of the present invention, a storage medium is provided for use in a computer as described above, the storage medium storing at least one executable instruction that causes a processor to perform operations as described above for an oil spill monitoring and tracking buoy.

[0046] According to the technical solution provided by the present invention, an oil spill monitoring and tracking buoy includes: an information acquisition module, a first information processing module, an information transmission module, and a second data processing module; wherein, the information acquisition module is used to acquire monitoring data using multiple sensors installed on the oil spill monitoring and tracking buoy; the first information processing module is used to filter one type of data from the monitoring data and process the data to obtain a type of result data; the information transmission module is used to transmit the monitoring data and the type of result data to a remote terminal; the second data processing module is used to process two other types of data besides the filtered one type of monitoring data to obtain two types of result data, and combine the first type of result data to obtain an oil spill judgment result. The technical solution of this invention utilizes an oil spill monitoring and tracking buoy. An information acquisition module within the buoy collects information related to the oil spill situation and the buoy's location. Through capacitance, ultraviolet fluorescence, infrared spectroscopy, visible light, image processing, and radar monitoring subunits within the oil spill detection unit, data is acquired based on various information types and their corresponding acquisition methods to determine the oil spill situation. This diverse collection of data broadens the foundational data for subsequent judgment, making the acquired data more objective and improving the accuracy of subsequent oil spill assessments. Furthermore, by filtering the collected data, only data requiring simple processing can be selected for judgment. Data such as capacitance and fluorescent light data are processed and judged on-board at the buoy, allowing for a preliminary assessment of the oil spill situation before transmission, enabling timely feedback of partial spill assessment results. After transmission, the remaining data requiring complex processing is treated as secondary data and processed and judged remotely by computing equipment. This yields judgment results for each data type, and combining these results with the primary and secondary data to comprehensively determine the oil spill situation, significantly improving accuracy. The judgment results, combined with location information, clearly inform relevant personnel about the specific details of the oil spill, aiding in further action and minimizing the harm and risks caused by the spill. Furthermore, a backpropagation neural network and its constructed confidence allocation function scientifically assign weights to the judgment results of each data type, calculating the oil spill assessment ratio. Based on this ratio and comparison with a preset ratio, the existence of an oil spill is ultimately determined. This intelligent data processing further enhances the overall accuracy and scientific rigor of the assessment.

[0047] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description and the corresponding accompanying drawings.

[0048] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0049] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0050] Figure 1 A structural block diagram of an oil spill monitoring and tracking buoy according to an embodiment of the present invention is shown;

[0051] Figure 2 A structural block diagram of an oil spill monitoring and tracking buoy according to another embodiment of the present invention is shown;

[0052] Figure 3 A schematic diagram of an ultraviolet fluorescence monitoring subunit for an oil spill monitoring and tracking buoy;

[0053] Figure 4 A schematic diagram of an ultraviolet fluorescence monitoring subunit for an oil spill monitoring and tracking buoy;

[0054] Figure 5 A schematic diagram of an ultraviolet fluorescence monitoring subunit for an oil spill monitoring and tracking buoy;

[0055] Figure 6 A flowchart illustrating an oil spill determination method based on neural network technology according to an embodiment of the present invention is shown.

[0056] Figure 7 A flowchart illustrating an oil spill monitoring and tracking buoy control method according to an embodiment of the present invention is shown.

[0057] Figure 8 A schematic diagram of the structure of a computer according to an embodiment of the present invention is shown. Detailed Implementation

[0058] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0059] Figure 1 A structural block diagram of an oil spill monitoring and tracking buoy according to an embodiment of the present invention is shown. The system includes: an information acquisition module 21, a first information processing module 12, an information transmission module 13, and a second data processing module 14; wherein,

[0060] The information acquisition module 21 is used to collect monitoring data using various sensors installed on the oil spill monitoring and tracking buoy 100.

[0061] Preferably, the information acquisition module 21 includes at least: an oil spill monitoring unit 211 and a location monitoring unit 212;

[0062] The oil spill monitoring unit 211 further includes: a capacitance monitoring subunit 2111, an ultraviolet fluorescence monitoring subunit 2112, an infrared remote sensing monitoring subunit 2113, an optical monitoring subunit 2114, an image monitoring subunit 2115 and / or a radar monitoring subunit 2116, a temperature sensing monitoring subunit 2117 and / or a contact analysis subunit 2118.

[0063] The first information processing module 12 is used to filter the monitoring data according to a preset type to obtain a type of data, and to process the obtained type of data to obtain a type of result data.

[0064] The information transmission module 13 is used to transmit monitoring data and a type of result data to a remote terminal.

[0065] Specifically, the information transmission module 13 is further used for:

[0066] Monitoring data and a type of result data are transmitted to a remote terminal via wireless communication; wherein the wireless communication includes at least mobile communication or satellite communication. For example, mobile communication can be 5G communication. The specific transmission method used can be determined according to actual needs and is not limited here.

