Marine environment online monitoring and early warning system based on Internet of Things

Abstract

The invention belongs to the technical field of marine environment monitoring, and particularly relates to a marine environment online monitoring and early warning system based on the Internet of Things, which comprises a marine environment monitoring module, a regional environment pollution analysis module, a pollution trend evaluation module and a marine monitoring center, according to the invention, the marine environment monitoring module monitors the marine supervision region, and the regional environment pollution analysis module and the pollution trend evaluation module accurately judge the real-time pollution condition and pollution trend of the environment of the marine supervision region and give an early warning in time, so that the effective monitoring management of the environment of the marine supervision region is realized. All buoy devices are positioned and monitored through the buoy positioning and monitoring module, and the buoy management abnormity decision-making module analyzes the management conditions of the buoy devices in the ocean supervision area, so that the monitoring effect and the monitoring stability of the ocean environment are ensured, and the difficulty of ocean environment monitoring and management is remarkably reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of marine environment monitoring, and in particular to an online marine environment monitoring and early warning system based on the Internet of Things. Background Art

[0002] With the increasing development and utilization of marine resources, the monitoring and protection of the marine environment has become particularly important. The Chinese invention patent with the publication number CN115580790A discloses an Internet-based marine environment monitoring system, which can comprehensively obtain marine environmental data and generate corresponding marine environmental data reports, thus playing an efficient and reasonable role in promoting the development of the marine environment.

[0003] However, in actual application, although the above invention technical solution can realize the comprehensive collection of marine environmental parameters, it is unable to reasonably analyze and accurately feedback the real-time pollution status and pollution trend of the corresponding marine area, and it is unable to accurately evaluate the management performance of all buoy equipment when monitoring the marine environment through buoy equipment, which is not conducive to ensuring the monitoring effect and monitoring stability of the marine environment, and the marine environment monitoring management is difficult;

[0004] In view of the above technical defects, a solution is now proposed. Summary of the invention

[0005] The purpose of the present invention is to provide an online monitoring and early warning system for the marine environment based on the Internet of Things, which solves the problems that the prior art cannot reasonably analyze and accurately feedback the real-time pollution status and pollution trend of the corresponding marine area, and cannot accurately evaluate the management performance of all buoy equipment when monitoring the ocean through buoy equipment, making the marine environment monitoring and management difficult.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] An online marine environment monitoring and early warning system based on the Internet of Things, including a marine environment monitoring module, a regional environmental pollution analysis module, a pollution trend assessment module and a marine monitoring center;

[0008] The marine environment monitoring module obtains the marine area that needs to be monitored and marks it as a marine regulatory area. It monitors the marine environment through a number of buoy devices distributed in the marine regulatory area, and sends the monitoring data of various pollution parameters of the marine environment to the regional environmental pollution analysis module and the marine monitoring center;

[0009] The regional environmental pollution analysis module conducts real-time analysis of the pollution status of the marine regulatory area, generates regional high pollution signals or regional low pollution signals through analysis, and sends the marine high pollution signals or marine low pollution signals to the marine monitoring center;

[0010] The pollution trend assessment module is used to set the monitoring period. If no high marine pollution signal is generated during the monitoring period, the pollution trend of the marine regulatory area during the monitoring period will be analyzed, and a pollution trend warning signal or a pollution trend qualified signal will be generated through the analysis. The pollution trend warning signal or the pollution trend qualified signal will be sent to the marine monitoring center; the marine monitoring center will issue a corresponding warning when it receives a regional high pollution signal or a pollution trend warning signal.

[0011] Furthermore, the ocean monitoring center is connected to the buoy positioning monitoring module through communication. The buoy positioning monitoring module obtains all buoy devices distributed in the ocean supervision area, collects the real-time position of the corresponding buoy device, and marks the movement distance of the real-time position of the corresponding buoy device compared to its initial position as the buoy movement inspection value;

[0012] The buoy movement detection value is compared with the preset buoy movement detection threshold. If the buoy movement detection value exceeds the preset buoy movement detection threshold, a positioning warning signal of the corresponding buoy equipment is generated, and the positioning warning signal of the corresponding buoy equipment is sent to the ocean monitoring center. When the ocean monitoring center receives the positioning warning signal, it will issue a corresponding warning.

