Road underway monitoring method and system based on big data

Abstract

The invention relates to the technical field of big data analysis, in particular to a road underway monitoring method and system based on big data, pollution source request data and an underway route are collected, the pollution source request data comprise radiation POIs, and the radiation POIs are POIs corresponding to gas detected by an alarm air sensor; deciding an alarm air sensor according to the pollution source request data and the underway route; monitoring records of the alarm air sensor are collected; deciding an alarm state according to the monitoring record; and deciding a retest log according to the alarm state, wherein the retest log comprises a candidate air sensor, an associated dependent air sensor and a retest method. According to the invention, the problems of inaccurate underway monitoring data, large deviation of multiple data measurement and isolated measurement data results can be effectively solved, and the effectiveness of underway monitoring results is ensured.

Description

Technical Field

[0001] The present application relates to the technical field of big data analysis, and in particular to a road navigation monitoring method and system based on big data. Background Art

[0002] Cruise monitoring is an environmental monitoring technology that mainly uses vehicle-mounted rapid monitoring equipment to conduct continuous and automatic monitoring while on the move, combined with fixed-point monitoring, to conduct qualitative and quantitative analysis of pollutants, and to display the spatial continuous distribution of pollutants based on geographic location information. The main difference between cruise monitoring and general mobile monitoring vehicles or mobile laboratories is its ability to conduct continuous and automatic monitoring while on the move. Cruise monitoring can obtain as much qualitative and quantitative information on pollutants as possible while on the move, and stop at the pollution point for retesting, or use other equipment to assist in the qualitative and quantitative analysis of pollutants. However, in the prior art, inaccurate monitoring data, large deviations in multiple data measurements, and isolated measurement data results often occur during the cruise monitoring process, making it difficult to ensure the effectiveness of the cruise monitoring results. Summary of the invention

[0003] To achieve the above objectives, this application provides the following technical solutions: According to a first aspect of the present invention, the present invention claims protection for a road navigation monitoring method based on big data, comprising: Collecting pollution source request data and navigation routes, wherein the pollution source request data includes radiation POI, and the radiation POI is the POI corresponding to the gas detected by the alarm air sensor; Alerting the air sensor according to the pollution source request data and the navigation route decision; Collecting monitoring records of the alarm air sensor; Determine an alarm state based on the monitoring records; A retest log is determined according to the alarm status, wherein the retest log includes candidate air sensors, associated dependent air sensors and a retest method.

[0004] Further, the air sensor alarm is determined based on the pollution source request data and the navigation route, including: Polling a first air sensor from the navigation route, where the first air sensor is an air sensor at a preset distance from the radiation POI; Collecting a first monitoring record of the first air sensor; Performing concentration distribution analysis on the first monitoring record to determine whether to issue an alarm; The first air sensor corresponding to the first monitoring record with an alarm is determined as an alarm air sensor.

[0005] Furthermore, the step of determining an alarm state based on the monitoring record includes: Analyze the monitoring records and determine the type of pollution source; Determine the first pollution source according to the pollution source type and preset rules; Collect the completed retest results; Determine the last retest time and the last retest status based on the completed retest results; Determine a second pollution source based on the last retest time, the last retest status, and the first pollution source; An alarm state is determined based on the pollution source type and the second pollution source.

[0006] Furthermore, before retesting the log according to the alarm status decision, the method further includes: Collecting the first POI and industrial projects within the air monitoring point, where the first POI is all POIs within the air monitoring point; Determine a second POI according to the industrial project, wherein the second POI is a POI required for the industrial project; Determine a first priority of the first POI according to a first weight association, wherein the first POI includes the second POI; Determine a second priority of the second POI according to a second weight association and the industrial project; modifying the priority of the second POI according to the first priority and the second priority; Determine the scope of attention based on the priority and range of POIs; The focus range is queued and a plurality of focus POIs are output, wherein candidate air sensors are installed in the focus POIs.

[0007] Further, the retest log is determined based on the alarm status, including: Determine the first POI influence range according to the alarm air sensor; Determine a POI of interest that overlaps with the influence range of the first POI as a first POI of interest; Determine the degree of intersection between the first POI of interest and the influence range of the first POI; sorting the first POIs of interest according to the intersection degree; The first concerned POI having a ranking position in front of a preset position and a crossing degree greater than a preset crossing degree is determined as the influence range of the second POI; Sending a start instruction to the candidate air sensors corresponding to the influence range of the second POI; The total POI formed by the second POI influence range is determined as the candidate POI influence range; Compare the candidate POI influence range with the first POI influence range, and output an associated dependent POI influence range, wherein the associated dependent POI influence range is a POI included in the first POI influence range but not included in the candidate POI influence range; The decision on the associated dependent air sensor is made based on the POI impact range of the air sensor in the air monitoring point; An association-dependent instruction is sent to the association-dependent air sensor.

