Environment law enforcement evidence obtaining method and system based on augmented reality technology

Abstract

The invention relates to the technical field of environment monitoring, and discloses an environment law enforcement evidence obtaining method and system based on an augmented reality technology, and the method comprises the steps: obtaining real-time pollution discharge data and real-time environment data in the production process of an enterprise, and obtaining a panoramic video of a detection region; obtaining standard information matched with the real-time pollution discharge data in real time, comparing the real-time pollution discharge data with the standard information, and obtaining an abnormal site according to a comparison result; correcting the real-time pollution discharge data and the abnormal site according to the real-time environment data; and according to the corrected abnormal site, adding an AR mark in the panoramic video, and according to the AR mark, constructing an environment law enforcement evidence obtaining report. According to the invention, through a series of innovative measures such as comprehensive data acquisition, intelligent comparison and analysis, environmental data correction, AR marking assistance and report system construction, intelligence, precision and high efficiency of environmental law enforcement work are realized.

Description

Technical Field

[0001] The present invention relates to the field of environmental monitoring technology, and in particular to a method and system for environmental law enforcement evidence collection based on augmented reality technology. Background Art

[0002] Traditional environmental law enforcement evidence collection methods, such as on-site photography, video recording and sampling, have played a certain role in the past, but their limitations cannot be ignored. These methods generally face the risk of low evidence collection efficiency, evidence being tampered with or lost, and it is difficult to intuitively and comprehensively present the facts of the violation.

[0003] Traditional evidence collection methods have exposed shortcomings such as low evidence collection efficiency, difficulty in evidence preservation, and insufficient on-site restoration capabilities when dealing with complex and ever-changing environmental challenges, bringing unprecedented challenges to environmental law enforcement. Therefore, exploring more efficient, safe, and intuitive evidence collection methods has become an important issue that needs to be urgently addressed in the field of environmental law enforcement. Summary of the invention

[0004] In view of this, the present invention proposes a method and system for environmental law enforcement evidence collection based on augmented reality technology, aiming to bring revolutionary changes to the environmental law enforcement evidence collection process by integrating augmented reality (AR) technology.

[0005] The present invention proposes a method for collecting evidence for environmental law enforcement based on augmented reality technology, comprising:

[0006] Obtain real-time pollution data and real-time environmental data during the production process of the enterprise, and obtain panoramic video of the detection area;

[0007] Acquire standard information matching the real-time sewage discharge data in real time, compare the real-time sewage discharge data with the standard information, and obtain abnormal locations according to the comparison results;

[0008] Correcting the real-time sewage discharge data and the abnormal location according to the real-time environmental data;

[0009] According to the corrected abnormal site, an AR marker is added to the panoramic video; wherein the AR marker includes location information, timestamp, real-time sewage discharge data, real-time environmental data and abnormality level; the location information includes the corrected abnormal site coordinates, and the location information also includes the relative position of the corrected abnormal site coordinates and the enterprise facilities;

[0010] According to the timestamp, a video segment containing the abnormal occurrence is captured from the panoramic video as environmental law enforcement evidence.

[0011] Preferably, obtaining standard information matching the real-time sewage discharge data in real time includes:

[0012] Establishing a standard database, which includes enterprise production scale information and its corresponding emission standards;

[0013] Evaluate and obtain the production scale information of the enterprise based on its production capacity, product output, and raw material consumption;

[0014] According to the production scale information of the enterprise, a matching emission standard is selected from the standard database;

[0015] Standard information matching the real-time pollution emission data is obtained from the emission standards.

[0016] Preferably, when screening matching emission standards from the standard database according to the production scale information of the enterprise, it includes:

[0017] Determine the industry category to which the enterprise belongs based on its main business;

[0018] Obtain the production characteristics and pollution discharge characteristics of the enterprise according to the industry category to which the enterprise belongs;

[0019] Obtain the key emissions of the enterprise based on the production characteristics and emission characteristics of the enterprise;

[0020] Matching emission standards are screened from the standard database according to the key emissions.

[0021] Preferably, comparing the real-time sewage discharge data with the standard information and obtaining abnormal sites according to the comparison results includes:

[0022] Acquire a number of real-time sewage collection data at a number of collection points, and after eliminating obvious error values ​​and abnormal values, obtain a number of real-time sewage data;

[0023] Each of the real-time pollution discharge data is compared with the standard information. When the comparison result shows that the real-time pollution discharge data exceeds the specified range of the standard information, the pollution discharge point corresponding to the real-time pollution discharge data exceeding the range is marked as an abnormal site.

[0024] Preferably, the real-time sewage discharge data includes at least any one of sewage outlet flow information, nanoparticle information, greenhouse gas emission information, heavy metal emission information and volatile organic compound information.

