Block chain-based security monitoring analysis method and system

Abstract

The invention discloses a safety monitoring analysis method and system based on a block chain, relates to the technical field of regional chain safety monitoring, and aims to provide decision support through data analysis and model establishment so as to ensure construction safety and noise control. According to the system, multiple influence factors such as building construction noise, weather factors, traffic noise and commercial noise are comprehensively considered, so that reasonable construction arrangement and noise management are realized; and in the analysis process, the calculation of the correlation coefficient R can help to analyze the incidence relation of the traffic noise Jtz, the commercial noise Syz, the construction noise Jzz and the weather data Weather, so that the mutual influence among the traffic noise Jtz, the commercial noise Syz, the construction noise Jzz and the weather data Weather can be better understood. And by setting a threshold value Q and comparing the threshold value Q with a noise offset coefficient zyxs, whether the current time period is suitable for construction or not can be better decided, and proper measures can be taken as required to reduce the influence of noise on the surrounding environment and residents.

Description

Technical Field

[0001] The present invention relates to the technical field of blockchain security monitoring, and specifically to a security monitoring and analysis method and system based on blockchain. Background Art

[0002] Blockchain is a decentralized distributed ledger technology. By recording data in a blockchain network jointly maintained by multiple participants, blockchain ensures the security and immutability of data. The characteristics of blockchain include decentralization, immutability, traceability, and transparency. Blockchain technology can be applied to the field of security monitoring. For example, a blockchain security monitoring and analysis system can be applied to environmental monitoring, such as noise monitoring. In current urban planning, there are municipal engineering construction, construction project construction, and developer building construction, etc., such as the noise of construction machinery and equipment like excavators, drills, and pile drivers. These noises may have a negative impact on the quality of life and sense of tranquility of surrounding residents, and may affect people's health under long-term exposure.

[0003] The impact of noise on safety is complex, and the specific impact of noise in different situations on safety will vary. When construction noise is generated, it will not only spread due to weather factors and affect residential areas, but also be offset by other noises when there is construction noise in urban areas. How to effectively solve the problems of construction environment monitoring and noise control is the current security monitoring direction that needs to be studied. Summary of the Invention

[0004] (1) Technical Problems to be Solved

[0005] Aiming at the deficiencies of the prior art, the present invention provides a security monitoring and analysis method and system based on blockchain. Through data analysis and model establishment, it provides decision-making support to ensure the safety of construction and noise control. It comprehensively considers multiple influencing factors such as construction noise, weather factors, traffic noise, and commercial noise to achieve reasonable construction arrangements and noise management.

[0006] (2) Technical Solutions

[0007] To achieve the above objectives, the present invention is realized through the following technical solutions: A security monitoring and analysis method based on blockchain includes the following steps,

[0008] Collect the location images of construction and establish a three-dimensional twin model;

[0009] In the 3D twin model, deploy the roads near the construction site as the first target area and deploy the first sensor group; deploy the commercial areas of the roads near the construction site as the second target area and deploy the second sensor group; deploy the areas within the construction site as the third target area and deploy the third sensor group; deploy the fourth sensor group in the first target area, the second target area, and the third target area to collect weather data;

[0010] Collect the noise data of the first sensor group in the first target area and label it as traffic noise Jtz; collect the noise data of the second sensor group in the second target area and label it as commercial noise Syz; collect the noise data of the third sensor group in the third target area and label it as construction noise Jzz;

[0011] Correlate and calculate the traffic noise Jtz, commercial noise Syz, construction noise Jzz, and weather data Weather to obtain the correlation coefficient R, and input it into the 3D twin model for deep learning to calculate the weather influence degree yxd of the weather data Weather on the construction noise Jzz; and analyze and calculate the noise cancellation coefficient zyxs of the traffic noise Jtz and commercial noise Syz on the construction noise Jzz; the noise cancellation coefficient zyxs is obtained through the following formula:

[0012]

[0013] In the formula: T 1 、T 2 、T 3 、...、Tn represent the sum of the noise values of the traffic noise Jtz and commercial noise Syz collected at several time axes; M X represents the sum of the noise values of the traffic noise Jtz and commercial noise Syz with a peripheral radius of X meters centered on a certain center point; X is set to be adjusted by the user; D 1 represents the maximum noise upper limit value of the construction noise Jzz, D 2 represents the minimum noise upper limit value of the construction noise Jzz, cx represents the average duration of the construction noise Jzz; C represents the correction coefficient;

[0014] Compare and calculate the noise cancellation coefficient zyxs with the set threshold Q. If the noise cancellation coefficient zyxs is higher than the threshold Q, it means that the current period is suitable for construction. If the noise cancellation coefficient zyxs is lower than the threshold Q, it means that the noise that cannot cancel the threshold, so it is not suitable for construction in the current period.