[0008] Furthermore, the decision of associating dependent air sensors according to the POI influence range of the air sensors in the air monitoring points includes: Determine the air sensor whose possible POI influence range includes the associated dependent POI influence range as the first candidate associated dependent air sensor; If there are multiple first candidate association-dependent air sensors, the priority of the POI corresponding to the first candidate association-dependent air sensor is collected, and the POI corresponding to the first candidate association-dependent air sensor is the POI included in the gas detected by the first candidate association-dependent air sensor; Decide the first candidate association-dependent air sensor corresponding to the POI with the lowest priority as the association-dependent air sensor; If the first candidate associated dependent air sensor is not present, an air sensor having an intersection between the possible POI influence range and the associated dependent POI influence range is determined as a second candidate associated dependent air sensor; Queuing the second candidate association-dependent air sensors, and outputting a plurality of candidate association-dependent air sensor queues, each of the candidate association-dependent air sensor queues including at least two of the second candidate association-dependent air sensors; Merging the POI influence ranges corresponding to the second candidate association-dependent air sensor in the candidate association-dependent air sensor queue, and outputting a plurality of merged POI influence ranges; The combined POI influence range completely covers the associated dependent POI influence range, and the candidate associated dependent air sensor queue with the least number of second candidate associated dependent air sensors is determined as the associated dependent queue; The second candidate association-dependent air sensor corresponding to the association-dependent queue is decided as the association-dependent air sensor.

[0009] Further, the retest log is determined based on the alarm status, including: Determine the type and source of pollution based on the alarm status; Collect retest monitoring point information; Determine the number of retest monitoring points based on the type of pollution source, the pollution source and the number of preset retest monitoring points; Determine a first retest monitoring point according to the number of retest monitoring points, preset retest rules and the retest monitoring point information, wherein the first retest monitoring point is the retest monitoring point of the pollution source; Collecting a retest report based on the pollution source type and the pollution source, wherein the retest report includes a POI to be used; A retest method is generated according to the retest monitoring points and the retest report.

[0010] According to a second aspect of the present invention, the present invention claims protection for a road navigation monitoring system based on big data, comprising: A first collection unit is used to collect pollution source request data and a navigation route, wherein the pollution source request data includes a radiation POI, and the radiation POI is a POI corresponding to the gas detected by the alarm air sensor; An alarm decision unit, used for deciding to alarm the air sensor according to the pollution source request data and the navigation route; A second collection unit is used to collect monitoring records of the alarm air sensor; A state decision unit, used for deciding an alarm state according to the monitoring record; A log decision unit, configured to decide a retest log according to the alarm state, wherein the retest log includes a candidate air sensor, an associated dependent air sensor, and a retest method; The road navigation monitoring system based on big data is used to execute the road navigation monitoring method based on big data.

[0011] The present application relates to the technical field of big data analysis, and in particular to a road navigation monitoring method and system based on big data, which collects pollution source request data and navigation routes, wherein the pollution source request data includes radiation POI, and the radiation POI is the POI corresponding to the gas detected by the alarm air sensor; determines the alarm air sensor based on the pollution source request data and the navigation route; collects the monitoring records of the alarm air sensor; determines the alarm state based on the monitoring records; determines the retest log based on the alarm state, and the retest log includes candidate air sensors, associated dependent air sensors, and retest methods. The present invention can effectively solve the problems of inaccurate navigation monitoring data, large deviations in multiple data measurements, and isolated measurement data results, and ensure the effectiveness of the navigation monitoring results. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 A workflow diagram of a road navigation monitoring method based on big data as claimed in an embodiment of the present application; Figure 2This is a structural block diagram of a road navigation monitoring system based on big data that is requested to be protected by an embodiment of the present application. DETAILED DESCRIPTION

[0013] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. According to the embodiments in the present application, all other embodiments obtained by the ordinary technical monitoring points in this field without creative work are within the scope of protection of this application.

[0014] The terms "first", "second" and "third" in this application are only used for descriptive purposes and cannot be understood as indicating or implying relative attention or implicitly indicating the number of indicated technical features. Therefore, the features defined as "first", "second" and "third" can explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "multiple" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined. All directional indications (such as up, down, left, right, front, back...) in the embodiments of this application are only used to explain the relative range relationship, motion state, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication also changes accordingly. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions. For example, a process, method, system, product or POI that includes a series of steps or units is not limited to the listed steps or units, but optionally also includes steps or units that are not listed, or optionally also includes other steps or units inherent to these processes, methods, products or POIs.

