Automobile cabin pollutant monitoring method, system, equipment and medium

Abstract

The invention provides an automobile cabin pollutant monitoring method, system and device and a medium, and relates to the technical field of automobile electronics and environment control, and the method comprises the steps: monitoring the concentration of a target pollutant in a cabin; under the condition that the concentration of the target pollutant is greater than a basic concentration threshold value of the target pollutant, obtaining respective state information of all members in a cabin and current driving scene information; determining a target concentration threshold correction factor according to the respective state information of all the members and the current driving scene information; correcting a basic concentration threshold value of the target pollutant through the target concentration threshold value correction factor to obtain a corrected concentration threshold value; and under the condition that the concentration of the target pollutant is greater than or equal to the corrected concentration threshold value, determining that the target pollutant in the cabin exceeds the standard. Therefore, the identification rationality and adaptability of the low-concentration harmful gas pollution risk in the cabin are improved.

Description

Technical Field

[0001] This application relates to the fields of automotive electronics and environmental control technology, and in particular to a method, system, device and medium for monitoring pollutants in automotive cabins. Background Technology

[0002] Existing in-vehicle air purification systems mostly rely on fixed thresholds or static rules for control based on a limited number of environmental parameters. While these systems can improve in-vehicle air quality to some extent, they still have significant shortcomings in complex and ever-changing real-world usage scenarios. On the one hand, in-vehicle air pollution comes from diverse sources, and traditional solutions have limited ability to detect low concentrations of harmful gases and biological pollutants, making it difficult to comprehensively reflect the true air risk status. On the other hand, existing control strategies generally ignore individual differences among occupants and changes in their state during driving, resulting in insufficient targeting and adaptability of the purification response.

[0003] Based on the above problems, this application proposes a new method for monitoring pollutants in automobile cabins. Summary of the Invention

[0004] In view of the above problems, embodiments of this application provide a method, system, device and medium for monitoring pollutants in an automotive cabin, so as to overcome the above problems or at least partially solve the above problems.

[0005] A first aspect of this application provides a method for monitoring pollutants in an automotive cabin, the method comprising: Monitor the concentration of target pollutants inside the cabin; If the concentration of the target pollutant is greater than the baseline concentration threshold of the target pollutant, obtain the status information of each member in the cabin and the current driving scenario information. Based on the status information of all members and the current driving scenario information, determine the target concentration threshold correction factor; The base concentration threshold of the target pollutant is corrected by the target concentration threshold correction factor to obtain the corrected concentration threshold; If the concentration of the target pollutant is greater than or equal to the corrected concentration threshold, it is determined that the target pollutant exceeds the standard in the cabin.

[0006] Optionally, determining the target concentration threshold correction factor based on the individual state information of all members and the current driving scenario information includes: Based on the status information of all members, determine the image information and physiological status information of the target member, wherein the target member is any one of all members; Based on the current driving scenario information, as well as the image information and physiological state information of the target member, a candidate concentration threshold correction factor for the target member is determined; Based on the candidate concentration threshold correction factors of all target members, the candidate concentration threshold correction factor with the highest value is determined as the target concentration threshold correction factor.

[0007] Optionally, determining the candidate concentration threshold correction factor for the target member based on the current driving scenario information, as well as the image information and physiological state information of the target member, includes: Perform facial recognition on the image information of the target member to obtain the image recognition result of the target member; Based on the image recognition results of the target member, determine the individual adjustment factor of the target member; Based on the physiological state information of the target member, a first physiological state index and a second physiological state index are determined for the target member. The first physiological state index represents a physiological state index based on heart rate variability, and the second physiological state index represents a physiological state index based on skin conductance response. Based on the current driving scenario information, determine the first weight corresponding to the first physiological state index and the second weight corresponding to the second physiological state index; The candidate concentration threshold correction factor for the target member is calculated based on the first physiological state index, the first weight, the second physiological state index, the second weight, and the individual regulation factor.

[0008] Optionally, determining the individual adjustment factor of the target member based on the image recognition result of the target member includes: Based on the image recognition results, the target member is identified to obtain the identification result; Based on the identity recognition result, retrieve the health record corresponding to the target member; Based on the health status recorded in the health records, determine the individual moderating factors of the target members; Wherein, when the health status indicates that the target member is an unhealthy population, the individual moderating factor is negative; when the health status indicates that the target member is a healthy population, the individual moderating factor is zero.

[0009] Optionally, determining the first physiological state index and the second physiological state index of the target member based on the target member's physiological state information includes: Obtain the baseline and current values ​​of the heart rate variability data of the target member. The ratio of the difference between the baseline value and the current value of the heart rate variability data to the baseline value of the heart rate variability data is determined as the first physiological state index. The ratio of the difference between the current value and the baseline value of the skin conductance response data to the baseline value of the skin conductance response data is determined as the second physiological state index.

[0010] Optionally, after determining that the target pollutant exceeds the standard in the vehicle cabin environment, the method further includes: Obtain the type of the target pollutant; Based on the type of the target pollutant, control the air purification system in the car cabin to perform the air purification operation corresponding to the target pollutant; When the target pollutant is ammonia or hydrogen sulfide, the air purification system is controlled to turn on ultraviolet light for purification. When the target pollutant is carbon dioxide, the air purification system is controlled to activate external circulation purification. When the target pollutant is PM2.5, the air purification system is controlled to activate negative ion pulse purification.

