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.

What is claimed is: 
     
         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.