DEVICE FOR HIGH-COVERAGE MONITORING OF VEHICLE INTERIOR AIR QUALITY

Abstract

The disclosure provides a device for high-coverage monitoring of vehicle interior air quality. The device includes at least two types of mobile monitoring vehicles for atmospheric pollutants. At least one type of mobile monitoring vehicles is an optimal group of certain number of vehicles selected from candidate vehicles, by installing air pollution detection equipment on the mobile monitoring vehicles, to monitor air quality of the urban area. A method for selection of the optimal group of certain number of vehicles includes decomposing the road network of the urban area into road segment units (RSUs); initializing a database of RSUs, which comprises RSU numbers, RSU locations, and RSU detection records; counting the traveling route of each candidate vehicle that travels within a certain period of time; recording the number of times that each candidate vehicle passes each RSU.

Claims

1. A device for high-coverage monitoring of vehicle interior air quality, the device comprises at least two types of mobile monitoring vehicles for atmospheric pollutants; wherein at least one type of mobile monitoring vehicles is an optimal group of a plurality of vehicles selected from candidate vehicles, the mobile monitoring vehicles comprising air pollution detection equipment, to monitor air quality of the urban area; a method for selection of the optimal group of certain number of vehicles comprising: 1) decomposing the road network of the urban area into road segment units (RSUs); initializing a database of RSUs, which comprises RSU numbers, RSU locations, and RSU detection records; 2) counting the traveling route of each candidate vehicle that travels within a certain period of time; recording the number of times that each candidate vehicle passes each RSU; a maximum number of times for each mobile monitoring vehicle passing any RSU within a counting period is 1; obtaining a statistical distribution graph of each candidate vehicle passing any RSU; 3) selecting an optimal group of certain number of vehicles from the candidate vehicles, superimposing the statistical distribution graph of each vehicle, and maximizing the number of scheduled detections of road section units that reach the predetermined monitoring times.

2. The method of claim 1, wherein the road segment units comprise detection device number, accumulative time since each mobile monitoring vehicle enters each RSU, and accumulative number of times of each mobile monitoring vehicle passing each RSU; and an initial value of the accumulative number of times is 0.

3. The method of claim 1, wherein a length of the RSU is 100 meters or 200 meters.

4. The method of claim 1, wherein a range of the counting period is 15 min, 30 min, or 1 hour.

5. The method of claim 1, wherein a value of the covered range is 70% -80%; the number of scheduled detections is 5-10 times.

6. The method of claim 5, wherein one type of the mobile monitoring vehicles is taxis.

7. The method of claim 6, wherein the air pollution detection equipment comprises a control module and a detection module; the detection module comprises at least one sub-sensor unit; the sub-sensor unit is one of the following sensors: PM1 sensor, PM2.5 sensor, PM10 sensor, PM100 sensor, Sulphur dioxide sensor, nitrogen oxide sensor, ozone sensor, carbon monoxide sensor, VOCs sensor, or TVOC sensor.

8. The method of claim 7, wherein the detection module comprises a sensor module comprising at least two sub-sensor units of same type; the at least two sub-sensor units operate at a normal frequency; the detection module comprises a low-frequency calibration module comprising at least one sub-sensor unit that is of the same type as the at least two sub-sensor units of the sensor module; the sub-sensor unit of the calibration module operates at a lower frequency than that of the sensor module.

9. The method of claim 8, wherein a ratio of operating frequencies between the at least two sub-sensor units of the sensor module and the sub-sensor unit of the calibration module is 2:1, 3:1, 4:1, 5:1, 6:1, 7:1, 8:1, 9:1, 10:1, 15:1, or 20:1.

10. The method of claim 7, wherein when the control module detects one suspected abnormal sub-sensor unit in the sensor module, and judges that the suspected abnormal sub-sensor unit is an abnormal sub-sensor unit; the suspected abnormal sub-sensor unit is isolated and classified into an isolation zone, and the sensor module is degraded, and continues to operate; when the abnormal sub-sensor unit in the isolation zone self-heals, the abnormal sub-sensor unit operates at a lower frequency; the control module monitors the operation of the abnormal sub-sensor unit to judge whether a recovery condition is met; when the recovery condition is met, the abnormal sub-sensor unit is released from the isolation zone and back to the sensor module.

