A road mobile monitoring method and system based on big data

Abstract

This application relates to the field of big data analysis technology, and particularly to a road cruise monitoring method and system based on big data, which collect pollution source request data and cruise routes. The pollution source request data includes radiation POIs, and the radiation POIs are the POIs corresponding to the gases detected by alarm air sensors. Based on the pollution source request data and the cruise routes, alarm air sensors are determined. The monitoring records of the alarm air sensors are collected. Based on the monitoring records, alarm states are determined. Based on the alarm states, retest logs are determined, and the retest logs include candidate air sensors, associated dependent air sensors, and retest methods. The present invention can effectively solve the problems of inaccurate cruise monitoring data, large deviations in multiple data measurements, and isolated measurement data results, and ensure the effectiveness of the cruise monitoring results.

Description

Technical Field

[0001] This application relates to the field of big data analysis technology, and in particular, to a road cruising monitoring method and system based on big data. Background Art

[0002] Cruising is an environmental monitoring technology that mainly uses vehicle-mounted rapid monitoring equipment to conduct continuous automatic monitoring during travel. Combining with fixed-point monitoring, qualitative and quantitative analysis of pollutants is carried out, and the spatial continuous distribution of pollutants is displayed based on geographical location information. The main difference between cruising monitoring and general mobile monitoring vehicles or mobile laboratories lies in its continuous automatic monitoring ability during travel. Cruising monitoring can obtain as much qualitative and quantitative information of pollutants as possible during travel, and stop at pollution points for remeasurement, or use other equipment to assist in the qualitative and quantitative analysis of pollutants.

[0003] However, in the prior art, inaccurate monitoring data, large deviations in multiple data measurements, and isolated measurement data results often occur during the cruising monitoring process, and it is difficult to ensure the effectiveness of the cruising monitoring results. Summary of the Invention

[0004] To achieve the above object, the present application provides the following technical solutions:

[0005] According to the first aspect of the present invention, the present invention claims protection for a road cruising monitoring method based on big data, including:

[0006] Collect pollution source request data and a cruising route, where 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;

[0007] Determine the alarm air sensor based on the pollution source request data and the cruising route;

[0008] Collect the monitoring records of the alarm air sensor;

[0009] Determine the alarm status based on the monitoring records;

[0010] Determine the remeasurement log based on the alarm status, and the remeasurement log includes candidate air sensors, associated dependent air sensors, and remeasurement methods.

[0011] Further, the determining the alarm air sensor based on the pollution source request data and the cruising route includes:

[0012] Poll the first air sensor from the cruising route, and the first air sensor is the air sensor at a preset distance from the radiation POI;

[0013] Collect the first monitoring record of the first air sensor;

[0014] Perform a concentration distribution analysis on the first monitoring record to decide whether to give an alarm;

[0015] Decide the first air sensor corresponding to the first monitoring record with an alarm as an alarm air sensor.

[0016] Further, the decision of the alarm status based on the monitoring record includes:

[0017] Analyze the monitoring record to decide the type of pollution source;

[0018] Decide the first pollution source based on the type of pollution source and preset rules;

[0019] Collect the completed retest results;

[0020] Decide the last retest time and the last retest status based on the completed retest results;

[0021] Decide the second pollution source based on the last retest time, the last retest status and the first pollution source;

[0022] Decide the alarm status based on the type of pollution source and the second pollution source.

[0023] Further, before deciding the retest log based on the alarm status, the method further includes:

[0024] Collect the first POI and industrial projects within the air monitoring point, where the first POI is all POIs within the air monitoring point;

[0025] Decide the second POI based on the industrial project, where the second POI is the POI required by the industrial project;

[0026] Decide the first priority of the first POI based on the first weight association, where the first POI includes the second POI;

[0027] Decide the second priority of the second POI based on the second weight association and the industrial project;

[0028] Modify the priority of the second POI based on the first priority and the second priority;

[0029] Decide the scope of concern based on the priority of the POI and the scope of the POI;

[0030] Queue the scope of concern and output multiple POIs of concern, where candidate air sensors are installed within the POIs of concern.