[0013] Furthermore, the ocean monitoring center is connected to the buoy management abnormality decision module through communication, and the buoy management abnormality decision module divides the ocean supervision area into a number of sub-areas of equal area, and marks the corresponding sub-area as target area i, where i is a natural number greater than 1;

[0014] The management status of the buoy equipment will be analyzed, and a buoy management abnormality signal or a buoy management normal signal will be generated through the analysis. The buoy management abnormality signal or the buoy management normal signal will be sent to the ocean monitoring center. When the ocean monitoring center receives the buoy management abnormality signal, it will issue a corresponding warning.

[0015] Furthermore, the specific analysis process of the buoy distribution anomaly decision module includes:

[0016] The number of buoy devices distributed in the target area i is collected and marked as a buoy distribution detection value, and the failure rate and loss rate of the buoy devices in the target area i in the historical stage are collected and marked as a buoy failure detection value and a buoy loss detection value, respectively, and the buoy distribution decision value is obtained by numerically calculating the buoy distribution detection value, the buoy failure detection value and the buoy loss detection value;

[0017] The buoy distribution decision value is numerically compared with the preset buoy distribution decision value range. If the buoy distribution decision value is not within the preset buoy distribution decision value range, the target area i is marked as a red alert area; if a red alert area exists, a buoy management abnormality signal is generated.

[0018] Furthermore, if there is no red alert area, the difference between the buoy distribution decision value of the target area i and the median of the preset buoy distribution decision value range is calculated and the absolute value is taken to obtain the buoy distribution deviation value, and the buoy distribution deviation values ​​of all sub-areas in the marine regulatory area are averaged to obtain the buoy distribution deviation value;

[0019] The buoy equipment abnormality value of the corresponding buoy equipment is obtained through analysis, and the buoy equipment abnormality value is compared with the preset buoy equipment abnormality threshold. If the buoy equipment abnormality value exceeds the preset buoy equipment abnormality threshold, the corresponding buoy equipment is marked as abnormal equipment; the number ratio of abnormal equipment is obtained and marked as abnormal detection value, and the average of all buoy equipment abnormality values ​​is calculated to obtain the abnormality comprehensive inspection value;

[0020] The pipe condition assessment value is obtained by numerically calculating the buoy distribution deviation value, pipe abnormality detection value and pipe abnormality comprehensive inspection value, and the pipe condition assessment value is numerically compared with the preset pipe condition assessment threshold. If the pipe condition assessment value exceeds the preset pipe condition assessment threshold, a buoy management abnormality signal is generated; if the pipe condition assessment value does not exceed the preset pipe condition assessment threshold, a buoy management normal signal is generated.

[0021] Furthermore, the method for analyzing and obtaining the abnormal value of the buoy equipment is as follows:

[0022] Set the detection period, collect the duration of the corresponding buoy equipment being unable to operate normally due to the fault, compare the corresponding duration with the corresponding preset duration threshold, and assign the fault response symbol ZP-1 if the corresponding duration exceeds the preset duration threshold;

[0023] The ratio of the corresponding duration to the corresponding preset duration threshold is marked as the duration value, the average of all the duration values ​​corresponding to the corresponding buoy equipment during the detection period is calculated to obtain the duration analysis value, and the number of times the corresponding buoy equipment is assigned the fault response symbol ZP-1 during the detection period is marked as the fault response value; the buoy equipment management abnormal value is obtained by numerically calculating the duration analysis value and the fault response value.

