CN115687447B - Ocean environment monitoring system and method based on Internet of things - Google Patents
Ocean environment monitoring system and method based on Internet of things Download PDFInfo
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Abstract
The invention discloses a marine environment monitoring system and a method based on the Internet of things, wherein the marine environment monitoring system comprises a plurality of marine data monitoring devices, an Internet of things data analysis server, a data monitoring platform and a monitoring terminal; the marine data monitoring equipment comprises main acquisition equipment, auxiliary acquisition equipment, a battery management system, an MCU, an Internet of things transmission equipment and an internal communication bus; the data analysis server of the Internet of things comprises a data abnormality judging module, an equipment abnormality judging module, a time window dividing module, an acquisition frequency adjusting module and an uploading frequency adjusting module. According to the marine data monitoring device, whether the data are abnormal can be analyzed according to the data collected by the marine data monitoring device, whether the device is abnormal is judged, and the reliability of data collection is improved. The invention also provides a complete frequency adjustment mechanism, which dynamically adjusts the frequency of data acquisition and uploading based on the change condition of the acquired first data and electric quantity information, effectively reduces the power consumption and ensures that ocean data is continuously acquired and observed for a long time.
Description
Technical Field
The invention relates to the technical field of data monitoring of the Internet of things, in particular to a marine environment monitoring system and method based on the Internet of things.
Background
With the improvement of the technology level, ocean resources are continuously developed, and ocean environment monitoring is an important basis for ocean resource development. Scientific researchers collect and observe marine environment data through setting up various types of monitoring equipment, upload the data that gathers to monitoring center and carry out analysis processing again to realize remote monitoring marine environment.
However, the ocean environment is severe and complex, and with the continuous increase of the types and the magnitudes of the ocean environment monitoring data, the importance of the quality control of the monitoring data is increasingly outstanding. If the monitoring equipment is abnormal, the health degree of the monitoring data is reduced, and a large amount of unreliable data is generated, the comprehensive evaluation, ecological protection, disaster early warning, management decision, resource development and the like of the marine environment can be directly influenced. Therefore, how to judge the abnormality of the monitoring data and the abnormality of the monitoring equipment in time determines the accuracy and the reliability of the ocean data, and has important scientific significance and social value. On the other hand, the ocean monitoring area is wide, the monitoring equipment is usually in an unmanned area, the electric energy supply problem is the problem that the face is required to be straight, and because batteries are difficult to replace, if the monitoring equipment is too high in energy consumption, the equipment is difficult to ensure the electric quantity collected and uploaded in real time, so that the technical problem that how to save the energy consumption of the monitoring equipment is required to be solved.
The invention patent CN112650116B proposes a marine environment monitoring system based on the Internet of things, which acquires the operation range of an offshore operation platform, marks traffic equipment expected to pass in the operation range of the offshore operation platform and the Internet of things equipment as acquisition terminals, acquires the acquisition value of the acquisition terminals, selects the acquisition terminal with the largest acquisition value in the same interval of the passing start time and the passing end time as the optimal acquisition terminal, sends an acquisition signal to the optimal acquisition terminal and completes acquisition, and the monitoring platform compares real-time monitoring data of the offshore operation platform with data acquired by the optimal acquisition terminal to complete auxiliary verification, so that the failure of a detection module in the offshore operation platform is prevented, and the problem that the offshore operation platform lacks auxiliary monitoring in remote detection is solved. However, the technical scheme of the invention is too dependent on the vehicles near the offshore operation platform, and the offshore operation platform in practical application is often arranged in a remote sea area, so that the vehicles passing near the offshore operation platform are very few, and therefore, the auxiliary monitoring of the invention is difficult, faults cannot be detected in time, and the reliability of monitoring data cannot be ensured.
The invention patent CN108106741B provides a variable-period seawater temperature acquisition and transmission method and system, which are used for selecting the number and the placement positions of seawater temperature acquisition devices according to the specific conditions of a seawater area to be monitored; the transmission period of the seawater temperature is changed in a multi-mode manner, so that the acquisition and transmission of the seawater temperature change period are realized; the battery status information is monitored and reacted. According to the invention, the period of collection and transmission is changed according to the change condition of the temperature of the seawater, so that the energy consumption is reduced. However, the invention does not disclose specific logic for the adjustment of the acquisition and transmission periods, i.e. when to increase or decrease the period, whether to adjust the acquisition and transmission periods simultaneously or to adjust either individually. Moreover, the invention only judges whether the period needs to be changed according to the difference of two adjacent temperature sampling values, and the reliability of the data is not considered.
Disclosure of Invention
The invention aims to: aiming at the problems, the invention provides a marine environment monitoring system and a marine environment monitoring method based on the Internet of things.