[0015] Preferably, use drone remote sensing technology to collect images of the construction site, process and analyze the collected images, and extract key building, structural, and environmental features;

[0016] Using computer vision and image processing techniques, convert the processed image into a 3D twin model; and confirm the boundaries of the first target area, the second target area, and the third target area in the 3D twin model;

[0017] Adopt one or more of a noise sensor or a sound level meter as the first sensor group to collect road noise data, labeled as traffic noise Jtz; adopt one or more of a noise sensor or a sound level meter as the second sensor group to collect commercial noise data, labeled as commercial noise Syz; adopt one or more of a noise sensor or a sound level meter as the third sensor group to collect construction noise data, labeled as construction noise Jzz; adopt a meteorological sensor, a wind direction and speed sensor, an air quality sensor, and a barometric pressure sensor as the fourth sensor group to collect weather data Weather.

[0018] Preferably, preprocess the collected traffic noise Jtz, commercial noise Syz, construction noise Jzz, and weather data Weather; the preprocessing methods altogether include data cleaning and data alignment to ensure that the data has consistent timestamps at the same time point, and normalize the collected data to obtain data in the same format for subsequent analysis.

[0019] Preferably, perform a correlation calculation on the traffic noise Jtz, commercial noise Syz, construction noise Jzz, and weather data Weather to obtain a correlation coefficient R, and the correlation coefficient R is calculated by the following formula:

[0020]

[0021] In the formula, where X and Y respectively represent the observed values of two variables, X′ and Y respectively represent the means of the two variables, Σ represents the summation operation, and sqrt represents the square root operation.

[0022] Preferably, the means of the X variable and the Y variable in the correlation coefficient R are calculated specifically according to the following steps:

[0023] S1. Calculate the mean of each variable: Calculate the means of the traffic noise Jtz, commercial noise Syz, construction noise Jzz, and weather data Weather respectively, and label them as X′Jtz, X′Syz, X′Jzz, and X′Weather;

[0024] S2. Calculate the difference between each variable and the mean: Subtract the mean of each variable from the observed value of each variable to obtain (X - X′Jtz), (Z - X′Jzz) and (W - X′Weather);

[0025] S3. Calculate the product of differences: Multiply the difference between each variable and the mean to obtain ((X - X′Jtz) * (Y - X′Syz)), and ((X - X′Jtz) * (W - X′Weather));

[0026] S4. Accumulate and sum the products: Accumulate and sum the products obtained in the previous step to get Σ((X - X′Jtz) * (Z - X′Jzz)) and Σ((X - X′Jtz) * (W - X′Weather)).

[0027] S5. Calculate the square of the difference between each variable and the mean: Square the difference between each variable and the mean to obtain ((X - X′Jtz)^2), ((Y - X′Syz)^2), ((Z - X′Jzz)^2), and ((W - X′Weather)^2);

[0028] S6. Accumulate and sum the squares: Accumulate and sum the squares obtained in the previous step to get Σ((X - X′Jtz)^2), Σ((Y - X′Syz)^2), Σ((Z - X′Jzz)^2), and Σ((W - X′Weather)^2);

[0029] S7. Calculate the correlation coefficient R: Substitute the results of steps S4 and S6 into the calculation formula of the correlation coefficient R, that is:

[0030]

[0031]

[0032]

[0033] The meaning of the formula is to judge the strength of the correlation according to the value range of the Pearson correlation coefficient R; the value range of the Pearson correlation coefficient R is from -1 to 1, where -1 represents a perfect negative correlation, 1 represents a perfect positive correlation, and 0 represents no correlation.

[0034] Preferably, the weather influence degree yxd is obtained through the formula:

[0035]

[0036] In the formula, fx represents the influence value of wind direction and wind speed on noise, md represents the influence value of air density on noise, qy represents the influence value of atmospheric pressure on noise, and w1, w2, and w3 are the weight values of the influence value of wind direction and wind speed on noise fx, the influence value of air density on noise md, and the influence value of atmospheric pressure on noise qy respectively. Among them, 0.35 ≤ w 1≤0.55, 0.25 ≤ w 2 ≤0.45, 0.50 ≤ w 3 ≤085, where w 1 + w 2 + w 3 ≥1.0, where β represents a correction constant.

[0037] Preferably, a threshold Q is set. The threshold Q is determined according to the requirements of the construction environment and the noise sensitivity of residents, and it can be set as a fixed value or adjusted dynamically according to the actual situation;

[0038] Based on previous calculations and correlation analyses, the value of the noise cancellation coefficient zyxs is obtained; the noise cancellation coefficient zyxs is an index used to measure the noise cancellation ability of traffic noise Jtz and commercial noise Syz against construction noise Jtz;

[0039] Compare the noise cancellation coefficient zyxs with the set threshold Q;

[0040] If the noise cancellation coefficient zyxs is higher than the threshold Q, i.e., zyxs > threshold Q, it means that the current time period is suitable for construction because the noise cancellation ability of traffic noise Jtz and commercial noise Syz can meet the expectations;

[0041] If the noise cancellation coefficient zyxs is lower than the threshold Q, i.e., zyxs < threshold Q, it means that the noise of the threshold Q cannot be cancelled, so it is not suitable for construction in the current time period.

