Air quality detection method based on multi-source information fusion technology

Abstract

The invention belongs to the technical field of air detection, and particularly relates to an air quality detection method based on a multi-source information fusion technology. Through multi-source information fusion, data of a plurality of monitoring channels can be integrated, errors possibly caused by a single channel are avoided, the accuracy of air quality detection is improved, air change trend analysis is utilized, air quality changes can be more sensitively captured, fluctuation of air conditions can be reflected in time, a certain prediction capability is achieved, and the method is suitable for popularization and application. According to the historical performance and reliability of each channel, the data weight is dynamically adjusted, so that the final air quality evaluation is more in line with the actual situation, various types of air monitoring data sources such as fixed stations, mobile equipment and remote sensing satellites can be flexibly accessed, the comprehensiveness and coverage range of the data are ensured, and the air quality evaluation efficiency is improved. The accuracy and timeliness of air quality monitoring can be effectively improved, and more reliable data support is provided for environmental protection and pollution abatement.

Description

Technical Field

[0001] The invention belongs to the technical field of air detection, and in particular relates to an air quality detection method based on multi-source information fusion technology. Background Art

[0002] With the acceleration of urbanization, air pollution has become one of the important environmental issues that need to be addressed worldwide, which has had a profound impact on human health, ecosystems, and social economy. Traditional air quality detection methods mainly rely on data collected from a single or a few monitoring stations. These data have limitations in terms of coverage and accuracy in time and space, making it difficult to fully and accurately reflect the regional air quality status and its changing trends.

[0003] In recent years, with the rapid development of remote sensing technology, Internet of Things technology, big data processing technology, etc., multi-source information fusion technology has shown great application potential and advantages in the field of air quality detection. Multi-source information fusion technology can significantly improve the accuracy and reliability of air quality monitoring by integrating data from different sources and structures.

[0004] When processing these multi-source information and various monitoring data, existing air quality detection methods often lack dynamic evaluation of the data quality from each source and fail to fully consider historical performance and reliability, resulting in inaccurate fusion results and difficulty in fully leveraging the advantages of multi-source information. Summary of the invention

[0005] The purpose of the present invention is to provide an air quality detection method based on multi-source information fusion technology, which can integrate air monitoring data from multiple sources and dynamically adjust data weights to accurately reflect the current air quality status.

[0006] The technical solution adopted by the present invention is as follows: An air quality detection method based on multi-source information fusion technology, comprising: The source channel for obtaining each air monitoring information; Construct a first time period, obtain air monitoring data of each source channel in the first time period, and obtain the air quality weight of the corresponding source channel according to the air monitoring data of each source channel; Construct a second time period, obtain air monitoring data of each source channel in the second time period, and obtain the air change trend of the corresponding source channel according to the air monitoring data of each source channel; Obtain the target air monitoring value corresponding to each source channel; The fused air quality value is obtained based on the target air monitoring value of each source channel, the air quality weight and the air change trend, and the air quality grade is obtained based on the fused air quality value.

[0007] In a preferred embodiment, the steps of constructing a first time period, obtaining air monitoring data of each source channel in the first time period, and obtaining the air quality weight of the corresponding source channel according to the air monitoring data of each source channel include: Construct the first period; Acquire air monitoring data from each source channel within a first period of time and mark it as first air information; Acquire a plurality of corresponding air monitoring values ​​according to the first air information, and mark each air monitoring value as a first air value; Acquire corresponding air reference values ​​according to the plurality of first air values; The air quality weight of the corresponding source channel is obtained according to each air reference value.

[0008] In a preferred embodiment, the step of constructing the first time period includes: Obtain real-time air monitoring values ​​from each source channel; Obtain air standard monitoring values; Determine whether multiple real-time air monitoring values ​​exceed air standard monitoring values; If any of the multiple real-time air monitoring values ​​exceeds the air standard monitoring value, the air quality is determined to be abnormal, and the time when the real-time air monitoring value exceeds the air standard monitoring value is marked as the first end time; If none of the multiple real-time air monitoring values ​​exceeds the air standard monitoring value, the air quality is judged to be normal; Get the first duration; Obtain a first start time according to the first duration and the first end time; A first time period is constructed according to the first start time and the first end time.

[0009] In a preferred embodiment, the step of obtaining the air quality weight of the corresponding source channel according to each air reference value includes: Obtaining a corresponding source weight table according to a source channel corresponding to each air reference value, wherein the source weight table includes a plurality of air reference interval values ​​and an air quality weight corresponding to each air reference interval value; Obtaining a corresponding target air reference interval value according to the air reference value; Obtain the corresponding air quality weight from the source weight table according to the target air reference interval value.