[0025] Preferably, when the real-time pollution discharge data and the abnormal location are corrected according to the real-time environmental data, it includes:

[0026] The discharge information of the sewage outlet is corrected according to wind speed, wind direction and air pressure. The correction calculation formula is:

[0027]

[0028] Among them, Fc represents the corrected flow information of the sewage outlet, Fm represents the measured flow information of the sewage outlet, Pr represents the reference air pressure, Pc represents the current air pressure, Wc represents the current wind speed, and α represents the influence coefficient of wind speed on flow;

[0029] The nanoparticle information is corrected according to humidity and temperature, and the correction formula is:

[0030] Cc=Cm·(1-βHc)·(1+γTc);

[0031] Wherein, Cc represents the corrected nanoparticle information, Cm represents the measured nanoparticle information, Hc represents the current humidity, β represents the humidity influence coefficient, Tc represents the current temperature, and γ represents the temperature influence coefficient;

[0032] The greenhouse gas emission information is corrected according to atmospheric stability and air pressure. The correction formula is:

[0033]

[0034] Among them, Gc represents the corrected greenhouse gas emission information, Gm represents the measured greenhouse gas emission information, and Sc represents the current atmospheric stability parameter;

[0035] The heavy metal emission information is corrected according to precipitation and wind speed. The correction formula is:

[0036] Mc=Mm·(1+δ·Rc)·(1+ε·Wc);

[0037] Among them, Mc represents the corrected heavy metal emission information, Mm represents the measured heavy metal emission information, Rc represents the current precipitation, δ represents the precipitation influence coefficient, and ∈ represents the wind speed influence coefficient;

[0038] Volatile organic compounds are corrected according to temperature and humidity. The correction formula is:

[0039] Vc=Vm·(1+κ·Tc)·(1-λ·Hc);

[0040] Wherein, Vc represents the corrected volatile organic compounds, Vm represents the measured volatile organic compounds, κ represents the temperature influence coefficient, and λ represents the humidity influence coefficient.

[0041] Preferably, when the real-time sewage discharge data and the abnormal location are corrected according to the real-time environmental data, it also includes:

[0042] Establish xyz stereo coordinates in the panoramic video of the detection area. Let the coordinates of the detection point be (xo, yo, zo), which represents the three-dimensional position in space. xo and yo represent the longitude and latitude of the detection point respectively, and zo represents the height of the detection point from the ground.

[0043] Δx=Wc·t·cos(θc);

[0044] Δy=Wc·t·sin(θc);

[0045] Δz = μ·(Tc-Tf);

[0046] Wherein, Δx represents the horizontal displacement in the x direction, Δy represents the horizontal displacement in the y direction, Δz represents the vertical displacement; Tf represents the standard reference temperature;

[0047] Combine the original coordinates with the correction value to obtain the corrected abnormal site coordinates:

[0048] xc=xo+Δx;

[0049] yc=yo+Δy;

[0050] zc=zo+Δz;

[0051] The corrected coordinates of the abnormal site are (xc, yc, zc).

[0052] Preferably, according to the timestamp, when a video segment containing an abnormality is intercepted from the panoramic video as environmental law enforcement evidence, the method includes:

[0053] When it is detected that any data in the real-time pollution discharge data exceeds the corresponding emission standard, the timestamp of the abnormality is recorded at the beginning of video capture, and the recording is continued until the abnormal data returns to the standard range, forming a complete video segment of the abnormality occurrence process;

[0054] If the abnormal data does not return to the standard range within the preset time, the video capture records the timestamp of the abnormality, and continues to record until manual intervention or the preset maximum recording time is reached, forming a complete video segment of the abnormality process;

[0055] The complete video segment of the abnormal occurrence process is associated with the corresponding real-time pollution discharge data and the corrected coordinates of the abnormal site, and the associated video segment of the abnormal occurrence process is used as evidence for environmental law enforcement.

[0056] Preferably, the method for dividing the abnormality levels includes:

[0057] According to the following calculation formula, the degree of exceeding the standard is calculated for each real-time pollution discharge data of the abnormal location:

[0058]

[0059] When the degree of exceeding the standard is less than 10%, the abnormality level is determined to be a slight abnormality;

[0060] When 10%≤exceeding degree<30%, the abnormality level is determined to be moderate abnormality;

[0061] When 30%≤exceeding degree<50%, the abnormality level is determined to be a serious abnormality;

[0062] When 50% ≤ the exceeding degree, the abnormality level is determined to be an extremely serious abnormality.

[0063] The present invention also proposes a system for environmental law enforcement evidence collection based on augmented reality technology, which is used to implement the above-mentioned method for environmental law enforcement evidence collection based on augmented reality technology.