[0067] The second data processing module 14 is used to process the second type of data other than the first type of data in the screened monitoring data to obtain the second type of result data, and combine the first type of result data to obtain the oil spill judgment result.

[0068] Preferably, the oil spill monitoring and tracking buoy may further include an on-premises storage unit for recording on-premises data.

[0069] An oil spill monitoring and tracking buoy provided according to this embodiment includes: an information acquisition module, a first information processing module, an information transmission module, and a second data processing module; wherein, the information acquisition module is used to acquire monitoring data using multiple sensors installed on the oil spill monitoring and tracking buoy; the first information processing module is used to filter one type of data from the monitoring data and process the data to obtain a type of result data; the information transmission module is used to transmit the monitoring data and the type of result data to a remote terminal; the second data processing module is used to process the other two types of data besides the filtered one type of monitoring data to obtain two types of result data, and combine the first type of result data to obtain an oil spill judgment result. This embodiment provides an oil spill monitoring and tracking buoy. The buoy utilizes an information acquisition module to collect information related to the oil spill situation and the buoy's location. Based on various information types and their corresponding acquisition methods, it obtains data for determining the oil spill situation. This diverse collection of data broadens the foundational data for subsequent judgments, making the acquired data more objective and improving the accuracy of subsequent oil spill assessments. By filtering the collected data, data requiring only simple processing is selected as the first type and processed and judged on-board at the buoy, allowing for an initial assessment of the oil spill situation before transmission. After transmission, the remaining data requiring complex processing is treated as the second type and processed and judged using remote computing equipment. The judgment results for each type of data are then combined to comprehensively determine the oil spill situation, significantly improving the accuracy of the assessment.

[0070] Figure 2 A structural block diagram of an oil spill monitoring and tracking buoy according to another embodiment of the present invention is shown, such as Figure 2 As shown, the system includes: an information acquisition module 21, a first information processing module 12, an information transmission module 13, and a second data processing module 14; wherein,

[0071] The functions that the information transmission module 13 can perform are the same as those described above, and will not be repeated here.

[0072] Specifically, the information acquisition module 21 includes at least: an oil spill monitoring unit 211 and a location monitoring unit 212; wherein,

[0073] The oil spill monitoring unit 211 is used to determine whether there is an oil spill at its location;

[0074] The location monitoring unit 212 is used to acquire the location information of the oil spill monitoring and tracking buoy.

[0075] Preferably, the information acquisition module 21 may further include a temperature monitoring unit 213; the temperature monitoring unit 213 is used to acquire temperature information at the oil spill monitoring and tracking buoy based on a temperature sensor, thereby determining whether the oil spill has caused combustion.

[0076] By collecting the above information, it is easier to determine the specific location of the oil spill based on the assessment of the oil spill and the location information, which will help staff to locate the spill and then carry out the next steps of containment and clear follow-up handling; combined with temperature information, it can be determined whether the oil spill is flammable, so as to avoid danger during subsequent handling.

[0077] Preferably, the oil spill monitoring unit 211 further includes: a capacitance monitoring subunit 2111, an ultraviolet fluorescence monitoring subunit 2112, an infrared remote sensing monitoring subunit 2113, an optical monitoring subunit 2114, an image monitoring subunit 2115 and / or a radar monitoring subunit 2116, a temperature sensing monitoring subunit 2117 and / or a contact analysis subunit 2118; wherein

[0078] The capacitance monitoring subunit 2111 is used to detect capacitance data at the water surface.

[0079] The ultraviolet fluorescence monitoring subunit 2112 is used to emit ultraviolet light towards the water surface by utilizing the excitation spectrum and fluorescence spectrum characteristics of oils, to obtain the reflected light and determine the wavelength data of the reflected light.

[0080] The infrared remote sensing monitoring subunit 2113 is used to acquire infrared radiation data from the water surface;

[0081] The optical monitoring subunit 2114 is used to emit light towards the water surface by utilizing the difference in refractive index of different liquids, and to collect light intensity data at the light acquisition point.

[0082] The image monitoring subunit 2115 is used to acquire water surface image data or water surface video data at the current moment.

[0083] The radar monitoring subunit 2116 is used to transmit radar waves to the water surface and acquire radar wave feedback data; wherein, the radar wave feedback data is the reflected wave collected by the radar after being scattered by the water surface.

[0084] The temperature sensing monitoring subunit 2117 is used to acquire water surface temperature data and water body temperature data;

[0085] The contact analysis subunit 2118 is used to acquire material property data using a contact probe sensor.

[0086] Preferably, the capacitance monitoring subunit 2111 determines the capacitance data at the water surface by setting an electrode plate in a container inserted into the water, based on the difference in dielectric constant between water and oil, and collecting the capacitance signal between the two electrodes, so as to determine whether there is an oil film on the water surface.

