Monitoring method for intelligently judging smoking behavior based on changes in indoor air composition

Abstract

The present invention discloses a monitoring method for intelligently determining smoking behavior based on changes in indoor air composition. The method collects environmental factors such as PM2.5 data and TVOC data in an indoor environment in real time to obtain real-time PM2.5 data and TVOC data. The method also calculates a PM2.5 baseline value and a TVOC baseline value for each moment in the indoor environment. The PM2.5 baseline value and the TVOC baseline value for each moment are optimized and updated. The TVOC value-added value at that moment is calculated based on the TVOC baseline value, and the PM2.5 value-added value at that moment is calculated based on the PM2.5 baseline value. The method determines whether smoking behavior has occurred based on the TVOC value-added and PM2.5 value-added results. When smoking behavior is determined to have occurred, an alarm signal is issued. The method has the advantage of high monitoring sensitivity.

Description

Technical Field

[0001] The present invention relates to the technical field related to smoking monitoring, and specifically to a monitoring method for intelligently judging smoking behavior based on changes in indoor air components. Background Art

[0002] The health hazards of smoking are well-known. Research has found that a lit cigarette releases approximately 6,800 chemicals, of which approximately 4,000 are harmful to human health. These include tar, ammonia, nicotine, particulate matter, PM2.5, polonium-210, and over 3,800 other harmful chemicals, as well as dozens of carcinogens. Furthermore, the harmful effects of secondhand smoke (SHS) have long been the most widespread and serious indoor air pollution problem and a leading cause of death worldwide. Extensive evidence demonstrates that SHS causes numerous health risks, including increased risk of cardiovascular disease, cancer, and respiratory illnesses in adults, worsening asthma in children, and causing pneumonia, otitis media, and even behavioral problems. The harm is particularly severe for pregnant women and adolescents.

[0003] Given the significant safety hazards posed by smoking in public places and indoors (such as subways, trains, and shopping malls) to the health and environmental safety of smokers and those around them, relevant departments have implemented stricter management measures to prevent smoking in public places, supplemented by appropriate detection methods to monitor smoking behavior. Traditional smoking detection methods mostly rely on smoke sensors, but public acceptance of e-cigarettes is increasing, and e-cigarettes account for an increasing proportion of smokers' consumption. E-cigarettes also pose a significant threat to human health and environmental safety. The small amount of smoke produced by e-cigarettes makes existing smoke sensors insensitive and inaccurate. Summary of the Invention

[0004] In order to solve the problem in the prior art that traditional smoking detection means mostly rely on smoke sensors and have the defects of poor detection sensitivity and accuracy, the present invention provides a smoking monitoring alarm method.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0006] The present invention is a monitoring method for intelligently judging smoking behavior based on changes in indoor air composition, comprising the following steps:

[0007] Step 1: Collect the environmental factors of PM2.5 data and TVOC data in the indoor environment in real time to obtain real-time PM2.5 data and real-time TVOC data;

[0008] Step 2: Calculate the indoor PM2.5 baseline value and TVOC baseline value at each moment based on the obtained real-time PM2.5 data and real-time TVOC data;

[0009] Step 3: Calculate the TVOC value-added value at that moment based on the TVOC baseline value at that moment, and calculate the PM2.5 value-added value at that moment based on the PM2.5 baseline value at that moment;

[0010] Step 4: Determine whether there is smoking behavior based on the TVOC value-added and PM2.5 value-added results; when it is determined that smoking behavior has occurred, an alarm signal is automatically issued.

[0011] As a preferred technical solution of the present invention, the method described in step 2 for calculating the indoor PM2.5 baseline value at each moment based on the collected indoor real-time PM2.5 data is to divide a day into multiple large time periods of equal length, and divide each large time period into multiple small time periods of equal length. If the average PM2.5 value in the previous large time period is b, and the average PM2.5 value in the previous small time period is a, if |ab|≥c, then the average PM2.5 value a of the previous small time period is taken as the PM2.5 baseline value at the current moment, otherwise b is taken as the PM2.5 baseline value at the current moment, where c is an artificially set standard deviation; if smoking behavior occurs in the previous small time period, then the baseline value is the PM2.5 baseline value used to calculate the smoking behavior in the previous small time period.

[0012] As a preferred technical solution of the present invention, the method described in step 2 for calculating the indoor TVOC baseline value at each moment based on the collected indoor real-time TVOC data is that if the average TVOC value in the previous large time period is m, and the average TVOC value in the previous small time period is n, if |nm|≥d, then the average TVOC value n of the previous small time period is taken as the TVOC baseline value at the current moment, otherwise m is taken as the TVOC baseline value at the current moment, where d is the artificially set standard deviation. If smoking behavior occurred in the previous small time period, then the TVOC baseline value can be the TVOC baseline value used to calculate the smoking behavior in the previous small time period.