[0024] Furthermore, the specific analysis process of the regional environmental pollution analysis module is as follows:

[0025] Obtain the monitoring data of various pollution parameters collected by the corresponding buoy equipment, compare each monitoring data with the corresponding preset data requirements one by one, if the corresponding monitoring data does not meet the corresponding preset data requirements, mark the corresponding pollution parameter as an abnormal parameter; mark the deviation value of the monitoring data corresponding to the abnormal parameter compared with the corresponding preset data requirements as an abnormal value, set each type of pollution parameter to correspond to a set of preset weight values ​​in advance, multiply the corresponding abnormal value with the corresponding preset weight value to obtain the abnormal value;

[0026] Obtain all the anomaly table values ​​corresponding to the corresponding buoy equipment and sum them up to obtain the buoy area anomaly detection value, compare the buoy area anomaly detection value with the preset buoy area anomaly detection threshold, and if the buoy area anomaly detection value exceeds the preset buoy area anomaly detection threshold, mark the area corresponding to the corresponding buoy equipment as a polluted area;

[0027] The number percentage of polluted areas in the marine regulatory area is obtained and marked as the marine pollution share value, and the buoy area detection values ​​of all buoy equipment are averaged to obtain the regional pollution performance value, and the buoy area detection value with the largest value is marked as the regional pollution detection amplitude value; the regional pollution comprehensive evaluation value is obtained by numerically calculating the marine pollution share value, the regional pollution performance value and the regional pollution detection amplitude value, and the regional pollution comprehensive evaluation value is numerically compared with the preset regional pollution comprehensive evaluation threshold. If the regional pollution comprehensive evaluation value exceeds the preset regional pollution comprehensive evaluation threshold, a high marine pollution signal is generated; if the regional pollution comprehensive evaluation value does not exceed the preset regional pollution comprehensive evaluation threshold, a low marine pollution signal is generated.

[0028] Furthermore, the specific analysis process of the pollution trend assessment module is as follows:

[0029] Obtain all regional pollution comprehensive evaluation values ​​within the monitoring period, calculate the difference between two adjacent groups of regional pollution comprehensive evaluation values ​​to obtain the regional pollution growth value, mark the number of positive regional pollution growth values ​​within the monitoring period as the pollution trend anomaly detection value, compare the pollution trend anomaly detection value with the preset pollution trend anomaly detection threshold, and generate a pollution trend warning signal if the pollution trend anomaly detection value exceeds the preset pollution trend anomaly detection threshold.

[0030] Furthermore, if the pollution trend anomaly detection value does not exceed the preset pollution trend anomaly detection threshold, the positive regional pollution growth value is numerically compared with the preset regional pollution growth threshold, and the number of regional pollution growth values ​​exceeding the preset regional pollution growth threshold during the monitoring period is marked as the regional pollution increase anomaly value, and the regional pollution growth value with the largest value is marked as the regional pollution increase value;

[0031] The pollution trend assessment value is obtained by numerically calculating the pollution trend anomaly detection value, the regional pollution increase anomaly value and the regional pollution increase value, and the pollution trend assessment value is numerically compared with the preset pollution trend assessment threshold. If the pollution trend assessment value exceeds the preset pollution trend assessment threshold, a pollution trend warning signal is generated; if the pollution trend assessment value does not exceed the preset pollution trend assessment threshold, a pollution trend qualified signal is generated.

[0032] Compared with the prior art, the present invention has the following beneficial effects:

[0033] 1. In the present invention, the marine regulatory area is monitored by the marine environment monitoring module, and the regional environmental pollution analysis module analyzes the pollution status of the marine regulatory area in real time. If no regional high pollution signal is generated during the monitoring period, the pollution trend of the marine regulatory area during the monitoring period is analyzed by the pollution trend assessment module. When a regional high pollution signal or a pollution trend warning signal is generated, the marine monitoring center issues an early warning, thereby achieving effective monitoring and management of the marine regulatory area environment and significantly reducing the work difficulty of marine monitoring personnel;

[0034] 2. In the present invention, all buoy devices are positioned and monitored through the buoy positioning monitoring module. When a positioning warning signal is generated, the corresponding buoy device is searched and returned to its position. The management status of the buoy equipment in the marine supervision area is analyzed through the buoy management abnormality decision module. A buoy management abnormality signal or a buoy management normal signal is generated through analysis. When the buoy management abnormality signal is generated, the supervision of all buoy devices is strengthened to ensure the subsequent monitoring effect and monitoring stability of the marine environment, and further reduce the management difficulty of marine environment monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to facilitate understanding by those skilled in the art, the present invention is further described below in conjunction with the accompanying drawings;