[0010] In a preferred embodiment, the steps of constructing a second time period, obtaining air monitoring data of each source channel in the second time period, and obtaining the air change trend of the corresponding source channel according to the air monitoring data of each source channel include: Construct the second period; Acquire the air monitoring data of each source channel in the second time period and mark it as the second air information; Acquire a plurality of corresponding second air values ​​according to the second air information; Obtain the air standard value corresponding to each source channel; Acquire the air change value of the corresponding source channel according to the plurality of second air values ​​and the corresponding air standard value; Get the air trend assessment interval; Determine whether the air change value is within the air trend assessment range; If the air change value is within the air trend assessment interval, the air change trend is determined to be stable; If the air change value is not within the air trend evaluation interval and is greater than the upper limit value of the air trend evaluation interval, it is determined that the air change trend is increasing.

[0011] If the air change value is not within the air trend assessment interval and is less than the lower limit of the air trend assessment interval, the air change trend is determined to be decreasing.

[0012] In a preferred embodiment, the step of constructing the second time period includes: Get the duration of the first period of time and mark it as the first duration; Obtaining a second coefficient according to the air quality weight corresponding to each source channel; Obtain the real-time air monitoring value corresponding to each source channel in the first period; Get the air anomaly threshold; Obtain the number of times that multiple real-time air monitoring values ​​exceed the air abnormality threshold in the first period, and mark it as the number of abnormal excesses; Obtain a second duration according to the second coefficient, the number of abnormal exceeding times and the first duration; Mark the end time of the first period as the start time of the second period; Obtaining the end time of the second period according to the second duration and the start time of the second period; The second time period is constructed according to the start time of the second time period and the end time of the second time period.

[0013] In a preferred embodiment, the step of obtaining the target air monitoring value corresponding to each source channel includes: Get the end time of the second period; Obtain the data collection time of each source channel of air monitoring information, sort all data collection times in order from long to short, select the data collection time with the longest duration and mark it as the unified collection time; Obtaining a unified collection time node of the data collection time according to the end time of the second period and the unified collection duration; Obtain the air monitoring information of each source channel within the unified collection time node, and mark it as the target air monitoring value corresponding to each source channel.

[0014] In a preferred embodiment, the step of obtaining a fused air quality value according to the target air monitoring value of each source channel, the air quality weight and the air change trend, and obtaining the air quality level according to the fused air quality value comprises: Obtain the air monitoring value corresponding to each source channel collected at the end time node of the first period, and mark it as the control air monitoring value; Obtain the corresponding air change value according to the air change trend of each source channel; The fused air quality value is calculated based on the target air monitoring value, reference air monitoring value, air quality weight and air change value of each source channel, where the calculation formula is: Where P represents the fused air quality value, a represents the number of the target air monitoring value, reference air monitoring value, air quality weight and air change value corresponding to each source channel, and b=1,2,3…b, It is represented by the target air monitoring value corresponding to the a-th source channel, It is expressed as the air quality weight corresponding to the a-th source channel, It is expressed as the air change value corresponding to the a-th source channel, It is expressed as the control air monitoring value corresponding to the a-th source channel; Get the corresponding air quality level according to the fused air quality value.

[0015] In a preferred embodiment, after the step of obtaining the corresponding air quality level according to the fused air quality value, the method further includes: Constructing the third period; Acquire air monitoring information from each source channel within a third time period, and obtain corresponding multiple air monitoring values, and aggregate them into a third air set; Obtaining the number of the plurality of air monitoring values ​​in the third air set that exceeds the air standard monitoring value, and marking the number as a third exceeding number; Obtaining a risk threshold quantity, and determining whether the third excess quantity exceeds the risk threshold quantity; If the third exceeding quantity exceeds the risk threshold quantity, the air quality is judged to be seriously polluted and an alarm message is issued.

[0016] And, an air quality detection terminal based on multi-source information fusion technology, comprising: one or more processors; a storage device having one or more programs stored thereon; When the one or more programs are executed by the one or more processors, the one or more processors implement the air quality detection method based on multi-source information fusion technology.