The technical scheme is as follows:
in a first aspect, the present invention provides an ocean environment monitoring system based on the internet of things, including:
the system comprises a plurality of marine data monitoring devices, an Internet of things data analysis server, a data monitoring platform and a monitoring terminal;
preferably, the ocean data monitoring equipment comprises a main acquisition equipment, an auxiliary acquisition equipment, a battery management system, an MCU, an Internet of things transmission equipment and an internal communication bus, wherein the first data acquired by the main acquisition equipment, the second data acquired by the auxiliary acquisition equipment and the electric quantity information of the battery management system are uploaded to the Internet of things data analysis server through the Internet of things transmission equipment;
the data acquisition frequency of the main acquisition equipment is greater than that of the auxiliary acquisition equipment;
the data analysis server of the Internet of things comprises a data abnormality judging module, an equipment abnormality judging module, a time window dividing module, an acquisition frequency adjusting module and an uploading frequency adjusting module;
the data abnormality judging module judges whether the first data is abnormal according to the first data and the second data in the first time window, the equipment abnormality judging module analyzes and judges whether the abnormal data is accidental abnormal data and judges whether the marine data monitoring equipment fails, and the acquisition frequency adjusting module and the uploading frequency adjusting module are used for adjusting the data acquisition frequency and the data uploading frequency according to the first data and the electric quantity information.
Preferably, the data anomaly determination module determines whether the first data is anomalous according to the first data and the second data in the first time window, including:
the time window dividing module divides a first time window in the ocean monitoring data sequence, so that the length of the first time window is 1/f B A moving step length of 1/f B ；
The data abnormality judging module predicts the value of the nth first data according to the first (n-1) first data in the first time window;
the data abnormality judging module judges that the value of the nth first data is compared and analyzed with the value of the corresponding second data in the first time window, and judges whether the difference between the value of the nth first data and the value of the corresponding second data is in a threshold range, wherein n=f A /f B ；
If the first data in the first time window is judged to be abnormal within the threshold range, the first time window is enabled to slide backwards to continue judgment;
if the first data in the first time window exceeds the threshold range, judging whether the marine data monitoring equipment fails or not through analysis of the equipment abnormality judging module.
Preferably, the device abnormality determination module analyzes and determines whether the abnormal data is accidental abnormal data or not, and determines whether the marine data monitoring device has a fault or not, including:
the time window dividing module extracts adjacent forward first time window data for the first time window with abnormal first data to form a target analysis data sequence, and sets a second time window in the target analysis data sequence, wherein the length of the second time window is 1/f B A moving step length of 1/f A ；
The equipment abnormality judging module predicts the value of the nth first data according to the first (n-1) first data in the second time window; judging whether the difference between the value of the nth first data and the measured value of the corresponding first data in the second time window is within a threshold value range or not through comparison analysis; if the threshold value range is exceeded, judging the abnormal data;
the equipment abnormality judging module slides the second time window until all the first data in the first time window are judged, the proportion of the abnormal data is counted, if the proportion is lower than the preset proportion, the abnormal data is judged to be accidental abnormal data, and if the proportion is higher than the preset proportion, the marine data monitoring equipment is judged to be faulty.
Preferably, the collecting frequency adjusting module and the uploading frequency adjusting module are configured to adjust the data collecting frequency and the data uploading frequency according to the first data and the electric quantity information, and include:
deleting accidental abnormal data in the first time window, obtaining standard deviation sigma of the rest first data in the first time window, and adjusting data acquisition frequency f of the main acquisition equipment A And data acquisition frequency f of the auxiliary acquisition device B The method comprises the following steps of:
f B ＝f A /n；
wherein sigma 0 For the preset standard deviation reference value, beta is a preset standard deviation correction value, f 0 The default main acquisition frequency is adopted;
if the electric quantity is less than 50%, the uploading frequency f is reduced UL Stopping uploading when the electric quantity is reduced to 20, namely:
wherein E is the electric quantity of the marine data monitoring equipment, and the range of E is [20, 50), f U The frequency is the default uploading frequency;
if the electric quantity is less than 30%, increasing the value of n to n 0 Thereby reducing the data acquisition frequency of the auxiliary acquisition equipment under the condition of keeping the data acquisition frequency of the main acquisition equipment unchanged;
if the electric quantity is less than 10%, reducing the data acquisition frequency of the main acquisition equipment to 0.2 times f A The data acquisition frequency of the corresponding auxiliary acquisition equipment is reduced to f which is 0.2 times as high as that of the corresponding auxiliary acquisition equipment B ；
If the electric quantity is less than 5%, the collection and uploading are suspended, and the historical data are only stored when the device enters the dormant state.