[0036] Figure 1 This is a system block diagram of Embodiment 1 of the present invention;

[0037] Figure 2 This is a system block diagram of Embodiment 2 and Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0038] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0039] Embodiment 1: Figure 1 As shown, the present invention proposes an online marine environment monitoring and early warning system based on the Internet of Things, including a marine environment monitoring module, a regional environmental pollution analysis module, a pollution trend assessment module and a marine monitoring center;

[0040] The marine environment monitoring module obtains the marine areas that need to be monitored and marks them as marine regulatory areas. It monitors the marine environment through a number of buoy devices distributed in the marine regulatory areas, and sends the monitoring data of various pollution parameters of the marine environment (such as dissolved oxygen, turbidity and heavy metals) to the regional environmental pollution analysis module and the marine monitoring center through the Internet of Things, which is conducive to a detailed understanding of the pollution status at various locations in the marine regulatory area.

[0041] It should be noted that various sensors are installed inside the buoy equipment to monitor marine physical, chemical, biological and other indicators in real time. The buoy equipment is fixed to the seabed by anchor chains, and the buoy equipment is divided into two parts, above water and underwater. The above water part is equipped with a variety of meteorological element sensors (such as wind speed, wind direction, air temperature, air pressure and temperature, etc.), and the underwater part has a variety of hydrological element sensors, which can not only monitor the above-mentioned pollution parameters, but also monitor parameters such as waves, currents, tide levels and sea temperatures.

[0042] The regional environmental pollution analysis module conducts real-time analysis of the pollution status of the marine regulatory area, generates regional high pollution signals or regional low pollution signals through analysis, and sends the marine high pollution signals or marine low pollution signals to the marine monitoring center. When the marine monitoring center receives the regional high pollution signal, it issues a corresponding warning, realizes accurate assessment of the environmental pollution status of the marine regulatory area and issues a timely warning, which is conducive to grasping the risk of marine pollution; the specific analysis process of the regional environmental pollution analysis module is as follows:

[0043] Obtain the monitoring data of various pollution parameters collected by the corresponding buoy equipment, compare each monitoring data with the corresponding preset data requirements one by one, and if the corresponding monitoring data does not meet the corresponding preset data requirements, mark the corresponding pollution parameter as an abnormal parameter;

[0044] The deviation value of the monitoring data corresponding to the abnormal parameter compared with the corresponding preset data requirement is marked as an abnormal value, and each type of pollution parameter is set in advance to correspond to a set of preset weight values, wherein the values ​​of the preset weight values ​​are all positive numbers, and the more serious the harm caused by the corresponding pollution parameter to the marine environment, the greater the value of the preset weight value adapted to it; the corresponding abnormal value is multiplied by the corresponding preset weight value to obtain the abnormal value;

[0045] All the anomaly table values ​​corresponding to the corresponding buoy equipment are obtained and summed up to obtain the buoy area detection value, wherein the larger the value of the buoy area detection value is, the more serious the pollution condition at the location of the corresponding buoy equipment is; the buoy area detection value is compared with the preset buoy area detection threshold value, if the buoy area detection value exceeds the preset buoy area detection threshold value, it indicates that the pollution condition at the location of the corresponding buoy equipment is more serious, then the area corresponding to the corresponding buoy equipment is marked as a polluted area;

[0046] The percentage of polluted areas in the marine regulatory area is obtained and marked as the marine pollution percentage value, and the buoy regional outlier values ​​of all buoy equipment are averaged to obtain the regional pollution performance value, and the buoy regional outlier value with the largest value is marked as the regional pollution amplitude value;

[0047] The marine pollution occupancy value QS, the regional pollution performance value QP and the regional pollution detection amplitude value QY are numerically calculated by the formula QL=rq1*QS+(rq2*QP+rq3*QY) / 2 to obtain the regional pollution comprehensive evaluation value QL; wherein rq1, rq2, and rq3 are preset proportional coefficients, rq1>rq2>rq3>0; and the larger the value of the regional pollution comprehensive evaluation value QL, the more serious the marine environmental pollution situation in the marine regulatory area is in general;