[0011] Optionally, after controlling the air purification system to perform the target air purification operation corresponding to the target pollutant, the method further includes: Acquire seat pressure monitoring data from the seat pressure sensor, and when the seat pressure monitoring data indicates that the vehicle cabin is unloaded, activate the target level of the ultraviolet light purification system, wherein the target level of the ultraviolet light purification system is the highest level among all the ultraviolet light purification levels; and / or, Obtain ozone concentration monitoring data, and turn off the negative ion purification when the ozone concentration monitoring data is greater than or equal to a preset ozone concentration threshold and the negative ion pulse purification is in the on state.

[0012] A second aspect of this application provides a vehicle cabin pollutant monitoring system, the system comprising: The monitoring module is used to monitor the concentration of target pollutants inside the cabin; The acquisition module is used to acquire the status information of all occupants in the cabin and the current driving scenario information when the concentration of the target pollutant is greater than the basic concentration threshold of the target pollutant. The first determining module is used to determine the target concentration threshold correction factor based on the status information of each member and the current driving scenario information; The correction module is used to correct the basic concentration threshold of the target pollutant using the target concentration threshold correction factor to obtain the corrected concentration threshold. The second determining module is used to determine that the target pollutant exceeds the standard in the cabin when the concentration of the target pollutant is greater than or equal to the corrected concentration threshold.

[0013] Optionally, the first determining module, which determines the target concentration threshold correction factor based on the state information of all members and the current driving scenario information, includes: The first determining submodule is used to determine the image information and physiological state information of the target member based on the state information of all members, wherein the target member is any one of all members; The second determining submodule is used to determine the candidate concentration threshold correction factor of the target member based on the current driving scenario information, as well as the image information and physiological state information of the target member; The third determining submodule is used to determine the candidate concentration threshold correction factor with the highest value as the target concentration threshold correction factor based on the candidate concentration threshold correction factors of each of the target members.

[0014] Optionally, the step of determining the candidate concentration threshold correction factor for the target member based on the current driving scenario information, as well as the image information and physiological state information of the target member, and the second determining submodule, includes: A face recognition subunit is used to perform face recognition on the image information of the target member to obtain the image recognition result of the target member; The first determining subunit is used to determine the individual adjustment factor of the target member based on the image recognition result of the target member; The second determining subunit is used to determine a first physiological state index and a second physiological state index of the target member based on the physiological state information of the target member. The first physiological state index represents a physiological state index based on heart rate variability, and the second physiological state index represents a physiological state index based on skin conductance response. The third determining subunit is used to determine the first weight corresponding to the first physiological state index and the second weight corresponding to the second physiological state index based on the current driving scenario information. The calculation subunit is used to calculate the candidate concentration threshold correction factor of the target member based on the first physiological state index, the first weight, the second physiological state index, the second weight, and the individual regulation factor of the target member.

[0015] Optionally, the first determining subunit, which determines the individual adjustment factor of the target member based on the image recognition result of the target member, includes: An identity recognition subunit is used to perform identity recognition on the target member based on the image recognition result, and obtain an identity recognition result; The retrieval subunit is used to retrieve the health record corresponding to the target member based on the identity recognition result; The fourth determining subunit is used to determine the individual regulatory factors of the target member based on the health status recorded in the health record; Wherein, when the health status indicates that the target member is an unhealthy population, the individual moderating factor is negative; when the health status indicates that the target member is a healthy population, the individual moderating factor is zero.

[0016] Optionally, the step of determining a first physiological state index and a second physiological state index of the target member based on the target member's physiological state information, wherein the second determining subunit includes: The acquisition subunit is used to acquire the baseline and current values ​​of the heart rate variability data of the target member. The fifth determining subunit is used to determine the first physiological state index by the ratio of the difference between the baseline value and the current value of the heart rate variability data to the baseline value of the heart rate variability data; The sixth determining subunit is used to determine the second physiological state index by the ratio of the difference between the current value and the baseline value of the skin conductance response data to the baseline value of the skin conductance response data.

[0017] Optionally, the system further includes: The first acquisition submodule is used to acquire the type of the target pollutant; The control submodule is used to control the air purification system in the car cabin to perform the air purification operation corresponding to the target pollutant according to the type of the target pollutant. The first control subunit is used to control the air purification system to turn on ultraviolet light for purification when the target pollutant is ammonia or hydrogen sulfide. The second control subunit is used to control the air purification system to start external circulation purification when the target pollutant is carbon dioxide. The third control subunit is used to control the air purification system to activate negative ion pulse purification when the target pollutant is PM2.5.

[0018] Optionally, the system further includes: The second acquisition submodule is used to acquire seat pressure monitoring data from the seat pressure sensor, and when the seat pressure monitoring data indicates that the car cabin is unloaded, to activate the target level of the ultraviolet light purification, wherein the target level of the ultraviolet light purification is the highest level among all the ultraviolet light purification levels; and / or, The third acquisition submodule is used to acquire ozone concentration monitoring data, and to turn off the negative ion purification when the ozone concentration monitoring data is greater than or equal to a preset ozone concentration threshold and the negative ion pulse purification is in the on state.