[0017] The technical effects achieved by the present invention are: The present invention can integrate data from multiple monitoring channels through multi-source information fusion, avoid errors that may be caused by a single channel, and improve the accuracy of air quality detection. By utilizing air change trend analysis, it can more sensitively capture changes in air quality and timely reflect fluctuations in air conditions. It has a certain predictive ability and dynamically adjusts data weights based on the historical performance and reliability of each channel, so that the final air quality assessment is more in line with the actual situation. It can flexibly access various types of air monitoring data sources, such as fixed sites, mobile equipment, remote sensing satellites, etc., to ensure the comprehensiveness and coverage of the data, and can effectively improve the accuracy and timeliness of air quality monitoring, providing more reliable data support for environmental protection and pollution control. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a flow chart of the method provided by the present invention. DETAILED DESCRIPTION

[0019] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0020] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0021] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure or characteristic that may be included in at least one implementation of the present invention. The phrase "in a preferred embodiment" that appears in different places in this specification does not refer to the same embodiment, nor is it a separate or selective embodiment that is mutually exclusive with other embodiments.

[0022] Secondly, the present invention is described in detail in conjunction with schematic diagrams. When describing the embodiments of the present invention in detail, for the convenience of explanation, the schematic diagrams are only examples and should not limit the scope of protection of the present invention.

[0023] Please see attached Figure 1 As shown, an air quality detection method based on multi-source information fusion technology is provided, including: S1. The source channel for obtaining each air monitoring information; S2. Construct a first time period, obtain air monitoring data of each source channel in the first time period, and obtain the air quality weight of the corresponding source channel according to the air monitoring data of each source channel; S3, constructing a second time period, obtaining air monitoring data of each source channel in the second time period, and obtaining the air change trend of the corresponding source channel according to the air monitoring data of each source channel; S4. Obtain the target air monitoring value corresponding to each source channel; S5. Obtain a fused air quality value based on the target air monitoring value of each source channel, the air quality weight, and the air change trend, and obtain the air quality grade based on the fused air quality value.

[0024] As in the above steps S1 to S5, first, the source channel of each air monitoring information is obtained (such as different monitoring sites, satellite remote sensing, mobile monitoring equipment, etc.), and the air monitoring data from each channel is collected in the first time period. According to the reliability, historical performance and other factors of each source channel, the air quality weight of the channel is assigned. In the second time period, the air quality change trend of each source channel is obtained by comparing the air monitoring data in different time periods. According to the monitoring data collected in the early stage, the current target air monitoring value is obtained from each source channel. According to the target air monitoring value, air quality weight and air change trend of each source channel, the final fused air quality value is calculated, and the air is divided into different The quality level (such as excellent, good, medium, poor, etc.) can integrate data from multiple monitoring channels through multi-source information fusion, avoid errors that may be caused by a single channel, and improve the accuracy of air quality detection. By using air change trend analysis, it can more sensitively capture changes in air quality and promptly reflect fluctuations in air conditions. It has a certain predictive ability and dynamically adjusts data weights based on the historical performance and reliability of each channel, so that the final air quality assessment is more in line with the actual situation. It can flexibly access various types of air monitoring data sources, such as fixed sites, mobile equipment, remote sensing satellites, etc., to ensure the comprehensiveness and coverage of the data, which can effectively improve the accuracy and timeliness of air quality monitoring and provide more reliable data support for environmental protection and pollution control.

[0025] In a specific embodiment, the steps of constructing a first time period, obtaining air monitoring data of each source channel in the first time period, and obtaining an air quality weight of the corresponding source channel according to the air monitoring data of each source channel include: S201, constructing a first period; S202, obtaining air monitoring data from each source channel within a first period of time, and marking the data as first air information; S203, acquiring a plurality of corresponding air monitoring values ​​according to the first air information, and marking each air monitoring value as a first air value; S204, acquiring corresponding air reference values ​​according to the multiple first air values; S205. Obtain the air quality weight of the corresponding source channel according to each air reference value.

[0026] As in the above steps S201 to S205, first, a time period is set as the basis for analyzing the data. The time period can be a fixed time period (such as 1 hour, 1 day) or a dynamically adjusted time period. In the constructed first time period, air monitoring data are obtained from different source channels. These data include information such as pollutant concentration, PM2.5, PM10, CO2, temperature and humidity, and these data are uniformly marked as "first air information". According to the first air information obtained from different source channels, the specific air monitoring values ​​of each channel are extracted and marked, which are called "first air values". These values ​​represent the air quality status of different source channels in the time period. According to the first air values ​​of multiple channels, a comprehensive air reference value is calculated, wherein the calculation formula for obtaining the corresponding air reference value according to multiple first air values ​​is a reference function, and the reference function is , where C represents the air reference value, i represents the number of multiple first air values, where i=1,2,3…n, It is expressed as the i-th first air value, and multiple first air values ​​corresponding to each source channel are input into the reference function, and the output result is marked as the first air value. Based on the air reference value of each channel, according to the deviation between the value and the air quality standard, the data reliability and quality of each source channel are evaluated, and the air quality weight of the channel is obtained through the difference between the air reference value of each channel and the overall air condition. By constructing a unified time period, data from multiple source channels can be obtained synchronously, and these data are deeply integrated to make the final air quality weight more representative. According to the air reference value of each channel and its matching degree with the air standard, the air quality weight of the channel is dynamically adjusted to ensure that the contribution of each data source reflects its actual performance, optimize the weight allocation mechanism, and be able to flexibly handle various types of monitoring data. Whether it is fixed site data or mobile monitoring equipment data, it can be uniformly processed through this process.