[0048] The regional pollution comprehensive assessment value QL is numerically compared with the preset regional pollution comprehensive assessment threshold. If the regional pollution comprehensive assessment value QL exceeds the preset regional pollution comprehensive assessment threshold, it indicates that the marine environmental pollution situation in the marine regulatory area is generally serious, and a high marine pollution signal is generated; if the regional pollution comprehensive assessment value QL does not exceed the preset regional pollution comprehensive assessment threshold, it indicates that the marine environmental pollution situation in the marine regulatory area is generally mild, and a low marine pollution signal is generated.

[0049] The pollution trend assessment module is used to set the monitoring period. If no high marine pollution signal is generated during the monitoring period, the pollution trend of the marine regulatory area during the monitoring period will be analyzed, and a pollution trend warning signal or a pollution trend qualified signal will be generated through analysis, and the pollution trend warning signal or the pollution trend qualified signal will be sent to the marine monitoring center. When the marine monitoring center receives the pollution trend warning signal, it will issue a corresponding warning, so as to accurately judge the environmental pollution trend of the marine regulatory area and issue a timely warning, which is conducive to grasping the trend of marine pollution. The specific analysis process of the pollution trend assessment module is as follows:

[0050] Obtain all regional pollution comprehensive evaluation values ​​within the monitoring period, calculate the difference between two adjacent groups of regional pollution comprehensive evaluation values ​​to obtain the regional pollution growth value, mark the number of positive regional pollution growth values ​​within the monitoring period as the pollution trend anomaly detection value, and compare the pollution trend anomaly detection value with the preset pollution trend anomaly detection threshold. If the pollution trend anomaly detection value exceeds the preset pollution trend anomaly detection threshold, indicating that the environmental pollution in the marine regulatory area is gradually becoming serious, a pollution trend warning signal is generated.

[0051] Furthermore, if the pollution trend anomaly detection value does not exceed the preset pollution trend anomaly detection threshold, the positive regional pollution growth value is numerically compared with the preset regional pollution growth threshold, and the number of regional pollution growth values ​​exceeding the preset regional pollution growth threshold during the monitoring period is marked as the regional pollution increase anomaly value, and the regional pollution growth value with the largest positive value is marked as the regional pollution increase value;

[0052] By formula The pollution trend abnormal detection value LP, the regional pollution increase abnormal value LX and the regional pollution increase value LF are numerically calculated to obtain the pollution trend assessment value LZ; wherein ur1, ur2 and ur3 are preset proportional coefficients, ur2>ur1>ur3>0; and the larger the value of the pollution trend assessment value LZ is, the more serious the environmental pollution in the marine regulatory area is.

[0053] The pollution trend assessment value LZ is numerically compared with the preset pollution trend assessment threshold. If the pollution trend assessment value LZ exceeds the preset pollution trend assessment threshold, indicating that the environmental pollution in the marine regulatory area tends to be serious on the whole, then a pollution trend warning signal is generated; if the pollution trend assessment value LZ does not exceed the preset pollution trend assessment threshold, indicating that the environmental pollution in the marine regulatory area does not tend to be serious on the whole, then a pollution trend qualified signal is generated.

[0054] Embodiment 2: Figure 2 As shown, the difference between this embodiment and the first embodiment is that the ocean monitoring center is connected to the buoy positioning monitoring module through communication, the buoy positioning monitoring module obtains all buoy devices distributed in the ocean supervision area, collects the real-time position of the corresponding buoy device, and marks the moving distance of the real-time position of the corresponding buoy device compared to its initial position as the buoy movement inspection value;

[0055] The buoy movement detection value is compared with the preset buoy movement detection threshold. If the buoy movement detection value exceeds the preset buoy movement detection threshold, indicating that the corresponding buoy equipment is at risk of leaving the corresponding position, a positioning warning signal of the corresponding buoy equipment is generated, and the positioning warning signal of the corresponding buoy equipment is sent to the ocean monitoring center. When the ocean monitoring center receives the positioning warning signal, it will issue a corresponding warning, and promptly find the corresponding buoy equipment and return it to its position, significantly reducing the difficulty of supervision by management personnel.