In a second aspect, the invention also provides a marine environment monitoring method based on the internet of things, which is characterized by comprising the following steps:
step A, presetting the data acquisition frequency and the data uploading frequency of the marine data monitoring equipment, comprising setting the data acquisition frequency of the main acquisition equipment and the data acquisition frequency of the auxiliary acquisition equipment,
wherein, the data acquisition frequency f of the main acquisition equipment A Far greater than the data acquisition frequency f of the auxiliary acquisition equipment B The method comprises the steps of carrying out a first treatment on the surface of the Preferably f A Is n times the size f B The value of n can be an integer of 100-500;
step B, the ocean data monitoring equipment uploads the collected ocean monitoring data and electric quantity information, wherein the uploading frequency f is achieved through the Internet of things transmission equipment UL Uploading to an internet of things data analysis server, wherein the ocean monitoring data comprises first data of a main acquisition device and second data acquired by an auxiliary acquisition device;
and C, the data analysis server of the Internet of things processes the ocean monitoring data and judges whether analysis is abnormal or not, and the method comprises the following steps:
step C1, judging whether the ocean monitoring data is abnormal or not;
step C11, dividing a first time window in the ocean monitoring data sequence, wherein the length of the first time window is 1/f B A moving step length of 1/f B ；
Step C12, estimating the value of the nth first data according to the first (n-1) first data in the first time window;
step C13, comparing and analyzing the value of the nth first data with the value of the corresponding second data in the first time window, and judging whether the difference between the values is in the threshold range, wherein n=f A /f B ；
If the first data in the first time window is judged to be abnormal within the threshold range, the first time window is enabled to slide backwards to continue judgment;
if the first data exceeds the threshold range, judging that the first data in the first time window is abnormal, and entering a step C2;
step C2, judging the reliability of the marine data monitoring equipment;
and D, carrying out feedback adjustment on the data acquisition frequency and the data uploading frequency of the marine data monitoring equipment of the data analysis server of the Internet of things.
Preferably, the step C2 of determining the reliability of the marine data monitoring device includes:
step C21, for the first time window with abnormal first data, extracting the data of the adjacent forward first time window to form a target analysis data sequence, and setting a second time window in the target analysis data sequence, wherein the length of the second time window is 1/f B A moving step length of 1/f A ；
Step C22, estimating the value of the nth first data according to the first (n-1) first data in the second time window; judging whether the difference between the value of the nth first data and the measured value of the corresponding first data in the second time window is within a threshold value range or not through comparison analysis; if the threshold value range is exceeded, judging the abnormal data;
and C23, sliding the second time window until the judgment of all the first data in the first time window is completed, counting the proportion of the abnormal data, judging the abnormal data as accidental abnormal data if the proportion is lower than the preset proportion, and judging that the marine data monitoring equipment fails if the proportion is higher than the preset proportion.
Preferably, the step D, performing feedback adjustment on the data acquisition frequency and the data uploading frequency of the marine data monitoring device by the data analysis server of the internet of things, includes:
step D1, deleting accidental abnormal data in the first time window, obtaining the standard deviation sigma of the rest first data in the first time window, and adjusting the data acquisition frequency f of the main acquisition equipment A And data acquisition frequency f of the auxiliary acquisition device B The method comprises the following steps of:
f B ＝f A /n；
wherein sigma 0 For the preset standard deviation reference value, beta is a preset standard deviation correction value, f 0 The default main acquisition frequency is adopted;
step D2, if the electric quantity of the marine data monitoring equipment is more than 50%, the frequency f in the formula D1 is adopted A And f B Data acquisition is carried out according to the default uploading frequency f U Uploading data;
step D3, if the electric quantity is smaller than 50%, reducing the uploading frequency, stopping uploading when the electric quantity is reduced to 20, and uploading the frequency f UL Calculated according to the following formula:
wherein E is the electric quantity of the marine data monitoring equipment, E in the step D3 ranges from [20, 50), f U The frequency is the default uploading frequency;
step D4, if the electric quantity is less than 30%, increasing the value of n to n 0 From the slaveThe data acquisition frequency of the auxiliary acquisition equipment is reduced under the condition that the data acquisition frequency of the main acquisition equipment is kept unchanged;
step D5, if the electric quantity is smaller than 10%, reducing the data acquisition frequency of the main acquisition equipment to 0.2 times f A The data acquisition frequency of the corresponding auxiliary acquisition equipment is reduced to f which is 0.2 times as high as that of the corresponding auxiliary acquisition equipment B ；
And D6, if the electric quantity is less than 5%, suspending acquisition and uploading, and entering a dormant state at the moment only storing historical data.
Preferably, after judging the accidental abnormal data, the data analysis server of the internet of things rejects and stores the accidental abnormal data, and displays the residual data after the accidental abnormal data is rejected to the data monitoring center for analysis by a user.
Preferably, after judging that the ocean data monitoring equipment fails, the data analysis server of the Internet of things sends alarm information to the data monitoring center, and a user checks information such as the number and coordinates of the failed ocean data monitoring equipment through the monitoring terminal.
