Marine monitoring system based on Internet of Things

Abstract

The invention relates to the technical field of ocean monitoring, in particular to an ocean monitoring system based on the Internet of Things, which comprises a data acquisition module, a data transmission module, a data processing module, a data analysis module, a data storage module, an early warning module and a user interaction module, the data transmission module is used for transmitting data acquired by the data acquisition module to the data processing module, the data processing module is used for primarily processing the transmitted data, and the data analysis module is used for deeply analyzing the processed data. Through long-term trend analysis of the data, the change trend of the marine environment can be predicted, through correlation analysis, the mutual relation between different marine environment factors can be found, through anomaly detection and anomaly analysis, the abnormal condition in the marine environment can be found in time, and the reason and influence of the abnormal condition can be analyzed.

Description

Technical Field

[0001] The present invention relates to the technical field of ocean monitoring, and specifically to an ocean monitoring system based on the Internet of Things. Background Art

[0002] The ocean, as the cradle of life on Earth and a key part of the global ecosystem, contains rich resources and plays an irreplaceable role in regulating the climate, maintaining ecological balance, and promoting economic development. Effective monitoring of the ocean environment is not only a necessary means to understand ocean ecological changes and protect the ocean ecosystem, but also a key measure to ensure the sustainable use of ocean resources and prevent the threat of ocean disasters.

[0003] However, traditional ocean monitoring methods have many drawbacks. The traditional method relying on fixed observation stations and regular ocean survey ships has difficulty in comprehensively covering the vast ocean due to the sparse distribution of observation stations. Moreover, the operation range and time of survey ships are limited, making it impossible to achieve real-time and continuous monitoring of the ocean environment, resulting in spatial limitations and time lags in the obtained data. At the same time, the manual data collection process is inefficient, and data loss or inaccuracy may occur in harsh environments. In addition, traditional data processing and analysis methods are difficult to handle the increasing amount of data and cannot effectively mine data value, seriously restricting the timely insight into and response to ocean environmental changes. Summary of the Invention

[0004] In view of the deficiencies of the prior art, the present invention provides an ocean monitoring system based on the Internet of Things to solve the problems raised in the above background art.

[0005] To achieve the above objectives, the present invention is realized through the following technical solutions: An ocean monitoring system based on the Internet of Things includes a data collection module, a data transmission module, a data processing module, a data analysis module, a data storage module, an early warning module, and a user interaction module. The data collection module is used to collect various types of data of the ocean environment. The data transmission module is used to transmit the data collected by the data collection module to the data processing module. The data processing module is used to perform preliminary processing on the transmitted data. The data analysis module is used to perform in-depth analysis on the processed data. The data storage module is used to store the collected, processed, and analyzed data. The early warning module is used to issue corresponding early warning information according to the data analysis results. The user interaction module is used for users to interact with the system to obtain data and early warning information.

[0006] Preferably, the data acquisition module includes a water quality sensor unit, a meteorological sensor unit, an ocean dynamic sensor unit, and a video monitoring unit. The water quality sensor unit is used to collect ocean water quality data, including pH value, dissolved oxygen (DO), chemical oxygen demand (COD), etc. The meteorological sensor unit is used to collect meteorological data on the ocean surface, including wind speed, wind direction, air temperature, air pressure, etc. The ocean dynamic sensor unit is used to collect ocean dynamic data, including sea current speed, sea current direction, wave height, etc. The video monitoring unit is used to obtain images and video information on the ocean surface in real time.

[0007] Preferably, the dissolved oxygen (DO) in the water quality sensor unit is measured by an electrochemical method, and the calculation formula is: DO measured = k·I, where k is the sensitivity coefficient of the sensor, and I is the current value output by the sensor.

[0008] Preferably, the data transmission module includes wired transmission and wireless transmission. The wired transmission uses wired communication technologies such as Ethernet to transmit to the data processing module in a wired manner. The wireless transmission uses LoRa, ZigBee, or 4G / 5G wireless communication technologies to wirelessly transmit the collected data to the data processing module.

[0009] Preferably, the data processing module processes the collected data through the following steps:

[0010] S1. Clean the collected data to remove noise, outliers, and duplicate data in the collected data;

[0011] S2. Convert the format of the cleaned data into a unified format;

[0012] S3. Encrypt the data after format conversion. Use a symmetric encryption algorithm such as the AES algorithm. The calculation formula is: D encrypted = E K (D cleaned ), where E K is the AES encryption operation using the key K, and D cleaned is the data after cleaning and conversion;

[0013] S4. Normalize the encrypted data, and aggregate the normalized data at a certain time interval or spatial range, and calculate its average value. The calculation formula is: where n is the number of data in this time period, and x i is the i-th normalized data.