[0019] A third aspect of this application provides an electronic device including a processor, a memory, and a program or instructions stored in the memory and executable on the processor, wherein the program or instructions, when executed by the processor, implement the steps of the automotive cabin pollutant monitoring method as described in the first aspect of this application.

[0020] A fourth aspect of this application provides a readable storage medium storing a program or instructions that, when executed by a processor, implement the steps of the automotive cabin pollutant monitoring method described in the first aspect of this application.

[0021] The beneficial effects of this application are: This application provides a method for monitoring pollutants in a car cabin. The method includes: monitoring the concentration of a target pollutant in the cabin; if the concentration of the target pollutant is greater than a baseline concentration threshold, acquiring the status information of all occupants in the cabin and the current driving scenario information; determining a target concentration threshold correction factor based on the status information of all occupants and the current driving scenario information; correcting the baseline concentration threshold of the target pollutant using the target concentration threshold correction factor to obtain a corrected concentration threshold; and determining that the target pollutant exceeds the standard in the cabin if the concentration of the target pollutant is greater than or equal to the corrected concentration threshold.

[0022] This application dynamically corrects the pollutant concentration threshold by incorporating the status information of all occupants in the cabin and the current driving scenario information when the pollutant concentration exceeds the basic threshold. This enables the determination of pollutant exceedance based on the corrected threshold, so that pollution monitoring no longer relies on fixed or static threshold determination. It can take into account the individual differences of different occupants and changes in driving scenarios, improve the rationality and adaptability of identifying low-concentration harmful gas pollution risks, and thus improve the accuracy and pertinence of cabin air pollution monitoring. Attached Figure Description

[0023] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 This is a flowchart illustrating the steps of a method for monitoring pollutants in an automotive cabin, as provided in an embodiment of this application. Figure 2 This is a schematic diagram of the steps of an air purification operation provided in an embodiment of this application; Figure 3 This is a schematic diagram of the architecture of an air purification system provided in an embodiment of this application; Figure 4 This is a flowchart of a method for monitoring pollutants in an automotive cabin provided in an embodiment of this application; Figure 5 This is a schematic diagram of an automotive cabin pollutant monitoring system provided in an embodiment of this application; Figure 6 This is a schematic diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0025] Exemplary embodiments of this application will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of this application are shown in the drawings, it should be understood that this application may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of this application and to fully convey the scope of this application to those skilled in the art.

[0026] In a first aspect, this application provides a method for monitoring pollutants in an automotive cabin, such as... Figure 1 As shown, the method includes: S101 monitors the concentration of target pollutants inside the cabin.

[0027] In this step, the concentration of target pollutants within the vehicle cabin is monitored. These target pollutants include at least ammonia and hydrogen sulfide. In this application, the real-time concentrations of ammonia and hydrogen sulfide can be monitored using gas sensors installed within the cabin to obtain information on the current pollutant concentrations in the cabin environment. In some cases, the concentrations of target pollutants such as ammonia and hydrogen sulfide can be monitored using nanoporous gas sensor arrays installed in the ceiling ducts or under the seats.

[0028] S102, if the concentration of the target pollutant is greater than the basic concentration threshold of the target pollutant, obtain the status information of each member in the cabin and the current driving scenario information.

[0029] When the concentration of the target pollutant exceeds the corresponding baseline concentration threshold, the system acquires the individual status information of all occupants in the cabin, as well as the current driving scenario information. Occupant status information may include, but is not limited to, information reflecting the occupants' physiological, behavioral, or comfort states. Driving scenario information may include, but is not limited to, vehicle driving status, driving duration, road type, or vehicle operating conditions.

[0030] S103, determine the target concentration threshold correction factor based on the status information of each member and the current driving scenario information.

[0031] Based on the individual status information of all occupants in the cabin and the current driving scenario information, a target concentration threshold correction factor is determined. In this application, the target concentration threshold correction factor is used to characterize the degree of influence of different occupant statuses and driving scenarios on the pollutant concentration determination criteria.

[0032] S104, the basic concentration threshold of the target pollutant is corrected by the target concentration threshold correction factor to obtain the corrected concentration threshold.

[0033] The baseline concentration threshold corresponding to the target pollutant is corrected using a target concentration threshold correction factor to obtain the corrected concentration threshold. By correcting the baseline concentration threshold of the target pollutant, the threshold for determining pollutant concentration can be dynamically adjusted according to changes in crew status and driving scenarios.

[0034] S105, if the concentration of the target pollutant is greater than or equal to the corrected concentration threshold, it is determined that the target pollutant exceeds the standard in the cabin.

[0035] When the concentration of the target pollutant is greater than or equal to the corrected concentration threshold, the pollutant in the vehicle cabin is determined to be in an excessive state. By making judgments based on the corrected concentration threshold, the adaptability of cabin pollutant monitoring results to different usage scenarios and different occupant states can be improved.

[0036] This application dynamically corrects the pollutant concentration threshold by incorporating the status information of all occupants in the cabin and the current driving scenario information when the pollutant concentration exceeds the basic threshold. This enables the determination of pollutant exceedance based on the corrected threshold, so that pollution monitoring no longer relies on fixed or static threshold determination. It can take into account the individual differences of different occupants and changes in driving scenarios, improve the rationality and adaptability of identifying low-concentration harmful gas pollution risks, and thus improve the accuracy and pertinence of cabin air pollution monitoring.