In a third aspect, the present invention also provides a computer-readable storage medium having stored thereon a computer program characterized in that: the computer program when executed by the processor realizes the steps in the ocean environment monitoring method based on the Internet of things.
Compared with the prior art, the invention has the following beneficial effects:
1. according to the method and the device, whether the data are abnormal or not can be analyzed according to the data collected by the marine data monitoring equipment, whether the equipment is abnormal or not is judged, other equipment such as an unmanned aerial vehicle is not needed, and auxiliary monitoring is not needed when the other equipment is close to the periphery of the marine data monitoring equipment, so that abnormal conditions can be timely detected.
2. According to the marine data monitoring device, the main acquisition device and the auxiliary acquisition device are arranged in the marine data monitoring device, wherein the sampling frequency of the auxiliary acquisition device is smaller than that of the main acquisition device, so that the power consumption of the auxiliary acquisition device is lower, the data of the auxiliary acquisition device are used for assisting in verifying whether the first data acquired by the main acquisition device are abnormal, and the reliability of data acquisition is improved.
3. According to the invention, when the data abnormality is judged, whether the reason of the data abnormality is accidental abnormal data or data abnormality caused by the fault of the monitoring equipment can be further analyzed, so that the singular data value caused by the accidental factor can be removed, the accuracy of the data analysis of the data monitoring platform is improved, and an alarm can be timely sent when the fault of the equipment is judged.
4. The invention provides a complete frequency adjustment mechanism, which is used for respectively carrying out self-adaptive adjustment on the data acquisition frequency and the data uploading frequency under different conditions, dynamically adjusting the data acquisition and uploading frequency based on the change condition of the acquired first data and the electric quantity information, effectively reducing the power consumption of monitoring equipment, improving the endurance capacity and ensuring long-time effective acquisition and observation of ocean data.
Drawings
FIG. 1 is a schematic diagram of a marine environment monitoring system based on the Internet of things;
fig. 2 is a flowchart of a marine environment monitoring method based on the internet of things.
Detailed Description
It will be apparent that many modifications and variations are possible within the scope of the invention, as will be apparent to those skilled in the art based upon the teachings herein.
As used herein, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless expressly stated otherwise, as understood by those skilled in the art. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. It will be understood that when an element or component is referred to as being "connected" to another element or component, it can be directly connected to the other element or component or intervening elements or components may also be present. The term "and/or" as used herein includes any and all combinations of one or more of the associated listed items.
It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art.
In order to facilitate an understanding of the embodiments, the following description will be given in conjunction with the accompanying drawings, and the various embodiments do not constitute a limitation of the present invention. The technical scheme of the invention is further described below with reference to the accompanying drawings and examples.
Embodiment one:
as shown in fig. 1, the present invention proposes a marine environment monitoring system based on the internet of things, comprising:
the system comprises a plurality of marine data monitoring devices, an Internet of things data analysis server, a data monitoring platform and a monitoring terminal;
preferably, the ocean data monitoring equipment comprises a main acquisition equipment, an auxiliary acquisition equipment, a battery management system, an MCU, an Internet of things transmission equipment and an internal communication bus, wherein the first data acquired by the main acquisition equipment, the second data acquired by the auxiliary acquisition equipment and the electric quantity information of the battery management system are uploaded to the Internet of things data analysis server through the Internet of things transmission equipment;
the data acquisition frequency of the main acquisition equipment is greater than that of the auxiliary acquisition equipment;
the data analysis server of the Internet of things comprises a data abnormality judging module, an equipment abnormality judging module, a time window dividing module, an acquisition frequency adjusting module and an uploading frequency adjusting module;
the data abnormality judging module judges whether the first data is abnormal according to the first data and the second data in the first time window, the equipment abnormality judging module analyzes and judges whether the abnormal data is accidental abnormal data and judges whether the marine data monitoring equipment fails, and the acquisition frequency adjusting module and the uploading frequency adjusting module are used for adjusting the data acquisition frequency and the data uploading frequency according to the first data and the electric quantity information.
The main acquisition equipment and the auxiliary acquisition equipment acquire the same marine environment parameters including, but not limited to, parameters such as temperature, PH and the like; but howeverThe data acquisition frequencies of the main acquisition equipment and the auxiliary acquisition equipment are different; preferably, the data acquisition frequency f of the main acquisition device A Far greater than the data acquisition frequency f of the auxiliary acquisition equipment B The method comprises the steps of carrying out a first treatment on the surface of the For example, f A Is n times the size f B The value of n can be an integer of 100 to 500.