[0014] Preferably, the data analysis module includes a trend analysis unit, a correlation analysis unit, an anomaly detection unit, and an anomaly analysis unit. The trend analysis unit is used to analyze the change trend of marine environment data over time. The correlation analysis unit is used to analyze the correlation between different types of marine environment data. The calculation formula is: Where x i and y i are the i-th observations of two variables, and are the means of the two variables, and n is the number of observations. The anomaly detection unit is used to detect outliers in the marine environment data. The anomaly analysis unit is used to further analyze the detected outliers to determine the type and possible causes of the anomalies.

[0015] Preferably, the warning module is used for threshold setting and information release. The threshold setting is used to set warning thresholds for different types of marine environment data. The information release is used to send warning information to users via text messages, emails, or system messages when the data analysis results exceed the set warning thresholds.

[0016] The marine monitoring method based on the Internet of Things, which is applied to the marine monitoring system based on the Internet of Things described in any one of the above, includes the following steps:

[0017] 1) Collect various data of the marine environment through the data acquisition module;

[0018] 2) Use the data transmission module to transmit the collected data to the data processing module;

[0019] 3) The data processing module performs preliminary processing on the transmitted data, including data cleaning, data conversion, data encryption, data normalization, and data aggregation;

[0020] 4) The data analysis module performs in-depth analysis on the processed data, including trend analysis, correlation analysis, anomaly detection, and anomaly analysis;

[0021] 5) Store the collected, processed, and analyzed data in the data storage module;

[0022] 6) According to the data analysis results, send a warning message when the data exceeds the set threshold;

[0023] 7) The user interacts with the system through the user interaction module to obtain data and warning information.

[0024] The present invention provides a marine monitoring system based on the Internet of Things. It has the following beneficial effects:

[0025] 1. By deploying a large number of sensor nodes, the present invention can achieve all-round and multi-level monitoring of the marine environment. These sensor nodes can be distributed in different regions and depths of the ocean, including the sea surface, seabed, upper and middle layers of the ocean, etc., so as to obtain more comprehensive marine environment data, make up for the deficiencies of traditional monitoring methods in spatial coverage, and can collect various types of data of the marine environment in real time and accurately, such as water quality parameters, meteorological data, marine dynamic data, etc. At the same time, through the wireless communication technology of the Internet of Things, the data can be transmitted to the monitoring center in a timely manner, reducing the delay and error of data transmission and ensuring the timeliness and accuracy of the data.

[0026] 2. Through units such as data cleaning, transformation, encryption, normalization and aggregation, the present invention can quickly and effectively process the massive data collected, remove noise and outliers, unify the data format, improve the quality and usability of the data, and provide a solid foundation for subsequent data analysis. Through long-term trend analysis of the data, the change trend of the marine environment can be predicted. Through correlation analysis, the mutual relationship between different marine environment factors can be found. Through anomaly detection and anomaly analysis, anomalies in the marine environment can be discovered in a timely manner, and their causes and impacts can be analyzed, providing a scientific basis for marine management and decision-making. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a schematic diagram of the system flow of the present invention;

[0028] Figure 2 It is a schematic diagram of the data acquisition module system of the present invention;

[0029] Figure 3 It is a schematic diagram of the data analysis module system of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0030] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0031] As Figures 1 - 3As shown in the figure, the embodiment of the present invention provides an ocean monitoring system based on the Internet of Things, including a data acquisition module, a data transmission module, a data processing module, a data analysis module, a data storage module, an early warning module, and a user interaction module. The data acquisition module is used to collect various types of data of the ocean environment. The data transmission module is used to transmit the data collected by the data acquisition module to the data processing module. The data processing module is used to perform preliminary processing on the transmitted data. The data analysis module is used to perform in-depth analysis on the processed data. The data storage module is used to store the data collected, processed, and analyzed. The early warning module is used to issue corresponding early warning information according to the data analysis results. The user interaction module is used for users to interact with the system to obtain data and early warning information.

[0032] In this embodiment, the data acquisition module includes a water quality sensor unit, a meteorological sensor unit, an ocean dynamic sensor unit, and a video monitoring unit. The water quality sensor unit is used to collect ocean water quality data, including pH value, dissolved oxygen (DO), chemical oxygen demand (COD), etc. The meteorological sensor unit is used to collect meteorological data on the ocean surface, including wind speed, wind direction, air temperature, air pressure, etc. The ocean dynamic sensor unit is used to collect ocean dynamic data, including sea current speed, sea current direction, wave height, etc. The video monitoring unit is used to obtain real-time images and video information of the ocean surface.