[0087] Preferably, the temperature sensing monitoring subunit 2117 uses the temperature difference between the oil film and the water surface when the oil film floats on the water surface to determine whether there is an oil film on the water surface.

[0088] Specifically, the first information processing module 12 is used to filter the monitoring data according to a preset type to obtain a type of data, and to process the obtained type of data to obtain a type of result data.

[0089] Based on preset types, a category of data that needs to be processed by the machine is determined; preferably, capacitance data, reflected light wavelength data, infrared radiation data, light intensity data, water surface temperature data, water body temperature data, and material property data are considered as one category of data.

[0090] The system filters and processes one type of data from the monitoring data. Specifically, it compares preset standard capacitance data with capacitance data at the water surface to obtain capacitance judgment data; compares the wavelength data of reflected light with preset wavelength data to obtain fluorescence judgment data; determines the presence of temperature difference boundaries in the infrared radiation image to obtain infrared judgment data; compares light intensity data with preset light intensity data when only water is present to obtain optical judgment data; determines the presence of temperature differences between water surface temperature data and water body temperature data to obtain temperature judgment data; and determines the presence of oily substances on the water surface based on material property data to obtain property judgment data.

[0091] Preferably, the wavelength data of the reflected light is compared with preset wavelength data to obtain fluorescence judgment data. The principle is based on the fluorescence characteristics of oily substances. Aromatic hydrocarbons (such as benzene, naphthalene, anthracene and their derivatives) in oil spills such as petroleum, diesel, and crude oil have conjugated double bond structures. When excited by ultraviolet light (usually monochromatic light of 254 nm or 365 nm), electrons in the molecules will transition from the ground state to the excited state. When they return to the ground state, they release energy in the form of fluorescence, producing a fluorescence signal of a specific wavelength (usually blue-green light, wavelength range of 400-500 nm). The ultraviolet fluorescence monitoring subunit 2112 emits ultraviolet light to the water surface to excite the oily substances to produce fluorescence. Then, the fluorescence reflected from the water surface is collected, and light of non-target wavelengths (such as ambient light and ultraviolet light reflected from the water surface) is filtered out to determine the wavelength data of the reflected light. Based on the fluorescence judgment data, it is determined whether there is an oil spill.

[0092] Preferably, common light source types can be ultraviolet LEDs, mercury lamps, xenon lamps, or laser light sources; among them,

[0093] Ultraviolet LEDs: long lifespan, low power consumption, commonly used wavelength 365nm (near ultraviolet), suitable for portable devices;

[0094] Mercury lamp / xenon lamp: High emission intensity, covering short wavelengths such as 254nm (far ultraviolet), suitable for laboratory or high-precision online monitoring;

[0095] Laser source: such as pulsed lasers (e.g., Nd:YAG frequency-doubled lasers), used in laser-induced fluorescence (LIF) technology to improve spatial resolution and anti-interference capabilities.

[0096] Furthermore, an excitation light filter is installed at the light source to allow only ultraviolet light of a specific wavelength to pass through, preventing stray light excitation; a fluorescence filter is installed at the receiving point of the reflected light to allow only oil-based fluorescence wavelengths (e.g., 400–500 nm) to pass through, blocking ambient light (e.g., visible light from sunlight) and unabsorbed ultraviolet light. The ultraviolet fluorescence monitoring subunit 2112 can be configured as follows: Figure 3 , 4 As shown in Figure 5, Figure 3 , 4 Figures 5 and 6 are schematic diagrams of an ultraviolet fluorescence monitoring subunit of an oil spill monitoring and tracking buoy.

[0097] Preferably, the principle of acquiring infrared judgment data is: based on thermal radiation theory and electromagnetic spectrum characteristics, that is, the infrared radiation characteristics emitted or reflected by the object itself, to acquire target information. Since the thermal infrared emissivity of oil film is lower than that of water, and the difference between oil temperature and water temperature can form a clear boundary, by discovering the thermal radiation difference in infrared radiation image, all-weather, non-contact perception of the target status is achieved. Its core advantages are thermal information acquisition capability and day and night applicability.

[0098] The processed capacitance judgment data, fluorescence judgment data, infrared judgment data, optical judgment data, temperature judgment data and / or attribute judgment data sets are used to generate a type of result data.

[0099] Specifically, the settings for monitoring sub-units and the determination of a type of data can be modified according to actual needs, and are not limited here.

[0100] Specifically, the second information processing module 24 is further used for,

[0101] Image analysis and judgment are performed on water surface image data or water surface video data to obtain image judgment data; image analysis and judgment on water surface image data or water surface video data includes: artificial intelligence analysis and judgment or video sequence motion analysis and judgment;

[0102] Based on radar wave feedback data, radar judgment data is obtained according to the difference in echo energy.

