A regional environmental monitoring system based on big data

Abstract

The present invention relates to the field of regional environmental monitoring technology, and in particular to a regional environmental monitoring system based on big data, comprising an information acquisition module, which is used to collect vegetation information and vehicle information in a monitoring area, an information storage module, which is used to store vegetation information and vehicle information within a monitoring period, an information analysis module, which is used to analyze environmental parameters according to vegetation information and vehicle information and generate analysis results, and an information output module, which is used to collect the analysis results of the information analysis module and output the analysis results to a public query module. By this, the present invention can monitor the data in the monitoring area within the monitoring period at any time, assist the backstage management personnel to monitor the monitoring area in real time, so that the backstage management personnel can adjust the monitoring area in time, and can synchronize the environmental conditions of the monitoring area within the monitoring period to the public query module, so as to facilitate the query of ordinary users.

Description

Technical Field

[0001] The present invention relates to the technical field of regional environment monitoring, and in particular to a regional environment monitoring system based on big data. Background Art

[0002] Regional environmental monitoring refers to the technology of real-time monitoring and analysis of environmental parameters in a specific area, involving data collection and transmission technology, big data analysis and processing technology, etc. It can measure environmental parameters in real time and realize trend analysis and prediction of the regional environment. With the increase in the number of vehicles, the exhaust gas and dust emitted by vehicles are constantly affecting the air quality of the environment. Although the vegetation in the regional environment can purify some exhaust gas and dust, the purification capacity of vegetation is limited. Some areas with small vegetation coverage and large traffic volume still need artificial management to improve the air quality in the area.

[0003] At present, most regional environmental monitoring adopts the method of collecting information manually, which not only wastes manpower, but also fails to monitor the situation in the monitoring area in real time. The collected information is usually diverse, and not only cannot provide intuitive prompts to back-end management personnel, which easily leads to untimely governance, but also cannot be queried by ordinary users, and cannot provide convenience for ordinary users' travel.

[0004] How to monitor the data in the monitoring area during the monitoring period at any time, assist the back-end management personnel to monitor the monitoring area in real time, so that the back-end management personnel can adjust the monitoring area in time, and synchronize the environmental conditions of the monitoring area during the monitoring period to the public query module for the convenience of ordinary users to query, has become a technical problem that needs to be broken through.

[0005] In summary, the prior art obviously has inconveniences and defects in practical use, so it is necessary to improve it. Summary of the invention

[0006] In view of the above-mentioned defects, the purpose of the present invention is to provide a regional environmental monitoring system based on big data, which can monitor the data in the monitoring area within the monitoring period at any time, assist the back-end management personnel to monitor the monitoring area in real time, so that the back-end management personnel can adjust the monitoring area in time, and can synchronize the environmental conditions of the monitoring area within the monitoring period to the public query module for the convenience of ordinary users to query.

[0007] In order to achieve the above object, the present invention provides a regional environment monitoring system based on big data, comprising:

[0008] The information collection module is used to collect vegetation information and vehicle information in the monitoring area.

[0009] The information storage module is connected to the information collection module and is used to store vegetation information and vehicle information within the monitoring period.

[0010] The information analysis module is connected to the information storage module and is used to analyze environmental parameters according to vegetation information and vehicle information and generate analysis results.

[0011] The information output module is connected to the information analysis module and is used to collect the analysis results of the information analysis module and output the analysis results to the public query module.

[0012] According to the regional environment monitoring system based on big data of the present invention, the information collection module includes a drone module for collecting existing vegetation information in the monitoring area and a real-time monitoring module for collecting road vehicle information in the monitoring area. The information collected by the drone module includes the vegetation coverage Fvc and the high-class vegetation coverage Tfvc in the monitoring area. The information collected by the real-time monitoring module includes the traffic volume Trav and the average vehicle residence time Adwellt during the road monitoring period in the monitoring area. The information collection module transmits the collected information to the information storage module.

[0013] According to the regional environmental monitoring system based on big data of the present invention, the vegetation coverage Fvc is the ratio of the area occupied by all vegetation in the monitoring area to the area of ​​non-vegetation area, and the tall vegetation coverage Tfvc is the ratio of the area occupied by tall plants in the monitoring area to the area occupied by all vegetation, and the tall plants are plants with a height of more than 2 meters.