[0042] Preferably, if construction must be carried out in the current time period, if the noise cancellation coefficient zyxs is higher than the threshold Q, construction activities can be continued or increased;

[0043] If the noise cancellation coefficient zyxs is lower than the threshold Q, but construction is required in the current time period, appropriate sound insulation facilities need to be added around the construction site. The sound insulation facilities include building enclosures and installing sound insulation walls to reduce the residents' noise perception level.

[0044] A blockchain-based security monitoring and analysis system includes a data collection module, a model establishment module, a correlation coefficient R calculation module, a threshold comparison module, a decision-making module, and a blockchain storage and sharing module;

[0045] The data collection module is used to collect images of the building construction location and obtain image data of the building construction site using unmanned aerial vehicle remote sensing technology; at the same time, noise sensors or sound level meters are deployed at appropriate positions to collect traffic noise Jtz, commercial noise Syz, and construction noise Jzz data, and weather data Weather is collected using meteorological sensors;

[0046] The model establishment module is used to process and analyze the collected image data by using computer vision and image processing technologies, and convert the processed image data into a 3D twin model, including determining the boundaries of the first target area, the second target area, and the third target area;

[0047] The correlation coefficient R calculation module is used to correlate and calculate traffic noise Jtz, commercial noise Syz, construction noise Jzz, and weather data Weather to obtain the correlation coefficient R between them. By calculating the correlation coefficient R, the influence degree yxd of weather on construction noise and the noise cancellation coefficient zyxs of traffic noise Jtz and commercial noise Syz on construction noise Jzz are calculated;

[0048] The threshold comparison module is used to compare the noise cancellation coefficient zyxs with the set threshold Q; if the noise cancellation coefficient zyxs is higher than the threshold Q, it means that construction is suitable for the current period; if the noise cancellation coefficient zyxs is lower than the threshold Q, it means that the noise that cannot cancel the threshold, so construction is not suitable for the current period;

[0049] The decision-making module is used to make corresponding construction adjustments according to the result of the comparison calculation with the threshold Q; if the noise cancellation coefficient zyxs is higher than the threshold Q, construction activities can continue or increase; if the noise cancellation coefficient zyxs is lower than the threshold Q, but construction is required in the current period, appropriate sound insulation facilities need to be added around the construction site;

[0050] The blockchain storage and sharing module is used to store and share the associated data of the collected building construction image data, noise data, and weather data in the form of blockchain technology; blockchain technology is used for data verification and traceability of the collected data.

[0051] (III) Beneficial effects

[0052] The present invention provides a security monitoring and analysis method and system based on blockchain. It has the following beneficial effects:

[0053] (1) The steps in the security monitoring and analysis method based on blockchain are to collect, analyze, and evaluate construction noise and its related factors to determine whether construction is suitable for the current period, so as to achieve the purpose of security monitoring and control. The purpose of this security monitoring and analysis method based on blockchain is to provide decision-making support through data analysis and model establishment to ensure the safety of construction and noise control. It comprehensively considers multiple influencing factors such as construction noise, weather factors, traffic noise, and commercial noise to achieve reasonable construction arrangements and noise management.

[0054] (2) The calculation of the correlation coefficient R can help analyze the correlation between traffic noise Jtz, commercial noise Syz, construction noise Jzz, and weather data Weather, so as to better understand their mutual influence. This helps to formulate effective safety monitoring strategies and take corresponding measures to reduce the impact of noise on construction safety and the quality of life of residents.

[0055] (3) Calculating the weather influence degree yxd can help evaluate the impact of weather conditions on construction noise. By understanding the influence of weather factors such as wind direction and speed, air density, and atmospheric pressure on noise, the changing trend of construction noise can be better predicted, and corresponding measures can be taken to reduce its impact on the surrounding environment and residents; by setting a threshold Q and comparing it with the noise cancellation coefficient zyxs, it can be better determined whether it is appropriate to carry out construction during the current period, and appropriate measures can be taken to reduce the impact of noise on the surrounding environment and residents when necessary.