[0031] Further, the decision of the retest log based on the alarm status includes:

[0032] Determine the influence range of the first POI based on the alarm air sensor;

[0033] Determine the POI of interest that intersects with the influence range of the first POI as the first POI of interest;

[0034] Determine the intersection degree between the first POI of interest and the influence range of the first POI;

[0035] Sort the first POIs of interest according to the intersection degree;

[0036] Determine the POIs of interest with sorting positions in the front preset positions and the intersection degree greater than the preset intersection degree as the influence range of the second POI;

[0037] Send a start instruction to the candidate air sensor corresponding to the influence range of the second POI;

[0038] Determine the total POI formed by the influence range of the second POI as the candidate POI influence range;

[0039] Compare the candidate POI influence range with the influence range of the first POI, and output the associated dependent POI influence range, where the associated dependent POI influence range is the POIs included in the influence range of the first POI but not included in the candidate POI influence range;

[0040] Determine the associated dependent air sensor based on the influence range of the POI that the air sensor in the air monitoring point can affect;

[0041] Send an associated dependent instruction to the associated dependent air sensor.

[0042] Further, the determining the associated dependent air sensor based on the influence range of the POI that the air sensor in the air monitoring point can affect includes:

[0043] Determine the air sensors whose influence range of the POI that can be affected includes the influence range of the associated dependent POI as the first candidate associated dependent air sensors;

[0044] If there are multiple first candidate associated dependent air sensors, collect the priorities of the POIs corresponding to the first candidate associated dependent air sensors, where the POIs corresponding to the first candidate associated dependent air sensors are the POIs included in the gas detected by the first candidate associated dependent air sensors;

[0045] Determine the first candidate associated dependent air sensor corresponding to the POI with the lowest priority as the associated dependent air sensor;

[0046] If there is no such first candidate associated dependent air sensor, then the air sensor whose affected range of the POI that can be affected intersects with the affected range of the associated dependent POI is determined as the second candidate associated dependent air sensor;

[0047] Queue the second candidate associated dependent air sensors, and output multiple queues of candidate associated dependent air sensors. Each queue of candidate associated dependent air sensors includes at least two of the second candidate associated dependent air sensors;

[0048] Merge the affected ranges of the POI that can be affected corresponding to the second candidate associated dependent air sensors in the queue of candidate associated dependent air sensors, and output multiple merged affected ranges of the POI;

[0049] Determine the queue of candidate associated dependent air sensors in which the merged affected range of the POI completely covers the affected range of the associated dependent POI and the number of the second candidate associated dependent air sensors is the least as the associated dependent queue;

[0050] Determine the second candidate associated dependent air sensors corresponding to the associated dependent queue as the associated dependent air sensors.

[0051] Further, the decision of the retest log based on the alarm status includes:

[0052] Determine the type of pollution source and the pollution source based on the alarm status;

[0053] Collect information of the retest monitoring points;

[0054] Associate and determine the number of retest monitoring points based on the type of pollution source, the pollution source and the preset number of retest monitoring points;

[0055] Determine the first retest monitoring points based on the number of retest monitoring points, the preset retest rules and the information of the retest monitoring points. The first retest monitoring points are the retest monitoring points of the current pollution source;

[0056] Collect a retest report based on the type of pollution source and the pollution source. The retest report includes POIs to be used;

[0057] Generate a retest method based on the retest monitoring points and the retest report.

[0058] According to the second aspect of the present invention, the present invention claims protection for a road mobile monitoring system based on big data, including:

[0059] A first collection unit for collecting pollution source request data and a mobile route. The pollution source request data includes radiation POIs, and the radiation POIs are POIs corresponding to the gases detected by the alarm air sensors;

[0060] An alarm decision-making unit, configured to decide an alarm air sensor according to the pollution source request data and the vehicle routing;

[0061] A second acquisition unit, configured to acquire the monitoring records of the alarm air sensor;

[0062] A status decision-making unit, configured to decide an alarm status according to the monitoring records;

[0063] A log decision-making unit, configured to decide a retest log according to the alarm status, where the retest log includes candidate air sensors, associated dependent air sensors, and retest methods;

[0064] The road vehicle routing monitoring system based on big data is configured to execute the road vehicle routing monitoring method based on big data.