[0037] In one embodiment, determining the target concentration threshold correction factor based on the individual state information of all members and the current driving scenario information includes: Based on the status information of all members, determine the image information and physiological status information of the target member, wherein the target member is any one of all members; Based on the current driving scenario information, as well as the image information and physiological state information of the target member, a candidate concentration threshold correction factor for the target member is determined; Based on the candidate concentration threshold correction factors of all target members, the candidate concentration threshold correction factor with the highest value is determined as the target concentration threshold correction factor.

[0038] In this embodiment, image information and physiological state information corresponding to a target member are determined based on the state information of all members in the cockpit, where the target member is any member in the cockpit. In this embodiment, different members can be analyzed separately to obtain the image features and physiological state features corresponding to each member.

[0039] Furthermore, by combining the current driving scenario information and based on the image and physiological state information of the target member, candidate concentration threshold correction factors are determined for the target member. These candidate concentration threshold correction factors characterize the sensitivity of the target member to changes in pollutant concentration under the current driving scenario.

[0040] Furthermore, a comparative analysis was conducted on the candidate concentration threshold correction factors corresponding to each target member, and the candidate concentration threshold correction factor with the highest value was determined as the final target concentration threshold correction factor. By adopting the candidate concentration threshold correction factor with the highest value, the pollutant threshold correction results can reflect the situation of the cabin occupants who are most sensitive to air pollution.

[0041] This embodiment acquires image and physiological information for different occupants in the cabin, and determines corresponding candidate concentration threshold correction factors for each occupant based on the current driving scenario information. Then, it selects the highest value from multiple candidate concentration threshold correction factors as the final target concentration threshold correction factor. This allows the pollutant concentration determination to be dynamically adjusted based on the occupant most sensitive to air quality in the cabin, thereby avoiding the risk underestimation caused by averaging or fixed threshold determination, improving the adaptability of pollutant exceedance identification to individual differences among occupants and changes in the scenario, and enhancing the safety, rationality, and pertinence of cabin air pollution monitoring results.

[0042] In one embodiment, determining the candidate concentration threshold correction factor for the target member based on the current driving scenario information, as well as the image information and physiological state information of the target member, includes: Perform facial recognition on the image information of the target member to obtain the image recognition result of the target member; Based on the image recognition results of the target member, determine the individual adjustment factor of the target member; Based on the physiological state information of the target member, a first physiological state index and a second physiological state index are determined for the target member. The first physiological state index represents a physiological state index based on heart rate variability, and the second physiological state index represents a physiological state index based on skin conductance response. Based on the current driving scenario information, determine the first weight corresponding to the first physiological state index and the second weight corresponding to the second physiological state index; The candidate concentration threshold correction factor for the target member is calculated based on the first physiological state index, the first weight, the second physiological state index, the second weight, and the individual regulation factor.

[0043] In this embodiment, the process of determining the candidate concentration threshold correction factor for the target member based on the current driving scenario information, as well as the image information and physiological state information of the target member, is further described as follows: Facial recognition processing is performed on the image information of the target member to obtain the image recognition result corresponding to the target member. The identity of different members can be distinguished by the image recognition result.

[0044] Furthermore, based on the image recognition results of the target members, individual adjustment factors corresponding to the target members are determined. In this embodiment, the individual adjustment factors are used to reflect the individual differences among different members in terms of air pollution sensitivity.

[0045] Based on the physiological state information of the target member, a first physiological state index and a second physiological state index are determined. The first physiological state index characterizes physiological state changes based on heart rate variability, and the second physiological state index characterizes physiological state changes based on skin conductance response. By constructing multiple physiological state indices, the current state level of the member can be reflected from different physiological dimensions. In this embodiment, heart rate variability physiological state information of the target member can be obtained by a piezoelectric ceramic sensor installed in the steering wheel grip area, and skin conductance response physiological state information of the target member can be obtained by a capacitive thin-film sensor installed in the driver's seat and passenger seat cushion.

[0046] Furthermore, based on the current driving scenario information, the first weight corresponding to the first physiological state index and the second weight corresponding to the second physiological state index are determined respectively. The first weight and the second weight can be calibrated based on the driving scenario during the experiment. That is, the values ​​of the first weight and the second weight are different under different driving scenarios. This application does not specifically limit the calibration process here.

[0047] Based on the first physiological state index, the first weight, the second physiological state index, the second weight, and the individual adjustment factor, the candidate concentration threshold correction factor for the target member is calculated. By integrating multidimensional physiological information, individual differences, and driving scenario factors, a candidate concentration threshold correction factor that matches the current state of the target member is obtained.

[0048] In this application, the calculation process of the candidate concentration threshold correction factor can be represented by the following formula: (1) in, Indicates the candidate concentration threshold correction factor; Indicates the first weight; Indicates the first physiological state index; Indicates the second weight; Indicates the second physiological state index; This represents an individual regulatory factor.

[0049] This embodiment introduces an individual adjustment factor based on facial recognition and constructs a multidimensional physiological state index by combining heart rate variability and skin conductance response. At the same time, different physiological indicators are weighted according to the driving scenario, so that the calculation of the candidate concentration threshold correction factor can simultaneously reflect the individual differences of members, changes in physiological state and driving scenario characteristics, thereby improving the accuracy and scenario adaptability of pollutant threshold correction results.