[0027] In a specific embodiment, the step of constructing the first time period includes: S2011. Obtain the real-time air monitoring value of each source channel; S2012. Obtain air standard monitoring values; S2013, determining whether multiple real-time air monitoring values ​​exceed air standard monitoring values; If any of the multiple real-time air monitoring values ​​exceeds the air standard monitoring value, the air quality is determined to be abnormal, and the time when the real-time air monitoring value exceeds the air standard monitoring value is marked as the first end time; If none of the multiple real-time air monitoring values ​​exceeds the air standard monitoring value, the air quality is judged to be normal; S2014, obtaining a first duration; S2015. Obtain a first start time according to the first duration and the first end time; S2016: Construct a first time period according to the first start time and the first end time.

[0028] As in the above steps S2011 to S2016, first, the current real-time air monitoring values ​​are obtained from each source channel. These data include pollutant concentrations, PM2.5, PM10 and other air quality indicators, reflecting the air conditions of each source channel at the current moment. The air standard monitoring values ​​are reference values ​​set according to national or local environmental standards, usually including the maximum allowable values ​​of pollutants such as PM2.5, PM10, sulfur dioxide, carbon monoxide, etc. These values ​​are used as a benchmark for judging whether the air quality is abnormal. The real-time air monitoring values ​​of each source channel are compared with the air standard monitoring values ​​to determine whether any real-time monitoring value of any source channel exceeds the standard monitoring value. If one or more real-time air monitoring values ​​exceed the air standard monitoring value, the air quality will be judged to be abnormal, and this moment will be marked as the "first end time". If no monitoring value exceeds the standard, the air quality will be judged to be normal, and monitoring will continue. A fixed time length is set, called the "first duration", which is used to define the time from the current abnormal event forward. The time range of tracing can be adjusted according to different application scenarios, such as 1 hour, 3 hours or one day. The "first start time" is calculated according to the recorded "first end time" and "first duration", that is, the first duration is moved forward from the abnormal time point to determine the start time of the abnormal air quality event. According to the "first start time" and "first end time", a time period is constructed, namely the "first period". This period represents the time range of abnormal air quality. By comparing the real-time monitoring values ​​with the air standards, it is possible to quickly identify whether the air quality exceeds the standard, so as to respond in time and mark the moment of abnormal air quality. According to the comparison between the real-time air monitoring values ​​and the standards, the start and end time of the abnormal event can be dynamically determined. The precise monitoring period is defined by the "first duration", which is helpful for subsequent air data analysis and processing. The time period can be dynamically adjusted according to the actual monitoring data to ensure that the most critical time range is captured in time when the air quality is abnormal, making the subsequent data analysis more targeted and timely.

[0029] In a specific embodiment, the step of obtaining the air quality weight of the corresponding source channel according to each air reference value includes: S2051. Acquire a corresponding source weight table according to a source channel corresponding to each air reference value, wherein the source weight table includes a plurality of air reference interval values ​​and an air quality weight corresponding to each air reference interval value; S2052, obtaining a corresponding target air reference interval value according to the air reference value; S2053. Obtain corresponding air quality weights from a source weight table according to the target air reference interval value.

[0030] As in the above steps S2051 to S2053, first, the "source weight table" of each source channel is obtained. This is a reference table preset for each channel. The table contains multiple air reference interval values ​​(for example, PM2.5, PM10, etc. with different concentrations), and the air quality weight corresponding to each reference interval value. The weight table of each channel may be adjusted according to the historical data quality and reliability of the channel to reflect its contribution. According to the air reference value of the source channel, its position in the source weight table is found to determine which "air reference interval value" it belongs to. According to the target air reference interval value, the corresponding air quality weight is extracted from the source weight table. Each source channel obtains a specific weight according to its air reference value. By setting a different weight table for each source channel, its weight can be differentiated according to the data quality and reliability of each channel, thereby improving the accuracy of multi-source information fusion. The source weight table provides a dynamic adjustment mechanism for channel reliability to ensure more accurate weight allocation. By corresponding the air reference value to a specific air reference interval, a more refined weight allocation can be achieved. The influence of data in different intervals on the final fusion result is gradually increasing or decreasing, making the air quality calculation more accurate.