Preferably, the data anomaly determination module determines whether the first data is anomalous according to the first data and the second data in the first time window, including:
the time window dividing module divides a first time window in the ocean monitoring data sequence, so that the length of the first time window is 1/f B A moving step length of 1/f B ；
The data abnormality judging module predicts the value of the nth first data according to the first (n-1) first data in the first time window;
the data abnormality judging module judges that the value of the nth first data is compared and analyzed with the value of the corresponding second data in the first time window, and judges whether the difference between the value of the nth first data and the value of the corresponding second data is in a threshold range, wherein n=f A /f B ；
If the first data in the first time window is judged to be abnormal within the threshold range, the first time window is enabled to slide backwards to continue judgment;
if the first data in the first time window exceeds the threshold range, judging whether the marine data monitoring equipment fails or not through analysis of the equipment abnormality judging module.
Preferably, the device abnormality determination module analyzes and determines whether the abnormal data is accidental abnormal data or not, and determines whether the marine data monitoring device has a fault or not, including:
the time window dividing module extracts adjacent forward first time window data for the first time window with abnormal first data to form a target analysis data sequence, and sets a second time window in the target analysis data sequence, wherein the length of the second time window is 1/f B A moving step length of 1/f A ；
The equipment abnormality judging module predicts the value of the nth first data according to the first (n-1) first data in the second time window; judging whether the difference between the value of the nth first data and the measured value of the corresponding first data in the second time window is within a threshold value range or not through comparison analysis; if the threshold value range is exceeded, judging the abnormal data;
the equipment abnormality judging module slides the second time window until all the first data in the first time window are judged, the proportion of the abnormal data is counted, if the proportion is lower than the preset proportion, the abnormal data is judged to be accidental abnormal data, and if the proportion is higher than the preset proportion, the marine data monitoring equipment is judged to be faulty.
Preferably, the collecting frequency adjusting module and the uploading frequency adjusting module are configured to adjust the data collecting frequency and the data uploading frequency according to the first data and the electric quantity information, and include:
deleting accidental abnormal data in the first time window, obtaining standard deviation sigma of the rest first data in the first time window, and adjusting data acquisition frequency f of the main acquisition equipment A And data acquisition frequency f of the auxiliary acquisition device B The method comprises the following steps of:
f B ＝f A /n；
wherein sigma 0 For the preset standard deviation reference value, beta is a preset standard deviation correction value, f 0 The default main acquisition frequency is adopted;
if the electric quantity is less than 50%, the uploading frequency f is reduced UL Stopping uploading when the electric quantity is reduced to 20, namely:
wherein E is the electric quantity of the marine data monitoring equipment, and the range of E is [20, 50), f U The frequency is the default uploading frequency;
if the electric quantity is less than 30%, increasing the value of n to n 0 Thereby reducing the auxiliary acquisition under the condition of keeping the data acquisition frequency of the main acquisition equipment unchangedThe data acquisition frequency of the device;
if the electric quantity is less than 10%, reducing the data acquisition frequency of the main acquisition equipment to 0.2 times f A The data acquisition frequency of the corresponding auxiliary acquisition equipment is reduced to f which is 0.2 times as high as that of the corresponding auxiliary acquisition equipment B ；
If the electric quantity is less than 5%, the collection and uploading are suspended, and the historical data are only stored when the device enters the dormant state.
Embodiment two:
as shown in fig. 2, the invention provides a marine environment monitoring method based on internet of things, which is characterized by comprising the following steps:
step A, presetting the data acquisition frequency and the data uploading frequency of the marine data monitoring equipment, comprising setting the data acquisition frequency of the main acquisition equipment and the data acquisition frequency of the auxiliary acquisition equipment,
wherein, the data acquisition frequency f of the main acquisition equipment A Far greater than the data acquisition frequency f of the auxiliary acquisition equipment B The method comprises the steps of carrying out a first treatment on the surface of the Preferably f A Is n times the size f B The value of n can be an integer of 100-500;
step B, the ocean data monitoring equipment uploads the collected ocean monitoring data and electric quantity information, wherein the uploading frequency f is achieved through the Internet of things transmission equipment UL Uploading to an internet of things data analysis server, wherein the ocean monitoring data comprises first data of a main acquisition device and second data acquired by an auxiliary acquisition device;
and C, the data analysis server of the Internet of things processes the ocean monitoring data and judges whether analysis is abnormal or not, and the method comprises the following steps:
step C1, judging whether the ocean monitoring data is abnormal or not;
step C11, dividing a first time window in the ocean monitoring data sequence, wherein the length of the first time window is 1/f B A moving step length of 1/f B ；
Step C12, estimating the value of the nth first data according to the first (n-1) first data in the first time window;
step C13, judging the value of the nth first data and the first timeComparing and analyzing the corresponding values of the second data in the window to judge whether the difference is in the threshold value range, wherein n=f A /f B ；
If the first data in the first time window is judged to be abnormal within the threshold range, the first time window is enabled to slide backwards to continue judgment;
if the first data exceeds the threshold range, judging that the first data in the first time window is abnormal, and entering a step C2;
step C2, judging the reliability of the marine data monitoring equipment;
and D, carrying out feedback adjustment on the data acquisition frequency and the data uploading frequency of the marine data monitoring equipment of the data analysis server of the Internet of things.