[0013] As a preferred technical solution of the present invention, the TVOC value-added is the difference between the average value of multiple TVOC data taken within a certain 1 minute at that moment and the TVOC baseline value;

[0014] The PM2.5 value-added is the difference between the average value of multiple PM2.5 data taken within a certain 1 minute in this small time period and the PM2.5 baseline value.

[0015] As a preferred technical solution of the present invention, the method for judging whether there is smoking behavior based on the TVOC value-added and PM2.5 value-added results in step 4 is: at any time, the calculated PM2.5 value-added and TVOC value-added are judged, and smoking behavior is only considered to have occurred if PM2.5 value-added ≥ H and TVOC value-added ≥ L are simultaneously satisfied, where H and L are manually set values.

[0016] As a preferred technical solution of the present invention, a system for implementing the monitoring method of intelligently judging smoking behavior based on changes in indoor air composition is provided, wherein the system comprises a PM2.5 sensor, a VOC sensor group, a data processing module, and a communication module arranged indoors, wherein the PM2.5 sensor, the VOC sensor group, and the communication module are all connected to the data processing module;

[0017] The PM2.5 sensor is used to collect indoor PM2.5 data in real time;

[0018] The VOC sensor group is used to collect indoor TVOC data in real time;

[0019] The data processing module is used to receive and process data from the PM2.5 sensor and the VOC sensor group, and then upload it to the monitoring cloud through the communication module; when smoking behavior is detected, the monitoring cloud automatically sends a smoking alarm reminder to the user APP and web terminal.

[0020] As a preferred technical solution of the present invention, it also includes an alarm module connected to the data processing module. When smoking behavior is detected, the alarm module automatically issues a reminder warning message.

[0021] The beneficial effects of the present invention are:

[0022] This monitoring method, which intelligently determines smoking behavior based on changes in indoor air composition, collects real-time PM2.5 and TVOC data from indoor environments. It then calculates and optimizes the PM2.5 and TVOC baseline values ​​for each moment. It then calculates the TVOC value-added value at that moment based on the TVOC baseline value, and the PM2.5 value-added value at that moment based on the PM2.5 baseline value. Based on the TVOC value-added and PM2.5 value-added results, it determines whether smoking is occurring. When smoking is detected, an alarm is automatically issued. This method has the advantage of high monitoring sensitivity.

[0023] 2. This monitoring method, which intelligently determines smoking behavior based on changes in indoor air composition, divides a day into multiple large time periods of equal length, and divides each large time period into multiple small time periods of equal length. If the average PM2.5 value in the previous large time period is b, and the average PM2.5 value in the previous small time period is a, and if |ab| ≥ c, then the average PM2.5 value a in the previous small time period is taken as the PM2.5 baseline value at the current moment; otherwise, b is taken as the PM2.5 baseline value at the current moment, where c is an artificially set standard deviation; if smoking behavior occurred in the previous small time period, then the baseline value is the PM2.5 baseline value used to calculate smoking behavior in the previous small time period. Similarly, the TVOC baseline value at each moment is also obtained using the same method. When the real-time PM2.5 data and real-time TVOC data indoors show a slow increase, the baseline value of the previous moment is used as the baseline value of the current moment, and the PM2.5 value-added and TVOC value-added calculations are performed. This makes the PM2.5 value-added results and PM2.5 value-added results more obvious, indicating that the indoor PM2.5 values ​​and TVOC values ​​have changed significantly, thereby detecting smoking behavior and achieving a stronger sensitivity for smoking detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0025] Figure 1 It is a structural diagram of the monitoring method for intelligently judging smoking behavior based on changes in indoor air composition according to the present invention;

[0026] Figure 2 This is a system block diagram of the monitoring method for intelligently judging smoking behavior based on changes in indoor air components of the present invention.

[0027] In the figure: 1. PM2.5 sensor; 2. VOC sensor group; 3. Data processing module; 4. Communication module; 5. Alarm module. DETAILED DESCRIPTION

[0028] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention and are not used to limit the present invention.

[0029] Implementation case: Figure 1 As shown, the present invention is a monitoring method for intelligently judging smoking behavior based on changes in indoor air composition, comprising the following steps:

[0030] Step 1: Collect the environmental factors of PM2.5 data and TVOC data in the indoor environment in real time to obtain real-time PM2.5 data and real-time TVOC data;

[0031] Step 2: Calculate the indoor PM2.5 baseline value and TVOC baseline value at each moment based on the obtained real-time PM2.5 data and real-time TVOC data;

[0032] Step 3: Calculate the TVOC value-added value at that moment based on the TVOC baseline value at that moment, and calculate the PM2.5 value-added value at that moment based on the PM2.5 baseline value at that moment;

[0033] Step 4: Based on the TVOC and PM2.5 value increases, determine whether there is smoking behavior; if smoking behavior is determined to have occurred, automatically issue an alarm signal. This method has the advantage of high monitoring sensitivity.