[0033] In this embodiment, the dissolved oxygen (DO) measurement in the water quality sensor unit adopts an electrochemical method, and the calculation formula is: DO measured = k·I, where k is the sensitivity coefficient of the sensor and I is the current value output by the sensor.

[0034] In this embodiment, the data transmission module includes wired transmission and wireless transmission. Wired transmission uses wired communication technologies such as Ethernet to transmit data to the data processing module in a wired manner. Wireless transmission uses LoRa, ZigBee, or 4G / 5G wireless communication technologies to wirelessly transmit the collected data to the data processing module.

[0035] Specifically, by deploying a large number of sensor nodes, it is possible to achieve all-round and multi-level monitoring of the ocean environment. These sensor nodes can be distributed in different regions and depths of the ocean, including the sea surface, the seabed, the upper and middle layers of the ocean, etc., so as to obtain more comprehensive ocean environment data, make up for the deficiencies of traditional monitoring methods in spatial coverage, and can collect various types of data of the ocean environment in real time and accurately, such as water quality parameters, meteorological data, ocean dynamic data, etc. At the same time, through the wireless communication technology of the Internet of Things, the data can be transmitted to the monitoring center in a timely manner, reducing the delay and error of data transmission, and ensuring the timeliness and accuracy of the data.

[0036] In this embodiment, the data processing module processes the collected data including the following steps:

[0037] S1. Clean the collected data to remove noise, outliers, and duplicate data from the collected data;

[0038] S2. Convert the format of the cleaned data into a unified format;

[0039] S3. Encrypt the data after format conversion using a symmetric encryption algorithm such as the AES algorithm. The calculation formula is: D encrypted = E K (D cleaned ), where E K is the AES encryption operation using the key K, and D cleaned is the data after cleaning and conversion;

[0040] S4. Normalize the encrypted data and aggregate the normalized data at a certain time interval or spatial range, and calculate its average value. The calculation formula is: where n is the number of data in this time period, and x i is the i-th normalized data.

[0041] In this embodiment, the data analysis module includes a trend analysis unit, a correlation analysis unit, an anomaly detection unit, and an anomaly analysis unit. The trend analysis unit is used to analyze the change trend of ocean environment data over time. The correlation analysis unit is used to analyze the correlation between different types of ocean environment data. The calculation formula is: where x i and y i are the i-th observations of two variables, and are the means of the two variables, and n is the number of observations. The anomaly detection unit is used to detect outliers in the ocean environment data, and the anomaly analysis unit is used to further analyze the detected outliers to determine the type and possible causes of the anomalies.

[0042] In this embodiment, the warning module is used for threshold setting and information publishing. Threshold setting is used to set warning thresholds for different types of ocean environment data. Information publishing is used to send warning information to users via text messages, emails, or system messages when the data analysis results exceed the set warning thresholds.

[0043] The ocean monitoring method based on the Internet of Things, applied to the ocean monitoring system based on the Internet of Things in any one of the above, includes the following steps:

[0044] 1). Collect various types of data of the ocean environment through the data collection module;

[0045] 2). Use the data transmission module to transmit the collected data to the data processing module;

[0046] 3) The data processing module performs preliminary processing on the transmitted data, including data cleaning, data conversion, data encryption, data normalization, and data aggregation;

[0047] 4) The data analysis module conducts in-depth analysis on the processed data, including trend analysis, correlation analysis, anomaly detection, and anomaly analysis;

[0048] 5) Store the collected, processed, and analyzed data into the data storage module;

[0049] 6) According to the data analysis results, issue a warning message when the data exceeds the set threshold;

[0050] 7) Users interact with the system through the user interaction module to obtain data and warning messages.

[0051] Specifically, through units such as data cleaning, conversion, encryption, normalization, and aggregation, it is possible to quickly and effectively process the massive amounts of data collected, remove noise and outliers, unify the data format, improve the quality and usability of the data, and provide a solid foundation for subsequent data analysis. Through long-term trend analysis of the data, the changing trends of the marine environment can be predicted. Through correlation analysis, the interrelationships between different marine environmental factors can be discovered. Through anomaly detection and anomaly analysis, anomalies in the marine environment can be promptly detected, and their causes and impacts can be analyzed, providing a scientific basis for marine management and decision-making. At the same time, it can, based on the data analysis results, monitor in real time whether the marine environment data exceeds the set warning threshold. Once an anomaly is detected, the system can quickly send warning messages to users via text messages, emails, or system messages, providing timely decision support for the prevention and response to marine disasters. Moreover, through the analysis and mining of a large amount of marine environment data, intelligent decision support can be provided. For example, based on marine water quality data and fishery resource data, scientific advice can be provided for fishery fishing. Based on marine dynamic data and meteorological data, safety guarantees can be provided for maritime navigation and marine engineering. It can promote the cross-integration and cross-field cooperation of multiple fields such as marine science, information technology, and environmental science. Experts and researchers in different fields can carry out joint research and technological innovation based on the data and analysis results provided by the system, jointly promoting the development and application of marine monitoring technologies.