[0015] Reference to "embodiment" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiment may be included in at least one embodiment of the present application. The appearance of the phrase in various scopes in the specification does not necessarily refer to the same embodiment, nor is it an independent or candidate embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0016] like Figure 1 As shown, a road navigation monitoring method based on big data, the main process of the method is described as follows (steps S101 to S105): Step S101: Collect pollution source request data and navigation routes.

[0017] Among them, the pollution source request data includes radiation POI, which is the POI corresponding to the gas detected by the alarm air sensor. The navigation route includes the range of each air sensor and the distribution status of each POI in the air monitoring point.

[0018] In this embodiment, pollution source request data is collected from each pollution source, and the navigation route is collected from the database.

[0019] Step S102: Alarm the air sensor based on the pollution source request data and the navigation route decision.

[0020] After the pollution source request data is collected, the range of the alarm air sensor and the decision alarm air sensor are polled from the navigation route according to the pollution source request data.

[0021] Specifically, the alarm air sensor is decided based on the pollution source request data and the navigation route, including: polling the first air sensor from the navigation route, the first air sensor is an air sensor at a preset distance from the radiation POI; collecting the first monitoring record of the first air sensor; performing concentration distribution analysis on the first monitoring record to decide whether there is an alarm; and deciding the first air sensor corresponding to the first monitoring record with an alarm as an alarm air sensor.

[0022] In this embodiment, the first POI is determined by the radiation POI, and the first POI is a POI with the radiation POI as the center and a preset distance as the radius, wherein the preset distance is set according to the actual state and is not specifically limited here. The first POI is marked in the navigation route, and the air sensor in the first POI is determined to be the first air sensor, that is, the air sensor that may have an alarm. The first monitoring record of the first air sensor is collected from the database, and the concentration distribution analysis of the first monitoring record is performed through a preset concentration distribution analysis model to determine whether there is an alarm, wherein the preset concentration distribution analysis model is not specifically limited here. If there is an alarm, the first air sensor corresponding to the first monitoring record is determined as the alarm air sensor, and the range of the alarm air sensor can be quickly known from the navigation route, so that the re-test monitoring point can reach the range as soon as possible for re-testing.

[0023] Step S103: collecting monitoring records of alarm air sensors.

[0024] The monitoring records of the alarm air sensors are collected from the database to facilitate subsequent decision-making on the alarm status.

[0025] Step S104: determine the alarm status based on the monitoring records.

[0026] Specifically, deciding the alarm state based on the monitoring records includes: analyzing the monitoring records to decide the type of pollution source; deciding the first pollution source based on the pollution source type and preset rules; collecting completed re-test results; deciding the last re-test time and the last re-test status based on the completed re-test results; deciding the second pollution source based on the last re-test time, the last re-test status and the first pollution source; and deciding the alarm state based on the pollution source type and the second pollution source.

[0027] In this embodiment, the monitoring records are analyzed by a preset pollution source analysis model to output the pollution source type, wherein the preset pollution source analysis model is not specifically limited here, and preset rules are collected from a database, the preset rules are the correspondence between pollution source types and pollution sources, so the first pollution source can be determined by the pollution source type and the preset rules, the first pollution source is the cause that may cause the pollution source type, the completed retest results are collected from the database, and the completed retest results corresponding to the alarm air sensor are polled from the completed retest results, so that the last retest time and the last retest status of the alarm air sensor can be determined, the last retest status includes the pollution source type, the pollution source and the retest method, the first span between the last retest time and the current time is calculated, and the correspondence between the pollution source and the span is collected from the database, because some pollution sources will not occur again in a short time, so some possible pollution sources can be excluded through the first span of this time, so as to determine the second pollution source, that is, the first pollution source includes the second pollution source, and the pollution source type and the second pollution source are jointly determined as the alarm state.

[0028] Step S105: Retest the log based on the alarm status.

[0029] The retest log includes candidate air sensors, associated dependent air sensors, and retest methods.

[0030] When an alarm occurs, the alarm air sensor cannot monitor the smart air monitoring point well. At this time, other air sensors (candidate air sensors and / or associated dependent air sensors) are needed to complete the monitoring to reduce the impact of the alarm, and appropriate retesting methods should be adopted to retest as soon as possible.

[0031] Specifically, before deciding on the retest log based on the alarm status, the method also includes: collecting the first POI and industrial projects within the air monitoring point, the first POI being all POIs within the air monitoring point; deciding on the second POI based on the industrial project, the second POI being the POI required for the industrial project; deciding on the first priority of the first POI based on the first weight association, the first POI including the second POI; deciding on the second priority of the second POI based on the second weight association and the industrial project; correcting the priority of the second POI based on the first priority and the second priority; deciding on the focus range based on the priority of the POI and the range of the POI; queuing the focus range and outputting multiple focus POIs, wherein the focus POIs have candidate air sensors installed therein.