[0103] Two types of result data are generated by combining image judgment data and radar judgment data;

[0104] Based on location monitoring information, combined with Class I and Class II result data, it is determined whether there is an oil spill at the location of the oil spill monitoring and tracking buoy, and the oil spill judgment result is obtained.

[0105] Preferably, the second information processing module 24 can also be used for,

[0106] By embedding "oil spill drift simulation software" technology into the back-end analysis and processing system of oil spill tracking buoys, and by using artificial intelligence technology and data obtained from the monitoring of the oil spill tracking buoy's surface terminal, it is possible not only to more accurately identify and judge the trajectory of oil spill drift, but also to more timely and accurately predict the location and spread of oil spill drift in the future.

[0107] Due to the unpredictable nature of marine weather and hydrology, the relevant oil spill drift parameters are constantly changing. In particular, when it is impossible to provide continuous, real-time oil spill drift location information and corresponding time parameters, it is quite difficult to accurately predict oil spill drift data using only traditional oil spill models.

[0108] By utilizing artificial intelligence (AI) technology, not only can the monitoring data uploaded by oil spill tracking buoys be quickly identified and analyzed, improving the ability to accurately and rapidly identify oil spill drift trajectories, but also, by providing real-time, continuous, and dynamic oil spill tracking buoy monitoring data, coupled with big data training, pattern recognition technology, and autonomous learning, the accuracy of oil spill drift prediction data becomes more precise. Therefore, the oil spill tracking buoy monitoring system not only possesses the ability to accurately and in real-time track and monitor oil spill trajectories, but also the function of predicting the future drift trajectory and spread range of oil spills. This provides a new technological means for emergency response to oil spill accidents.

[0109] Furthermore, "oil spill drift simulation software" includes, but is not limited to, GNOME (General NOAA Operational Modeling Environment) model; OSMS (Oil Spill Modeling System) model; FVCOM+ (FiniteVolume Coastal Ocean Model) oil particle model; NMEFC3D oil spill model; DELFT3D model, etc.

[0110] Among them, the GNOME model supports wind and flow field inputs and can simulate the drift, diffusion, and weathering processes of oil slicks; the OSMS model can predict the drift trajectory, landfall time, and sedimentation of oil slicks over the next few hours to months, and supports inversion simulation, which can be used for source tracing analysis; the FVCOM+ oil particle model combines the FVCOM hydrodynamic model to provide high-precision flow field data and is suitable for three-dimensional oil spill simulation analysis; the NMEFC3D oil spill model combines dispersant usage effect simulation and can optimize oil droplet breakup and coalescence algorithms, suitable for diffusion prediction of low and medium viscosity oils under complex wind and wave conditions; the DELFT3D model is suitable for environmental impact assessment of land reclamation projects and simulates oil spill drift under complex tidal conditions. In practical applications, users can selectively embed the above-mentioned different "oil spill drift simulation software" according to their actual needs. For example, for emergency response needs, the GNOME model and OSMS model can be embedded; for scientific research and high-precision simulation needs, the FVCOM+ oil particle model and NMEFC3D oil spill model can be embedded.

[0111] According to the aforementioned device, based on an oil spill monitoring and tracking buoy, an information acquisition module within it collects information related to the oil spill situation and the buoy's location. Through capacitance, ultraviolet fluorescence, infrared spectroscopy, visible light, image processing, and radar monitoring subunits in the oil spill detection unit, data for determining the oil spill situation is acquired based on various information types and their corresponding acquisition methods. This multi-faceted data collection enhances the breadth of the foundational data for subsequent judgments, making the acquired data more objective and contributing to the accuracy of subsequent oil spill assessments. Furthermore, by filtering the collected data, only data requiring simple processing for judgment is selected. For the first type of data, such as capacitance and fluorescent light data, processing and judgment are completed on-board at the buoy. A preliminary assessment of the oil spill situation is made as early as possible before transmission, allowing for timely feedback of partial spill assessment results. After transmission, the remaining data requiring more complex processing is treated as the second type of data and processed and judged using remote computing equipment. This yields judgment results for each type of data, and combining the first and second type results comprehensively completes the assessment of the oil spill situation, significantly improving accuracy. The judgment results, combined with location information, clearly indicate the specific details of the oil spill to relevant personnel, aiding in further handling and minimizing the harm and risks caused by the oil spill.

[0112] Figure 6 A flowchart illustrating an oil spill determination method based on neural network technology according to an embodiment of the present invention is shown.

[0113] The method includes the following steps:

[0114] Step S601: Based on the first type of result data and the second type of result data, set corresponding weight values ​​for each judgment data contained therein.

[0115] Step S602: Calculate the oil spill judgment ratio based on each judgment data and its corresponding weight value.

[0116] Specifically, the oil spill judgment ratio is the percentage of judgment data that shows an oil spill situation multiplied by the corresponding weight, and then expressed as a percentage of all judgment data.