[0014] According to the regional environment monitoring system based on big data of the present invention, the information output module includes a background management module and a public query module. The background management personnel input the standard vegetation coverage sFvc, the standard high-class vegetation coverage sTfvc, the standard vehicle flow sTrav and the standard average vehicle stay time sAdwellt through the background management module. The information analysis module compares the information collected in real time by the information collection module with the standard information input by the background management personnel, and divides the monitoring area of ​​the monitoring period into four levels: high-quality area, good area, medium area and ordinary area.

[0015] According to the regional environment monitoring system based on big data of the present invention, the information analysis module analyzes the data collected by the information collection module, including the following steps:

[0016] S1: The information analysis module compares the vegetation coverage Fvc of multiple monitoring areas in the same monitoring period with the standard vegetation coverage sFvc, and divides the corresponding monitoring areas into good areas and medium areas.

[0017] S2: The information analysis module compares the product of the traffic volume Trav and the average vehicle dwelling time Adwellt divided into the good area and the medium area in step S1 with the product of the standard traffic volume sTrav and the standard average vehicle dwelling time sAdwellt, and divides the areas in the good area that do not meet the standards into the medium area, and divides the areas in the medium area that do not meet the standards into the ordinary area.

[0018] S3: The information analysis module compares the high-class vegetation coverage Tfvc classified as a good area in step S2 with the standard high-class vegetation coverage sTfvc, and classifies the area that meets the standard into a high-quality area.

[0019] S4: The information analysis module feeds back the results of the division to the public query module, and the public query module publicizes the results to facilitate the query by ordinary users who log in to the platform.

[0020] According to the regional environment monitoring system based on big data of the present invention, in S1, when the good area and the medium area are divided for the first time:

[0021] When Fvc of the monitoring area ≥ sFvc, the monitoring area of ​​the monitoring period is classified into the good area.

[0022] When Fvc of the monitoring area is less than sFvc, the monitoring area of ​​the monitoring period is divided into the medium area.

[0023] According to the regional environment monitoring system based on big data of the present invention, in said S2, when the good area and the medium area are divided again:

[0024] When Trav×Adwellt in the good area ≤ sTrav×sAdwellt, the monitoring area in the monitoring period remains in the good area.

[0025] When Trav×Adwellt in the good area>sTrav×sAdwellt, the monitoring area in the monitoring period is divided into the medium area.

[0026] When Trav×Adwellt in the medium area ≤ sTrav×sAdwellt, the monitoring area in the monitoring period remains in the medium area.

[0027] When Trav×Adwellt in the medium area>sTrav×sAdwellt, the monitoring area in this monitoring period is divided into the ordinary area.

[0028] According to the regional environment monitoring system based on big data of the present invention, in S3, when the good area is divided again:

[0029] When Tfvc of the good area>sTfvc, the monitoring area of ​​the monitoring period is divided into the high-quality area.

[0030] When Tfvc ≤ sTfvc in the good region, the monitoring region of the monitoring period remains in the good region.

[0031] According to the regional environment monitoring system based on big data of the present invention, if the product of the vehicle flow Trav and the average vehicle residence time Adwellt in the ordinary area is more than 1.5 times the product of the standard vehicle flow sTrav and the standard average vehicle residence time sAdwellt or the ordinary area is a densely populated area, the back-end management personnel will make manual corrections in the area to improve the air quality in the monitored area.

[0032] The purpose of the present invention is to provide a regional environmental monitoring system based on big data, including an information collection module, an information analysis module and an information output module, which can monitor the data in the monitoring area within the monitoring period at any time, assist the background management personnel to monitor the monitoring area in real time, so that the background management personnel can adjust the monitoring area in time; the information analysis module is connected to the public query module of the information output module, and the environmental conditions of the monitoring area within the monitoring period can be synchronized to the public query module, which is convenient for ordinary users to query. In summary, the beneficial effects of the present invention are: it can monitor the data in the monitoring area within the monitoring period at any time, assist the background management personnel to monitor the monitoring area in real time, so that the background management personnel can adjust the monitoring area in time, and the environmental conditions of the monitoring area within the monitoring period can be synchronized to the public query module, which is convenient for ordinary users to query. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 is a flow chart of the present invention; DETAILED DESCRIPTION

[0034] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0035] In the description of the present invention, it should be noted that the terms "upper", "lower", "inside", "outside", "top / bottom" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention.