[0064] Compared with the prior art, the present invention has the following beneficial effects:

[0065] Real-time and accuracy: By collecting pollution data in real time and immediately comparing it with standard information, abnormal sites can be quickly discovered, greatly improving the response speed and accuracy of environmental law enforcement. At the same time, the use of natural language processing technology and AI work assistants for data processing and analysis ensures the clarity, logical rigor and reasoning accuracy of the response, further improving the efficiency and accuracy of data processing.

[0066] Multi-dimensional data correction: Multi-dimensional correction of pollution data is carried out based on real-time environmental data (such as wind speed, wind direction, air pressure, humidity, temperature, precipitation, atmospheric stability, etc.), making the assessment of pollution data closer to the actual situation, reducing errors caused by environmental factors, and improving the reliability and scientificity of the data.

[0067] Augmented reality technology assistance: AR technology is used to visually display key information such as the location information, timestamp, real-time pollution data, real-time environmental data, and abnormality level of abnormal sites in front of law enforcement officers, which not only improves the intuitiveness and convenience of law enforcement, but also enhances the transparency and credibility of law enforcement. At the same time, the location information in the AR tag also includes the relative position with the enterprise facilities, which helps law enforcement officers quickly locate the source of the problem and improve law enforcement efficiency.

[0068] Clear classification of abnormal levels: Clear classification of abnormal levels according to the degree of exceeding the standard helps law enforcement personnel take corresponding law enforcement measures according to the abnormal level, realizing the rational allocation and efficient use of law enforcement resources. At the same time, it also provides strong data support for subsequent environmental governance and supervision.

[0069] Systematic and integrated: The environmental law enforcement evidence collection system based on augmented reality technology proposed in the present invention organically integrates multiple links such as data collection, data processing, data correction, anomaly detection, anomaly classification and AR display, forming a systematic and integrated solution, which greatly improves the overall efficiency and intelligence level of environmental law enforcement.

[0070] In summary, the present invention effectively solves the problems of slow response, inaccurate data, and opaque law enforcement in traditional environmental law enforcement by introducing innovative means such as real-time data collection, multi-dimensional data correction, augmented reality technology assistance, and abnormal level classification, providing a more efficient, accurate, convenient, and transparent solution for environmental law enforcement. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0072] Figure 1 Flowchart of the method for environmental law enforcement evidence collection based on augmented reality technology. DETAILED DESCRIPTION

[0073] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, in the absence of conflict, the embodiments of the present invention and the features described in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0074] See also Figure 1 This embodiment provides a method for collecting evidence for environmental law enforcement based on augmented reality technology, including:

[0075] Obtain real-time pollution data and real-time environmental data during the production process of the enterprise, and obtain panoramic video of the detection area;

[0076] Acquire standard information matching the real-time sewage discharge data in real time, compare the real-time sewage discharge data with the standard information, and obtain abnormal locations according to the comparison results;

[0077] Correcting the real-time sewage discharge data and the abnormal location according to the real-time environmental data;

[0078] According to the corrected abnormal site, an AR marker is added to the panoramic video; wherein the AR marker includes location information, timestamp, real-time sewage discharge data, real-time environmental data and abnormality level; the location information includes the corrected abnormal site coordinates, and the location information also includes the relative position of the corrected abnormal site coordinates and the enterprise facilities;

[0079] According to the timestamp, a video segment containing the abnormal occurrence is captured from the panoramic video as environmental law enforcement evidence.

[0080] It is understandable that in today's era of increasing attention to environmental protection, environmental law enforcement has become an important means to ensure corporate compliance with emissions and maintain ecological balance. In order to further improve the efficiency and accuracy of environmental law enforcement, this embodiment innovatively proposes an environmental law enforcement evidence collection method based on augmented reality technology.

[0081] 1. Comprehensive data collection to ensure that no information is missed

[0082] First, the method uses advanced sensor networks and Internet of Things technologies to fully collect real-time pollution data and environmental data during the production process of enterprises. At the same time, it uses high-definition cameras and panoramic shooting technology to obtain panoramic videos of the detection area, providing rich and intuitive image data for subsequent law enforcement and evidence collection.

[0083] 2. Intelligent comparison and analysis to accurately locate abnormalities

[0084] Based on data collection, this method uses big data analysis and artificial intelligence algorithms to obtain national or local standard information that matches real-time pollution data in real time. By accurately comparing these real-time pollution data with standard information, the system can quickly identify abnormal sites that exceed the standard range. This process not only improves the timeliness of law enforcement, but also ensures the accuracy and objectivity of abnormal identification.