[0031] In a specific embodiment, the steps of constructing a second time period, obtaining air monitoring data of each source channel in the second time period, and obtaining the air change trend of the corresponding source channel according to the air monitoring data of each source channel include: S301, constructing a second period; S302, obtaining air monitoring data from each source channel in a second period of time, and marking the data as second air information; S303, acquiring a plurality of corresponding second air values ​​according to the second air information; S304, obtaining the air standard value corresponding to each source channel; S305, acquiring the air change value of the corresponding source channel according to the plurality of second air values ​​and the corresponding air standard value; S306, obtaining an air trend assessment interval; S307, determining whether the air change value is within the air trend assessment interval; If the air change value is within the air trend assessment interval, the air change trend is determined to be stable; If the air change value is not within the air trend evaluation interval and is greater than the upper limit value of the air trend evaluation interval, it is determined that the air change trend is increasing.

[0032] If the air change value is not within the air trend assessment interval and is less than the lower limit of the air trend assessment interval, the air change trend is determined to be decreasing.

[0033] As in the above steps S301 to S307, a new monitoring time period (second time period) is defined according to the change in air quality. In the second time period, the latest air monitoring data is obtained from each source channel and marked as "second air information". These data represent the changes in air quality monitored by each channel in the time period, including pollutant concentration, PM2.5, PM10, etc. Multiple air monitoring values ​​are extracted from the second air information and marked as "second air values". The air standard values ​​of each channel are obtained from the air standard. These standard values ​​are used to measure whether the monitoring values ​​are normal. The air change value is calculated by comparing the "second air value" with the corresponding "air standard value", wherein the calculation formula for obtaining the air change value of the corresponding source channel according to the multiple second air values ​​and the corresponding air standard values ​​is a trend function, and the trend function is , where Q represents the air change value corresponding to each source channel, and k represents the number of multiple second air values ​​corresponding to each source channel, where k=1,2,3…m, Represents the kth second air value corresponding to each source channel, It is represented as the air standard value corresponding to each source channel. Multiple second air values ​​corresponding to each source channel and the corresponding air standard value are input into the trend function, and the output result is marked as the air change value. A predefined air trend evaluation interval is set. The interval is set according to historical data and is used to determine whether the air change value is within the normal range. According to the relationship between the air change value and the air trend evaluation interval, the air change trend is determined. If the air change value is within the trend evaluation interval, the air change is determined to be stable, indicating that the air quality does not fluctuate much. If the air change value exceeds the upper limit of the trend evaluation interval, the air change trend is determined to be increasing, indicating that the degree of air pollution is increasing. If the air change value is lower than the lower limit of the trend evaluation interval, the air change trend is determined to be decreasing, indicating that the degree of air pollution is decreasing or the air quality is improving. By calculating the air change value of each source channel and combining the air trend evaluation interval, the changing trend of air quality can be accurately determined. Whether the air pollution is increasing or decreasing, it can be captured in real time and feedback can be provided. By setting the second time period, the monitoring time range can be dynamically adjusted. Compared with fixed time period monitoring, this method is more flexible and can adjust the monitoring strategy according to the fluctuation of air quality to adapt to different environmental changes.

[0034] In a specific embodiment, the step of constructing the second time period includes: S3011, obtaining the duration of the first time period and marking it as the first duration; S3012, obtaining a second coefficient according to the air quality weight corresponding to each source channel; S3013, obtaining the real-time air monitoring value corresponding to each source channel in the first period; S3014, obtaining an air anomaly threshold; S3015, obtaining the number of times that multiple real-time air monitoring values ​​exceed the air abnormality threshold value in the first period, and marking it as the number of abnormal excesses; S3016, obtaining a second duration according to the second coefficient, the number of abnormal exceeding times and the first duration; S3017, marking the end time of the first period as the start time of the second period; S3018. Obtaining the end time of the second time period according to the second duration and the start time of the second time period; S3019: Construct a second time period according to the start time of the second time period and the end time of the second time period.