Preferably, the step C2 of determining the reliability of the marine data monitoring device includes:
step C21, for the first time window with abnormal first data, extracting the data of the adjacent forward first time window to form a target analysis data sequence, and setting a second time window in the target analysis data sequence, wherein the length of the second time window is 1/f B A moving step length of 1/f A ；
Step C22, estimating the value of the nth first data according to the first (n-1) first data in the second time window; judging whether the difference between the value of the nth first data and the measured value of the corresponding first data in the second time window is within a threshold value range or not through comparison analysis; if the threshold value range is exceeded, judging the abnormal data;
and C23, sliding the second time window until the judgment of all the first data in the first time window is completed, counting the proportion of the abnormal data, judging the abnormal data as accidental abnormal data if the proportion is lower than the preset proportion, and judging that the marine data monitoring equipment fails if the proportion is higher than the preset proportion.
Preferably, the step D, performing feedback adjustment on the data acquisition frequency and the data uploading frequency of the marine data monitoring device by the data analysis server of the internet of things, includes:
step D1, deleting accidental abnormal data in the first time window, and obtaining the accidental abnormal data in the first time windowStandard deviation sigma of the remaining first data of the main acquisition device, the data acquisition frequency f of the main acquisition device is adjusted A And data acquisition frequency f of the auxiliary acquisition device B The method comprises the following steps of:
f B ＝f A /n；
wherein sigma 0 For the preset standard deviation reference value, beta is a preset standard deviation correction value, f 0 The default main acquisition frequency is adopted;
step D2, if the electric quantity of the marine data monitoring equipment is more than 50%, the frequency f in the formula D1 is adopted A And f B Data acquisition is carried out according to the default uploading frequency f U Uploading data;
step D3, if the electric quantity is smaller than 50%, reducing the uploading frequency, stopping uploading when the electric quantity is reduced to 20, and uploading the frequency f UL Calculated according to the following formula:
wherein E is the electric quantity of the marine data monitoring equipment, E in the step D3 ranges from [20, 50), f U The frequency is the default uploading frequency;
step D4, if the electric quantity is less than 30%, increasing the value of n to n 0 Thereby reducing the data acquisition frequency of the auxiliary acquisition equipment under the condition of keeping the data acquisition frequency of the main acquisition equipment unchanged;
step D5, if the electric quantity is smaller than 10%, reducing the data acquisition frequency of the main acquisition equipment to 0.2 times f A The data acquisition frequency of the corresponding auxiliary acquisition equipment is reduced to f which is 0.2 times as high as that of the corresponding auxiliary acquisition equipment B ；
And D6, if the electric quantity is less than 5%, suspending acquisition and uploading, and entering a dormant state at the moment only storing historical data.
Preferably, after judging the accidental abnormal data, the data analysis server of the internet of things rejects and stores the accidental abnormal data, and displays the residual data after the accidental abnormal data is rejected to the data monitoring center for analysis by a user.
Preferably, after judging that the ocean data monitoring equipment fails, the data analysis server of the Internet of things sends alarm information to the data monitoring center, and a user checks information such as the number and coordinates of the failed ocean data monitoring equipment through the monitoring terminal.
Preferably, the monitoring terminal comprises an application layer, and particularly comprises software and hardware facilities for analyzing ocean monitoring data; when a user performs data analysis through the monitoring terminal, the marine environment data can be monitored remotely and in real time based on the application layer, and the real marine condition can be obtained in time; all data acquired in the data analysis server of the Internet of things can be acquired through the recovery function, and even the first data which is considered as accidental error data can be acquired, so that expert personnel can comprehensively re-analyze all monitoring data through the monitoring terminal.
In particular, the invention is not limited to the embodiments and descriptions contained herein, and the claims should be construed to include modifications to those embodiments that include portions of the embodiments and combinations of elements of different embodiments within the scope of the appended claims. All disclosures described herein, including patent and non-patent disclosures, are hereby incorporated by reference in their entireties.