[0050] In this application, the baseline concentration threshold of the target pollutant is corrected using a candidate concentration threshold correction factor, as shown in Table 1 below:

[0051] Table 1 As shown in Table 1, the correction formulas are different for different target pollutants. In Table 1, T_NH3 is used to represent the concentration threshold after ammonia correction; T_H2S is used to represent the concentration threshold after hydrogen sulfide correction; T_CO2 is used to represent the concentration threshold after carbon dioxide correction; and T_PM2.5 is used to represent the concentration threshold after PM2.5 correction.

[0052] In one embodiment, determining a first physiological state index and a second physiological state index of the target member based on the target member's physiological state information includes: Obtain the baseline and current values ​​of the heart rate variability data of the target member. The ratio of the difference between the baseline value and the current value of the heart rate variability data to the baseline value of the heart rate variability data is determined as the first physiological state index. The ratio of the difference between the current value and the baseline value of the skin conductance response data to the baseline value of the skin conductance response data is determined as the second physiological state index.

[0053] In this embodiment, the process of determining the first and second physiological state indices of the target member based on the target member's physiological state information is further described as follows: The baseline and current values ​​of the target member's heart rate variability data are obtained. A first physiological state index is calculated by comparing the difference between the current value and the baseline value with the baseline value. This first physiological state index is used to quantitatively characterize the physiological state changes of the target member based on heart rate variability.

[0054] The baseline and current values ​​of the target member's skin conductance response (SCRR) data are obtained. A second physiological state index is calculated by comparing the difference between the current value and the baseline value. This index is used to quantitatively characterize the physiological state changes of the target member based on SCRR. SCRR reflects an individual's psychological or physiological stress level under environmental stimuli. Combining it with heart rate variability provides a comprehensive reflection of the target member's current state from different physiological dimensions.

[0055] By constructing a first physiological state index and a second physiological state index, precise quantification of the multidimensional physiological state of the target member can be achieved. Simultaneously, it enables real-time monitoring of individual physiological changes, dynamically reflecting the member's sensitivity and stress state during driving.

[0056] This embodiment achieves a comprehensive assessment of the physiological state of the target group by constructing a multidimensional physiological index, so as to dynamically adjust the purification strategy according to the individual's physiological state, thereby improving the protection efficiency of sensitive groups while ensuring the comfort and safety of healthy groups.

[0057] In one embodiment, determining the individual adjustment factor of the target member based on the image recognition result of the target member includes: Based on the image recognition results, the target member is identified to obtain the identification result; Based on the identity recognition result, retrieve the health record corresponding to the target member; Based on the health status recorded in the health records, determine the individual moderating factors of the target members; Wherein, when the health status indicates that the target member is an unhealthy population, the individual moderating factor is negative; when the health status indicates that the target member is a healthy population, the individual moderating factor is zero.

[0058] In this embodiment, facial recognition processing is performed on the image information of the target member to obtain the image recognition result corresponding to the target member. The identity of different members can be distinguished through the image recognition result.

[0059] Furthermore, based on the image recognition results of the target member, identity verification is performed to obtain the identity verification result. Using the identity verification result, the health record corresponding to the target member is retrieved. Based on the health status recorded in the health record, the individual moderating factor of the target member is determined. Specifically, when the health status indicates that the target member is unhealthy, the individual moderating factor takes a negative value; when the health status indicates that the target member is healthy, the individual moderating factor takes a zero value.

[0060] In this embodiment, by combining image recognition and health record information, it is possible to accurately assess the individual differences in air pollution sensitivity among different members, thereby effectively improving the protection effect for sensitive groups.

[0061] In one embodiment, after determining that the target pollutant exceeds the standard in the vehicle cabin environment, the method is as follows: Figure 2 As shown, it also includes: S106, Obtain the type of the target pollutant; S107, Based on the type of the target pollutant, control the air purification system in the car cabin to perform the air purification operation corresponding to the target pollutant; S1071, when the target pollutant is ammonia or hydrogen sulfide, control the air purification system to turn on ultraviolet light for purification; S1072, when the target pollutant is carbon dioxide, control the air purification system to start external circulation purification; S1073, when the target pollutant is PM2.5, control the air purification system to activate negative ion pulse purification.

[0062] In this embodiment, when the concentration of a target pollutant in the vehicle cabin environment exceeds the standard, the type information of the target pollutant is first obtained. Based on the different types of target pollutants, the vehicle cabin air purification system is controlled to perform corresponding air purification operations to achieve targeted pollutant purification.

[0063] When the target pollutant is ammonia or hydrogen sulfide, the air purification system is activated by turning on the ultraviolet light purification module. Through the synergistic effect of ultraviolet light and catalyst, the microbial metabolites and harmful gases are rapidly inactivated and degraded.

[0064] When the target pollutant is carbon dioxide, the air purification system is activated to open the external circulation duct. By increasing the fresh air volume and air replacement rate, the carbon dioxide concentration in the cabin is reduced, thus improving the breathing environment for the occupants.

[0065] When the target pollutant is PM2.5, the air purification system is activated to switch to negative ion pulse purification mode. Positive and negative ions are released through high-voltage pulses to promote the aggregation and sedimentation of particulate matter in the air or to be captured by the air duct filter, thereby rapidly reducing the PM2.5 concentration.