[0035] As in the above steps S3011 to S3019, first, the monitoring time length is obtained from the first period, marked as the first time length, and the corresponding "second coefficient" is calculated according to the air quality weight of each source channel, wherein the calculation formula for obtaining the second coefficient according to the air quality weight corresponding to each source channel is the coefficient function, and the coefficient function is , where It is expressed as the second coefficient, r is the number of the air quality weight corresponding to each source channel, r=1,2,3…u, is represented as the air quality weight corresponding to the rth source channel, L is represented as the air quality standard weight, the air quality weight corresponding to each source channel is input into the coefficient function, and the output result is marked as the second coefficient, the real-time air monitoring value of each source channel is obtained in the first time period, and an "air abnormality threshold" is set, which represents the critical value of abnormal air quality. If the monitoring value exceeds this threshold, it means that the air quality has deteriorated seriously. In the first time period, the number of times the real-time monitoring value of each source channel exceeds the air abnormality threshold is counted, and marked as "abnormal exceedance times", and the "second duration" is calculated according to the "second coefficient", the abnormal exceedance times and the first duration, where the calculation formula for obtaining the second duration according to the second coefficient, the abnormal exceedance times and the first duration is the duration function, and the duration function is , where Represented as the second duration, Expressed as the second coefficient, Represents the first duration, It is expressed as the total number of multiple real-time air monitoring values ​​in the first period. It is expressed as the number of abnormal exceedances. The end time of the first period is marked as the start time of the second period to ensure the continuity between the periods. The end time of the second period is obtained according to the second duration and the start time of the second period. The second period is successfully constructed according to the start time and end time of the second period. This period will be used to continue monitoring the air quality, especially when the monitoring data of the first period indicates that the air quality may change. By dynamically adjusting the duration of the second period according to factors such as the number of abnormal exceedances and the second coefficient, it can flexibly respond to fluctuations in air quality. Compared with fixed periods, this method can more accurately capture real-time changes in air quality, especially when the air quality changes dramatically. Extending the duration helps to obtain data more comprehensively. The air quality weight of each source channel directly affects the construction of the second period, so that when significant changes are detected in important channels, timely responses can be made to ensure that the focus of air quality monitoring is placed on high-weight data sources and improve the reliability and representativeness of the data.

[0036] In a specific embodiment, the step of obtaining the target air monitoring value corresponding to each source channel includes: S401, obtaining the end time of the second period; S402, obtaining the data collection time of each source channel of air monitoring information, sorting all data collection times in order from long to short, selecting the data collection time with the longest duration and marking it as a unified collection time; S403, obtaining a unified collection time node of the data collection time according to the end time of the second period and the unified collection duration; S404: Acquire the air monitoring information of each source channel within the unified collection time node, and mark it as the target air monitoring value corresponding to each source channel.

[0037] As in the above steps S401 to S404, first, determine the end time of the second time period as the reference time point for the entire data collection. The data collection frequency and duration of each source channel may be different. The data collection duration of all channels is obtained and sorted. In this way, the source channel with the longest collection time can be identified, thereby ensuring the adequacy and representativeness of the monitoring data. After sorting, select the channel with the longest collection time, and mark its collection time as "unified collection duration" as the reference time for subsequent unified data alignment. According to the end time of the second time period and the unified collection duration, a unified data collection time node is obtained. This node can ensure that the monitoring values ​​of all data sources are aligned and integrated within a unified time period. Within the unified collection time node, air monitoring information is obtained from each channel, and this information is marked as their respective target air monitoring values. By selecting a unified collection duration, it can ensure that the monitoring data of different source channels are aligned within the same time node. This can avoid data inconsistency caused by differences in collection durations of different channels, thereby improving the precision and accuracy of overall air monitoring.

[0038] In a specific embodiment, the step of obtaining a fused air quality value according to the target air monitoring value of each source channel, the air quality weight, and the air change trend, and obtaining the air quality level according to the fused air quality value includes: S501, obtaining the air monitoring value corresponding to each source channel collected at the end time node of the first period, and marking it as a control air monitoring value; S502, obtaining a corresponding air change value according to the air change trend of each source channel; S503. Calculate the fused air quality value according to the target air monitoring value, the reference air monitoring value, the air quality weight and the air change value of each source channel, wherein the calculation formula is: Where P represents the fused air quality value, a represents the number of the target air monitoring value, reference air monitoring value, air quality weight and air change value corresponding to each source channel, and b=1,2,3…b, It is represented by the target air monitoring value corresponding to the a-th source channel, It is expressed as the air quality weight corresponding to the a-th source channel, It is expressed as the air change value corresponding to the a-th source channel, It is expressed as the control air monitoring value corresponding to the a-th source channel; S504: Obtain a corresponding air quality level according to the fused air quality value.

[0039] As in the above steps S501 to S504, at the end of the first period, the air monitoring values ​​of each source channel are obtained and marked as control air monitoring values. According to the air change trend of each source channel, the corresponding air change value is calculated. The fused air quality value is calculated by combining the target air monitoring value, the control air monitoring value, the air quality weight and the air change value. According to the calculated fused air quality value, it is compared with the preset air quality grade standard to determine the current air quality grade, which can be "good", "general", "poor", etc., to help users quickly understand the air quality status. By integrating air monitoring values ​​from multiple sources, a more accurate air quality assessment can be provided. Data from different channels complement each other, reducing possible deviations in a single channel and improving the reliability of monitoring.