[0052] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An ocean monitoring system based on the Internet of Things, comprising a data acquisition module, a data transmission module, a data processing module, a data analysis module, a data storage module, an early warning module and a user interaction module, characterized in that, The data acquisition module is used to collect various types of data of the marine environment. The data transmission module is used to transmit the data collected by the data acquisition module to the data processing module. The data processing module is used to preliminarily process the transmitted data. The data analysis module is used to deeply analyze the processed data. The data storage module is used to store the data after collection, processing, and analysis. The warning module is used to issue corresponding warning information according to the data analysis results. The user interaction module is used for users to interact with the system to obtain data and warning information.

2. The marine monitoring system based on the Internet of Things according to claim 1, characterized in that, The data acquisition module includes a water quality sensor unit, a meteorological sensor unit, a marine dynamics sensor unit, and a video monitoring unit. The water quality sensor unit is used to collect marine water quality data, including acidity and alkalinity (pH value), dissolved oxygen (DO), chemical oxygen demand (COD), etc. The meteorological sensor unit is used to collect meteorological data on the ocean surface, including wind speed, wind direction, air temperature, air pressure, etc. The marine dynamics sensor unit is used to collect marine dynamics data, including sea current speed, sea current direction, wave height, etc. The video monitoring unit is used to obtain images and video information on the ocean surface in real time.

3. The marine monitoring system based on the Internet of Things according to claim 1, characterized in that The dissolved oxygen (DO) measurement in the water quality sensor unit adopts an electrochemical method, and the calculation formula is: DO measured = k·I, where k is the sensitivity coefficient of the sensor and I is the current value output by the sensor.

4. The ocean monitoring system based on the Internet of Things according to claim 1, characterized in that The data transmission module includes wired transmission and wireless transmission. The wired transmission uses wired communication technologies such as Ethernet to transmit data to the data processing module in a wired manner. The wireless transmission uses LoRa, ZigBee, or 4G / 5G wireless communication technologies to wirelessly transmit the collected data to the data processing module.

5. The marine monitoring system based on the Internet of Things according to claim 1, characterized in that The data processing module processes the collected data including the following steps: S1. Clean the collected data to remove noise, outliers, and duplicate data in the collected data; S2. Convert the format of the cleaned data into a unified format; S3. Encrypt the data after format conversion using a symmetric encryption algorithm such as the AES algorithm. The calculation formula is: D encrypted = E K (D cleaned ), where E K is the AES encryption operation using the key K, and D cleaned is the data after cleaning and conversion; S4. Normalize the encrypted data, aggregate the normalized data at certain time intervals or within a certain spatial range, and calculate its average value. The calculation formula is as follows: In the formula, n is the number of data within this time period, and x i is the i-th normalized data.

6. The ocean monitoring system based on the Internet of Things according to claim 1, wherein The data analysis module includes a trend analysis unit, a correlation analysis unit, an anomaly detection unit, and an anomaly analysis unit. The trend analysis unit is used to analyze the change trend of marine environmental data over time. The correlation analysis unit is used to analyze the correlation between different types of marine environmental data. The calculation formula is: where x i and y i are the i-th observations of two variables, and are the means of the two variables, and n is the number of observations. The anomaly detection unit is used to detect outliers in the marine environmental data. The anomaly analysis unit is used to further analyze the detected outliers to determine the type and possible causes of the anomalies.

7. The ocean monitoring system based on the Internet of Things according to claim 1, characterized in that, The warning module is used for threshold setting and information release. The threshold setting is used to set warning thresholds for different types of marine environment data. The information release is used to send warning information to users via text messages, emails, or system messages when the data analysis results exceed the set warning thresholds.

8. An ocean monitoring method based on the Internet of Things, applied to the ocean monitoring system based on the Internet of Things according to any one of claims 1-7, characterized in that, Including the following steps: 1). Collect various types of data of the marine environment through the data acquisition module; 2). Use the data transmission module to transmit the collected data to the data processing module; 3). The data processing module preliminarily processes the transmitted data, including data cleaning, data conversion, data encryption, data normalization, and data aggregation; 4). The data analysis module deeply analyzes the processed data, including trend analysis, correlation analysis, anomaly detection, and anomaly analysis; 5). Store the data after collection, processing, and analysis into the data storage module; 6). According to the data analysis results, issue warning information when the data exceeds the set threshold; 7). Users interact with the system through the user interaction module to obtain data and warning information.

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