[0085] 3. Correction of environmental data to improve judgment accuracy

[0086] It is worth noting that changes in environmental factors such as wind direction and humidity may affect the interpretation of pollution data. Therefore, based on comparative analysis, this method further introduces real-time environmental data to correct real-time pollution data and abnormal sites. This correction mechanism that comprehensively considers environmental factors effectively reduces the risk of misjudgment and missed judgment, and improves the scientificity and accuracy of law enforcement judgment.

[0087] 4. AR Marking Assistance, Intuitive Presentation of Evidence

[0088] In order to more intuitively display the results of law enforcement evidence collection, this method innovatively introduces augmented reality technology. The AR markers added to the panoramic video not only contain location information, timestamps, real-time pollution data, real-time environmental data and abnormality levels, but also enable law enforcement officers and regulators to intuitively see the specific location and extent of pollution through augmented reality devices or applications. These AR markers can be dynamic and displayed at the corresponding position as the panoramic video is played, making abnormal situations clear at a glance.

[0089] 5. Secure video evidence to ensure fair law enforcement

[0090] After the abnormal location is determined, the system will extract the video segment containing the abnormality from the panoramic video according to the timestamp. These video segments can be stored and backed up as direct evidence for environmental law enforcement, ensuring that they can be traced back and verified at any time. The fixation of video evidence not only enhances the transparency of law enforcement, but also ensures the fairness of the law enforcement process, providing strong support for possible legal proceedings.

[0091] 6. Multi-dimensional data integration to support decision-making

[0092] By integrating real-time pollution data, real-time environmental data, panoramic videos, and AR tags, this method provides a multi-dimensional data analysis platform for environmental regulators. Regulators can use this data to conduct in-depth analysis, assess the environmental impact of enterprises, and formulate more scientific and reasonable environmental policies and regulatory measures. At the same time, this data can also be used for public education and environmental awareness, helping the public better understand the importance of environmental protection.

[0093] To sum up, the environmental law enforcement evidence collection method based on augmented reality technology proposed in this embodiment not only improves the efficiency and accuracy of environmental law enforcement, but also enhances the transparency and fairness of law enforcement through technical means, providing strong technical support for environmental protection work.

[0094] In some embodiments of the present application, obtaining standard information matching the real-time sewage discharge data in real time includes:

[0095] Establishing a standard database, which includes enterprise production scale information and its corresponding emission standards;

[0096] Evaluate and obtain the production scale information of the enterprise based on its production capacity, product output, and raw material consumption;

[0097] According to the production scale information of the enterprise, a matching emission standard is selected from the standard database;

[0098] Standard information matching the real-time pollution emission data is obtained from the emission standards.

[0099] It is understandable that obtaining standard information that accurately matches real-time pollution data is a complex and delicate process. The core of this process is to build an efficient, comprehensive and flexible standard database system, and on this basis, through refined data analysis and intelligent matching, ensure accurate benchmarking and compliance assessment of pollution data.

[0100] First of all, the establishment of a standard database is the foundation and guarantee of the entire process. This database needs to include various pollution discharge standards formulated by the country, local governments and even the industry, including but not limited to detailed regulations for different emission sources such as wastewater, waste gas, and solid waste. In order to ensure the timeliness and accuracy of the database, it is also necessary to regularly update the latest environmental protection policies, regulations and standard changes to ensure that enterprises have a basis and rules to rely on when facing environmental protection supervision.

[0101] Next, based on the company's production capacity, product output, and raw material consumption, we can comprehensively evaluate the company's actual production scale information. This process is like "tailoring" for the company. Through detailed data analysis and comparison, it can not only accurately depict the company's production profile, but also provide a solid basis for subsequent emission standard screening. For example, a large chemical plant and a small textile plant must have significant differences in production scale, raw material use, and pollution characteristics. Therefore, when matching emission standards, these differences must be fully considered to achieve accurate positioning.

[0102] Based on the production scale information of the enterprise, the system will automatically select the emission standards that match it from the standard database. This process makes full use of the advantages of modern information technology, and through algorithm optimization and intelligent matching technology, it realizes the rapid processing and precise positioning of massive data. It is worth noting that the "matching" here is not a simple "one-to-one" relationship, but a comprehensive evaluation and comparison of various indicators in the emission standards (such as emission concentration, emission volume, etc.) based on the specific situation of the enterprise.

[0103] Finally, from the selected emission standards, the system can quickly obtain standard information that matches the real-time pollution data. This information not only provides companies with clear compliance guidelines, but also provides a reference for companies to optimize production processes and reduce pollutant emissions.

[0104] In some embodiments of the present application, when screening matching emission standards from the standard database according to the production scale information of the enterprise, it includes:

[0105] Determine the industry category to which the enterprise belongs based on its main business;

[0106] Obtain the production characteristics and pollution discharge characteristics of the enterprise according to the industry category to which the enterprise belongs;

[0107] Obtain the key emissions of the enterprise based on the production characteristics and emission characteristics of the enterprise;

[0108] Matching emission standards are screened from the standard database according to the key emissions.