[0040] In a specific embodiment, after the step of obtaining the corresponding air quality level according to the fused air quality value, the method further includes: S505, constructing the third period; S506, obtaining air monitoring information from each source channel in a third time period, and obtaining a corresponding plurality of air monitoring values, and summarizing them into a third air set; S507, obtaining the number of the plurality of air monitoring values ​​in the third air set that exceeds the air standard monitoring value, and marking it as a third exceeding number; S508, obtaining a risk threshold quantity, and determining whether the third excess quantity exceeds the risk threshold quantity; If the third exceeding quantity exceeds the risk threshold quantity, the air quality is judged to be seriously polluted and an alarm message is issued.

[0041] As in the above steps S505 to S508, the time range of the third time period is determined as a new monitoring cycle. During the third time period, air monitoring information is obtained from each source channel, and the corresponding air monitoring values ​​are extracted and summarized into a data set called "third air set". The air monitoring values ​​in the "third air set" are obtained, and it is calculated how many values ​​exceed the preset air standard monitoring values. The number exceeding the standard is marked as the "third exceeding number", a preset risk threshold number is obtained, and it is determined whether the "third exceeding number" exceeds this threshold. If it exceeds, the air quality is judged to be seriously polluted and an alarm information is generated. By constructing the third time period and conducting air monitoring, changes in air quality can be tracked in real time, abnormal conditions can be discovered in time, and early warnings can be triggered. This dynamic monitoring improves the response speed to changes in air quality and helps to take timely measures.

[0042] And, an air quality detection terminal based on multi-source information fusion technology, comprising: one or more processors; a storage device having one or more programs stored thereon; When the one or more programs are executed by the one or more processors, the one or more processors implement the air quality detection method based on multi-source information fusion technology.

[0043] The above is only a preferred embodiment of the present invention. It should be noted that, for those skilled in the art, several improvements and modifications can be made without departing from the principles of the present invention, and these improvements and modifications should also be considered as the protection scope of the present invention. The structures, devices and operating methods not specifically described and explained in the present invention shall be implemented according to the conventional means in the art unless otherwise specified and limited.

Claims

1. An air quality detection method based on multi-source information fusion technology, characterized in that: include: Obtain the source channel of each air monitoring information; Construct a first time period, obtain air monitoring data of each source channel in the first time period, and obtain the air quality weight of the corresponding source channel according to the air monitoring data of each source channel; Construct a second time period, obtain air monitoring data of each source channel in the second time period, and obtain the air change trend of the corresponding source channel according to the air monitoring data of each source channel; Obtain the target air monitoring value corresponding to each source channel; The fused air quality value is obtained based on the target air monitoring value of each source channel, the air quality weight and the air change trend, and the air quality grade is obtained based on the fused air quality value.

2. The air quality detection method based on multi-source information fusion technology according to claim 1 is characterized in that: The step of constructing a first time period, obtaining air monitoring data of each source channel in the first time period, and obtaining the air quality weight of the corresponding source channel according to the air monitoring data of each source channel includes: Construct the first period; Acquire air monitoring data from each source channel within a first period of time and mark it as first air information; Acquire a plurality of corresponding air monitoring values ​​according to the first air information, and mark each air monitoring value as a first air value; Acquire corresponding air reference values ​​according to the plurality of first air values; The air quality weight of the corresponding source channel is obtained according to each air reference value.

3. The air quality detection method based on multi-source information fusion technology according to claim 2 is characterized in that: The step of constructing the first time period includes: Obtain real-time air monitoring values ​​from each source channel; Obtain air standard monitoring values; Determine whether multiple real-time air monitoring values ​​exceed air standard monitoring values; If any of the multiple real-time air monitoring values ​​exceeds the air standard monitoring value, the air quality is determined to be abnormal, and the time when the real-time air monitoring value exceeds the air standard monitoring value is marked as the first end time; If none of the multiple real-time air monitoring values ​​exceeds the air standard monitoring value, the air quality is judged to be normal; Get the first duration; Obtain a first start time according to the first duration and the first end time; A first time period is constructed according to the first start time and the first end time.