[0034] Among them, the method described in step 2 for calculating the indoor PM2.5 baseline value at each moment based on the collected indoor real-time PM2.5 data is to divide a day into multiple large time periods of equal length, and divide each large time period into multiple small time periods of equal length. If the average PM2.5 value in the previous large time period is b, and the average PM2.5 value in the previous small time period is a, if |ab|≥c, then the average PM2.5 value a of the previous small time period is taken as the PM2.5 baseline value at the current moment, otherwise b is taken as the PM2.5 baseline value at the current moment, where c is an artificially set standard deviation; if smoking behavior occurs in the previous small time period, then the baseline value is the PM2.5 baseline value used to calculate the smoking behavior in the previous small time period.

[0035] Similarly, the TVOC baseline value at each moment is obtained using the same method. The method described in step 2 for calculating the indoor TVOC baseline value at each moment based on the collected indoor real-time TVOC data is as follows: if the average TVOC value in the previous large time period is m, and the average TVOC value in the previous small time period is n, if |nm|≥d, then the average TVOC value n of the previous small time period is taken as the TVOC baseline value at the current moment; otherwise, m is taken as the TVOC baseline value at the current moment, where d is the manually set standard deviation. If smoking occurred in the previous small time period, then the TVOC baseline value is the TVOC baseline value used in the calculation of smoking behavior in the previous small time period.

[0036] In this way, when the real-time PM2.5 data and real-time TVOC data indoors show a slow increase, the baseline value at the previous moment is used as the baseline value at the current moment to calculate the PM2.5 value-added and TVOC value-added. This makes the PM2.5 value-added results and PM2.5 value-added results more obvious, indicating that the PM2.5 value and TVOC value indoors have obvious changes, thereby detecting smoking behavior and achieving a stronger sensitivity of smoking detection.

[0037] The TVOC increment is calculated as the difference between the TVOC baseline value and the average value of multiple TVOC data points taken within a 1-minute period. The PM2.5 increment is calculated as the difference between the PM2.5 baseline value and the average value of multiple PM2.5 data points taken within a 1-minute period. This allows for the determination of TVOC and PM2.5 increments at each moment, thereby providing dynamic data on PM2.5 and TVOC. If a significant increase is observed, smoking is detected. This detection method offers high sensitivity.

[0038] Among them, the method for judging whether there is smoking behavior based on the TVOC value-added and PM2.5 value-added results in step 4 is: at any time, the calculated PM2.5 value-added and TVOC value-added are judged. Only when PM2.5 value-added ≥ H and TVOC value-added ≥ L are simultaneously satisfied, it is considered that there is smoking behavior, where H and L are manually set values.

[0039] Among them, it includes a system for implementing the monitoring method of intelligently judging smoking behavior based on changes in indoor air components, such as Figure 2 As shown, the system includes a PM2.5 sensor 1, a VOC sensor group 2, a data processing module 3 and a communication module 4 arranged indoors, and the PM2.5 sensor 1, the VOC sensor group 2 and the communication module 4 are all connected to the data processing module 3;

[0040] The PM2.5 sensor 1 is used to collect indoor PM2.5 data in real time;

[0041] The VOC sensor group 2 is used to collect indoor TVOC data in real time;

[0042] The data processing module 3 receives and processes data from the PM2.5 sensor 1 and the VOC sensor group 2, and then uploads it to the monitoring cloud via the communication module 4. When smoking is detected, the monitoring cloud sends a smoking alert to the user's app or website. Also included is an alarm module 5 connected to the data processing module 3. When smoking is detected, the alarm module 5 issues a warning message.

[0043] Specifically, this invention uses specific actual parameters for illustration. Under stable environmental conditions, the average PM2.5 value in a room over the past hour is referred to as the "PM2.5 baseline value," and the average TVOC value is referred to as the "TVOC baseline value." Each hour is divided into six time periods, with each ten-minute period being considered a time period.

[0044] The operation of determining the reference value in the present invention is as follows: assuming that the current time is 10:17, the average PM2.5 value at 9 o'clock is b, and the average PM2.5 value in the previous 10 minutes is a, and ab|≥15, then the current "PM2.5 reference value" is a instead of b; if smoking occurred in the previous ten minutes, then the reference value is the reference value used for calculating the smoking behavior in the previous ten minutes; wherein the present invention regards each hour as a large time period, and divides each hour into 6 small time periods, each ten minutes into a small time period: 00-10, 10-20...50-60; if it is 9:15 now, then the previous small time period refers to the 00-10 small time period;

[0045] A day is divided into 24 hours, and each hour can be considered a large time period. For example, if it is 9:15 now, then the previous large time period is 8:00-9:00;

[0046] When calculating the baseline value at 9:15, we will calculate the average value a of the 9:00-9:10 time period and the average value b of the 8:00-9:00 time period. If |ab|≥15, we use a as the baseline value at 9:15; otherwise, we use b.