[0032] In this embodiment, the status corresponding to all POIs in the air monitoring point and the status of the industrial project are collected from the management monitoring point or the database. For the convenience of description, all POIs are expressed as the first POI, and the POI required for the industrial project is decided as the second POI, that is, the second POI is a part of the first POI.

[0033] The first weight association and the second weight association are collected from the database, the first weight association is the corresponding association relationship between the POI and the priority, the second weight association is the corresponding association relationship between the industrial project and the priority, the first weight association is used to determine the first priority of each first POI, the second weight association is used to determine the second priority of each industrial project, and the second priority of the industrial project is determined as the second priority of the corresponding second POI. At this time, the second POI has both the first priority and the second priority, and both the first priority and the second priority have three weights, weight I, weight II and weight III, each weight has a corresponding weight score, and the weight score corresponding to the first priority * the first weight + the weight score corresponding to the second priority * the second weight output score is determined as the POI score, the first weight and the second weight are preset, and the specific values ​​are not specifically limited here, the corresponding relationship between the POI score and the priority is collected from the database, so the final priority of each second POI can be determined by the POI score, and the priority of the POI other than the second POI in the first POI is the corresponding first priority, wherein the priority also has three weights, namely weight I, weight II and weight III.

[0034] The range corresponding to the POI with priority weight I is decided as the focus range, the focus range is marked on the navigation route, and the distance between each two focus ranges is calculated, and two ranges with a distance less than a preset distance are divided into a queue, and multiple queues are output. Each queue can have multiple ranges, but for each range, the distance with other ranges in the queue must be less than the preset distance, and the multiple ranges in each queue are connected on the navigation route, and the POI surrounded by the connection line is decided as the focus POI; similarly, the queue can also have only one range, and the POI with the range as the center and the preset distance as the radius is decided as the focus POI, and the focus POI is sent to the working monitoring point, so that the working monitoring point installs a candidate air sensor in the focus POI, wherein the preset distance is determined according to the detection state of the candidate air sensor, for example: it can be the detection distance of the candidate air sensor.

[0035] When deciding on a POI to focus on, the air monitoring point can also be divided into several small POIs according to a preset division rule, and the small POI with a priority of weight I can be decided as a POI to focus on, and candidate air sensors can be installed, wherein the preset division rule is pre-set and is not specifically limited here.

[0036] Specifically, the retest log is decided based on the alarm state, including: determining the first POI influence range based on the alarm air sensor; determining the POI of interest that has an intersection with the first POI influence range as the first POI of interest; determining the degree of intersection between the first POI of interest and the first POI influence range; sorting the first POI of interest based on the degree of intersection; determining the first POI of interest that has a front preset position in the sorting and a degree of intersection greater than the preset degree of intersection as the second POI influence range; sending a start instruction to the candidate air sensor corresponding to the second POI influence range; determining the total POI formed by the second POI influence range as the candidate POI influence range; comparing the candidate POI influence range with the first POI influence range, and outputting the associated dependent POI influence range, the associated dependent POI influence range being the POI included in the first POI influence range but not included in the candidate POI influence range; determining the associated dependent air sensor based on the POI influence range of the air sensor in the air monitoring point; and sending an associated dependent instruction to the associated dependent air sensor.

[0037] In this embodiment, when a pollution source occurs in the air sensor, a suitable candidate air sensor is first found and enabled. For the associated dependent POI influence range that cannot be monitored by the candidate air sensor, the associated dependent air sensor is started to monitor, so that the candidate air sensor and the associated dependent air sensor can jointly complete the monitoring of the first POI influence range and reduce the impact of the pollution source.

[0038] The specific steps are as follows: the POI monitored by the alarm air sensor is decided as the first POI influence range, and the attention POI having a range intersection with the first POI influence range is decided as the first attention POI; the area of ​​the intersection between the first attention POI and the first POI influence range and the area of ​​the first POI influence range are calculated according to the pixel counting method, and the intersection degree is calculated by the formula, the formula is: intersection degree = area of ​​the intersection part / area of ​​the first POI influence range; the first attention POI is sorted from high to low according to the intersection degree, and the first attention POI with a preset position in the front and an intersection degree greater than the preset intersection degree is decided as the second POI influence range, wherein the preset position and the preset intersection degree are preset and are not specifically limited here; a start instruction is sent to the candidate air sensor corresponding to the second POI influence range, and when multiple candidate air sensors are started, the total POI formed by the multiple second POI influence ranges is decided as the candidate POI influence range.