Claims (8)
1. The marine environment monitoring system based on the Internet of things comprises a plurality of marine data monitoring devices, an Internet of things data analysis server, a data monitoring platform and a monitoring terminal; the ocean data monitoring device is characterized by comprising a main acquisition device, an auxiliary acquisition device, a battery management system, an MCU, an Internet of things transmission device and an internal communication bus, wherein first data acquired by the main acquisition device, second data acquired by the auxiliary acquisition device and electric quantity information of the battery management system are uploaded to an Internet of things data analysis server through the Internet of things transmission device; the data acquisition frequency of the main acquisition equipment is greater than that of the auxiliary acquisition equipment; the data analysis server of the Internet of things comprises a data abnormality judging module, an equipment abnormality judging module, a time window dividing module, an acquisition frequency adjusting module and an uploading frequency adjusting module; the data abnormality judging module judges whether the first data is abnormal according to the first data and the second data in the first time window, the equipment abnormality judging module analyzes and judges whether the abnormal data is accidental abnormal data and judges whether the marine data monitoring equipment fails, and the acquisition frequency adjusting module and the uploading frequency adjusting module are used for adjusting the data acquisition frequency and the data uploading frequency according to the first data and the electric quantity information;
the acquisition frequency adjusting module and the uploading frequency adjusting module are used for adjusting the data acquisition frequency and the data uploading frequency according to the first data and the electric quantity information, and the data acquisition frequency adjusting module comprises:
deleting accidental abnormal data in the first time window, obtaining standard deviation sigma of the rest first data in the first time window, and adjusting data acquisition frequency f of the main acquisition equipment A And data acquisition frequency f of the auxiliary acquisition device B The method comprises the following steps of:
f B ＝f A /n；
wherein sigma 0 For the preset standard deviation reference value, beta is a preset standard deviation correction value, f 0 The default main acquisition frequency is adopted;
if the electric quantity is less than 50%, the uploading frequency f is reduced UL Stopping uploading when the electric quantity is reduced to 20%, namely:
wherein E is the electric quantity of the marine data monitoring equipment, f U The frequency is the default uploading frequency;
if the electric quantity is less than 30%, increasing the value of n to n 0 Thereby maintaining the main acquisition deviceThe data acquisition frequency of the auxiliary acquisition equipment is reduced under the condition that the data acquisition frequency is unchanged;
if the electric quantity is less than 10%, reducing the data acquisition frequency of the main acquisition equipment to 0.2 times f A The data acquisition frequency of the corresponding auxiliary acquisition equipment is reduced to f which is 0.2 times as high as that of the corresponding auxiliary acquisition equipment B ；
If the electric quantity is less than 5%, the collection and uploading are suspended, and the historical data are only stored when the device enters the dormant state.
2. The internet of things-based marine environment monitoring system of claim 1, wherein the data anomaly determination module determines whether the first data is anomalous based on the first data and the second data within the first time window comprises:
the time window dividing module divides a first time window in the ocean monitoring data sequence, so that the length of the first time window is 1/f B A moving step length of 1/f B ；
The data abnormality judging module predicts the value of the nth first data according to the first (n-1) first data in the first time window;
the data abnormality judging module compares and analyzes the value of the nth first data with the value of the corresponding second data in the first time window to judge whether the difference between the value of the nth first data and the value of the corresponding second data is in a threshold range, wherein n=f A /f B The method comprises the steps of carrying out a first treatment on the surface of the If the first data in the first time window is judged to be abnormal within the threshold range, the first time window is enabled to slide backwards to continue judgment; if the first data in the first time window exceeds the threshold range, judging whether the marine data monitoring equipment fails or not through analysis of the equipment abnormality judging module.
3. The internet of things-based marine environment monitoring system of claim 2, wherein the equipment anomaly determination module analyzing and determining whether the anomaly data is occasional anomaly data and whether the marine data monitoring equipment fails comprises:
the time window dividing module takes out adjacent forward directions for a first time window of first data abnormalityThe data of the first time window form a target analysis data sequence, a second time window is arranged in the target analysis data sequence, and the length of the second time window is 1/f B A moving step length of 1/f A ；
The equipment abnormality judging module predicts the value of the nth first data according to the first (n-1) first data in the second time window; comparing and analyzing the value of the nth first data with the actual measurement value of the corresponding first data in the second time window, and judging whether the difference between the value of the nth first data and the actual measurement value of the corresponding first data is in a threshold range; if the threshold value range is exceeded, judging the abnormal data;
the equipment abnormality judging module slides the second time window until all the first data in the first time window are judged, the proportion of the abnormal data is counted, if the proportion is lower than the preset proportion, the abnormal data is judged to be accidental abnormal data, and if the proportion is higher than the preset proportion, the marine data monitoring equipment is judged to be faulty.