[0117] Preferably, a BP neural network is used to calculate the correlation coefficient of each judgment data with respect to the oil spill situation, a basic credibility allocation function is constructed, and the weight values ​​corresponding to each judgment data are set.

[0118] The rules for synthesizing the various judgment data are as follows:

[0119]

[0120] Where e(A) is the result of synthesizing the judgment data; e1…e n For each judgment data; A1…A n represents the judgment result corresponding to each judgment data point, and includes only two results: yes or no oil spill situation; k is the conflict coefficient between each judgment data point.

[0121] Preferably, the weight values ​​corresponding to each judgment data are as follows: 10% for capacitance judgment data, 15% for fluorescence judgment data, 10% for infrared judgment data, 10% for optical judgment data, 10% for temperature judgment data, 15% for attribute judgment data, 20% for image judgment data, and 10% for radar judgment data.

[0122] Step S603: Compare the oil spill judgment ratio with the preset judgment ratio, and determine the oil spill judgment result based on the comparison result.

[0123] Specifically, when the oil spill detection ratio is greater than the preset ratio, the oil spill detection result is that there is an oil spill; when the oil spill detection ratio is not greater than the preset ratio, the oil spill detection result is that there is no oil spill.

[0124] Preferably, the preset ratio can be set to 80%.

[0125] Based on the above method, the judgment results of various types of data are scientifically assigned corresponding weight values ​​through a BP neural network and the confidence allocation function constructed therefrom. The oil spill judgment ratio is calculated, and the oil spill situation is finally determined based on the comparison with the preset ratio. Thus, the accuracy and scientific nature of the overall judgment are further improved by intelligent data processing.

[0126] Figure 7 A flowchart illustrating an oil spill monitoring and tracking buoy control method according to an embodiment of the present invention is shown; as follows: Figure 7 As shown, the method includes the following steps:

[0127] Step S701: Monitoring data is collected using multiple sensors installed on the oil spill monitoring and tracking buoy.

[0128] Specifically, the method of collecting monitoring data using multiple sensors installed on the oil spill monitoring and tracking buoy further includes:

[0129] Determine if there is an oil spill at the location;

[0130] Based on the location information of the oil spill monitoring and tracking buoy.

[0131] Specifically, determining whether there is an oil spill at the location further includes,

[0132] Detect capacitance data at the water surface;

[0133] By utilizing the excitation and fluorescence spectral characteristics of oils, ultraviolet light is emitted towards the water surface, the reflected light is obtained, and the wavelength data of the reflected light is determined.

[0134] Acquire infrared radiation data from the water surface;

[0135] Acquire water surface temperature data and water body temperature data;

[0136] Material property data are acquired using contact probe sensors;

[0137] By utilizing the difference in refractive index of different liquids, light is emitted toward the water surface, and the light intensity data at the light collection point is obtained.

[0138] Obtain current water surface image data or water surface video data;

[0139] It emits radar waves towards the water surface and acquires radar wave feedback data.

[0140] Step S702: Filter one type of data from the monitoring data and process the data to obtain a type of result data.

[0141] Specifically, the process of filtering and processing one type of data from the monitoring data to obtain a type of result data further includes:

[0142] The monitoring data is filtered according to the preset type to obtain one type of data, and the obtained one type of data is processed to obtain another type of result data.

[0143] Based on the preset type, determine the type of data that needs to be processed locally;

[0144] The system filters and processes one type of data from the monitoring data. Specifically, it compares preset standard capacitance data with capacitance data at the water surface to obtain capacitance judgment data; compares reflected light wavelength data with preset wavelength data to obtain fluorescence judgment data; compares infrared radiation data with a first preset light intensity data to obtain infrared judgment data; compares light intensity data with preset light intensity data when only water is present to obtain optical judgment data; determines whether there is a temperature difference between water surface temperature data and water body temperature data to obtain temperature judgment data; and determines whether there are oily substances on the water surface based on material property data to obtain property judgment data.

[0145] The processed capacitance judgment data, fluorescence judgment data, infrared judgment data, optical judgment data, temperature judgment data and / or attribute judgment data sets are used to generate a type of result data.

[0146] Step S703: The monitoring data and a type of result data are transmitted to the remote terminal.

[0147] Specifically, transmitting monitoring data and a type of result data to a remote terminal further includes,

[0148] Monitoring data and a type of result data are transmitted to a remote terminal via wireless communication; wherein, the wireless communication includes at least mobile communication or satellite communication.

[0149] Step S704: Process the second type of data other than the first type of data in the screened monitoring data to obtain the second type of result data, and combine it with the first type of result data to obtain the oil spill judgment result.

[0150] Specifically, the step of processing the second type of data (excluding the first type of data) from the screened monitoring data to obtain the second type of result data, and combining this with the first type of result data to obtain the oil spill judgment result, further includes:

[0151] Image analysis and judgment are performed on water surface image data or water surface video data to obtain image judgment data; image analysis and judgment on water surface image data or water surface video data includes: artificial intelligence analysis and judgment or video sequence motion analysis and judgment;

[0152] Based on radar wave feedback data, radar judgment data is obtained according to the difference in echo energy.