[0039] The influence range of the first POI that is not included in the influence range of the candidate POI is decided as the influence range of the associated dependent POI, and an associated dependent air sensor is decided through the POI influence range of the air sensor in the air monitoring point and the associated dependent POI influence range, and an associated dependent instruction is sent to the associated dependent air sensor, the associated dependent instruction being an air sensor rotation instruction, so that the associated dependent air sensor can detect both the gas within the original POI influence range of the air sensor and the gas within the associated dependent POI influence range. Similarly, the number of associated dependent air sensors may be one or more.

[0040] Specifically, an associated dependent air sensor is decided based on the POI influence range of the air sensor in the air monitoring point, including: deciding the air sensor whose POI influence range includes the associated dependent POI influence range as the first candidate associated dependent air sensor; if there are multiple first candidate associated dependent air sensors, collecting the priority of the POI corresponding to the first candidate associated dependent air sensor, and the POI corresponding to the first candidate associated dependent air sensor is the POI included in the gas detected by the first candidate associated dependent air sensor; deciding the first candidate associated dependent air sensor corresponding to the POI with the lowest priority as the associated dependent air sensor; if there is no first candidate associated dependent air sensor, deciding the air sensor whose POI influence range has an intersection with the associated dependent POI influence range. The forked air sensor is decided as the second candidate associated dependent air sensor; the second candidate associated dependent air sensors are queued, and multiple candidate associated dependent air sensor queues are output, each candidate associated dependent air sensor queue includes at least two second candidate associated dependent air sensors; the POI influence ranges corresponding to the second candidate associated dependent air sensors in the candidate associated dependent air sensor queues are merged, and multiple merged POI influence ranges are output; the merged POI influence range completely covers the associated dependent POI influence range, and the candidate associated dependent air sensor queue with the least number of second candidate associated dependent air sensors is decided as the associated dependent queue; the second candidate associated dependent air sensors corresponding to the associated dependent queue are decided as the associated dependent air sensor.

[0041] In this embodiment, an air sensor whose POI influence range completely covers the influence range of the associated dependent POI is decided as the first candidate associated dependent air sensor. There may be only one first candidate associated dependent air sensor. If there is only one first candidate associated dependent air sensor, the first candidate associated dependent air sensor is decided as the associated dependent air sensor. There may also be multiple first candidate associated dependent air sensors. If there are multiple first candidate associated dependent air sensors, the priority of the POI corresponding to the first candidate associated dependent air sensor is collected. The decision method of the POI priority has been explained above and will not be repeated here. The first candidate associated dependent air sensor corresponding to the POI with the lowest priority is decided as the associated dependent air sensor. At this time, the number of associated dependent air sensors is 1. If the first candidate associated dependent air sensor corresponds to multiple POIs, the POI with the highest priority among the multiple POIs is decided as the POI corresponding to the first candidate associated dependent air sensor.

[0042] If there is no first candidate associated dependent air sensor, then the air sensor whose POI influence range and associated dependent POI influence range have overlapping POIs is decided as the second candidate associated dependent air sensor, and the second candidate associated dependent air sensors are queued according to the exhaustive method to output multiple candidate associated dependent air sensor queues, and the number of second candidate associated dependent air sensors in each candidate associated dependent air sensor queue is greater than or equal to 2, and the POI influence ranges corresponding to the second candidate associated dependent air sensors in the candidate associated dependent air sensor queues are merged to output multiple merged POI influence ranges, and each candidate associated dependent air sensor queue corresponds to a merged POI influence range, and the candidate associated dependent air sensor queues are screened to completely cover the associated dependent POI influence range with the corresponding merged POI influence range, and the candidate associated dependent air sensor queue with the least number of second candidate associated dependent air sensors is decided as the associated dependent queue, and the second candidate associated dependent air sensor corresponding to the associated dependent queue is decided as the associated dependent air sensor, and at this time the number of associated dependent air sensors is greater than or equal to 2.

[0043] Specifically, deciding on the retest log based on the alarm status includes: deciding on the pollution source type and pollution source based on the alarm status; collecting retest monitoring point information; deciding on the number of retest monitoring points based on the association between the pollution source type, pollution source and the preset number of retest monitoring points; deciding on the first retest monitoring point based on the number of retest monitoring points, preset retest rules and retest monitoring point information, the first retest monitoring point being the retest monitoring point for this pollution source; collecting a retest report based on the pollution source type and pollution source, the retest report including the POI to be used; generating a retest method based on the retest monitoring points and the retest report.

[0044] The retest log not only includes starting candidate air sensors or associated dependent air sensors for temporary monitoring, but also requires arranging retest monitoring points to retest the alarm air sensors as soon as possible.