[0065] This application relates to the technical field of big data analysis, and in particular to a road vehicle routing monitoring method and system based on big data. Pollution source request data and vehicle routing are acquired, where the pollution source request data includes radiation POIs, and the radiation POIs are POIs corresponding to the gases detected by the alarm air sensors; an alarm air sensor is decided according to the pollution source request data and the vehicle routing; the monitoring records of the alarm air sensor are acquired; an alarm status is decided according to the monitoring records; a retest log is decided according to the alarm status, where the retest log includes candidate air sensors, associated dependent air sensors, and retest methods. The present invention can effectively solve the problems of inaccurate vehicle routing monitoring data, large deviations in multiple data measurements, and isolated measurement data results, and ensure the effectiveness of the vehicle routing monitoring results. Description of the Drawings

[0066] Figure 1 It is a working flowchart of a road vehicle routing monitoring method based on big data requested to be protected by an embodiment of this application;

[0067] Figure 2 It is a structural block diagram of a road vehicle routing monitoring system based on big data requested to be protected by an embodiment of this application. Detailed Embodiments

[0068] Next, the technical solutions in the embodiments of this application will be clearly and completely described with reference to the accompanying drawings in the embodiments of this application. Apparently, the described embodiments are only a part of the embodiments of this application, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in this application without creative efforts shall fall within the protection scope of this application.

[0069] The terms "first", "second", and "third" in this application are only used for descriptive purposes and should not be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first", "second", and "third" may explicitly or implicitly include at least one of such features. In the description of this application, the meaning of "a plurality" is at least two, such as two, three, etc., unless otherwise specifically defined. In the embodiments of this application, all directional indications (such as up, down, left, right, front, back...) are only used to explain the relative range relationship and motion state between components in a specific posture (as shown in the drawings). If the specific posture changes, the directional indications will also change accordingly. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. 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 not listed, or optionally also includes other steps or units inherent to these processes, methods, products, or POIs.

[0070] Reference to "embodiment" herein means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of this application. The phrase appearing in various scopes in the specification does not necessarily refer to the same embodiment, nor is it an independent or candidate embodiment mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0071] As Figure 1 shown, a road driving monitoring method based on big data, the main process of which is described as follows (Steps S101 - S105):

[0072] Step S101: Collect pollution source request data and driving route.

[0073] Among them, the pollution source request data includes radiation POIs. The radiation POIs are the POIs corresponding to the gases detected by the alarm air sensors. The driving route includes the ranges of each air sensor and the distribution status of each POI in the air monitoring points.

[0074] In this embodiment, the pollution source request data is collected from each pollution source, and the driving route is collected from the database.

[0075] Step S102: Determine the alarm air sensors based on the pollution source request data and the driving route.

[0076] After the pollution source request data is collected, the alarm air sensors are polled from the driving route according to the pollution source request data, and the ranges of the alarm air sensors are determined.

[0077] 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.

[0078] 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.

[0079] Step S103: collecting monitoring records of alarm air sensors.

[0080] The monitoring records of the alarm air sensors are collected from the database to facilitate subsequent decision-making on the alarm status.

[0081] Step S104: determine the alarm status based on the monitoring records.

[0082] 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.

[0083] In this embodiment, the monitoring records are analyzed by a preset pollution source analysis model to output the pollution source type. Here, the preset pollution source analysis model is not specifically limited. The preset rules are collected from the database, and the preset rules are the corresponding relationships between the pollution source types and the pollution sources. Therefore, the first pollution source can be determined through the pollution source type and the preset rules. The first pollution source is the reason 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. Thus, 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. Calculate the first span between the last retest time and the current time, and collect the corresponding relationship between the pollution source and the span from the database. Since some pollution sources will not occur again in a short time, some possible pollution sources can be excluded through the first span of this time, and thus the second pollution source is determined, that is, the first pollution source includes the second pollution source. The pollution source type and the second pollution source are jointly determined as the alarm status.

[0084] Step S105: Determine the retest log according to the alarm status.

[0085] The retest log includes the candidate air sensor, the associated dependent air sensor, and the retest method.

[0086] When an alarm occurs, the alarm air sensor cannot monitor the intelligent air monitoring point well. At this time, other air sensors (candidate air sensors and / or associated dependent air sensors) need to be used to complete the monitoring, so as to reduce the impact of the alarm, and an appropriate retest method is adopted to perform the retest as soon as possible.