[0153] Two types of result data are generated by combining image judgment data and radar judgment data;

[0154] Based on location monitoring information, combined with Class I and Class II result data, it is determined whether there is an oil spill at the location of the oil spill monitoring and tracking buoy, and the oil spill judgment result is obtained.

[0155] Preferably, the step of processing the second type of data (excluding the first type of data) from the screened monitoring data to obtain second type result data, and combining this with the first type of result data to obtain the oil spill judgment result, further includes:

[0156] Based on the first type of result data and the second type of result data, corresponding weight values ​​are set for each judgment data contained therein;

[0157] The oil spill assessment ratio is calculated based on the various assessment data and their respective weight values.

[0158] The oil spill judgment ratio is compared with the preset judgment ratio. When the oil spill judgment ratio is greater than the preset ratio, the oil spill judgment result is that there is an oil spill. When the oil spill judgment ratio is not greater than the preset ratio, the oil spill judgment result is that there is no oil spill.

[0159] According to the oil spill monitoring and tracking buoy control method provided in this embodiment, monitoring data is collected using multiple sensors installed on the buoy. One type of data is selected from the monitoring data and processed to obtain a first type of result data. The monitoring data and the first type of result data are transmitted to a remote terminal. The remaining second type of data (excluding the first type of data) is processed to obtain second type of result data, and combined with the first type of result data to obtain an oil spill judgment result. This oil spill monitoring and tracking buoy control method collects information related to the oil spill situation and the buoy's location. Through the capacitance, ultraviolet fluorescence, infrared spectroscopy, visible light, image, and radar monitoring subunits in the oil spill detection unit, corresponding data for oil spill situation judgment is obtained based on various different information and their corresponding acquisition methods. This multi-faceted collection of information data enhances the breadth of the basic data materials for subsequent judgment, making the acquired data more objective and contributing to the accuracy of subsequent oil spill situation judgment. By filtering the collected data, data requiring only simple processing for judgment is selected as the first type of data. Data such as capacitance and fluorescent light readings are processed and judged on-board at the buoy, allowing for a preliminary assessment of the oil spill situation before transmission, enabling timely feedback of partial spill assessment results. After transmission, the remaining data requiring complex processing is treated as secondary data and processed and judged remotely by computing equipment. This yields judgment results for each data type, which are then combined to determine the overall oil spill situation, significantly improving accuracy. The judgment results, combined with location information, clearly inform relevant personnel about the specific details of the oil spill, aiding in further action and minimizing the harm and risks caused by the spill. Furthermore, a backpropagation (BP) neural network and its constructed confidence allocation function scientifically assign weights to the judgment results of each data type, calculating the oil spill assessment ratio. Based on this ratio and comparison with a preset ratio, the existence of an oil spill is ultimately determined. This intelligent data processing further enhances the overall accuracy and scientific rigor of the assessment.

[0160] The present invention also provides a non-volatile computer storage medium storing at least one executable instruction that can perform the operation that an oil spill monitoring and tracking buoy in any of the above system embodiments can achieve.

[0161] Figure 8 A schematic diagram of a computer according to an embodiment of the present invention is shown. The specific implementation of the computer is not limited to any particular embodiment. The computer employs an oil spill monitoring and tracking buoy control method as described above.

[0162] like Figure 8As shown, the computer may include: a processor 802, a communications interface 804, a memory 806, and a communications bus 808.

[0163] in:

[0164] The processor 802, communication interface 804, and memory 806 communicate with each other through the communication bus 808.

[0165] The communication interface 804 is used to communicate with other network elements such as clients or other servers.

[0166] The processor 802 is used to execute program 810, which can specifically perform the operations that an oil spill monitoring and tracking buoy can achieve in the above-described embodiment of an oil spill monitoring and tracking buoy.

[0167] Specifically, program 810 may include program code, which includes computer operation instructions.

[0168] Processor 802 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention. The computer may include one or more processors of the same type, such as one or more CPUs; or it may include processors of different types, such as one or more CPUs and one or more ASICs.

[0169] Memory 806 is used to store program 810. Memory 806 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0170] Specifically, program 810 can be used to cause processor 802 to perform the operations that an oil spill monitoring and tracking buoy can achieve in any of the above system embodiments. The specific implementation of each step in program 810 can be found in the corresponding descriptions of the steps and units in the above-described oil spill monitoring and tracking buoy embodiment, and will not be repeated here. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the devices and modules described above can be referred to the corresponding process descriptions in the foregoing method embodiments, and will not be repeated here.