11. The method of claim 10, wherein the criteria for defining abnormal behavior of the sub-sensor, comprises: 1) abnormal fluctuation occurred in the sub-sensor unit; 2) abnormal drift occurred in the sub-sensor unit; and 3) abnormal correlation existing among the sub-sensor units.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0130] FIG. 1 is a schematic diagram of a system composition of the disclosure;

[0131] FIG. 2 is a schematic diagram of a grid-based fixed monitoring site layout mode;

[0132] FIG. 3 is a schematic diagram of an example monitoring platform in a city in Shandong;

[0133] FIG. 4 is a schematic diagram of the basic module composition of atmospheric pollutant monitoring equipment;

[0134] FIG. 5 illustrates the concealment using social vehicle monitoring;

[0135] FIG. 6 shows the characteristics of air pollution, which is time-sensitive;

[0136] FIG. 7 shows the relationship between the average undetected rate and the monitoring equipment release density index;

[0137] FIG. 8 is a schematic diagram of an air pollutant monitoring device comprising a video acquisition module;

[0138] FIG. 9 is a schematic diagram of a distribution of detection data in a grid in a mobile monitoring mode;

[0139] FIG. 10 is a schematic diagram of a cumulative detection distribution of a “belt”-shaped road network based on a section unit model;

[0140] FIG. 11 depicts statistical distribution of the monitoring times (taxi) within a 24-hour period in a certain urban area by road segment unit;

[0141] FIG. 12 is a schematic diagram of the monitoring times in the taxi and bus collaborative monitoring mode; and

[0142] FIG. 13 is a statistical distribution graph of a certain vehicle entering each grid within a week.

[0143] In the drawings, 10-taxi, 20-bus, 30-monitoring center, 40-fixed monitoring station, 50-user terminal, 70-other social vehicles, 60-air pollution monitoring equipment, 601-detection module, 602-video acquisition module, 603-communication module, 604- control module;

[0144] In the drawings, C- the number of taxi (monitoring car), C.sub.0- the rated number of taxi (monitoring car), b.sub.1- the local covered range (percentage) corresponding to the undetected segment of the bus line B.sub.1; f.sub.0- covered range initial value; f.sub.1-new covered range (considering b.sub.1).

DETAILED DESCRIPTION

EXAMPLE 1

[0145] A method and system for improving the objectivity of air pollutant monitoring data, using social vehicles to carry air pollutant monitoring equipment, comprising air pollutant monitoring equipment, a monitoring center, a fixed monitoring site, and a user terminal, as shown in FIG. 1.

[0146] Air pollutant monitoring equipment is installed on social vehicles to monitor the quality of the atmospheric environment where the vehicle is located. The air pollutant monitoring equipment has an information transmission function and can return the monitored data, location data and time information wirelessly to the monitoring center. It also can record road conditions and record road pollution, and can transmit the collected video back to the monitoring center. The air pollutant monitoring equipment has the function of storing data and video data, and saves the collected data and video data locally. The air pollutant monitoring equipment further comprises a data transmission interface, which can copy the saved data and video data to local maintenance or staff through local transmission.

[0147] The monitoring center can not only receive data returned from atmospheric pollutant monitoring equipment and store and process these data, but also collect data from other types of monitoring equipment, such as collecting data from miniature fixed monitoring sites, and collecting data from nearby fixed monitoring sites. The monitoring center can combine the data from the air pollutant monitoring equipment of social vehicles, the collected data from the miniature fixed monitoring stations, and the collected data from nearby fixed monitoring stations to generate a data list and data ranking and pollution clouds, historical playback and other data presentation methods. These processing result files are sent to user terminals through the network, and users can query and use them according to their needs. The monitoring center can also remotely control the operation of atmospheric pollutant monitoring equipment, such as turning on and off atmospheric pollutant monitoring equipment, turning on and off video acquisition modules, adjusting monitoring frequency, and correcting errors in atmospheric pollutant monitoring.