[0109] It is understandable that the present embodiment further refines and optimizes the process of screening emission standards that match the production scale of the enterprise. First, the system will accurately determine the industry category of the enterprise based on the main business information submitted by the enterprise. This step is crucial because the production processes, raw materials used, and waste generated by different industries are different, so their corresponding environmental protection standards and emission standards are bound to be different.

[0110] Next, the system will analyze the production characteristics and pollution emission characteristics of the industry according to the determined enterprise industry category. This step aims to fully understand the various pollutants and their emission characteristics that may be generated by the enterprise in its daily operations, and provide a solid basis for the subsequent emission standard screening.

[0111] Subsequently, the system will further identify and determine the key emissions of the enterprise based on the production characteristics and emission characteristics of the enterprise. Key emissions refer to pollutants that are produced in large quantities, are highly harmful, or require special attention during the production process. Identifying these key emissions will help the system to more accurately select matching emission standards from the standard database.

[0112] Finally, the system will accurately search and match the key emissions identified in the standard database to find the emission standard that best matches the actual situation of the enterprise. This step not only ensures the scientificity and rationality of the emission standards, but also provides strong support for subsequent environmental supervision and law enforcement.

[0113] In some embodiments of the present application, the real-time sewage discharge data and the standard information are compared, and when the abnormal site is obtained according to the comparison result, it includes:

[0114] Acquire a number of real-time sewage collection data at a number of collection points, and after eliminating obvious error values ​​and abnormal values, obtain a number of real-time sewage data;

[0115] Each of the real-time pollution discharge data is compared with the standard information. When the comparison result shows that the real-time pollution discharge data exceeds the specified range of the standard information, the pollution discharge point corresponding to the real-time pollution discharge data exceeding the range is marked as an abnormal site.

[0116] It is understandable that in order to effectively monitor and identify abnormal sites in the sewage system, this embodiment adopts a series of refined data processing and comparison processes. First, through multiple collection points distributed in key links of the sewage system, a series of sewage collection data are captured and collected in real time. These data directly reflect the current operating status and sewage discharge situation of the sewage system.

[0117] Next, in order to ensure the accuracy and reliability of subsequent analysis, we will conduct preliminary screening and cleaning of these raw data. Specifically, we will use statistical analysis and data verification techniques to identify and eliminate those erroneous values ​​and outliers that are obviously deviated from the normal range. This process effectively reduces the interference of noise data and lays a solid foundation for subsequent data comparison.

[0118] We then compare the cleaned real-time pollution data with the preset standard information one by one. These standard information are usually formulated based on environmental protection laws and regulations, industry standards and the company's own pollution control requirements, and clearly define the allowable range of various pollution indicators. During the comparison process, the system will automatically determine whether each real-time pollution data exceeds the range specified by the standard information.

[0119] Once it is found that the real-time sewage discharge data exceeds the standard range, the system will immediately trigger the abnormality identification mechanism. Specifically, the sewage discharge point corresponding to the real-time sewage discharge data that exceeds the range will be marked as an abnormal point. This mark not only clarifies the specific location where the abnormality occurs, but also provides clear guidance for subsequent troubleshooting, rectification and optimization.

[0120] In summary, this embodiment achieves effective identification and marking of abnormal sites in the sewage system through the above series of refined data processing and comparison processes.

[0121] In some embodiments of the present application, the real-time sewage discharge data includes at least any one of sewage outlet flow information, nanoparticle information, greenhouse gas emission information, heavy metal emission information and volatile organic compound information.

[0122] It is understandable that the real-time pollution data in this embodiment covers multiple key environmental indicators, aiming to comprehensively and accurately reflect the pollution status of the enterprise. These data include but are not limited to the flow information of the sewage outlet, which directly reflects the emission rate and total amount of pollutants and is an important indicator for evaluating the efficiency of pollution discharge; nanoparticle information, in view of the potential harm that nanoparticles may cause to human health and the environment, its monitoring is crucial to protecting the ecological environment and public health; greenhouse gas emission information, with the increasingly severe global climate change, greenhouse gas emission monitoring has become the focus of international attention and is of great significance to achieving the goal of carbon neutrality; heavy metal emission information, heavy metal pollution poses a long-term threat to the ecological environment and human health due to its difficulty in degradation and bioaccumulation, so real-time monitoring of its emissions is indispensable; and volatile organic compound information, this type of compound is one of the important sources of air pollution and has a significant impact on air quality and public health. In summary, the wide coverage of real-time pollution data ensures the comprehensiveness and effectiveness of environmental supervision.