[0087] Specifically, before determining the retest log according to the alarm status, the method further includes: collecting the first POI and industrial projects in the air monitoring point, where the first POI is all the POIs in the air monitoring point; determining the second POI according to the industrial project, and the second POI is the POI required by the industrial project; associating and determining the first priority of the first POI according to the first weight, and the first POI includes the second POI; determining the second priority of the second POI according to the second weight association and the industrial project; correcting the priority of the second POI according to the first priority and the second priority; determining the attention range according to the priority of the POI and the range of the POI; queuing the attention range to output multiple attention POIs, and candidate air sensors are installed in the attention POIs.

[0088] In this embodiment, the statuses of all the 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 the POIs are expressed as the first POI, and the POIs required by the industrial project are determined as the second POI, that is, the second POI is a part of the first POI.

[0089] Collect the first weight association and the second weight association from the database. The first weight association is the corresponding association relationship between POIs and priorities, and the second weight association is the corresponding association relationship between industrial projects and priorities. Decide the first priority of each first POI through the first weight association, and decide the second priority of each industrial project through the second weight association. Then, decide the second priority of the industrial project as the second priority of the corresponding second POI. At this time, the second POI has both the first priority and the second priority. 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. Decide the POI score by multiplying the weight score corresponding to the first priority by the first weight and adding the result to the product of the weight score corresponding to the second priority and the second weight. The first weight and the second weight are preset, and specific values are not specifically defined here. Collect the corresponding relationship between the POI score and the priority from the database. Therefore, the final priority of each second POI can be decided by the POI score. The priority of the POIs other than the second POI in the first POI is the corresponding first priority. Among them, the priority also has three weights, namely weight I, weight II, and weight III.

[0090] Decide the range corresponding to the POI with the priority of weight I as the attention range. Mark the attention range on the driving route and calculate the distance between every two attention ranges. Divide the two ranges with a distance less than the preset distance into a queue, and output multiple queues. Each queue can have multiple ranges, but for each range, the distance from it to other ranges in the queue must be less than the preset distance. Connect the multiple ranges in each queue on the driving route, and decide the POIs enclosed by the connection as the attention POIs. Similarly, a queue can also have only one range. Then, decide the POIs with the range as the center and the preset distance as the radius as the attention POIs, and send the attention POIs to the work monitoring point, so that the work monitoring point installs candidate air sensors in the attention POIs. Among them, the preset distance is decided according to the detection status of the candidate air sensor. For example, it can be the detection distance of the candidate air sensor.

[0091] When deciding the attention POIs, the air monitoring points can also be divided into several small POIs according to the preset division rules. Decide the small POIs with the POIs having the priority of weight I as the attention POIs and install candidate air sensors. Among them, the preset division rules are preset and not specifically defined here.

[0092] Specifically, making a retest log based on the alarm status decisions, including: determining the influence range of the first POI based on the alarm air sensor; determining the POIs of concern that intersect with the influence range of the first POI as the first POIs of concern; determining the intersection degree between the first POIs of concern and the influence range of the first POI; sorting the first POIs of concern according to the intersection degree; determining the POIs within the first preset ranking positions and with an intersection degree greater than the preset intersection degree 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; determining the total POIs formed by the influence range of the second POI as the candidate influence range of the POI; comparing the candidate influence range of the POI with the influence range of the first POI, and outputting the associated dependent influence range of the POI, where the associated dependent influence range of the POI is the POIs that are included in the influence range of the first POI but not included in the candidate influence range of the POI; determining the associated dependent air sensors based on the influence range of the POI that the air sensors within the air monitoring points can affect; sending an associated dependent instruction to the associated dependent air sensors.

[0093] In this embodiment, when a pollution source occurs in the air sensor, first find a suitable candidate air sensor and enable it. For the associated dependent influence range of the POI that the candidate air sensor cannot monitor, then start the associated dependent air sensor for monitoring. Thus, the candidate air sensor and the associated dependent air sensor can jointly complete the monitoring of the influence range of the first POI, reducing the impact caused by the pollution source.

[0094] The specific steps are as follows: Determine the POIs monitored by the alarm air sensor as the influence range of the first POI, determine the POIs of concern that have a range intersection with the influence range of the first POI as the first POIs of concern, calculate the area of the intersection part between the first POIs of concern and the influence range of the first POI and the area of the influence range of the first POI according to the pixel counting method, and calculate the intersection degree through the formula: intersection degree = area of the intersection part / area of the influence range of the first POI. Sort the first POIs of concern from high to low according to the intersection degree, determine the POIs within the first preset ranking positions and with an intersection degree greater than the preset intersection degree as the influence range of the second POI, where the preset ranking positions and the preset intersection degree are set in advance and are not specifically limited here. Send a start instruction to the candidate air sensors corresponding to the influence range of the second POI, and when multiple candidate air sensors are started, determine the total POIs formed by the multiple influence ranges of the second POI as the candidate influence range of the POI.