[0171] The algorithms and displays provided herein are not inherently related to any particular computer, virtual system, or other device. Various general-purpose systems can also be used in conjunction with the teachings herein. The required structure for constructing such systems is apparent from the above description. Furthermore, this invention is not directed to any particular programming language. It should be understood that the contents of the invention described herein can be implemented using various programming languages, and the above description of specific languages ​​is for the purpose of disclosing the best mode of implementation of the invention.

[0172] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0173] Similarly, it should be understood that, in order to streamline this disclosure and aid in understanding one or more of the various inventive aspects, in the above description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof. However, this method of disclosure should not be interpreted as reflecting an intention that the claimed invention requires more features than are expressly recited in each claim. Rather, as reflected in the claims, inventive aspects lie in fewer than all features of a single foregoing disclosed embodiment. Therefore, the claims following the detailed description are hereby expressly incorporated into that detailed description, wherein each claim itself is a separate embodiment of the invention.

[0174] Those skilled in the art will understand that modules in the device of the embodiments can be adaptively changed and placed in one or more devices different from that embodiment. Modules, units, or components in the embodiments can be combined into a single module, unit, or component, and further, they can be divided into multiple sub-modules, sub-units, or sub-components. Except where at least some of such features and / or processes or units are mutually exclusive, any combination can be used to combine all features disclosed in this specification (including the accompanying claims, abstract, and drawings) and all processes or units of any method or device so disclosed. Unless expressly stated otherwise, each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) may be replaced by an alternative feature that serves the same, equivalent, or similar purpose.

[0175] Furthermore, those skilled in the art will understand that although some embodiments described herein include certain features but not others included in other embodiments, combinations of features from different embodiments are intended to be within the scope of the invention and form different embodiments. For example, in the claims, any of the claimed embodiments can be used in any combination.

[0176] The various component embodiments of the present invention can be implemented in hardware, or as software modules running on one or more processors, or a combination thereof. Those skilled in the art will understand that microprocessors or digital signal processors (DSPs) can be used in practice to implement some or all of the functions of some or all of the components according to the embodiments of the present invention. The present invention can also be implemented as a device or apparatus program (e.g., a computer program and computer program product) for performing part or all of the methods described herein. Such programs implementing the present invention can be stored on a computer-readable medium, or can be in the form of one or more signals. Such signals can be downloaded from an Internet website, provided on a carrier signal, or provided in any other form.

[0177] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. An oil spill monitoring and tracking buoy, characterized in that, include: The system comprises an information acquisition module, a first information processing module, an information transmission module, and a second data processing module; among which, The information acquisition module is used to collect monitoring data using various sensors installed on the oil spill monitoring and tracking buoy; The information acquisition module includes at least an oil spill monitoring unit and a location monitoring unit; the oil spill monitoring unit further includes an ultraviolet fluorescence monitoring subunit, an infrared remote sensing monitoring subunit, an optical monitoring subunit, an image monitoring subunit, and / or a radar monitoring subunit. The first information processing module is used to filter a type of data from the monitoring data and process the data to obtain a type of result data; The information transmission module is used to transmit monitoring data and a type of result data to a remote terminal; The second data processing module is used to process the second type of data other than the first type of data in the screened monitoring data to obtain the second type of result data, and combine it with the first type of result data to obtain the oil spill judgment result; The second data processing module is also used for, The "oil spill drift simulation software" technology is embedded into the back-end analysis and processing system of the oil spill tracking buoy. Through artificial intelligence technology and data acquired from monitoring at the buoy's surface terminal, the system identifies and judges the trajectory of the oil spill drift, predicting its location and spread over a future period. The "oil spill drift simulation software" includes GNOME (General NOAAO Operational Modeling Environment), OSMS (Oil Spill Modeling System), FVCOM+ (Finite Volume Coastal Ocean Model), NMEFC3D oil spill model, or DELFT3D model. The specific "oil spill drift simulation software" can be selectively embedded according to actual needs. The second data processing module is also used to calculate the correlation coefficient of each judgment data with respect to the oil spill situation using a BP neural network based on the first type of result data and the second type of result data, construct a basic confidence allocation function, and set the weight values ​​corresponding to each judgment data. The rules for synthesizing the various judgment data are as follows: ； ； in, To determine the result of data synthesis; For each judgment data; The judgment results are for each judgment data item, and only include two results: yes or no oil spill. The conflict coefficient between the various judgment data; The oil spill judgment ratio is calculated based on the various judgment data and their corresponding weight values; the oil spill judgment ratio is compared with the preset judgment ratio, and the oil spill judgment result is determined based on the comparison result.

2. The oil spill monitoring and tracking buoy according to claim 1, characterized in that, The oil spill monitoring unit is used to determine whether there is an oil spill at the location; The location monitoring unit is used to acquire the location information of the oil spill monitoring and tracking buoy.