[0123] In some embodiments of the present application, when the real-time sewage discharge data and the abnormal location are corrected according to the real-time environmental data, it includes:

[0124] The discharge information of the sewage outlet is corrected according to wind speed, wind direction and air pressure. The correction calculation formula is:

[0125]

[0126] Among them, Fc represents the corrected flow information of the sewage outlet, Fm represents the measured flow information of the sewage outlet, Pr represents the reference air pressure, Pc represents the current air pressure, Wc represents the current wind speed, and α represents the influence coefficient of wind speed on flow;

[0127] The nanoparticle information is corrected according to humidity and temperature, and the correction formula is:

[0128] Cc=Cm·(1-βHc)·(1+γTc);

[0129] Wherein, Cc represents the corrected nanoparticle information, Cm represents the measured nanoparticle information, Hc represents the current humidity, β represents the humidity influence coefficient, Tc represents the current temperature, and γ represents the temperature influence coefficient;

[0130] The greenhouse gas emission information is corrected according to atmospheric stability and air pressure. The correction formula is:

[0131]

[0132] Among them, Gc represents the corrected greenhouse gas emission information, Gm represents the measured greenhouse gas emission information, and Sc represents the current atmospheric stability parameter;

[0133] The heavy metal emission information is corrected according to precipitation and wind speed. The correction formula is:

[0134] Mc=Mm·(1+δ·Rc)·(1+ε·Wc);

[0135] Among them, Mc represents the corrected heavy metal emission information, Mm represents the measured heavy metal emission information, Rc represents the current precipitation, δ represents the precipitation influence coefficient, and ∈ represents the wind speed influence coefficient;

[0136] Volatile organic compounds are corrected according to temperature and humidity. The correction formula is:

[0137] Vc=Vm·(1+κ·Tc)·(1-λ·Hc);

[0138] Wherein, Vc represents the corrected volatile organic compounds, Vm represents the measured volatile organic compounds, κ represents the temperature influence coefficient, and λ represents the humidity influence coefficient.

[0139] In some embodiments of the present application, when the real-time sewage discharge data and the abnormal location are corrected according to the real-time environmental data, it also includes:

[0140] Establish xyz stereo coordinates in the panoramic video of the detection area. Let the coordinates of the detection point be (xo, yo, zo), which represents the three-dimensional position in space. xo and yo represent the longitude and latitude of the detection point respectively, and zo represents the height of the detection point from the ground.

[0141] Δx=Wc·t·cos(θc);

[0142] Δy=Wc·t·sin(θc);

[0143] Δz = μ·(Tc-Tf);

[0144] Wherein, Δx represents the horizontal displacement in the x direction, Δy represents the horizontal displacement in the y direction, Δz represents the vertical displacement; Tf represents the standard reference temperature;

[0145] Combine the original coordinates with the correction value to obtain the corrected abnormal site coordinates:

[0146] xc=xo+Δx;

[0147] yc=yo+Δy;

[0148] zc=zo+Δz;

[0149] The corrected coordinates of the abnormal site are (xc, yc, zc).

[0150] In some embodiments of the present application, according to the timestamp, when a video segment containing an abnormality is intercepted from the panoramic video as environmental law enforcement evidence, it includes:

[0151] When it is detected that any data in the real-time pollution discharge data exceeds the corresponding emission standard, the timestamp of the abnormality is recorded at the beginning of video capture, and the recording is continued until the abnormal data returns to the standard range, forming a complete video segment of the abnormality occurrence process;

[0152] If the abnormal data does not return to the standard range within the preset time, the video capture records the timestamp of the abnormality, and continues to record until manual intervention or the preset maximum recording time is reached, forming a complete video segment of the abnormality process;

[0153] The complete video segment of the abnormal occurrence process is associated with the corresponding real-time pollution discharge data and the corrected coordinates of the abnormal site, and the associated video segment of the abnormal occurrence process is used as evidence for environmental law enforcement.

[0154] It is understandable that through the multi-dimensional data fusion method of this embodiment, environmental law enforcement departments can obtain more comprehensive and accurate evidence to support their decision-making. For example, when an illegal discharge incident occurs, there is not only video evidence recording the occurrence and duration of the illegal behavior, but also real-time pollution data and abnormal site coordinates to provide specific pollution conditions and location information. The combination of these data enables law enforcement departments to quickly locate the source of the problem, take appropriate measures, and provide strong evidence support for subsequent legal proceedings. In addition, the application of this technology can also improve the transparency of environmental supervision and enhance the public's trust in the fairness of environmental law enforcement.