[0045] In this embodiment, the pollution source type and pollution source (i.e., the second pollution source mentioned above) are polled from the alarm status, and the re-test monitoring point information is collected from the database. Different numbers of re-test monitoring points are arranged for different pollution source types and pollution sources for re-testing, thereby improving the re-testing efficiency and re-testing accuracy. The preset re-test monitoring point quantity association is collected from the database, and the preset re-test monitoring point quantity association is the relationship between the pollution source type and pollution source and the number of re-test monitoring points. The preset re-test monitoring point quantity association is determined according to the completed re-test results, so that the number of re-test monitoring points required this time can be decided according to the pollution source type and pollution source this time.

[0046] Preset retest rules are collected from the database, the preset retest rules are the correspondence between the number of retest monitoring points and the weight of the retest monitoring points, the retest monitoring point information includes the weight of the retest monitoring point and the current state, the current state includes the working state and the resting state, and the number of retest monitoring points that are in working state and whose weights satisfy the preset retest rules are selected from the retest monitoring points, and the selected retest monitoring points are decided as the first retest monitoring points. The retest report is collected from the pollution source retest resource library according to the pollution source type and pollution source, and the retest report includes the POI to be used, that is, the POI that may be used in this retest, to reduce the possibility that the retest monitoring point does not carry sufficient POI, thereby increasing the possibility of retest time, and the retest report also includes retest steps, and the first retest monitoring point and the retest report of this time are jointly decided as the retest method, and the first retest monitoring point retests the pollution source according to the retest method, which effectively shortens the retest time and improves the retest efficiency.

[0047] After each retest of the pollution source, the retest results will be collected from the retest monitoring points. The artificial intelligence analysis model will automatically extract useful information, such as the retest method, and store the information in the pollution source retest resource library, thereby improving the pollution source retest resource library. Among them, the artificial intelligence analysis model is a pre-trained model and is not specifically limited here.

[0048] Figure 2 A structural block diagram of a road navigation monitoring system based on big data provided in an embodiment of the present application.

[0049] like Figure 2 As shown in the figure, the road navigation monitoring system based on big data mainly includes: The first collection unit 201 is used to collect pollution source request data and navigation routes. The pollution source request data includes radiation POI, and the radiation POI is the POI corresponding to the gas detected by the alarm air sensor; An alarm decision unit 202 is used to make an alarm decision for an air sensor based on the pollution source request data and the navigation route; The second collection unit 203 is used to collect monitoring records of the alarm air sensor; A state decision unit 204, used to decide the alarm state according to the monitoring records; The log decision unit 205 is used to decide the retest log according to the alarm status, and the retest log includes candidate air sensors, associated dependent air sensors and retest methods.

[0050] As an optional implementation of this embodiment, the alarm decision unit 202 is also specifically used to decide on an alarm air sensor based on the pollution source request data and the navigation route, including: polling the first air sensor from the navigation route, the first air sensor being an air sensor at a preset distance from the radiation POI; collecting the first monitoring record of the first air sensor; performing concentration distribution analysis on the first monitoring record to decide whether there is an alarm; and deciding the first air sensor corresponding to the first monitoring record with an alarm as an alarm air sensor.

[0051] As an optional implementation manner of this embodiment, the state decision unit 204 is also specifically used to decide the alarm state based on the monitoring records, including: analyzing the monitoring records to decide the type of pollution source; deciding the first pollution source based on the pollution source type and preset rules; collecting completed re-test results; deciding the last re-test time and the last re-test status based on the completed re-test results; deciding the second pollution source based on the last re-test time, the last re-test status and the first pollution source; deciding the alarm state based on the pollution source type and the second pollution source.

[0052] As an optional implementation of this embodiment, the log decision unit 205 is also specifically used to, before deciding to retest the log based on the alarm status, also include: collecting the first POI and industrial projects within the air monitoring point, the first POI being all POIs within the air monitoring point; deciding the second POI based on the industrial project, the second POI being the POI required for the industrial project; deciding the first priority of the first POI based on the first weight association, the first POI including the second POI; deciding the second priority of the second POI based on the second weight association and the industrial project; correcting the priority of the second POI based on the first priority and the second priority; deciding the focus range based on the priority of the POI and the range of the POI; queuing the focus range and outputting multiple focus POIs, the focus POI having a candidate air sensor installed therein.

[0053] As an optional implementation manner of this embodiment, the log decision unit 205 is also specifically used to decide the retest log according to the alarm state, including: determining the first POI influence range according to the alarm air sensor; determining the POI of interest that has an intersection with the first POI influence range as the first POI of interest; determining the degree of intersection between the first POI of interest and the first POI influence range; sorting the first POI of interest according to the degree of intersection; determining the first POI of interest that has a preset ranking in the front and a degree of intersection greater than the preset degree of intersection as the second POI influence range; sending a start instruction to the candidate air sensor corresponding to the second POI influence range; determining the total POI formed by the second POI influence range as the candidate POI influence range; comparing the candidate POI influence range with the first POI influence range, and outputting the associated dependent POI influence range, the associated dependent POI influence range being the POI included in the first POI influence range but not included in the candidate POI influence range; determining the associated dependent air sensor according to the POI influence range of the air sensor in the air monitoring point; and sending an associated dependent instruction to the associated dependent air sensor.