[0036] In the description of the present invention, it should be noted that, unless otherwise clearly stipulated and limited, the terms "installed", "provided with", "mounted / connected", "connected", etc. should be understood in a broad sense. For example, "connected" can be a fixed connection, a detachable connection, or an integral connection. It can be a mechanical connection or an electrical connection. It can be a direct connection or an indirect connection through an intermediate medium. It can be the internal connection of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0037] See also Figure 1 The present invention provides a regional environment monitoring system based on big data, including an information collection module, which is used to collect vegetation information and vehicle information in the monitoring area; an information storage module, which is connected to the information collection module, and is used to store the vegetation information and vehicle information within the monitoring period; an information analysis module, which is connected to the information storage module, and is used to analyze environmental parameters according to the vegetation information and vehicle information, and generate analysis results; an information output module, which is connected to the information analysis module, and is used to collect the analysis results of the information analysis module, and output the analysis results to the public query module.

[0038] The information collection module includes a drone module for collecting existing vegetation information in the monitoring area and a real-time monitoring module for collecting road vehicle information in the monitoring area. The information collected by the drone module includes the vegetation coverage Fvc and the high-class vegetation coverage Tfvc in the monitoring area. The vegetation coverage Fvc is the ratio of the area occupied by all vegetation in the monitoring area to the area of ​​non-vegetated areas (including living areas and traffic areas). The high-class vegetation coverage Tfvc is the ratio of the area occupied by high-class plants in the monitoring area to the area occupied by all vegetation. High-class plants are plants with a height of more than 2 meters (usually Including trees, shrubs, and ground cover plants. In order to ensure that the sight of pedestrians and vehicles is not obstructed and avoid safety hazards, the height of shrubs is usually controlled below 1.5 meters. Trees are generally better than shrubs in air purification ability. Trees have a stronger absorption capacity for harmful gases and dust in the air. The information collected by the real-time monitoring module includes the traffic volume Trav and the average vehicle dwelling time Adwellt during the road monitoring period in the monitoring area (the average vehicle dwelling time Adwellt is the average time spent by each vehicle passing through the monitoring area during the monitoring period). The information collection module transmits the collected information to the information storage module.

[0039] Specifically, the real-time monitoring module is a high-definition camera and a speed measurement camera installed on street lamps on both sides of the road in the monitoring area.

[0040] The information output module includes a background management module and a public query module. The background management personnel input the standard vegetation coverage sFvc, the standard high-class vegetation coverage sTfvc, the standard traffic volume sTrav and the standard average vehicle stay time sAdwellt through the background management module. The information analysis module compares the information collected in real time by the information collection module with the standard information input by the background management personnel, and divides the monitoring area of ​​the monitoring period into four levels: high-quality area, good area, medium area and ordinary area.

[0041] The information analysis module analyzes the data collected by the information collection module, including the following steps:

[0042] S1: The information analysis module compares the vegetation coverage Fvc of multiple monitoring areas in the same monitoring period with the standard vegetation coverage sFvc, and divides the corresponding monitoring areas into good areas and medium areas.

[0043] S2: The information analysis module compares the product of the traffic volume Trav and the average vehicle dwelling time Adwellt divided into the good area and the medium area in step S1 with the product of the standard traffic volume sTrav and the standard average vehicle dwelling time sAdwellt, and divides the areas in the good area that do not meet the standards into the medium area, and divides the areas in the medium area that do not meet the standards into the ordinary area.

[0044] S3: The information analysis module compares the high-class vegetation coverage Tfvc classified as a good area in step S2 with the standard high-class vegetation coverage sTfvc, and classifies the areas that meet the standards into high-quality areas.