[0056] (4) The blockchain-based security monitoring and analysis system includes a data collection module, a model establishment module, a correlation coefficient R calculation module, a threshold comparison module, a decision-making module, and a blockchain storage and sharing module. Through the collaborative work of the above modules, the blockchain-based security monitoring and analysis system can achieve the monitoring of the construction environment, the analysis of noise impact, and the decision-making of construction adjustment to ensure that construction activities meet safety standards and the noise sensitivity requirements of residents. Description of the Drawings

[0057] Figure 1 It is a schematic diagram of the block diagram process of the blockchain-based security monitoring and analysis system of the present invention. Detailed Embodiments

[0058] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0059] Blockchain is a decentralized distributed ledger technology. By recording data in a blockchain network jointly maintained by multiple participants, blockchain ensures the security and immutability of data. The characteristics of blockchain include decentralization, immutability, traceability, and transparency. Blockchain technology can be applied to the fields of security monitoring. For example, a blockchain security monitoring and analysis system can be applied to environmental monitoring, such as noise monitoring. In current urban planning, there are municipal engineering construction, construction project construction, and developer building construction, etc., such as the noise generated by mechanical equipment like excavators, drills, and pile drivers. Such noise may have a negative impact on the quality of life and sense of tranquility of surrounding residents and may affect people's health under long-term exposure.

[0060] The impact of noise on safety is complex, and the specific impact of noise on safety varies in different situations. When construction noise is generated, it will not only spread due to weather factors and affect residential areas, but also be offset by other noises when there is construction noise in urban areas. How to effectively solve the problems of construction environment monitoring and noise control is the current direction of safety monitoring that needs to be studied.

[0061] Embodiment 1

[0062] The present invention proposes a security monitoring and analysis method based on blockchain, including the following steps:

[0063] Collect the location images of building construction and establish a three-dimensional twin model; by collecting the location images of the building construction area, a three-dimensional model corresponding to the actual construction environment can be established for subsequent data analysis and simulation.

[0064] In the three-dimensional twin model, deploy the roads near the building construction site as the first target area and deploy the first sensor group; deploy the commercial area of the road near the building construction site as the second target area and deploy the second sensor group; deploy the area within the building construction area as the third target area and deploy the third sensor group; deploy the fourth sensor group in the first target area, the second target area, and the third target area to collect weather data;

[0065] Collect the noise data of the first sensor group in the first target area and label it as traffic noise Jtz; collect the noise data of the second sensor group in the second target area and label it as commercial noise Syz; collect the noise data of the third sensor group in the third target area and label it as construction noise Jzz;

[0066] Correlate and calculate traffic noise Jtz, commercial noise Syz, construction noise Jzz, and weather data Weather to obtain a correlation coefficient R, and input it into a three-dimensional twin model for deep learning to calculate the weather impact degree yxd of weather data Weather on construction noise Jzz; through this process, the impact of weather factors on construction noise can be quantitatively analyzed. And analyze and calculate the noise cancellation coefficient zyxs of traffic noise Jtz and commercial noise Syz on construction noise Jzz; the noise cancellation coefficient zyxs is obtained through the following formula:

[0067]

[0068] Where: T 1 、T 2 、T 3 、...、Tn represent the sum of the noise values of traffic noise Jtz and commercial noise Syz collected at several time axes; M X represents the sum of the noise values of traffic noise Jtz and commercial noise Syz with a peripheral radius of X meters centered on a certain center point; X is set to be adjusted by the user; D 1 represents the maximum noise upper limit value of construction noise Jzz, D 2 represents the minimum noise upper limit value of construction noise Jzz, cx represents the average duration of construction noise Jzz; C represents a correction coefficient;

[0069] Compare and calculate the noise cancellation coefficient zyxs with a set threshold Q. If the noise cancellation coefficient zyxs is higher than the threshold Q, it means that construction is suitable at the current time period. If the noise cancellation coefficient zyxs is lower than the threshold Q, it means that the noise of the threshold cannot be cancelled, so construction is not suitable for the current time period.

[0070] In this embodiment, the steps in the security monitoring and analysis method based on blockchain are to collect, analyze, and evaluate construction noise and its related factors to determine whether construction is suitable at the current time period, so as to achieve the purpose of security monitoring and control. The purpose of this security monitoring and analysis method based on blockchain is to provide decision support through data analysis and model establishment to ensure the safety of construction and noise control. It comprehensively considers multiple influencing factors such as construction noise, weather factors, traffic noise, and commercial noise to achieve reasonable construction arrangements and noise management.

[0071] Embodiment 2. This embodiment is an explanatory description carried out in Embodiment 1. Specifically, use drone remote sensing technology to collect images of the construction site, process and analyze the collected images, and extract key building, structural, and environmental features;

[0072] Using computer vision and image processing technologies, convert the processed image into a 3D twin model; and confirm the boundaries of the first target area, the second target area, and the third target area in the 3D twin model; thereby providing accurate area division for subsequent data analysis.

[0073] Adopt one or more of a noise sensor or a sound level meter as the first sensor group to collect road noise data, marked as traffic noise Jtz; adopt one or more of a noise sensor or a sound level meter as the second sensor group to collect commercial noise data, marked as commercial noise Syz; adopt one or more of a noise sensor or a sound level meter as the third sensor group to collect construction noise data, marked as construction noise Jzz; adopt a meteorological sensor, a wind direction and speed sensor, an air quality sensor, and a barometric pressure sensor as the fourth sensor group to collect weather data Weather.