[0066] This embodiment achieves efficient treatment of various pollutants in the car cabin by performing specialized air purification for different types of pollutants. It can quickly respond to environmental changes, improve air purification efficiency, reduce the potential health risks of pollutants to occupants, and selectively activate corresponding air purification operations to achieve energy consumption optimization and intelligent control, providing occupants with a safer and more comfortable in-vehicle air environment.

[0067] Based on the above embodiments, this application also proposes a method such as Figure 3 The diagram shown illustrates the architecture of the air purification system. Figure 3 As shown, the air purification system includes a multi-source sensing layer, an analysis layer, and an execution control layer.

[0068] The multi-source sensing layer includes at least: a nanoporous gas sensor array, a laser PM2.5 sensor, a capacitive thin-film sensor, and a piezoelectric ceramic sensor. The nanoporous gas sensor array is used to monitor microbial metabolites such as ammonia, hydrogen sulfide, and carbon dioxide; in some cases, microbial metabolites may also include gases such as VOCs. The laser PM2.5 sensor is used to monitor particulate matter concentrations, including PM2.5 concentration; the capacitive thin-film sensor is used to monitor physiological state information such as heart rate variability; and the piezoelectric ceramic sensor is used to monitor physiological state information such as heart rate variability.

[0069] The analysis layer includes a target concentration threshold correction factor calculation model and a purification strategy decision engine. The target concentration threshold correction factor calculation model is used to calculate the target concentration threshold correction factor. The purification strategy decision engine is used to execute corresponding air purification strategies based on the corrected concentration thresholds of each target pollutant and the monitored concentrations of each target pollutant.

[0070] The execution control layer includes at least: an ultraviolet light generator, a negative ion generator, and an intelligent air duct control system. The execution control layer is used to control the activation of the ultraviolet light generator for purification when the target pollutant is ammonia or hydrogen sulfide; to control the activation of the intelligent air duct control system when the target pollutant is carbon dioxide; and to control the activation of the negative ion generator when the target pollutant is PM2.5.

[0071] In one embodiment, after controlling the air purification system to perform the target air purification operation corresponding to the target pollutant, the method further includes: Acquire seat pressure monitoring data from the seat pressure sensor, and when the seat pressure monitoring data indicates that the vehicle cabin is unloaded, activate the target level of the ultraviolet light purification system, wherein the target level of the ultraviolet light purification system is the highest level among all the ultraviolet light purification levels; and / or, Obtain ozone concentration monitoring data, and turn off the negative ion purification when the ozone concentration monitoring data is greater than or equal to a preset ozone concentration threshold and the negative ion pulse purification is in the on state.

[0072] In this embodiment, the process of performing safety protection control after controlling the air purification system to perform the air purification operation corresponding to the target pollutant is further described as follows: Acquire seat pressure monitoring data from the seat pressure sensor and determine whether the vehicle cabin is empty based on the monitoring data. When the seat pressure monitoring data indicates that the vehicle cabin is empty, control the air purification system to activate the target level of ultraviolet (UV) purification. The target level is the highest level of the UV purification module, to achieve efficient inactivation of microorganisms and harmful gases while ensuring occupant safety and preventing the risk of UV exposure to seated occupants. And / or, The system acquires ozone concentration monitoring data and determines the ozone concentration in the air based on this data. When the ozone concentration monitoring data is greater than or equal to a preset ozone concentration threshold, and the negative ion pulse purification mode is on, the control system shuts down the negative ion purification to prevent potential health risks caused by excessive ozone.

[0073] This application also provides a flowchart of a method for monitoring pollutants in an automotive cabin, such as... Figure 4 As shown: S201, monitoring the concentration of target pollutants; S202, Is the concentration of the target pollutant greater than the baseline concentration threshold? If yes, proceed to S203; otherwise, return to S201. S203, calculate the target concentration threshold correction factor; S204, corrects the baseline concentration threshold of the target pollutant; S205, Is the concentration of the target pollutant greater than or equal to the corrected concentration threshold? If yes, proceed to S206; otherwise, return to S201. S206, Select the corresponding air purification operation based on the target pollutant; S2061, if the target pollutant is ammonia or hydrogen sulfide, then control the activation of ultraviolet light for purification; S2062, If the target pollutant is carbon dioxide, then control the external circulation purification to start; S2063, if the target pollutant is PM2.5, then control the activation of negative ion pulse purification.

[0074] Based on the same inventive concept, a second aspect of the embodiments of this application provides an automotive cabin pollutant monitoring system, such as... Figure 5 As shown, the system includes: Monitoring module 301 is used to monitor the concentration of target pollutants inside the cabin; The acquisition module 302 is used to acquire the status information of all members in the cabin and the current driving scenario information when the concentration of the target pollutant is greater than the basic concentration threshold of the target pollutant. The first determining module 303 is used to determine the target concentration threshold correction factor based on the status information of each member and the current driving scenario information; The correction module 304 is used to correct the basic concentration threshold of the target pollutant using the target concentration threshold correction factor to obtain the corrected concentration threshold. The second determining module 305 is used to determine that the target pollutant exceeds the standard in the cabin when the concentration of the target pollutant is greater than or equal to the corrected concentration threshold.