[0056] Embodiment 3: Figure 2 As shown, the difference between this embodiment and the first and second embodiments is that the ocean monitoring center is connected to the buoy management abnormality decision module in communication, and the buoy management abnormality decision module divides the ocean supervision area into a number of sub-areas of equal area, and marks the corresponding sub-area as the target area i, and i is a natural number greater than 1;

[0057] The management status of the buoy equipment will be analyzed, and a buoy management abnormality signal or a buoy management normal signal will be generated through analysis, and the buoy management abnormality signal or the buoy management normal signal will be sent to the ocean monitoring center. When the ocean monitoring center receives the buoy management abnormality signal, it will issue a corresponding warning to strengthen the supervision of all buoy equipment in a timely manner in the future, so as to ensure the subsequent monitoring effect and monitoring stability of the marine environment; the specific analysis process of the buoy distribution abnormality decision module is as follows:

[0058] The number of buoy devices distributed in the target area i is collected and marked as the buoy distribution detection value, and the failure rate and loss rate of the buoy devices in the target area i in the historical stage are collected and marked as the buoy failure detection value and the buoy loss detection value respectively; it should be noted that the larger the values ​​of the buoy failure detection value and the buoy loss detection value, the easier it is for the buoy devices distributed in the target area i to fail and be lost, the more difficult it is to ensure the monitoring stability of the target area i, and the more it is necessary to increase the deployment of the buoy devices;

[0059] By formula The buoy distribution detection value FNi, the buoy fault detection value FYi and the buoy loss detection value FLi are numerically calculated to obtain the buoy distribution decision value FXi; wherein ew1, ew2 and ew3 are preset proportional coefficients with values ​​greater than zero, and when the value of the buoy distribution decision value FXi is too small, it indicates that the amount of buoy equipment deployed in the target area i is insufficient, and when the value of the buoy distribution decision value FXi is too large, it indicates that the amount of buoy equipment deployed in the target area i is excessive;

[0060] The buoy distribution decision value FXi is numerically compared with the preset buoy distribution decision value range. If the buoy distribution decision value FXi is not within the preset buoy distribution decision value range, it indicates that the layout quantity of buoy equipment in target area i is unreasonable, and the layout quantity of buoy equipment in target area i should be adjusted, then the target area i is marked as a red alert area; if there is a red alert area, a buoy management abnormality signal is generated.

[0061] Furthermore, if there is no red alert area, the difference between the buoy distribution decision value of the target area i and the median of the preset buoy distribution decision value range is calculated and the absolute value is taken to obtain the buoy distribution deviation value, and the buoy distribution deviation values ​​of all sub-areas in the marine regulatory area are averaged to obtain the buoy distribution deviation value; wherein, the larger the value of the buoy distribution deviation value is, the worse the overall distribution management performance of the buoy equipment in the marine regulatory area is;

[0062] A detection period is set, preferably, the detection period is fifteen days; the duration of the corresponding buoy equipment being unable to operate normally due to a fault is collected, wherein the larger the value of the corresponding duration is, the less timely the processing of the corresponding fault is; the corresponding duration is numerically compared with the corresponding preset duration threshold, if the corresponding duration exceeds the preset duration threshold, indicating that the processing of the corresponding fault is not timely, then the fault response symbol ZP-1 is assigned;

[0063] The ratio of the corresponding duration to the corresponding preset duration threshold is marked as the duration value, all the duration values ​​corresponding to the corresponding buoy equipment in the detection period are averaged to obtain the duration value, and the number of times the corresponding buoy equipment is assigned the fault response symbol ZP-1 in the detection period is marked as the fault response value;

[0064] The buoy equipment abnormal value TM is obtained by numerically calculating the duration analysis value TF and the fault response value TL through the formula TM=rp1*TF+rp2*TL; wherein rp1 and rp2 are preset proportional coefficients, rp2>rp1>0; and the larger the value of the buoy equipment abnormal value TM is, the worse the overall performance of the fault response to the corresponding buoy equipment during the detection period is;