[0074] In this embodiment, this method based on UAV remote sensing technology combines image processing, computer vision, and sensor technology, and can obtain detailed building construction information and environmental data. Through the processing and analysis of image and sensor data, the building construction noise and its association with weather factors can be accurately evaluated, providing beneficial effects for construction arrangements and noise control.

[0075] Example 3. This example is an explanatory illustration based on Example 1. Specifically, the collected traffic noise Jtz, commercial noise Syz, construction noise Jzz, and weather data Weather are preprocessed. The preprocessing methods include data cleaning and data alignment to ensure that the data has consistent timestamps at the same time point, and the collected data is normalized to obtain data in the same format for subsequent analysis. Data cleaning refers to removing outliers, error values, and missing values in the data to ensure the accuracy and reliability of the data. During the data cleaning process, the collected traffic noise Jtz, commercial noise Syz, construction noise Jzz, and weather data Weather are inspected and screened to remove possible outliers and error values. At the same time, the method for handling missing values can be to fill in the missing values or delete the data containing missing values to ensure the integrity and consistency of the data. Data alignment means that the data collected by different sensors has consistent timestamps at the same time point. Since there may be time deviations during the data collection process, the data needs to be aligned to make it consistent in time. This can be achieved through timestamp matching and alignment algorithms to ensure that the traffic noise Jtz, commercial noise Syz, construction noise Jzz, and weather data Weather correspond at the same time point. Data normalization refers to converting data with different ranges and units into the same standard format for subsequent data analysis and comparison. In this method, the collected traffic noise Jtz, commercial noise Syz, construction noise Jzz, and weather data Weather may have different value ranges and units, and need to be normalized. For example, the data is scaled to the range of 0 - 1 or standardized to data with a mean of 0 and a standard deviation of 1 for subsequent statistical analysis and model establishment.

[0076] In this example, through data cleaning and data alignment, it can be ensured that the collected data is accurate, consistent, and complete. And data normalization can unify data with different ranges and units to the same standard, facilitating subsequent analysis and comparison. These preprocessing steps help ensure the quality and consistency of the data and provide a reliable data basis for subsequent analysis.

[0077] Example 4. This example is an explanatory illustration based on Example 1. Specifically, the traffic noise Jtz, commercial noise Syz, construction noise Jzz, and weather data Weather are correlated and calculated to obtain the correlation coefficient R. The correlation coefficient R is calculated by the following formula:

[0078]

[0079] In the formula, where X and Y respectively represent the observed values of two variables, X′ and respectively represent the means of two variables, Σ represents the summation operation, and sqrt represents the square root operation.

[0080] The means of the X variable and the Y variable in the correlation coefficient R are calculated as follows:

[0081] S1. Calculate the mean of each variable: Calculate the means of traffic noise Jtz, commercial noise Syz, construction noise Jzz, and weather data Weather respectively, and mark them as X′Jtz, X′Syz, X′Jzz, and X′Weather;

[0082] S2. Calculate the difference between each variable and its mean: Subtract the mean of each variable from the observed value of each variable to obtain (X - X′Jtz), (Z - X′Jzz) and (W - X′Weather);

[0083] S3. Calculate the product of the differences: Multiply the difference between each variable and its mean to obtain ((X - X′Jtz) * (Y - X′Syz)), and ((X - X′Jtz) * (W - X′Weather));

[0084] S4. Accumulate and sum the products: Accumulate and sum the products obtained in the previous step to obtain and Σ((X - X′Jtz) * (W - X′Weather)).

[0085] S5. Calculate the square of the difference between each variable and its mean: Square the difference between each variable and its mean to obtain ((X - X′Jtz)^2), ((Y - X′Syz)^2), ((Z - X′Jzz)^2), and ((W - X′Weather)^2);

[0086] S6. Accumulate and sum the squares: Accumulate and sum the squares obtained in the previous step to obtain Σ((X - X′Jtz)^2), Σ((Y - X′Syz)^2), Σ((Z - X′Jzz)^2), and Σ((W - X′Weather)^2);

[0087] S7. Calculate the correlation coefficient R: Substitute the results of steps S4 and S6 into the calculation formula of the correlation coefficient R, that is:

[0088]

[0089]

[0090]

[0091] The meaning of the formula is to judge the strength of the correlation according to the value range of the Pearson correlation coefficient R. The value range of the Pearson correlation coefficient R is from -1 to 1, where -1 represents a perfect negative correlation, 1 represents a perfect positive correlation, and 0 represents no correlation.

[0092] In this embodiment, the calculation of the correlation coefficient R can help analyze the correlation relationship between traffic noise Jtz, commercial noise Syz, construction noise Jzz, and weather data Weather, so as to better understand their mutual influence. This helps to formulate effective safety monitoring strategies and take corresponding measures to reduce the impact of noise on construction safety and the quality of life of residents.

