Abstract: A method for determining a false negative rate of mobile monitoring and requisite number of mobile monitoring vehicles. The method focuses on road network of an urban area, by installing air pollution detection equipment on the mobile monitoring vehicles, to monitor air quality of the urban area. The method includes establishing a curve model of monitoring times for the mobile monitoring vehicles, determining two parameters of expected indicator: covered range, number of scheduled detections; and finding out a requisite number (C0) of the mobile monitoring vehicles, corresponding to a curve model which meets the two parameters of expected indicator.

Abstract: A multi-core sensor system in taxi roof light is provided. The multi-core sensor system can intelligently determine whether the change is caused by the sub-sensor failure or sudden pollution, when the data detected by the sub-sensor suddenly changes dramatically, so as to increase the reliability of detection data of the sub-sensor. The multi-core sensor system can automatically determine whether the repair is needed when a device fault occurs, thereby ensuring the continuity of the sub-sensor detection data; which has significant value for continuous monitoring required for a haze treatment operation. In addition, human and material resources for device maintenance may be saved, thereby reducing waste.

Abstract: A method for isolation and restoration for a multi-core sensor system within a taxi is provided. This method can intelligently determine whether the reason for an abrupt dramatic change in the data detected by sub-sensor is a sensor fault or sudden pollution, so as to increase the reliability of the data detected by the sub-sensor. This method can automatically determine if the repair can be performed when a device fault occurs, so as to ensure the continuity of the detection data of the sub-sensor, which has significant value for continuous monitoring required for a haze treatment operation. In addition, human and material resources for device maintenance may be saved, thereby reducing waste.

Abstract: A multi-core sensor system is provided. The multi-core sensor system can intelligently determine whether the reason for an abrupt dramatic change in sensor data is a sub-sensor fault or sudden pollution, so as to increase reliability of detected data of the sub-sensor. The multi-core sensor system can automatically determine whether the repair is needed when a device fault occurs, so as to ensure the continuity of sub-sensor detected data, which has significant value for continuous monitoring required for a haze treatment operation. In addition, human and material resources for device maintenance may be saved, thereby reducing waste.

Abstract: A method for determination and isolation for abnormal sub-sensors in a multi-core sensor. It can be intelligently determined whether the reason for an abrupt dramatic change in sensor data is a sensor fault or sudden pollution, so as to increase data reliability. A data online rate is increased if a repair can be performed via automatic determination when a device fault occurs, which has significant value for continuous monitoring required for a haze treatment operation. In addition, human and material resources for device maintenance may be saved, thereby reducing waste.

Abstract: A method for determining a false negative rate of mobile monitoring and requisite number of mobile monitoring vehicles. The method focuses on road network of an urban area, by installing air pollution detection equipment on the mobile monitoring vehicles, to monitor air quality of the urban area. The method includes establishing a curve model of monitoring times for the mobile monitoring vehicles, determining two parameters of expected indicator: covered range, number of scheduled detections; and finding out a requisite number (C0) of the mobile monitoring vehicles, corresponding to a curve model which meets the two parameters of expected indicator.

Abstract: The disclosure provides a method for determining a number of taxis through collaborative monitoring of taxis and buses. The method focuses on road network of an urban area, by installing air pollution detection equipment on the mobile monitoring vehicles, to monitor air quality of the urban area. The method includes establishing a curve model of monitoring times for the taxis; establishing a curve model of monitoring times for each bus line, in which its horizontal axis is consistent with the horizontal axis of the taxi detection frequency curve model; assigning monitoring times to the corresponding road section unit; sorting each bus line according to the numbers of undetected segments the each bus line covers; selecting the bus routes participating in collaborative monitoring; determining two parameters of the expected indicators; determining two parameters of the expected indicators.

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.

Abstract: The disclosure provides a method for selecting bus lines through collaborative monitoring of taxis and buses. The method focuses on road network of an urban area, by installing air pollution detection equipment on the mobile monitoring vehicles, to monitor air quality of the urban area. The method includes establishing a curve model of monitoring times for the taxis; establishing a curve model of monitoring times for each bus line, in which its horizontal axis is consistent with the horizontal axis of the taxi detection frequency curve model; assigning monitoring times to the corresponding road section unit; sorting each bus line according to the numbers of undetected segments the each bus line covers; and selecting the bus routes participating in collaborative monitoring.

Abstract: A taxi roof light includes a gas distribution tank, a control module, and a detection module. The gas distribution tank is used to distribute detected gas to each individual sub-sensor. The gas inlet of the gas distribution tank is connected to a gas sampling head. A floc prevention net is installed at the gas inlet. The arrangement of the floc prevention net at the gas inlet and the gas outlet can prevent the unexpected matter from entering the monitoring device to damage the monitoring device.

Abstract: A multi-core sensor system in taxi roof light is provided. The multi-core sensor system can intelligently determine whether the change is caused by the sub-sensor failure or sudden pollution, when the data detected by the sub-sensor suddenly changes dramatically, so as to increase the reliability of detection data of the sub-sensor. The multi-core sensor system can automatically determine whether the repair is needed when a device fault occurs, thereby ensuring the continuity of the sub-sensor detection data; which has significant value for continuous monitoring required for a haze treatment operation. In addition, human and material resources for device maintenance may be saved, thereby reducing waste.

Abstract: A multi-core sensor system is provided. The multi-core sensor system can intelligently determine whether the reason for an abrupt dramatic change in sensor data is a sub-sensor fault or sudden pollution, so as to increase reliability of detected data of the sub-sensor. The multi-core sensor system can automatically determine whether the repair is needed when a device fault occurs, so as to ensure the continuity of sub-sensor detected data, which has significant value for continuous monitoring required for a haze treatment operation. In addition, human and material resources for device maintenance may be saved, thereby reducing waste.

Abstract: A method for isolation and restoration for a multi-core sensor system within a taxi is provided. This method can intelligently determine whether the reason for an abrupt dramatic change in the data detected by sub-sensor is a sensor fault or sudden pollution, so as to increase the reliability of the data detected by the sub-sensor. This method can automatically determine if the repair can be performed when a device fault occurs, so as to ensure the continuity of the detection data of the sub-sensor, which has significant value for continuous monitoring required for a haze treatment operation. In addition, human and material resources for device maintenance may be saved, thereby reducing waste.

Abstract: A method for determination and isolation for abnormal sub-sensors in a multi-core sensor. It can be intelligently determined whether the reason for an abrupt dramatic change in sensor data is a sensor fault or sudden pollution, so as to increase data reliability. A data online rate is increased if a repair can be performed via automatic determination when a device fault occurs, which has significant value for continuous monitoring required for a haze treatment operation. In addition, human and material resources for device maintenance may be saved, thereby reducing waste.