EXAMPLE 2

[0148] The objective air pollutant monitoring data of a city can only reflect the true degree of air pollution in the city. The disclosure needs to set a series of the highest average undetected rate index M.sub.0 to represent the obj ectivity of the monitoring data. For example, a city needs to monitor PM.sub.10, and its undetected rate is expressed as m (PM.sub.10). If the city requires m (PM.sub.10)<20%, it means that the PM.sub.10 pollution event not captured by the monitoring equipment is less than 20% of the total PM.sub.10 pollution event.

[0149] In order to achieve m (PM.sub.10)<20%, the minimum delivery density index No is introduced. No represents the minimum delivery density index of the monitoring equipment required to reach M.sub.0. In this example, in order to reach m (PM.sub.10), the minimum delivery density of the monitoring equipment equipped with a PM.sub.10 sensor is n (PM.sub.10). The n (PM.sub.10) needs to be calculated based on the area of the city, the number of vehicles equipped with mobile monitoring equipment, the daily mileage of vehicles, the driving range of vehicles, the type of vehicles, and the accuracy of equipment installed, etc. The area of the city is directly proportional to the amount of monitoring equipment that needs to be deployed; the daily mileage of the vehicle and the vehicle exercise are inversely proportional to the amount of monitoring equipment that needs to be deployed.

EXAMPLE 3

[0150] PM.sub.10 and SO.sub.2 of a city are monitored. In the disclosure, the highest average undetected rate index M.sub.0 of this city is expressed as m (PM.sub.10), m (SO.sub.2). Different pollutants have different levels of pollution contribution, and different cities attach different degrees of importance, so the average undetected rate for different pollutants will have corresponding requirements. Generally, cities attach less importance to the monitoring of SO.sub.2 than PM.sub.10. In this example, the highest average undetected rate of PM.sub.10 and SO.sub.2 is set to m (PM.sub.10)=20% and m (SO.sub.2)=30%.

[0151] When m (PM.sub.10)=20%, m (SO.sub.2)=30%, only taxis are equipped with monitoring equipment that can only monitor PM.sub.10 or SO.sub.2, the minimum delivery density n (PM.sub.10) of the monitoring equipment will be greater than n (SO.sub.2), that is, more taxis equipped with PM.sub.10 monitoring equipment than taxis equipped with SO.sub.2 monitoring equipment.

EXAMPLE 4

[0152] PM.sub.10 and SO.sub.2 of a city are monitored. In the disclosure, the highest average undetected rate index M.sub.0 of this city is expressed as m (PM.sub.10), m (SO.sub.2). In this example, the highest average undetected rate of PM.sub.10 and SO.sub.2 is set to m (PM.sub.10)=20% and m (SO.sub.2)=30%. Current monitoring equipment can also measure multiple pollutants simultaneously through the combination of internal detection modules.

[0153] The first launch method in this example is that all vehicles are equipped with monitoring equipment that can simultaneously measure PM.sub.10 and SO.sub.2. Then the N.sub.0 minimum monitoring equipment release density index only needs to meet the strictest highest average undetected rate in the index. The first method is n (PM.sub.10)=n (SO.sub.2), and the specific n (PM.sub.10) value is calculated the parameter relationship of the city area and the delivery density index described in Example 2.

[0154] The second method of launch in this example is that some vehicles are equipped with monitoring equipment that can both measure PM.sub.10 and SO.sub.2, and other vehicles are equipped with vehicles that can only measure PM.sub.10 equipment. At this time, n (PM.sub.10)>n (SO.sub.2), specific n (PM.sub.10) and n (SO.sub.2) need to be calculated and finally satisfy m (PM.sub.10)=20%, m (SO.sub.2)=30%.