[0093] Example 5. This example is an explanatory description based on Example 1. Specifically, the weather influence degree yxd is obtained through the formula:

[0094]

[0095] In the formula, fx represents the influence value of wind direction and wind speed on noise, md represents the influence value of air density on noise, qy represents the influence value of atmospheric pressure on noise, and w1, w2, and w3 are the weight values of the influence value fx of wind direction and wind speed on noise, the influence value md of air density on noise, and the influence value qy of atmospheric pressure on noise respectively. Among them, 0.35 ≤ w 1 ≤ 0.55, 0.25 ≤ w 2 ≤ 0.45, 0.50 ≤ w 3 ≤ 0.85. Among them, w 1 + w 2 + w 3 ≥ 1.0, and β represents a correction constant.

[0096] In this embodiment, calculating the weather influence degree yxd can help evaluate the influence degree of weather conditions on construction noise. By understanding the influence of weather factors such as wind direction and wind speed, air density, and atmospheric pressure on noise, the change trend of construction noise can be better predicted, and corresponding measures can be taken to reduce its impact on the surrounding environment and residents.

[0097] Example 6. This example is an explanatory description based on Example 1. Specifically, a threshold Q is set. The threshold Q is determined according to the requirements of the construction environment and the noise sensitivity of residents, and it can be set as a fixed value or adjusted dynamically according to the actual situation;

[0098] According to the previous calculations and correlation analyses, the value of the noise cancellation coefficient zyxs is obtained. The noise cancellation coefficient zyxs is an index used to measure the noise cancellation ability of traffic noise Jtz and commercial noise Syz on construction noise Jtz;

[0099] Compare the noise cancellation coefficient zyxs with the set threshold Q;

[0100] If the noise cancellation coefficient zyxs is higher than the threshold Q, i.e., zyxs > threshold Q, it indicates that the current period is suitable for construction because the cancellation ability of traffic noise Jtz and commercial noise Syz can meet the expectations; this means that the current period is suitable for construction because the impacts of traffic noise Jtz and commercial noise Syz can be effectively cancelled.

[0101] If the noise cancellation coefficient zyxs is lower than the threshold Q, i.e., zyxs < threshold Q, it means that the noise of threshold Q cannot be cancelled, so it is not suitable for construction in the current period.

[0102] If construction must be carried out in the current period and the noise cancellation coefficient zyxs is higher than the threshold Q, construction activities can continue or increase;

[0103] If the noise cancellation coefficient zyxs is lower than the threshold Q but construction is required in the current period, appropriate sound insulation facilities need to be added around the construction site. The sound insulation facilities include building enclosures and installing sound insulation walls to reduce the residents' perception of noise.

[0104] In this embodiment, by setting the threshold Q and comparing it with the noise cancellation coefficient zyxs, it is possible to better decide whether the current period is suitable for construction and take appropriate measures to mitigate the impact of noise on the surrounding environment and residents when necessary.

[0105] For the security monitoring and analysis system based on blockchain, please refer to Figure 1 , including a data acquisition module, a model establishment module, a correlation coefficient R calculation module, a threshold comparison module, a decision-making module, and a blockchain storage and sharing module;

[0106] The data acquisition module is used to collect images of the construction location and obtain image data of the construction site using unmanned aerial vehicle remote sensing technology; at the same time, noise sensors or sound level meters are deployed at appropriate positions to collect traffic noise Jtz, commercial noise Syz, and construction noise Jzz data, and weather sensors are used to collect weather data Weather;

[0107] The model establishment module is used to process and analyze the collected image data using computer vision and image processing technologies, and convert the processed image data into a three-dimensional twin model, including determining the boundaries of the first target area, the second target area, and the third target area;

[0108] The correlation coefficient R calculation module is used to correlate and calculate traffic noise Jtz, commercial noise Syz, construction noise Jzz, and weather data Weather to obtain the correlation coefficient R between them. By calculating the correlation coefficient R, the influence degree yxd of weather on construction noise is calculated, as well as the noise cancellation coefficient zyxs of traffic noise Jtz and commercial noise Syz on construction noise Jzz;

[0109] The threshold comparison module is used to compare the noise cancellation coefficient zyxs with the set threshold Q; if the noise cancellation coefficient zyxs is higher than the threshold Q, it means that construction is suitable for the current period; if the noise cancellation coefficient zyxs is lower than the threshold Q, it means that the noise that cannot cancel the threshold, so it is not suitable for construction in the current period;

[0110] The decision-making module is used to make corresponding construction adjustments according to the results of the comparison calculation with the threshold Q; if the noise cancellation coefficient zyxs is higher than the threshold Q, construction activities can continue or increase; if the noise cancellation coefficient zyxs is lower than the threshold Q, but construction is required in the current period, appropriate sound insulation facilities need to be added around the construction site;

[0111] The blockchain storage and sharing module is used to store and share the associated data of the collected building construction image data, noise data, and weather data in the form of blockchain technology; blockchain technology is used for data verification and traceability of the collected data, enhancing the security and credibility of the data.