[0155] In some embodiments of the present application, the method for dividing the abnormality level includes:

[0156] According to the following calculation formula, the degree of exceeding the standard is calculated for each real-time pollution discharge data of the abnormal location:

[0157]

[0158] When the degree of exceeding the standard is less than 10%, the abnormality level is determined to be a slight abnormality;

[0159] When 10%≤exceeding degree<30%, the abnormality level is determined to be moderate abnormality;

[0160] When 30%≤exceeding degree<50%, the abnormality level is determined to be a serious abnormality;

[0161] When 50% ≤ the exceeding degree, the abnormality level is determined to be an extremely serious abnormality.

[0162] It can be understood that the abnormality classification method of this embodiment accurately calculates the degree of excess of the real-time sewage discharge data of the abnormal site, and divides the abnormality level into four levels: slight abnormality, moderate abnormality, severe abnormality and extremely severe abnormality. This method has the following beneficial effects:

[0163] Accurately locate the degree of abnormality: Through quantitative calculation of the degree of exceeding the standard, the abnormal degree of pollution discharge data can be accurately reflected, avoiding the ambiguity of subjective judgment.

[0164] Scientific classification of levels: According to the different ranges of the degree of exceeding the standard, four abnormal levels are scientifically and reasonably divided, which is helpful to carry out targeted treatment of abnormal situations of different degrees.

[0165] Improve supervision efficiency: Through clear classification of abnormal levels, regulatory authorities can quickly identify abnormal situations that require special attention, thereby optimizing the allocation of regulatory resources and improving supervision efficiency.

[0166] Promoting environmental compliance: This method helps companies to promptly detect and correct excessive pollution discharge, promote environmental compliance and reduce environmental pollution risks.

[0167] Support decision-making: Provides a scientific basis for decision-making and helps to formulate more reasonable and effective environmental protection policies and measures.

[0168] The present invention also proposes a system for collecting evidence for environmental law enforcement based on augmented reality technology, which is used to implement the above-mentioned method for collecting evidence for environmental law enforcement based on augmented reality technology.

[0169] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0170] The present application is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0171] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0172] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0173] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for collecting evidence for environmental law enforcement based on augmented reality technology, characterized in that: include: Obtain real-time pollution data and real-time environmental data during the production process of the enterprise, and obtain panoramic video of the detection area; Acquire standard information matching the real-time sewage discharge data in real time, compare the real-time sewage discharge data with the standard information, and obtain abnormal locations according to the comparison results; Correcting the real-time sewage discharge data and the abnormal location according to the real-time environmental data; According to the corrected abnormal site, an AR marker is added to the panoramic video; wherein the AR marker includes location information, timestamp, real-time sewage discharge data, real-time environmental data and abnormality level; the location information includes the corrected abnormal site coordinates, and the location information also includes the relative position of the corrected abnormal site coordinates and the enterprise facilities; According to the timestamp, a video segment containing the abnormal occurrence is captured from the panoramic video as environmental law enforcement evidence.

2. The method for collecting evidence for environmental law enforcement based on augmented reality technology according to claim 1 is characterized in that: When obtaining standard information matching the real-time sewage discharge data in real time, it includes: Establishing a standard database, which includes enterprise production scale information and its corresponding emission standards; Evaluate and obtain the production scale information of the enterprise based on its production capacity, product output, and raw material consumption; According to the production scale information of the enterprise, a matching emission standard is selected from the standard database; Standard information matching the real-time pollution emission data is obtained from the emission standards.

3. The method for collecting evidence for environmental law enforcement based on augmented reality technology according to claim 2 is characterized in that: When screening matching emission standards from the standard database based on the production scale information of the enterprise, it includes: Determine the industry category to which the enterprise belongs based on its main business; Obtain the production characteristics and pollution discharge characteristics of the enterprise according to the industry category to which the enterprise belongs; Obtain the key emissions of the enterprise based on the production characteristics and emission characteristics of the enterprise; Matching emission standards are screened from the standard database according to the key emissions.

4. The method for collecting evidence for environmental law enforcement based on augmented reality technology according to claim 1 is characterized in that: When comparing the real-time sewage discharge data with the standard information and obtaining abnormal sites according to the comparison results, the method includes: Acquire a number of real-time sewage collection data at a number of collection points, and after eliminating obvious error values ​​and abnormal values, obtain a number of real-time sewage data; Each of the real-time pollution discharge data is compared with the standard information. When the comparison result shows that the real-time pollution discharge data exceeds the specified range of the standard information, the pollution discharge point corresponding to the real-time pollution discharge data exceeding the range is marked as an abnormal site.

5. The method for collecting evidence for environmental law enforcement based on augmented reality technology according to claim 4 is characterized in that: The real-time sewage discharge data includes at least any one of sewage outlet flow information, nanoparticle information, greenhouse gas emission information, heavy metal emission information and volatile organic compound information.