[0054] As an optional implementation manner of the present embodiment, the log decision unit 205 is also specifically used to decide on the associated dependent air sensor based on the POI influence range of the air sensor in the air monitoring point, including: deciding the air sensor whose POI influence range includes the associated dependent POI influence range as the first candidate associated dependent air sensor; if there are multiple first candidate associated dependent air sensors, collecting the priority of the POI corresponding to the first candidate associated dependent air sensor, and the POI corresponding to the first candidate associated dependent air sensor is the POI included in the gas detected by the first candidate associated dependent air sensor; deciding the first candidate associated dependent air sensor corresponding to the POI with the lowest priority as the associated dependent air sensor; if there is no first candidate associated dependent air sensor, deciding the POI influence range and the associated dependent POI influence range as the first candidate associated dependent air sensor. The air sensor with an overlapping associated POI influence range is decided as the second candidate associated dependent air sensor; the second candidate associated dependent air sensors are queued to output multiple candidate associated dependent air sensor queues, each candidate associated dependent air sensor queue includes at least two second candidate associated dependent air sensors; the POI influence ranges corresponding to the second candidate associated dependent air sensors in the candidate associated dependent air sensor queues are merged to output multiple merged POI influence ranges; the candidate associated dependent air sensor queue with the merged POI influence range completely covering the associated dependent POI influence range and the least number of second candidate associated dependent air sensors is decided as the associated dependent queue; the second candidate associated dependent air sensors corresponding to the associated dependent queue are decided as the associated dependent air sensor.

[0055] As an optional implementation manner of this embodiment, the log decision unit 205 is also specifically used to decide the retest log based on the alarm status, including: deciding the pollution source type and pollution source based on the alarm status; collecting retest monitoring point information; deciding the number of retest monitoring points based on the association between the pollution source type, pollution source and the preset number of retest monitoring points; deciding the first retest monitoring point based on the number of retest monitoring points, preset retest rules and retest monitoring point information, the first retest monitoring point being the retest monitoring point of this pollution source; collecting a retest report based on the pollution source type and pollution source, the retest report including the POI to be used; generating a retest method based on the retest monitoring point and the retest report.

[0056] The technical monitoring points in the relevant field can be clearly understood. For the convenience and simplicity of description, the specific working processes of the above-described devices and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0057] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0058] In addition, each functional unit in each embodiment of the present application can be integrated into one processing unit, or each unit can be physically provided separately, or two or more units can be integrated into one unit. The above integrated unit can be implemented in the form of hardware or in the form of software functional units. The above is only an implementation method of the present application, and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the specification and drawings of this application, or directly or indirectly used in other related technical fields, is also included in the patent protection scope of the present application.

[0059] The specific implementation methods of the invention are described in detail above, but they are only examples, and the present application is not limited to the specific implementation methods described above. For technical monitoring points in this field, any equivalent modification or substitution of the invention is also within the scope of the present application. Therefore, equal transformations, modifications, improvements, etc. made without departing from the spirit and principle scope of the present application should be included in the scope of the present application.

Claims

1. A road navigation monitoring method based on big data, characterized in that: include: Collecting pollution source request data and navigation routes, wherein the pollution source request data includes radiation POI, and the radiation POI is the POI corresponding to the gas detected by the alarm air sensor; Alerting the air sensor according to the pollution source request data and the navigation route decision; Collecting monitoring records of the alarm air sensor; Determine an alarm state based on the monitoring records; A retest log is determined according to the alarm status, wherein the retest log includes candidate air sensors, associated dependent air sensors and a retest method.

2. A road navigation monitoring method based on big data as claimed in claim 1, characterized in that: The air sensor alarm according to the pollution source request data and the navigation route decision includes: Polling a first air sensor from the navigation route, where the first air sensor is an air sensor at a preset distance from the radiation POI; Collecting a first monitoring record of the first air sensor; Performing concentration distribution analysis on the first monitoring record to determine whether to issue an alarm; The first air sensor corresponding to the first monitoring record with an alarm is determined as an alarm air sensor.

3. The road navigation monitoring method based on big data as claimed in claim 1, characterized in that: The determining of the alarm state according to the monitoring record includes: Analyze the monitoring records and determine the type of pollution source; Determine the first pollution source according to the pollution source type and preset rules; Collect the completed retest results; Determine the last retest time and the last retest status based on the completed retest results; Determine a second pollution source based on the last retest time, the last retest status, and the first pollution source; An alarm state is determined based on the pollution source type and the second pollution source.