4. A marine environment monitoring method based on internet of things applied to the marine environment monitoring system based on internet of things as set forth in any one of claims 1 to 3, the method comprising:
step A, presetting the data acquisition frequency and the data uploading frequency of the marine data monitoring equipment, comprising setting the data acquisition frequency of the main acquisition equipment and the data acquisition frequency of the auxiliary acquisition equipment,
wherein, the data acquisition frequency f of the main acquisition equipment A Data acquisition frequency f greater than the secondary acquisition device B ；f A Is n times the size f B N is an integer of 100 to 500;
step B, the ocean data monitoring equipment uploads the collected ocean monitoring data and electric quantity information, wherein the uploading frequency f is achieved through the Internet of things transmission equipment UL Uploading to an internet of things data analysis server, wherein the ocean monitoring data comprises first data of a main acquisition device and second data acquired by an auxiliary acquisition device;
and C, the data analysis server of the Internet of things processes the ocean monitoring data and judges whether analysis is abnormal or not, and the method comprises the following steps:
step C1, judging whether the ocean monitoring data is abnormal or not;
step C11, dividing a first time window in the ocean monitoring data sequence, wherein the length of the first time window is 1/f B A moving step length of 1/f B ；
Step C12, estimating the value of the nth first data according to the first (n-1) first data in the first time window;
step C13, comparing and analyzing the value of the nth first data with the value of the corresponding second data in the first time window to determine whether the difference is within the threshold range, wherein n=f A /f B The method comprises the steps of carrying out a first treatment on the surface of the If the first data in the first time window is judged to be abnormal within the threshold range, the first time window is enabled to slide backwards to continue judgment; if the first data exceeds the threshold range, judging that the first data in the first time window is abnormal, and entering a step C2;
step C2, judging the reliability of the marine data monitoring equipment;
step D, the data acquisition frequency and the data uploading frequency of the ocean data monitoring equipment of the data analysis server of the Internet of things are subjected to feedback adjustment;
and D, carrying out feedback adjustment on the data acquisition frequency and the data uploading frequency of the marine data monitoring equipment of the data analysis server of the Internet of things, wherein the method comprises the following steps:
step D1, deleting accidental abnormal data in the first time window, obtaining the standard deviation sigma of the rest first data in the first time window, and adjusting the data acquisition frequency f of the main acquisition equipment A And data acquisition frequency f of the auxiliary acquisition device B The method comprises the following steps of:
f B ＝f A /n；
wherein sigma 0 For the preset standard deviation reference value, beta is a preset standard deviation correction value, f 0 The default main acquisition frequency is adopted;
step D2, if the electric quantity of the marine data monitoring equipment is 5Above 0%, according to the frequency f in the formula D1 A And f B Data acquisition is carried out according to the default uploading frequency f U Uploading data;
step D3, if the electric quantity is smaller than 50%, reducing the uploading frequency, stopping uploading when the electric quantity is reduced to 20%, and uploading the frequency f UL Calculated according to the following formula:
wherein E is the electric quantity of the marine data monitoring equipment, f U The frequency is the default uploading frequency;
step D4, if the electric quantity is less than 30%, increasing the value of n to n 0 Thereby reducing the data acquisition frequency of the auxiliary acquisition equipment under the condition of keeping the data acquisition frequency of the main acquisition equipment unchanged;
step D5, if the electric quantity is smaller than 10%, reducing the data acquisition frequency of the main acquisition equipment to 0.2 times f A The data acquisition frequency of the corresponding auxiliary acquisition equipment is reduced to f which is 0.2 times as high as that of the corresponding auxiliary acquisition equipment B ；
And D6, if the electric quantity is less than 5%, suspending acquisition and uploading, and entering a dormant state at the moment only storing historical data.
5. The method for monitoring marine environment based on internet of things according to claim 4, wherein the determining reliability of the marine data monitoring device in step C2 comprises:
step C21, for the first time window with abnormal first data, extracting the data of the adjacent forward first time window to form a target analysis data sequence, and setting a second time window in the target analysis data sequence, wherein the length of the second time window is 1/f B A moving step length of 1/f A ；
Step C22, estimating the value of the nth first data according to the first (n-1) first data in the second time window; comparing and analyzing the value of the nth first data with the actual measurement value of the corresponding first data in the second time window, and judging whether the difference between the value of the nth first data and the actual measurement value of the corresponding first data is in a threshold range; if the threshold value range is exceeded, judging the abnormal data;
and C23, sliding the second time window until the judgment of all the first data in the first time window is completed, counting the proportion of the abnormal data, judging the abnormal data as accidental abnormal data if the proportion is lower than the preset proportion, and judging that the marine data monitoring equipment fails if the proportion is higher than the preset proportion.
6. The internet of things-based marine environment monitoring method according to claim 5, wherein the internet of things data analysis server rejects and stores the accidental abnormal data after judging the accidental abnormal data, and displays the residual data after rejecting the accidental abnormal data to the data monitoring center for analysis by a user.
7. The ocean environment monitoring method based on the internet of things according to claim 6, wherein after the data analysis server of the internet of things judges that the ocean data monitoring equipment fails, alarm information is sent to the data monitoring center, and a user checks the serial number and the coordinate information of the failed ocean data monitoring equipment through the monitoring terminal.
8. A computer-readable storage medium having stored thereon a computer program, characterized by: the computer program, when executed by a processor, implements the steps in the internet of things based marine environment monitoring method of any of claims 4-7.
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