[0045] S4: The information analysis module feeds back the results of the division to the public query module, and the public query module publicizes the results to facilitate the query by ordinary users who log in to the platform.

[0046] Specifically, in step S1 of the present invention, when the good area and the medium area are divided for the first time:

[0047] When Fvc of the monitoring area ≥ sFvc, the monitoring area of ​​the monitoring period is classified into the good area.

[0048] When Fvc of the monitoring area is less than sFvc, the monitoring area of ​​the monitoring period is divided into the medium area.

[0049] Specifically, in step S2 of the present invention, when the good area and the medium area are divided again, the product of the vehicle flow Trav and the average vehicle residence time Adwellt in the area is compared with the product of the standard vehicle flow sTrav and the standard average vehicle residence time sAdwellt:

[0050] When Trav×Adwellt in the good area ≤ sTrav×sAdwellt, the monitoring area in the monitoring period remains in the good area.

[0051] When Trav×Adwellt in the good area>sTrav×sAdwellt, the monitoring area in the monitoring period is divided into the medium area.

[0052] When Trav×Adwellt in the medium area ≤ sTrav×sAdwellt, the monitoring area in the monitoring period remains in the medium area.

[0053] When Trav×Adwellt in the medium area>sTrav×sAdwellt, the monitoring area in this monitoring period is divided into the ordinary area.

[0054] Specifically, in step S3 of the present invention, when the good area is divided again:

[0055] When Tfvc of the good area>sTfvc, the monitoring area of ​​the monitoring period is divided into the high-quality area.

[0056] When Tfvc ≤ sTfvc in the good region, the monitoring region of the monitoring period remains in the good region.

[0057] Since the vegetation coverage Fvc of the monitoring area divided into the medium area and the ordinary area is relatively small, even if Tfvc of this monitoring area is greater than sTfvc, the environmental quality of this area is still not enough to be divided into the high-quality area, so the high-class vegetation coverage Tfvc of the medium area and the ordinary area is no longer compared.

[0058] Furthermore, the public query module of the information output module is an interactive platform (such as a public account), where ordinary users and backend managers can query real-time data. If the data in the ordinary area is significantly different from the standard data (the product of the ordinary area's traffic volume Trav and the average vehicle dwelling time Adwellt is greater than 1.5 times the product of the standard traffic volume sTrav and the standard average vehicle dwelling time sAdwellt) or the ordinary area is a densely populated area (the population in the area is >100 people / km2), the real-time data can be obtained by querying the public query module of the information output module. 2 ), the backend administrator can carry out artificial interference in the area, such as adding fog cannons, artificially reducing dust, and improving the air quality of the monitored area. After ordinary users query the real-time data, they can choose the route to avoid ordinary areas with poor environmental quality.

[0059] The present invention provides a regional environmental monitoring system based on big data, including an information collection module, an information analysis module and an information output module, which can monitor the data in the monitoring area within the monitoring period at any time, assist the background management personnel to monitor the monitoring area in real time, so that the background management personnel can adjust the monitoring area in time; the information analysis module is connected to the public query module of the information output module, and the environmental conditions of the monitoring area within the monitoring period can be synchronized to the public query module, which is convenient for ordinary users to query. In summary, the beneficial effects of the present invention are: it can monitor the data in the monitoring area within the monitoring period at any time, assist the background management personnel to monitor the monitoring area in real time, so that the background management personnel can adjust the monitoring area in time, and the environmental conditions of the monitoring area within the monitoring period can be synchronized to the public query module, which is convenient for ordinary users to query.

[0060] Of course, the present invention may have many other embodiments. Without departing from the spirit and essence of the present invention, those skilled in the art may make various corresponding changes and modifications based on the present invention, but these corresponding changes and modifications should all fall within the scope of protection of the claims attached to the present invention.