[0112] Through the collaborative work of the above modules, this system, the security monitoring and analysis system based on blockchain can realize the monitoring of the construction environment, noise impact analysis, and decision-making for construction adjustment to ensure that construction activities meet safety standards and the noise sensitivity requirements of residents.

[0113] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A security monitoring and analysis method based on blockchain, characterized by: The following steps are included: Collect location images of building construction and build a 3D twin model; In the three-dimensional twin model, the road near the construction site is deployed as the first target area, and the first sensor group is deployed; the commercial area of ​​the road near the construction site is deployed as the second target area, and the second sensor group is deployed; the area within the construction site is deployed as the third target area, and the third sensor group is deployed; deploying a fourth sensor group in the first target area, the second target area, and the third target area to collect weather data; Collect noise data of the first sensor group in the first target area, marked as traffic noise Jtz; The noise data of the second sensor group in the second target area is collected and marked as commercial noise Syz; the noise data of the third sensor group in the third target area is collected and marked as construction noise Jzz; Traffic noise Jtz, commercial noise Syz, construction noise Jzz and weather data Weather are correlated and calculated to obtain the correlation coefficient R, which is then input into the three-dimensional twin model for deep learning to calculate the weather impact yxd of weather data Weather on construction noise Jzz; and the noise coefficient zyxs of traffic noise Jtz and commercial noise Syz on construction noise Jzz is analyzed and calculated; the noise coefficient zyxs is obtained by the following formula: Where: T1, T2, T3, ..., Tn represent the sum of the noise values ​​of traffic noise Jtz and commercial noise Syz collected on several time axes; M X It represents the sum of the noise values ​​of traffic noise Jtz and commercial noise Syz with a radius of X meters from a central point; X is set to a user-adjusted value; D1 represents the maximum noise upper limit of construction noise Jzz, D2 represents the minimum noise upper limit of construction noise Jzz, cx represents the average duration of construction noise Jzz; C represents the correction coefficient; The noise cancellation coefficient zyxs is compared and calculated with the set threshold value Q. If the noise cancellation coefficient zyxs is higher than the threshold value Q, it means that the current period is suitable for construction. If the noise cancellation coefficient zyxs is lower than the threshold value Q, it means that the noise of the threshold cannot be cancelled, so it is not suitable for construction in the current period.

2. The security monitoring and analysis method based on blockchain according to claim 1 is characterized in that: Use drone remote sensing technology to collect images of construction sites, process and analyze the collected images, and extract key building, structural and environmental features; Using computer vision and image processing technology, converting the processed image into a three-dimensional twin model; and confirming the boundaries of the first target area, the second target area, and the third target area in the three-dimensional twin model; One or more noise sensors or sound level meters are used as the first sensor group to collect road noise data, which is marked as traffic noise Jtz; one or more noise sensors or sound level meters are used as the second sensor group to collect commercial noise data, which is marked as commercial noise Syz; one or more noise sensors or sound level meters are used as the third sensor group to collect construction noise data, which is marked as construction noise Jzz; meteorological sensors, wind direction and speed sensors, air quality sensors and air pressure sensors are used as the fourth sensor group to collect weather data Weather.

3. The security monitoring and analysis method based on blockchain according to claim 1 is characterized in that: The collected traffic noise Jtz, commercial noise Syz, construction noise Jzz and weather data Weather are preprocessed; the preprocessing method includes data cleaning and data alignment to ensure that the data has a consistent timestamp at the same time point, and normalize the collected data to obtain data in the same format.

4. The security monitoring and analysis method based on blockchain according to claim 1 is characterized in that: Traffic noise Jtz, commercial noise Syz, construction noise Jzz and weather data Weather are correlated and calculated to obtain a correlation coefficient R, which is calculated by the following formula: In the formula, X and Y represent the observed values ​​of two variables, X′ and They represent the means of two variables, Σ represents the sum operation, and sqrt represents the square root operation.

5. The security monitoring and analysis method based on blockchain according to claim 4 is characterized in that: The mean of the X variable and the Y variable in the correlation coefficient R is calculated as follows: S1. Calculate the mean of each variable: Calculate the mean of traffic noise Jtz, commercial noise Syz, construction noise Jzz and weather data Weather respectively, and mark them as X′Jtz, X′Syz, X′Jzz and X′Weather respectively; S2. Calculate the difference between each variable and the mean: subtract the mean of the corresponding variable from the observed value of each variable to obtain (XX′Jtz), (ZX′Jzz) and (WX′Weather); S3. Calculate the product of the differences: multiply the difference between each variable and the mean to obtain ((XX′Jtz)*(YX′Syz)), and ((XX′Jtz)*(WX′Weather)); S4. Accumulate and sum the products: Accumulate and sum the products calculated in the previous step to obtain Σ((XX′Jtz)*(ZX′Jzz)) and Σ((XX′Jtz)*(WX′Weather)); S5. Calculate the square of the difference between each variable and the mean: square the difference between each variable and the mean to obtain ((XX′Jtz)^2), ((YX′Syz)^2), ((ZX′Jzz)^2) and ((WX′Weather)^2); S6. Accumulate and sum the squares: Accumulate and sum the squares calculated in the previous step to obtain Σ((XX′Jtz)^2), Σ((YX′Syz)^2), Σ((ZX′Jzz)^2) and Σ((WX′Weather)^2); S7. Calculate the correlation coefficient R. Substitute the results of steps S4 and S6 into the calculation formula of the correlation coefficient R, which is: The meaning of the formula is to judge the strength of the correlation based on the value range of the Pearson correlation coefficient R; the value range of the Pearson correlation coefficient R is -1 to 1, where -1 represents a complete negative correlation, 1 represents a complete positive correlation, and 0 represents no correlation.