[0065] Compare the abnormal value of the buoy equipment with the preset abnormal threshold of the buoy equipment. If the abnormal value of the buoy equipment exceeds the preset abnormal threshold of the buoy equipment, it indicates that the fault response performance of the corresponding buoy equipment during the detection period is generally poor, and the corresponding buoy equipment is marked as abnormal equipment. Obtain the proportion of abnormal equipment and mark it as the abnormal detection value, and calculate the average of all abnormal values ​​of buoy equipment to obtain the comprehensive inspection value of abnormality.

[0066] By formula The buoy distribution deviation value NL, the pipe abnormality detection value NG and the pipe abnormality comprehensive inspection value NX are numerically calculated to obtain the pipe condition evaluation value NP; wherein, hg1, hg2 and hg3 are preset proportional coefficients with values ​​greater than zero, and the larger the value of the pipe condition evaluation value NP is, the worse the overall management performance of all buoy equipment during the inspection period is;

[0067] The pipe condition assessment value NP is numerically compared with the preset pipe condition assessment threshold. If the pipe condition assessment value NP exceeds the preset pipe condition assessment threshold, it indicates that the management performance of all buoy equipment during the detection period is generally poor, and a buoy management abnormality signal is generated; if the pipe condition assessment value NP does not exceed the preset pipe condition assessment threshold, it indicates that the management performance of all buoy equipment during the detection period is generally good, and a buoy management normal signal is generated.

[0068] The working principle of the present invention is as follows: when in use, the marine regulatory area is monitored through the marine environment monitoring module, and the monitoring data of various pollution parameters of the marine environment are sent to the regional environmental pollution analysis module through the Internet of Things. The regional environmental pollution analysis module analyzes the pollution status of the marine regulatory area in real time to generate a regional high pollution signal or a regional low pollution signal. If no regional high pollution signal is generated during the monitoring period, the pollution trend of the marine regulatory area during the monitoring period is analyzed through the pollution trend assessment module to generate a pollution trend warning signal or a pollution trend qualified signal. When a regional high pollution signal or a pollution trend warning signal is generated, the marine monitoring center issues a warning, which can accurately judge the real-time pollution status and pollution trend of the marine regulatory area environment and issue a timely warning, thereby realizing effective monitoring and management of the marine regulatory area environment and significantly reducing the work difficulty of marine monitoring personnel.

[0069] The above formulas are all dimensionless and numerical calculations. The formula is a formula obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formula are set by technicians in this field according to actual conditions. The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the contents of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that technicians in the relevant technical field can understand and use the present invention well. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. An online monitoring and early warning system for marine environment based on the Internet of Things, characterized in that: It includes marine environment monitoring module, regional environmental pollution analysis module, pollution trend assessment module and marine monitoring center; The marine environment monitoring module obtains the marine area that needs to be monitored and marks it as a marine regulatory area. It monitors the marine environment through a number of buoy devices distributed in the marine regulatory area, and sends the monitoring data of various pollution parameters of the marine environment to the regional environmental pollution analysis module and the marine monitoring center; The regional environmental pollution analysis module conducts real-time analysis of the pollution status of the marine regulatory area and generates regional high pollution signals or regional low pollution signals through analysis; The pollution trend assessment module is used to set the monitoring period. If no high marine pollution signal is generated during the monitoring period, the pollution trend of the marine regulatory area during the monitoring period will be analyzed, and a pollution trend warning signal or a pollution trend qualified signal will be generated through analysis; The marine monitoring center will issue corresponding warnings when it receives regional high pollution signals or pollution trend warning signals.

2. According to claim 1, the online monitoring and early warning system for marine environment based on the Internet of Things is characterized in that: The ocean monitoring center is connected to the buoy positioning monitoring module through communication. The buoy positioning monitoring module obtains all buoy devices distributed in the ocean supervision area and marks the movement distance of the real-time position of the corresponding buoy device compared to its initial position as the buoy movement inspection value; If the buoy movement detection value exceeds the preset buoy movement detection threshold, a positioning warning signal of the corresponding buoy equipment is generated, and the positioning warning signal of the corresponding buoy equipment is sent to the ocean monitoring center.