[0075] Optionally, the first determining module 303, which determines the target concentration threshold correction factor based on the state information of all members and the current driving scenario information, includes: The first determining submodule is used to determine the image information and physiological state information of the target member based on the state information of all members, wherein the target member is any one of all members; The second determining submodule is used to determine the candidate concentration threshold correction factor of the target member based on the current driving scenario information, as well as the image information and physiological state information of the target member; The third determining submodule is used to determine the candidate concentration threshold correction factor with the highest value as the target concentration threshold correction factor based on the candidate concentration threshold correction factors of each of the target members.

[0076] Optionally, the step of determining the candidate concentration threshold correction factor for the target member based on the current driving scenario information, as well as the image information and physiological state information of the target member, and the second determining submodule, includes: A face recognition subunit is used to perform face recognition on the image information of the target member to obtain the image recognition result of the target member; The first determining subunit is used to determine the individual adjustment factor of the target member based on the image recognition result of the target member; The second determining subunit is used to determine a first physiological state index and a second physiological state index of the target member based on the physiological state information of the target member. The first physiological state index represents a physiological state index based on heart rate variability, and the second physiological state index represents a physiological state index based on skin conductance response. The third determining subunit is used to determine the first weight corresponding to the first physiological state index and the second weight corresponding to the second physiological state index based on the current driving scenario information. The calculation subunit is used to calculate the candidate concentration threshold correction factor of the target member based on the first physiological state index, the first weight, the second physiological state index, the second weight, and the individual regulation factor of the target member.

[0077] Optionally, the first determining subunit, which determines the individual adjustment factor of the target member based on the image recognition result of the target member, includes: An identity recognition subunit is used to perform identity recognition on the target member based on the image recognition result, and obtain an identity recognition result; The retrieval subunit is used to retrieve the health record corresponding to the target member based on the identity recognition result; The fourth determining subunit is used to determine the individual regulatory factors of the target member based on the health status recorded in the health record; Wherein, when the health status indicates that the target member is an unhealthy population, the individual moderating factor is negative; when the health status indicates that the target member is a healthy population, the individual moderating factor is zero.

[0078] Optionally, the step of determining a first physiological state index and a second physiological state index of the target member based on the target member's physiological state information, wherein the second determining subunit includes: The acquisition subunit is used to acquire the baseline and current values ​​of the heart rate variability data of the target member. The fifth determining subunit is used to determine the first physiological state index by the ratio of the difference between the baseline value and the current value of the heart rate variability data to the baseline value of the heart rate variability data; The sixth determining subunit is used to determine the second physiological state index by the ratio of the difference between the current value and the baseline value of the skin conductance response data to the baseline value of the skin conductance response data.

[0079] Optionally, the system further includes: The first acquisition submodule is used to acquire the type of the target pollutant; The control submodule is used to control the air purification system in the car cabin to perform the air purification operation corresponding to the target pollutant according to the type of the target pollutant. The first control subunit is used to control the air purification system to turn on ultraviolet light for purification when the target pollutant is ammonia or hydrogen sulfide. The second control subunit is used to control the air purification system to start external circulation purification when the target pollutant is carbon dioxide. The third control subunit is used to control the air purification system to activate negative ion pulse purification when the target pollutant is PM2.5.

[0080] Optionally, the system further includes: The second acquisition submodule is used to acquire seat pressure monitoring data from the seat pressure sensor, and when the seat pressure monitoring data indicates that the car cabin is unloaded, to activate the target level of the ultraviolet light purification, wherein the target level of the ultraviolet light purification is the highest level among all the ultraviolet light purification levels; and / or, The third acquisition submodule is used to acquire ozone concentration monitoring data, and to turn off the negative ion purification when the ozone concentration monitoring data is greater than or equal to a preset ozone concentration threshold and the negative ion pulse purification is in the on state.

[0081] Based on the same inventive concept, a third aspect of the embodiments of this application provides a method as follows: Figure 6 The electronic device 100 shown includes a processor 120, a memory 110, and a program or instructions stored in the memory 110 and executable on the processor 120, wherein the program or instructions, when executed by the processor 120, implement the steps of the automotive cabin pollutant monitoring method as described in the first aspect of this application.

[0082] Based on the same inventive concept, in a fourth aspect of this application, a readable storage medium is provided, on which a program or instructions are stored, which, when executed by a processor, implement the steps of the vehicle cabin pollutant monitoring method as described in the first aspect of this application.

[0083] Each embodiment in this specification focuses on the differences from other embodiments. For the same or similar parts between the embodiments, please refer to each other.

[0084] Those skilled in the art will understand that embodiments of this application can be provided as methods, apparatus, or computer program products. Therefore, embodiments of this application can take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, embodiments of this application can take the form of computer program products implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0085] This application describes embodiments with reference to flowchart illustrations and / or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of this application. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, generate instructions for implementing the flowchart illustrations. Figure 1One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0086] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing terminal device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0087] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal equipment, causing a series of operational steps to be performed on the computer or other programmable terminal equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable terminal equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0088] Although preferred embodiments of the present application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the embodiments of the present application.

[0089] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or terminal device. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or terminal device that includes said element.