6. The method for collecting evidence for environmental law enforcement based on augmented reality technology according to claim 5 is characterized in that: When the real-time pollution discharge data and the abnormal location are corrected according to the real-time environmental data, it includes: The discharge information of the sewage outlet is corrected according to wind speed, wind direction and air pressure. The correction calculation formula is: Wherein, Fc represents the corrected flow rate information of the sewage outlet, Fm represents the measured flow rate information of the sewage outlet, Pr represents the reference air pressure, Pc represents the current air pressure, Wc represents the current wind speed, and α represents the influence coefficient of wind speed on flow rate; The nanoparticle information is corrected according to humidity and temperature, and the correction formula is: Cc=Cm·(1-βHc)·(1+γTc); Wherein, Cc represents the corrected nanoparticle information, Cm represents the measured nanoparticle information, Hc represents the current humidity, β represents the humidity influence coefficient, Tc represents the current temperature, and γ represents the temperature influence coefficient; The greenhouse gas emission information is corrected according to atmospheric stability and air pressure. The correction formula is: Among them, Gc represents the corrected greenhouse gas emission information, Gm represents the measured greenhouse gas emission information, and Sc represents the current atmospheric stability parameter; The heavy metal emission information is corrected according to precipitation and wind speed. The correction formula is: Mc=Mm·(1+δ·Rc)·(1+ε·Wc); Among them, Mc represents the corrected heavy metal emission information, Mm represents the measured heavy metal emission information, Rc represents the current precipitation, δ represents the precipitation influence coefficient, and ∈ represents the wind speed influence coefficient; Volatile organic compounds are corrected according to temperature and humidity. The correction formula is: Vc=Vm·(1+κ·Tc)·(1-λ·Hc); Wherein, Vc represents the corrected volatile organic compounds, Vm represents the measured volatile organic compounds, κ represents the temperature influence coefficient, and λ represents the humidity influence coefficient.

7. The method for collecting evidence for environmental law enforcement based on augmented reality technology according to claim 6 is characterized in that: When the real-time pollution discharge data and the abnormal location are corrected according to the real-time environmental data, it also includes: Establish xyz stereo coordinates in the panoramic video of the detection area. Let the coordinates of the detection point be (xo, yo, zo), which represents the three-dimensional position in space. xo and yo represent the longitude and latitude of the detection point respectively, and zo represents the height of the detection point from the ground. Δx=Wc·t·cos(θc); Δy=Wc·t·sin(θc); Δz = μ·(Tc-Tf); Wherein, Δx represents the horizontal displacement in the x direction, Δy represents the horizontal displacement in the y direction, Δz represents the vertical displacement; Tf represents the standard reference temperature; Combine the original coordinates with the correction value to obtain the corrected abnormal site coordinates: xc=xo+Δx; yc=yo+Δy; zc=zo+Δz; The corrected coordinates of the abnormal site are (xc, yc, zc).

8. The method for collecting evidence for environmental law enforcement based on augmented reality technology according to claim 7 is characterized in that: According to the timestamp, when the video segment containing the abnormality is intercepted from the panoramic video as environmental law enforcement evidence, it includes: When it is detected that any data in the real-time pollution discharge data exceeds the corresponding emission standard, the timestamp of the abnormality is recorded at the beginning of video capture, and the recording is continued until the abnormal data returns to the standard range, forming a complete video segment of the abnormality occurrence process; If the abnormal data does not return to the standard range within the preset time, the video capture records the timestamp of the abnormality, and continues to record until manual intervention or the preset maximum recording time is reached, forming a complete video segment of the abnormality process; The complete video segment of the abnormal occurrence process is associated with the corresponding real-time pollution discharge data and the corrected coordinates of the abnormal site, and the associated video segment of the abnormal occurrence process is used as evidence for environmental law enforcement.

9. The method for collecting evidence for environmental law enforcement based on augmented reality technology according to claim 1, characterized in that: The method for dividing the abnormality level includes: According to the following calculation formula, the degree of exceeding the standard is calculated for each real-time pollution discharge data of the abnormal location: When the degree of exceeding the standard is less than 10%, the abnormality level is determined to be a slight abnormality; When 10%≤exceeding degree<30%, the abnormality level is determined to be moderate abnormality; When 30%≤exceeding degree<50%, the abnormality level is determined to be a serious abnormality; When 50% ≤ the exceeding degree, the abnormality level is determined to be an extremely serious abnormality.

10. A system for environmental law enforcement evidence collection based on augmented reality technology, characterized in that: A method for environmental law enforcement evidence collection based on augmented reality technology for implementing any one of claims 1-9.

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