3. According to claim 2, the online monitoring and early warning system for marine environment based on the Internet of Things is characterized in that: The ocean monitoring center is connected to the buoy management abnormality decision module through communication. The buoy management abnormality decision module divides the ocean supervision area into several sub-areas of equal area, and marks the corresponding sub-area as target area i, where i is a natural number greater than 1; The management status of the buoy equipment will be analyzed, and a buoy management abnormality signal or a buoy management normal signal will be generated through the analysis. The buoy management abnormality signal or the buoy management normal signal will be sent to the ocean monitoring center. When the ocean monitoring center receives the buoy management abnormality signal, it will issue a corresponding warning.

4. According to claim 3, the online monitoring and early warning system for marine environment based on Internet of Things is characterized in that: The specific analysis process of the buoy distribution anomaly decision module includes: The buoy distribution decision value is obtained by numerically calculating the buoy distribution detection value, the buoy fault detection value and the buoy lost detection value; if the buoy distribution decision value is not within the preset buoy distribution decision value range, the target area i is marked as a red alert area; if a red alert area exists, a buoy management abnormality signal is generated.

5. The online monitoring and early warning system for marine environment based on Internet of Things according to claim 4 is characterized in that: If there is no red alert area, the buoy equipment pipe abnormality value of the corresponding buoy equipment is obtained through analysis, and the buoy distribution deviation value, pipe abnormality detection value and pipe abnormality comprehensive inspection value are numerically calculated to obtain the pipe condition assessment value. If the pipe condition assessment value exceeds the preset pipe condition assessment threshold, a buoy management abnormality signal is generated; if the pipe condition assessment value does not exceed the preset pipe condition assessment threshold, a buoy management normal signal is generated.

6. The online monitoring and early warning system for marine environment based on Internet of Things according to claim 5 is characterized in that: The analysis and acquisition method of the abnormal value of the buoy equipment is as follows: The detection period is set, and the mean of all the continuous time condition values ​​corresponding to the corresponding buoy equipment during the detection period is calculated to obtain the continuous time analysis value, and the number of times the corresponding buoy equipment is assigned the fault response symbol ZP-1 during the detection period is marked as the fault response value; the buoy equipment management abnormal value is obtained by numerically calculating the continuous time analysis value and the fault response value.

7. The online monitoring and early warning system for marine environment based on Internet of Things according to claim 1 is characterized in that: The specific analysis process of the regional environmental pollution analysis module is as follows: The regional pollution comprehensive assessment value is obtained by numerically calculating the ocean pollution occupancy value, regional pollution performance value and regional pollution detection amplitude value. If the regional pollution comprehensive assessment value exceeds the preset regional pollution comprehensive assessment threshold, a high ocean pollution signal is generated; if the regional pollution comprehensive assessment value does not exceed the preset regional pollution comprehensive assessment threshold, a low ocean pollution signal is generated.

8. The online monitoring and early warning system for marine environment based on Internet of Things according to claim 1 is characterized in that: The specific analysis process of the pollution trend assessment module is as follows: Obtain the comprehensive pollution assessment values ​​of all regions during the monitoring period, and mark the percentage of positive regional pollution growth values ​​during the monitoring period as the pollution trend anomaly detection value. If the pollution trend anomaly detection value exceeds the preset pollution trend anomaly detection threshold, a pollution trend warning signal is generated.

9. The online monitoring and early warning system for marine environment based on Internet of Things according to claim 8 is characterized in that: If the pollution trend anomaly detection value does not exceed the preset pollution trend anomaly detection threshold, the pollution trend assessment value is numerically compared with the preset pollution trend assessment threshold. If the pollution trend assessment value exceeds the preset pollution trend assessment threshold, a pollution trend warning signal is generated; If the pollution trend assessment value does not exceed the preset pollution trend assessment threshold, a pollution trend qualified signal is generated.

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