[0090] The above provides a detailed description of a method, system, device, and medium for monitoring pollutants in an automotive cabin. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for monitoring pollutants in an automobile cabin, characterized in that, The method includes: Monitor the concentration of target pollutants inside the cabin; If the concentration of the target pollutant is greater than the baseline concentration threshold of the target pollutant, obtain the status information of each member in the cabin and the current driving scenario information. Based on the status information of all members and the current driving scenario information, determine the target concentration threshold correction factor; The base concentration threshold of the target pollutant is corrected by the target concentration threshold correction factor to obtain the corrected concentration threshold; If the concentration of the target pollutant is greater than or equal to the corrected concentration threshold, it is determined that the target pollutant exceeds the standard in the cabin.

2. The method for monitoring pollutants in an automotive cabin according to claim 1, characterized in that, The step of determining the target concentration threshold correction factor based on the individual status information of all members and the current driving scenario information includes: Based on the status information of all members, determine the image information and physiological status information of the target member, wherein the target member is any one of all members; Based on the current driving scenario information, as well as the image information and physiological state information of the target member, a candidate concentration threshold correction factor for the target member is determined; Based on the candidate concentration threshold correction factors of all target members, the candidate concentration threshold correction factor with the highest value is determined as the target concentration threshold correction factor.

3. The method for monitoring pollutants in an automotive cabin according to claim 2, characterized in that, The step of determining the candidate concentration threshold correction factor for the target member based on the current driving scenario information, as well as the image information and physiological state information of the target member, includes: Perform facial recognition on the image information of the target member to obtain the image recognition result of the target member; Based on the image recognition results of the target member, determine the individual adjustment factor of the target member; Based on the physiological state information of the target member, a first physiological state index and a second physiological state index are determined for the target member. The first physiological state index represents a physiological state index based on heart rate variability, and the second physiological state index represents a physiological state index based on skin conductance response. Based on the current driving scenario information, determine the first weight corresponding to the first physiological state index and the second weight corresponding to the second physiological state index; The candidate concentration threshold correction factor for the target member is calculated based on the first physiological state index, the first weight, the second physiological state index, the second weight, and the individual regulation factor.

4. The method for monitoring pollutants in an automotive cabin according to claim 3, characterized in that, The step of determining the individual adjustment factor of the target member based on the image recognition result of the target member includes: Based on the image recognition results, the target member is identified to obtain the identification result; Based on the identity recognition result, retrieve the health record corresponding to the target member; Based on the health status recorded in the health records, determine the individual moderating factors of the target members; Wherein, when the health status indicates that the target member is an unhealthy population, the individual moderating factor is negative; when the health status indicates that the target member is a healthy population, the individual moderating factor is zero.

5. The method for monitoring pollutants in an automotive cabin according to claim 3, characterized in that, The step of determining the first physiological state index and the second physiological state index of the target member based on the target member's physiological state information includes: Obtain the baseline and current values ​​of the heart rate variability data of the target member. The ratio of the difference between the baseline value and the current value of the heart rate variability data to the baseline value of the heart rate variability data is determined as the first physiological state index. The ratio of the difference between the current value and the baseline value of the skin conductance response data to the baseline value of the skin conductance response data is determined as the second physiological state index.

6. The method for monitoring pollutants in an automobile cabin according to any one of claims 1-5, characterized in that, After determining that the target pollutant exceeds the standard in the vehicle cabin environment, the method further includes: Obtain the type of the target pollutant; Based on the type of the target pollutant, control the air purification system in the car cabin to perform the air purification operation corresponding to the target pollutant; When the target pollutant is ammonia or hydrogen sulfide, the air purification system is controlled to turn on ultraviolet light for purification. When the target pollutant is carbon dioxide, the air purification system is controlled to activate external circulation purification. When the target pollutant is PM2.5, the air purification system is controlled to activate negative ion pulse purification.

7. The method for monitoring pollutants in an automotive cabin according to claim 6, characterized in that, After controlling the air purification system to perform the target air purification operation corresponding to the target pollutant, the method further includes: Acquire seat pressure monitoring data from the seat pressure sensor, and when the seat pressure monitoring data indicates that the vehicle cabin is unloaded, activate the target level of the ultraviolet light purification system, wherein the target level of the ultraviolet light purification system is the highest level among all the ultraviolet light purification levels; and / or, Obtain ozone concentration monitoring data, and turn off the negative ion purification when the ozone concentration monitoring data is greater than or equal to a preset ozone concentration threshold and the negative ion pulse purification is in the on state.

8. A vehicle cabin pollutant monitoring system, characterized in that, The system includes: The monitoring module is used to monitor the concentration of target pollutants inside the cabin; The acquisition module is used to acquire the status information of all occupants in the cabin and the current driving scenario information when the concentration of the target pollutant is greater than the basic concentration threshold of the target pollutant. The first determining module is used to determine the target concentration threshold correction factor based on the status information of each member and the current driving scenario information; The correction module is used to correct the basic concentration threshold of the target pollutant using the target concentration threshold correction factor to obtain the corrected concentration threshold. The second determining module is used to determine that the target pollutant exceeds the standard in the cabin when the concentration of the target pollutant is greater than or equal to the corrected concentration threshold.

9. An electronic device, characterized in that, It includes a processor, a memory, and a program or instructions stored in the memory and executable on the processor, wherein the program or instructions, when executed by the processor, implement the steps of the vehicle cabin pollutant monitoring method as described in any one of claims 1-7.

10. A readable storage medium, characterized in that, The readable storage medium stores a program or instructions that, when executed by a processor, implement the steps of the automotive cabin pollutant monitoring method as described in any one of claims 1-7.

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