3. The oil spill monitoring and tracking buoy according to claim 1, characterized in that, The ultraviolet fluorescence monitoring subunit is used to emit ultraviolet light towards the water surface by utilizing the excitation and fluorescence spectral characteristics of oils, to obtain the reflected light and determine the wavelength data of the reflected light. The infrared remote sensing monitoring subunit is used to acquire infrared radiation images from the water surface; The optical monitoring subunit is used to emit light towards the water surface by utilizing the difference in refractive index of different liquids, and to collect light intensity data at the light acquisition point. The image monitoring subunit is used to acquire water surface image data or water surface video data at the current moment; The radar monitoring subunit is used to transmit radar waves to the water surface and acquire radar wave feedback data.

4. The oil spill monitoring and tracking buoy according to claim 1, characterized in that, The first information processing module is further configured to: The monitoring data is filtered according to the preset type to obtain one type of data, and the obtained one type of data is processed to obtain another type of result data. Based on the preset type, determine the type of data that needs to be processed locally; The system filters one type of data from the monitoring data and processes it locally. Specifically, it compares the wavelength data of the reflected light with preset wavelength data to obtain fluorescence judgment data; it obtains infrared judgment data based on whether there is a temperature difference boundary in the infrared radiation image; it obtains optical judgment data by comparing the light intensity data with preset light intensity data when there is only water; and it generates a set of result data by combining the processed fluorescence judgment data, infrared judgment data, and optical judgment data.

5. The oil spill monitoring and tracking buoy according to claim 1, characterized in that, The information transmission module is further used for: Monitoring data and a type of result data are transmitted to a remote terminal via wireless communication; wherein, the wireless communication includes at least mobile communication or satellite communication.

6. The oil spill monitoring and tracking buoy according to claim 1, characterized in that, The second data processing module is further used for: Image analysis and judgment are performed on water surface image data or water surface video data to obtain image judgment data; image analysis and judgment on water surface image data or water surface video data includes: artificial intelligence analysis and judgment or video sequence motion analysis and judgment; Based on radar wave feedback data, radar judgment data is obtained according to the difference in echo energy. Two types of result data are generated by combining image judgment data and radar judgment data; Based on location monitoring information, combined with Class I and Class II result data, it is determined whether there is an oil spill at the location of the oil spill monitoring and tracking buoy, and the oil spill judgment result is obtained.

7. A method for controlling oil spill monitoring and tracking buoys, characterized in that, The operation performed by an oil spill monitoring and tracking buoy as described in any one of claims 1-6 includes: Monitoring data is collected using multiple sensors installed on the oil spill monitoring and tracking buoy; The monitoring data includes at least those obtained from performing oil spill monitoring and location monitoring; oil spill monitoring further includes: ultraviolet fluorescence monitoring, infrared remote sensing monitoring, optical monitoring, image monitoring and / or radar monitoring; The monitoring data is filtered according to the preset type to obtain one type of data, and the obtained one type of data is processed to obtain another type of result data. Transmit monitoring data and a type of result data to a remote terminal; Data processing is performed on the second category of data (excluding the first category) from the selected monitoring data to obtain the second category of result data. This second category of result data is then combined with the first category of result data to obtain the oil spill judgment result. This includes: embedding "oil spill drift simulation software" technology into the back-end analysis and processing system of the oil spill tracking buoy. Through artificial intelligence technology and data obtained from the monitoring of the oil spill tracking buoy's surface terminal, the trajectory of the oil spill drift is identified and judged, and the location and spread of the oil spill in the future are predicted. The "oil spill drift simulation software" includes GNOME (General NOAA Operational Modeling Environment) model, OSMS (Oil Spill Modeling System) model, FVCOM+ (Finite Volume Coastal Ocean Model) oil particle model, NMEFC3D oil spill model, or DELFT3D model. The above-mentioned different "oil spill drift simulation software" are selectively embedded according to actual needs. Based on the first-class and second-class result data, the correlation coefficient of each judgment data with respect to the oil spill situation is calculated using a BP neural network, a basic confidence allocation function is constructed, and the weight values ​​corresponding to each judgment data are set. The rules for synthesizing the various judgment data are as follows: ； ； in, To determine the result of data synthesis; For each judgment data; The judgment results are for each judgment data item, and only include two results: yes or no oil spill. The conflict coefficient between the various judgment data; The oil spill judgment ratio is calculated based on the various judgment data and their corresponding weight values; the oil spill judgment ratio is compared with the preset judgment ratio, and the oil spill judgment result is determined based on the comparison result.

8. A computer, characterized in that, The oil spill monitoring and tracking buoy control method as described in claim 7 includes: a processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other through the communication bus; The memory is used to store at least one executable instruction that causes the processor to perform the operation implemented by an oil spill monitoring and tracking buoy as described in any one of claims 1-6.

9. A computer storage medium for use in a computer as described in claim 8, characterized in that, The storage medium stores at least one executable instruction that causes a processor to perform the operation implemented by an oil spill monitoring and tracking buoy as described in any one of claims 1-6.

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