[0095] Decide the first POI influence range that is not included in the candidate POI influence range as the associated dependent POI influence range, and determine the associated dependent air sensor based on the POI influence range that can be covered by the air sensor in the air monitoring point and the associated dependent POI influence range, and send an associated dependent instruction to the associated dependent air sensor. The associated dependent instruction is the air sensor rotation instruction, so that the associated dependent air sensor can detect the gas in the original POI influence range of the air sensor and the gas in the associated dependent POI influence range. Similarly, the associated dependent air sensor can be one or more.

[0096] Specifically, determining the associated dependent air sensor based on the POI influence range that can be covered by the air sensor in the air monitoring point includes: deciding the air sensor whose POI influence range that can be covered 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, collect the priorities of the POIs corresponding to the first candidate associated dependent air sensors, where 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; decide 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, decide the air sensor whose POI influence range that can be covered intersects with the associated dependent POI influence range as the second candidate associated dependent air sensor; queue the second candidate associated dependent air sensors to output multiple queues of candidate associated dependent air sensors, and each queue of candidate associated dependent air sensors includes at least two second candidate associated dependent air sensors; merge the POI influence ranges that can be covered corresponding to the second candidate associated dependent air sensors in the queue of candidate associated dependent air sensors to output multiple merged POI influence ranges; decide the queue of candidate associated dependent air sensors whose merged POI influence range completely covers the associated dependent POI influence range and has the fewest number of second candidate associated dependent air sensors as the associated dependent queue; decide the second candidate associated dependent air sensors corresponding to the associated dependent queue as the associated dependent air sensors.

[0097] In this embodiment, an air sensor whose POI influence range completely covers the associated dependent POI influence range is determined 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, then this first candidate associated dependent air sensor is determined 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, then the priorities of the POIs corresponding to the first candidate associated dependent air sensors are collected. The decision method of the POI priority has been described above and will not be elaborated here. The first candidate associated dependent air sensor corresponding to the POI with the lowest priority is determined as the associated dependent air sensor. At this time, the number of associated dependent air sensors is 1. Among them, if a first candidate associated dependent air sensor corresponds to multiple POIs, then the POI with the highest priority among these multiple POIs is determined as the POI corresponding to this first candidate associated dependent air sensor.

[0098] If there is no first candidate associated dependent air sensor, then an air sensor whose POI influence range has an intersection POI with the associated dependent POI influence range is determined as the second candidate associated dependent air sensor. The second candidate associated dependent air sensors are queued according to the exhaustive method, and multiple candidate associated dependent air sensor queues are output. The number of second candidate associated dependent air sensors in each candidate associated dependent air sensor queue is greater than or equal to 2. The POI influence ranges corresponding to the second candidate associated dependent air sensors in the candidate associated dependent air sensor queue are merged, and multiple merged POI influence ranges are output. Each candidate associated dependent air sensor queue corresponds to a merged POI influence range. The candidate associated dependent air sensor queues are screened, and the candidate associated dependent air sensor queue whose corresponding merged POI influence range completely covers the associated dependent POI influence range and has the smallest number of second candidate associated dependent air sensors is determined as the associated dependent queue. The second candidate associated dependent air sensors corresponding to the associated dependent queue are determined as the associated dependent air sensors. At this time, the number of associated dependent air sensors is greater than or equal to 2.

[0099] Specifically, the retest log is determined based on the alarm status, including: determining the pollution source type and pollution source based on the alarm status; collecting retest monitoring point information; determining the number of retest monitoring points based on the association of the pollution source type, pollution source, and the preset number of retest monitoring points; determining the first retest monitoring point based on the number of retest monitoring points, the preset retest rule, and the retest monitoring point information. The first retest monitoring point is the retest monitoring point of the current pollution source; collecting the retest report based on the pollution source type and pollution source. The retest report includes the POIs to be used; generating the retest method based on the retest monitoring points and the retest report.