EXAMPLE 5

[0155] Dust pollution in cities is mainly reflected in the value of PM.sub.100, and muck trucks are a major contribution to dust pollution. If the city needs to monitor PM.sub.2.5 and PM.sub.100, the highest average undetected rate indicator is m (PM.sub.10)=m (PM.sub.100)=20%. The distribution density can be distinguished according to the vehicle. By mounting PM.sub.100 monitoring equipment on the slag truck, it can more effectively monitor the dust pollution and more effectively achieve the density index of PM.sub.100 monitoring equipment. PM.sub.2.5 monitoring equipment has more assigned to small vehicles such as taxis.

EXAMPLE 6

[0156] The basic modules of air pollutant monitoring equipment comprise a detection module, a main control module and a communication module. The control module is connected to the power source of the mobile monitoring vehicle, and provides power for the detection module and the communication module. The control module is connected to the detection module and the communication module on the air pollutant monitoring equipment through a data interface, and performs data exchange with the detection module and the communication module. For example, the data collected by the detection module is processed by the control module and sent to the communication module, which is then returned to the monitoring center; the instructions sent by the monitoring center are received by the communication module and transmitted to the control module. The control module adjusts the detection according to the instructions Module operation. The control module has the function of storing and exporting data and video data. The control module has a positioning function or a data interface with a positioning device, and uses GPS, Beidou and other positioning technologies to record the vehicle position in real time.

EXAMPLE 7

[0157] The basic modules of air pollutant monitoring equipment comprise a detection module, a control module and a communication module. The detection module detects the pollutant content of the sampled gas through the air pollutant sensor mounted on it, and obtains the concentration data of the pollutant. The detection module can be equipped with a variety of air pollutant sensors, comprising PM.sub.1 sensor, PM.sub.2.5 sensor, PM.sub.10 sensor, PM.sub.100 sensor, nitrogen oxide sensor, ozone sensor, sulfur dioxide sensor, VOCs sensor or TVOC sensor for pollutant monitoring. For example, air pollutant monitoring equipment equipped with PM.sub.2.5 sensors and PM.sub.10 sensors can better monitor road dust, and can timely detect road dust pollution and provide early warning.

[0158] The detection module can also be equipped with other types of sensors, such as wind speed sensor, wind direction sensor, temperature sensor, humidity sensor, pressure sensor, and noise sensor, to provide richer monitoring information. And for example, the humidity sensor can provide humidity correction and calibration basis for the atmospheric pollutant sensor.

EXAMPLE 8

[0159] Mobile monitoring vehicles equipped with atmospheric pollutant monitoring equipment are social vehicles. Social vehicles comprise city buses, long-distance buses, taxis, earthmoving vehicles, municipal vehicles, official vehicles, ride-hailing vehicles, rental vehicles, shared vehicles, and vehicles with autonomous driving functions. These social vehicles do not need a dedicated site, and professional operators can perform real-time measurement of air pollution. The one-time investment is low, which reduces the energy consumption and road occupation brought by special vehicles. In the end, the occupation of public resources and the cost of air pollutant monitoring are decreased.

EXAMPLE 9

[0160] Install air pollution monitoring equipment equipped with particulate matter sensors on the bus. The characteristic of the bus is that the route is relatively fixed. Using one or several buses equipped with atmospheric particulate sensor monitoring equipment can monitor atmospheric particulate pollution along the entire bus line, reducing the monitoring cost. At the same time, due to the characteristics of the bus, it is possible to repeatedly measure a certain road section multiple times, which can give more reliable and more time data. The interval between buses is relatively even and there are many vehicles. When there are many shifts, it is usually the peak traffic time, and it is also the period when the particulate matter is polluted.

EXAMPLE 10

[0161] Atmospheric pollutant monitoring equipment equipped with particulate matter sensors is installed on large social vehicles such as dirt trucks, garbage disposal trucks, and long-distance vehicles. These large social vehicles often run on roads with severe dusting. Using these large social vehicles to monitor key dusting sections will do more with less. At the same time, you can also measure the dust pollution of your own vehicles. The data detected by these large social vehicles comprise the background pollution and the pollution of their own vehicles. Through the big data processing, the two types of data can be separated, and the road and self-pollution can be evaluated separately to facilitate control.