6. The security monitoring and analysis method based on blockchain according to claim 1 is characterized in that: The weather impact degree yxd is obtained by the formula: In the formula, fx represents the influence of wind direction and wind speed on noise, md represents the influence of air density on noise, qy represents the influence of atmospheric pressure on noise, w1, w2 and w3 are the weight values ​​of the influence of wind direction and wind speed on noise fx, the influence of air density on noise md and the influence of atmospheric pressure on noise qy, respectively, among which, 0.35≤w1≤0.55, 0.25≤w2≤0.45, 0.50≤w3≤085, among which, w1+w2+w3≥1.0, β represents the correction constant.

7. The security monitoring and analysis method based on blockchain according to claim 1 is characterized in that: Set the threshold Q. The threshold Q is determined based on the construction environment and residents' noise sensitivity requirements. It can be set as a fixed value or adjusted dynamically based on actual conditions. According to the previous calculation and related analysis, the value of the noise cancellation coefficient zyxs is obtained; the noise cancellation coefficient zyxs is used as an indicator to measure the ability of traffic noise Jtz and commercial noise Syz to cancel the construction noise Jtz; Compare the cancellation noise coefficient zyxs with the set threshold value Q; If the noise cancellation coefficient zyxs is higher than the threshold value Q, that is, zyxs>threshold value Q, it means that the current period is suitable for construction because the cancellation capacity of traffic noise Jtz and commercial noise Syz can reach the expected level; If the noise cancellation coefficient zyxs is lower than the threshold Q, that is, zyxs<threshold Q, it means that the noise of threshold Q cannot be cancelled, so it is not suitable for construction in the current period.

8. The security monitoring and analysis method based on blockchain according to claim 7 is characterized in that: If construction must be carried out during the current period, if the noise cancellation coefficient zyxs is higher than the threshold value Q, construction activities can be continued or increased; If the noise cancellation coefficient zyxs is lower than the threshold value Q, but construction needs to be carried out during the current period, appropriate sound insulation facilities need to be added around the construction site. The sound insulation facilities include building fences and installing sound insulation walls to reduce residents' noise perception.

9. The security monitoring and analysis system based on blockchain is characterized by: It includes data collection module, model building module, correlation coefficient R calculation module, threshold comparison module, decision module and blockchain storage and sharing module; The data acquisition module is used to collect images of construction sites and use drone remote sensing technology to obtain image data of construction sites. At the same time, noise sensors or sound level meters are deployed at appropriate locations to collect traffic noise Jtz, commercial noise Syz, and construction noise Jzz data, and meteorological sensors are used to collect weather data Weather. A model building module is used to process and analyze the collected image data using computer vision and image processing technology, and convert the processed image data into a three-dimensional twin model, including determining the boundaries of the first target area, the second target area, and the third target area; The correlation coefficient R calculation module is used to correlate traffic noise Jtz, commercial noise Syz, construction noise Jzz and weather data Weather to obtain the correlation coefficient R between them. By calculating the correlation coefficient R, the influence of weather on construction noise yxd and the noise coefficient zyxs of traffic noise Jtz and commercial noise Syz on construction noise Jzz are calculated. The threshold comparison module is used to compare the noise cancellation coefficient zyxs with the set threshold Q; if the noise cancellation coefficient zyxs is higher than the threshold Q, it means that the current period is suitable for construction; if the noise cancellation coefficient zyxs is lower than the threshold Q, it means that the noise of the threshold cannot be cancelled, so it is not suitable for construction in the current period; The decision module is used to make corresponding construction adjustments based on the calculation results compared with the threshold value Q; if the noise offset coefficient zyxs is higher than the threshold value Q, the construction activities can be continued or increased; if the noise offset coefficient zyxs is lower than the threshold value Q, but construction needs to be carried out during the current period, appropriate sound insulation facilities need to be added around the construction site; The blockchain storage and sharing module is used to store and share the collected construction image data, noise data and weather data in the form of blockchain technology; Blockchain technology is used to verify and trace the collected data.

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