[0100] The retest log not only includes starting the candidate air sensor or associating with the dependent air sensor for temporary monitoring, but also needs to arrange for retesting the alarm air sensor at the retest monitoring points as soon as possible.

[0101] In this embodiment, the pollution source type and the pollution source (i.e., the above-mentioned second pollution source) are polled from the alarm state, and the retest monitoring point information is collected from the database. For different pollution source types and pollution sources, different numbers of retest monitoring points are arranged for retesting, so as to improve the retest efficiency and accuracy. The preset retest monitoring point quantity association is collected from the database, and the preset retest monitoring point quantity association is the relationship between the pollution source type and the pollution source and the number of retest monitoring points. The preset retest monitoring point quantity association is determined according to the completed retest results, so that the number of retest monitoring points required for this time can be determined according to the pollution source type and the pollution source of this time.

[0102] The preset retest rules are collected from the database. The preset retest rules are the corresponding relationship between the number of retest monitoring points and the weights of the retest monitoring points. The retest monitoring point information includes the weights of the retest monitoring points and the current status. The current status includes the working status and the rest status. Select the number of retest monitoring points that are in the working state and whose weights of the retest monitoring points meet the preset retest rules from the retest monitoring points, and determine the selected retest monitoring points 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 the pollution source. The retest report includes the POIs to be used, that is, the POIs that may be used in this retest, reducing the possibility that the retest monitoring points carry insufficient POIs, thereby increasing the retest duration. The retest report also includes the retest steps. The first retest monitoring points and the retest report of this time are jointly determined as the retest method. The first retest monitoring points perform the pollution source retest according to this retest method, effectively shortening the retest duration and improving the retest efficiency.

[0103] After each pollution source retest, the retest results are collected from the retest monitoring points. The artificial intelligence analysis model will automatically extract useful information, such as: the retest method, and store this 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, which is not specifically limited here.

[0104] Figure 2 It is a structural block diagram of a road mobile monitoring system based on big data provided by an embodiment of the present application.

[0105] As Figure 2 shown, the road mobile monitoring system based on big data mainly includes:

[0106] The first acquisition unit 201 is used to acquire pollution source request data and the mobile route. The pollution source request data includes radiation POIs, and the radiation POIs are the POIs corresponding to the gases detected by the alarm air sensors;

[0107] An alarm decision-making unit 202, configured to decide an alarm air sensor according to pollution source request data and a cruise route;

[0108] A second acquisition unit 203, configured to acquire monitoring records of the alarm air sensor;

[0109] A status decision-making unit 204, configured to decide an alarm status according to the monitoring records;

[0110] A log decision-making unit 205, configured to decide a retest log according to the alarm status, where the retest log includes candidate air sensors, associated dependent air sensors, and retest methods.

[0111] As an alternative implementation manner of this embodiment, the alarm decision-making unit 202 is further specifically configured to decide an alarm air sensor according to pollution source request data and a cruise route, including: polling a first air sensor from the cruise route, where the first air sensor is an air sensor at a preset distance from a radiation POI; acquiring a 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 the alarm air sensor.

[0112] As an alternative implementation manner of this embodiment, the status decision-making unit 204 is further specifically configured to decide an alarm status according to the monitoring records, including: analyzing the monitoring records to decide a pollution source type; deciding a first pollution source according to the pollution source type and a preset rule; acquiring a completed retest result; deciding a last retest time and a last retest status according to the completed retest result; deciding a second pollution source according to the last retest time, the last retest status, and the first pollution source; and deciding an alarm status according to the pollution source type and the second pollution source.

[0113] As an alternative implementation manner of this embodiment, before deciding a retest log according to the alarm status, the log decision-making unit 205 is further specifically configured to: acquire a first POI and an industrial project in an air monitoring point, where the first POI is all POIs in the air monitoring point; decide a second POI according to the industrial project, where the second POI is a POI required by the industrial project; decide a first priority of the first POI according to a first weight association, where the first POI includes the second POI; decide a second priority of the second POI according to a second weight association and the industrial project; correct the priority of the second POI according to the first priority and the second priority; decide a focus range according to the priority of the POI and the range of the POI; queue the focus range, and output a plurality of focus POIs, where candidate air sensors are installed in the focus POIs.