Claims

1. A regional environmental monitoring system based on big data, characterized in that: include: An information collection module, which is used to collect vegetation information and vehicle information in the monitoring area; An information storage module, connected to the information collection module, for storing vegetation information and vehicle information within a monitoring period; An information analysis module, connected to the information storage module, for analyzing environmental parameters according to vegetation information and vehicle information, and generating analysis results; An information output module, which is connected to the information analysis module and is used to collect the analysis results of the information analysis module and output the analysis results to the public query module; The information collection module includes a drone module for collecting existing vegetation information in the monitoring area and a real-time monitoring module for collecting road vehicle information in the monitoring area. The information collected by the drone module includes the vegetation coverage Fvc and the high-class vegetation coverage Tfvc in the monitoring area. The information collected by the real-time monitoring module includes the traffic volume Trav and the average vehicle residence time Adwellt on the roads in the monitoring area during the monitoring period. The information collection module transmits the collected information to the information storage module. The vegetation coverage Fvc is the ratio of the area occupied by all vegetation in the monitoring area to the area of ​​non-vegetation area, and the high vegetation coverage Tfvc is the ratio of the area occupied by high plants to the area occupied by all vegetation in the monitoring area. The high plants are plants with a height of more than 2 meters. The information output module includes a background management module and a public query module. The background management personnel input the standard vegetation coverage sFvc, the standard high-class vegetation coverage sTfvc, the standard vehicle flow sTrav and the standard average vehicle stay time sAdwellt through the background management module. The information analysis module compares the information collected in real time by the information collection module with the standard information input by the background management personnel, and divides the monitoring area of ​​the monitoring period into four levels: high-quality area, good area, medium area and ordinary area; The information analysis module analyzes the data collected by the information collection module, including the following steps: S1: The information analysis module compares the vegetation coverage Fvc of multiple monitoring areas in the same monitoring period with the standard vegetation coverage sFvc, and divides the corresponding monitoring areas into good areas and medium areas; S2: The information analysis module compares the product of the traffic volume Trav and the average vehicle dwelling time Adwellt divided into the good area and the medium area in step S1 with the product of the standard traffic volume sTrav and the standard average vehicle dwelling time sAdwellt, and divides the areas that do not meet the standards in the good area into the medium area, and divides the areas that do not meet the standards in the medium area into the ordinary area; S3: The information analysis module compares the high-class vegetation coverage Tfvc classified as a good area in step S2 with the standard high-class vegetation coverage sTfvc, and classifies the area that meets the standard into a high-quality area; S4: The information analysis module feeds back the results of the division to the public query module, and the public query module publicizes the results to facilitate the query by ordinary users who log in to the platform.

2. The regional environment monitoring system based on big data according to claim 1 is characterized in that: In S1, when the good area and the medium area are divided for the first time: When Fvc of the monitoring area ≥ sFvc, the monitoring area of ​​the monitoring period is classified into the good area; When Fvc of the monitoring area is less than sFvc, the monitoring area of ​​the monitoring period is divided into the medium area.

3. The regional environment monitoring system based on big data according to claim 1 is characterized in that: In S2, when the good area and the medium area are divided again: When Trav×Adwellt≤sTrav×sAdwellt in the good area, the monitoring area of ​​the monitoring period remains in the good area; When Trav×Adwellt in the good area>sTrav×sAdwellt, the monitoring area in this monitoring period is divided into the medium area; When Trav×Adwellt≤sTrav×sAdwellt in the medium area, the monitoring area of ​​the monitoring period remains in the medium area; When Trav×Adwellt in the medium area>sTrav×sAdwellt, the monitoring area in this monitoring period is divided into the ordinary area.

4. The regional environment monitoring system based on big data according to claim 1 is characterized in that: In S3, when the good area is divided again: When Tfvc of the good area>sTfvc, the monitoring area of ​​the monitoring period is divided into the high-quality area; When Tfvc ≤ sTfvc in the good region, the monitoring region of the monitoring period remains in the good region.

5. The regional environment monitoring system based on big data according to claim 1 is characterized in that: If the product of the traffic volume Trav and the average vehicle dwelling time Adwellt in the ordinary area is more than 1.5 times the product of the standard traffic volume sTrav and the standard average vehicle dwelling time sAdwellt, or the ordinary area is a densely populated area, the back-end management personnel will make artificial corrections in the area to improve the air quality in the monitored area.

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