[0162] The feature of long-distance buses is that they can cover the blind spots of monitoring between cities and achieve a wider range of monitoring.

EXAMPLE 11

[0163] Install air pollution monitoring equipment equipped with particulate matter sensors on taxis. Taxi is characterized by a wide distribution range and a wide time range, which can measure places that other social vehicles cannot reach. Using social vehicles such as taxis to monitor atmospheric pollutants can more easily find areas with higher environmental health risks, because people-populated areas are hotspots and areas where these social vehicles appear more frequently. Repeated monitoring of these areas can obtain more accurate pollution information in densely populated areas, enabling environmental management departments to deal with pollution problems in a more targeted manner. At the same time, the height of the taxi ceiling light is basically the same as the height of the mouth and nose of the personnel at which the personnel mainly breathe. Using a taxi equipped with atmospheric pollutant monitoring equipment to monitor the atmosphere at this height can effectively reflect the impact on people's breathing. It is of great significance for the governance of the atmospheric environment.

[0164] FIG. 3 shows the monitoring results of a taxi equipped with atmospheric particulate monitoring equipment in a city in Shandong. A total of about 100 vehicles that a total trip of more than 23,000 kilometers per day can generate 1.2 million sets of data. Through the big data processing platform of the monitoring center, these data can automatically generate urban haze maps. Technicians can further judge whether the supervision of pollution sources in the relevant area is in place, and guide the precise treatment plan. The monitoring center also ranks districts, counties, sub-district offices and road sections to provide technical means for governance assessment.

EXAMPLE 12

[0165] Air pollutant monitoring equipment can adjust the monitoring density according to the situation of pollutants. For example, when a social vehicle equipped with air pollutant monitoring equipment passes by a certain section, the air pollutant monitoring equipment detects that the pollutant concentration exceeds the upper limit of the preset value, such as PM.sub.2.5 value≥100 μg/m.sup.3 (also 150 μg/m.sup.3, 200 μg/m.sup.3, 250 μg/m.sup.3, etc.), the air pollutant monitoring equipment increases the frequency of air pollutant concentration detection output. For example, the value of a pollutant concentration calculated every 3 seconds is changed to a pollutant calculated every 1 second. The pollutant that triggers the increase of the detection output frequency may be other pollutants (such as nitrogen oxides, ozone, etc.) that are monitored. When the pollutant concentration is lower than the lower limit of the set value, the air pollutant monitoring equipment reduces the detection output frequency. For example, after PM.sub.2.5≤50 μg/m.sup.3, the detection output frequency is restored to output a pollutant concentration value or longer time interval every 3 seconds.

EXAMPLE 13

[0166] The air pollutant monitoring equipment can adjust the frequency of return of the detected value according to the situation of the pollutant and adjust the monitoring density and return frequency according to the designated area or road section.

[0167] When a social vehicle equipped with atmospheric pollutant monitoring equipment enters an area or road section that needs to be monitored, the atmospheric pollutant monitoring equipment increases the output frequency of the corresponding atmospheric pollutant monitoring value. For example, the value of a pollutant concentration calculated every 3 seconds is changed to a pollutant calculated every 1 second; when the mobile monitoring vehicle leaves the area or road section that needs to be monitored, the air pollutant monitoring device reduces the frequency of the corresponding air pollutant monitoring output, such as the output frequency returns to the level before entering the key area or road section.

[0168] When a mobile monitoring vehicle passes by an area or road section that needs to be monitored, the air pollutant monitoring device can also increase the frequency of transmitting the corresponding air pollutant monitoring data to the monitoring center, for example, the value back every 3 seconds is changed to once every 1 second; when the mobile monitoring vehicle leaves the area or road section that needs to be monitored, the air pollutant monitoring device reduces the frequency of transmitting the corresponding air pollutant monitoring data to the monitoring center, for example, transmission frequency returns to the level before entering the key area or road section.

[0169] It will be obvious to those skilled in the art that changes and modifications may be made, and therefore, the aim in the appended claims is to cover all such changes and modifications.