4. The road navigation monitoring method based on big data as claimed in claim 1, characterized in that: Before retesting the log according to the alarm status decision, the method further includes: Collecting the first POI and industrial projects within the air monitoring point, where the first POI is all POIs within the air monitoring point; Determine a second POI according to the industrial project, wherein the second POI is a POI required for the industrial project; Determine a first priority of the first POI according to a first weight association, wherein the first POI includes the second POI; Determine a second priority of the second POI according to a second weight association and the industrial project; modifying the priority of the second POI according to the first priority and the second priority; Determine the scope of attention based on the priority and range of POIs; The focus range is queued and a plurality of focus POIs are output, wherein candidate air sensors are installed in the focus POIs.

5. A road navigation monitoring method based on big data as claimed in claim 4, characterized in that: The retest log is determined based on the alarm status, including: Determine the first POI influence range according to the alarm air sensor; Determine a POI of interest that overlaps with the influence range of the first POI as a first POI of interest; Determine the degree of intersection between the first POI of interest and the influence range of the first POI; sorting the first POIs of interest according to the intersection degree; The first concerned POI having a ranking position in front of a preset position and a crossing degree greater than a preset crossing degree is determined as the influence range of the second POI; Sending a start instruction to the candidate air sensors corresponding to the influence range of the second POI; The total POI formed by the second POI influence range is determined as the candidate POI influence range; Compare the candidate POI influence range with the first POI influence range, and output an associated dependent POI influence range, wherein the associated dependent POI influence range is a POI included in the first POI influence range but not included in the candidate POI influence range; The decision on the associated dependent air sensor is made based on the POI impact range of the air sensor in the air monitoring point; An association-dependent instruction is sent to the association-dependent air sensor.

6. A road navigation monitoring method based on big data as claimed in claim 5, characterized in that: The decision of associating dependent air sensors according to the POI influence range of the air sensors in the air monitoring points includes: Determine the air sensor whose possible POI influence range includes the associated dependent POI influence range as the first candidate associated dependent air sensor; If there are multiple first candidate association-dependent air sensors, the priority of the POI corresponding to the first candidate association-dependent air sensor is collected, and the POI corresponding to the first candidate association-dependent air sensor is the POI included in the gas detected by the first candidate association-dependent air sensor; Decide the first candidate association-dependent air sensor corresponding to the POI with the lowest priority as the association-dependent air sensor; If the first candidate associated dependent air sensor is not present, an air sensor having an intersection between the possible POI influence range and the associated dependent POI influence range is determined as a second candidate associated dependent air sensor; Queuing the second candidate association-dependent air sensors, and outputting a plurality of candidate association-dependent air sensor queues, each of the candidate association-dependent air sensor queues including at least two of the second candidate association-dependent air sensors; Merging the POI influence ranges corresponding to the second candidate association-dependent air sensor in the candidate association-dependent air sensor queue, and outputting a plurality of merged POI influence ranges; The combined POI influence range completely covers the associated dependent POI influence range, and the candidate associated dependent air sensor queue with the least number of second candidate associated dependent air sensors is determined as the associated dependent queue; The second candidate association-dependent air sensor corresponding to the association-dependent queue is decided as the association-dependent air sensor.

7. The road navigation monitoring method based on big data as claimed in claim 1, characterized in that: The retest log is determined based on the alarm status, including: Determine the type and source of pollution based on the alarm status; Collect information on retest monitoring points; Determine the number of retest monitoring points based on the type of pollution source, the pollution source and the number of preset retest monitoring points; Determine a first retest monitoring point according to the number of retest monitoring points, preset retest rules and the retest monitoring point information, wherein the first retest monitoring point is the retest monitoring point of the pollution source; Collecting a retest report based on the pollution source type and the pollution source, wherein the retest report includes a POI to be used; A retest method is generated according to the retest monitoring points and the retest report.

8. A road navigation monitoring system based on big data, characterized in that: include: A first collection unit is used to collect pollution source request data and a navigation route, wherein the pollution source request data includes a radiation POI, and the radiation POI is a POI corresponding to the gas detected by the alarm air sensor; An alarm decision unit, used for deciding to alarm the air sensor according to the pollution source request data and the navigation route; A second collection unit is used to collect monitoring records of the alarm air sensor; A state decision unit, used for deciding an alarm state according to the monitoring record; A log decision unit, configured to decide a retest log according to the alarm state, wherein the retest log includes a candidate air sensor, an associated dependent air sensor, and a retest method; The road navigation monitoring system based on big data is used to execute the road navigation monitoring method based on big data as described in any one of claims 1-7.

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