4. The air quality detection method based on multi-source information fusion technology according to claim 2 is characterized in that: The step of obtaining the air quality weight of the corresponding source channel according to each air reference value includes: Obtaining a corresponding source weight table according to a source channel corresponding to each air reference value, wherein the source weight table includes a plurality of air reference interval values ​​and an air quality weight corresponding to each air reference interval value; Obtaining a corresponding target air reference interval value according to the air reference value; Obtain the corresponding air quality weight from the source weight table according to the target air reference interval value.

5. The air quality detection method based on multi-source information fusion technology according to claim 1 is characterized in that: The steps of constructing a second time period, obtaining air monitoring data of each source channel in the second time period, and obtaining the air change trend of the corresponding source channel according to the air monitoring data of each source channel include: Construct the second period; Acquire the air monitoring data of each source channel in the second time period and mark it as the second air information; Acquire a plurality of corresponding second air values ​​according to the second air information; Obtain the air standard value corresponding to each source channel; Acquire the air change value of the corresponding source channel according to the plurality of second air values ​​and the corresponding air standard value; Get the air trend assessment interval; Determine whether the air change value is within the air trend assessment range; If the air change value is within the air trend assessment interval, the air change trend is determined to be stable; If the air change value is not within the air trend assessment interval and is greater than the upper limit of the air trend assessment interval, the air change trend is determined to be increasing; If the air change value is not within the air trend assessment interval and is less than the lower limit of the air trend assessment interval, the air change trend is determined to be decreasing.

6. The air quality detection method based on multi-source information fusion technology according to claim 5 is characterized in that: The step of constructing the second time period includes: Get the duration of the first period of time and mark it as the first duration; Obtaining a second coefficient according to the air quality weight corresponding to each source channel; Obtain the real-time air monitoring value corresponding to each source channel in the first period; Get the air anomaly threshold; Obtain the number of times that multiple real-time air monitoring values ​​exceed the air abnormality threshold in the first period, and mark it as the number of abnormal excesses; Obtain a second duration according to the second coefficient, the number of abnormal exceeding times and the first duration; Mark the end time of the first period as the start time of the second period; Obtaining the end time of the second period according to the second duration and the start time of the second period; The second time period is constructed according to the start time of the second time period and the end time of the second time period.

7. The air quality detection method based on multi-source information fusion technology according to claim 1 is characterized in that: The step of obtaining the target air monitoring value corresponding to each source channel includes: Get the end time of the second period; Obtain the data collection time of each source channel of air monitoring information, sort all data collection times in order from long to short, select the data collection time with the longest duration and mark it as the unified collection time; Obtaining a unified collection time node of the data collection time according to the end time of the second period and the unified collection duration; Obtain the air monitoring information of each source channel within the unified collection time node, and mark it as the target air monitoring value corresponding to each source channel.

8. The air quality detection method based on multi-source information fusion technology according to claim 1 is characterized in that: The step of obtaining a fused air quality value according to the target air monitoring value of each source channel, the air quality weight, and the air change trend, and obtaining the air quality level according to the fused air quality value includes: Obtain the air monitoring value corresponding to each source channel collected at the end time node of the first period, and mark it as the control air monitoring value; Obtain the corresponding air change value according to the air change trend of each source channel; The fused air quality value is calculated based on the target air monitoring value, reference air monitoring value, air quality weight and air change value of each source channel, where the calculation formula is: ; In the formula, P represents the fused air quality value, a represents the number of the target air monitoring value, control air monitoring value, air quality weight and air change value corresponding to each source channel, and b=1,2,3…b, It is represented by the target air monitoring value corresponding to the a-th source channel, It is expressed as the air quality weight corresponding to the a-th source channel, It is expressed as the air change value corresponding to the a-th source channel, It is expressed as the control air monitoring value corresponding to the a-th source channel; Get the corresponding air quality level according to the fused air quality value.

9. The air quality detection method based on multi-source information fusion technology according to claim 8 is characterized in that: After the step of obtaining the corresponding air quality level according to the fused air quality value, the method further includes: Constructing the third period; Acquire air monitoring information from each source channel within a third time period, and obtain corresponding multiple air monitoring values, and aggregate them into a third air set; Obtaining the number of the plurality of air monitoring values ​​in the third air set that exceeds the air standard monitoring value, and marking the number as a third exceeding number; Obtaining a risk threshold quantity, and determining whether the third excess quantity exceeds the risk threshold quantity; If the third exceeding quantity exceeds the risk threshold quantity, the air quality is judged to be seriously polluted and an alarm message is issued.

10. An air quality detection terminal based on multi-source information fusion technology, characterized in that: include: one or more processors; a storage device having one or more programs stored thereon; When the one or more programs are executed by the one or more processors, the one or more processors implement the air quality detection method based on multi-source information fusion technology as described in any one of claims 1 to 9.

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