[0114] As an alternative implementation of this embodiment, the log decision unit 205 is further specifically configured to decide on retest logs based on the alarm status, including: deciding on the first POI influence range based on the alarm air sensor; deciding on the POIs of concern that intersect with the first POI influence range as the first POIs of concern; deciding on the intersection degree between the first POIs of concern and the first POI influence range; sorting the first POIs of concern according to the intersection degree; deciding on the second POI influence range for the first POIs of concern whose sorting positions are in the front preset positions and whose intersection degrees are greater than the preset intersection degree; sending a start instruction to the candidate air sensors corresponding to the second POI influence range; deciding on the total POIs 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, where the associated dependent POI influence range is the POIs that are included in the first POI influence range but not included in the candidate POI influence range; deciding on the associated dependent air sensors based on the POI influence ranges that the air sensors in the air monitoring points can cover; and sending an associated dependent instruction to the associated dependent air sensors.

[0115] As an alternative implementation of this embodiment, the log decision unit 205 is further specifically configured to decide on the associated dependent air sensors based on the POI influence ranges that the air sensors in the air monitoring points can cover, including: deciding on the first candidate associated dependent air sensors for the air sensors whose POI influence ranges cover the associated dependent POI influence range; if there are multiple first candidate associated dependent air sensors, collecting the priorities of the POIs corresponding to the first candidate associated dependent air sensors, where the POIs corresponding to the first candidate associated dependent air sensors are the POIs included in the gases detected by the first candidate associated dependent air sensors; deciding on the first candidate associated dependent air sensor corresponding to the POI with the lowest priority as the associated dependent air sensor; if there are no first candidate associated dependent air sensors, deciding on the second candidate associated dependent air sensors for the air sensors whose POI influence ranges intersect with the associated dependent POI influence range; queuing the second candidate associated dependent air sensors to output multiple queues of candidate associated dependent air sensors, where each queue of candidate associated dependent air sensors includes at least two second candidate associated dependent air sensors; merging the POI influence ranges corresponding to the second candidate associated dependent air sensors in the queues of candidate associated dependent air sensors to output multiple merged POI influence ranges; deciding on the queue of candidate associated dependent air sensors whose merged POI influence ranges completely cover the associated dependent POI influence range and whose number of second candidate associated dependent air sensors is the least as the associated dependent queue; and deciding on the second candidate associated dependent air sensors corresponding to the associated dependent queue as the associated dependent air sensors.

[0116] As an alternative implementation of this embodiment, the log decision unit 205 is further specifically configured to make a retest log decision based on the alarm status, including: making a decision on the pollution source type and pollution source based on the alarm status; collecting retest monitoring point information; making an associated decision on the number of retest monitoring points based on the pollution source type, pollution source, and the preset number of retest monitoring points; making a decision on the first retest monitoring point based on the number of retest monitoring points, the preset retest rules, and the retest monitoring point information, where the first retest monitoring point is the retest monitoring point for the current pollution source; collecting a retest report based on the pollution source type and pollution source, and the retest report includes POIs to be used; generating a retest method based on the retest monitoring points and the retest report.

[0117] Those skilled in the art can clearly understand that for the sake of convenience and brevity of description, the specific working processes of the above-described devices and units can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0118] In 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 merely illustrative. For example, the division of units is only a logical function division, and there can 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 displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces, and the indirect couplings or communication connections of devices or units can be in electrical, mechanical, or other forms.

[0119] In addition, each functional unit in various embodiments of the present application can be integrated into one processing unit, or each unit can be physically separate, or two or more units can be integrated into one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units. The above is only the implementation mode 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 specification and drawings of the present application, or directly or indirectly applied to other related technical fields, shall be equally included in the patent protection scope of the present application.

[0120] The specific implementation modes of the invention have been described in detail above, but they are only examples, and the present application is not limited to the specific implementation modes described above. For those skilled in the art, any equivalent modification or substitution of the invention is also within the scope of the present application. Therefore, all equivalent transformations, modifications, and improvements made without departing from the spirit and principles of the present application should be covered by 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 based on the alarm status, wherein the retest log includes candidate air sensors, associated dependent air sensors, and a retest method; 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; Determine the first air sensor corresponding to the first monitoring record with an alarm as an alarm air sensor; 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; Determine an alarm state according to the type of the pollution source and the second pollution source; 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.

2. A 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.

3. A road navigation monitoring method based on big data as claimed in claim 2, 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.

4. 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 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.

5. 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 1-4.

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