[0047] If smoking occurred in the previous hour, for example, smoking was detected at any time between 9:00 and 9:10, and the benchmark used to determine whether smoking occurred during the hour between 9:00 and 9:10 was d; then at any time between 9:10 and 9:20, the benchmark value for smoking determination can be directly d.

[0048] Similarly, the TVOC baseline value for each small time period is calculated using the same method. If the average TVOC value for the previous large time period is m, and the average TVOC value for the previous small time period is n, if |nm| ≥ d, then the average TVOC value n for the previous small time period is used as the current TVOC baseline value. Otherwise, m is used as the current TVOC baseline value, where d is the manually set standard deviation. If smoking occurred in the previous small time period, the TVOC baseline value used for smoking in the previous small time period can be used as the TVOC baseline value. If |nm| ≥ 30, where d is 30, then the TVOC baseline value is n instead of m.

[0049] When PM2.5 sensor 1 and VOC sensor group 2 in a room just start recording data, or when PM2.5 sensor 1 and VOC sensor group 2 are offline for a period of time, resulting in no data for the past hour or 10 minutes in this space, the PM2.5 baseline value and TVOC baseline value are the average of the previous 3 minutes, and smoking determination is not performed in the first 3 minutes. To describe this with specific data, suppose it is 10:17 now, but you just connected our product at 10:12. In this case, there is no data from 8:00-9:00 and no data from 9:00-9:10, so the baseline value cannot be calculated. In this case, the baseline value is the average of the previous 3 minutes, that is, the average value from 10:12-10:15.

[0050] At any moment, the calculated "PM2.5 value-added" and "TVOC value-added" are judged. Only when the PM2.5 value-added is ≥40 and the TVOC value-added is ≥30 at the same time, is it considered as smoking behavior.

[0051] Finally, it should be noted that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art will be able to modify the technical solutions described in the aforementioned embodiments or substitute equivalents for some of the technical features. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A monitoring method for intelligently determining smoking behavior based on changes in indoor air composition, characterized by: The following steps are included: Step 1: Collect the environmental factors of PM2.5 data and TVOC data in the indoor environment in real time to obtain real-time PM2.5 data and real-time TVOC data; Step 2: Calculate the indoor PM2.5 baseline value and TVOC baseline value at each moment based on the obtained real-time PM2.5 data and real-time TVOC data; Step 3: Calculate the TVOC value-added value at that moment based on the TVOC baseline value at that moment, and calculate the PM2.5 value-added value at that moment based on the PM2.5 baseline value at that moment; Step 4: Determine whether there is smoking behavior based on the TVOC and PM2.5 value-added results; When it is determined that smoking behavior occurs, an alarm signal is automatically issued; The method for calculating the indoor PM2.5 baseline value and TVOC baseline value at each moment based on the obtained real-time PM2.5 data and real-time TVOC data in step 2 is to divide a day into multiple large time periods of equal length, and divide each large time period into multiple small time periods of equal length. If the average PM2.5 value in the previous large time period is b, and the average PM2.5 value in the previous small time period is a, if |ab|≥c, then the average PM2.5 value a of the previous small time period is taken as the PM2.5 baseline value at the current moment, otherwise b is taken as the PM2.5 baseline value at the current moment, where c is an artificially set standard deviation; if smoking behavior occurs in the previous small time period, then the baseline value is the PM2.5 baseline value used for calculating the smoking behavior in the previous small time period.

2. The method for intelligently judging smoking behavior based on changes in indoor air composition according to claim 1, characterized in that: In step 2, the method for calculating the indoor PM2.5 baseline value and TVOC baseline value at each moment based on the obtained real-time PM2.5 data and real-time TVOC data is as follows: if the average TVOC value in the previous large time period is m, and the average TVOC value in the previous small time period is n, if |nm|≥d, then the average TVOC value n of the previous small time period is taken as the TVOC baseline value at the current moment; otherwise, m is taken as the TVOC baseline value at the current moment, where d is the artificially set standard deviation. If smoking behavior occurs in the previous small time period, then the TVOC baseline value is the TVOC baseline value used for calculating the smoking behavior in the previous small time period.

3. The method for intelligently judging smoking behavior based on changes in indoor air composition according to claim 1, characterized in that: The TVOC value-added is the difference between the average value of multiple TVOC data taken within a certain 1 minute at that moment and the TVOC baseline value; The PM2.5 value-added is the difference between the average value of multiple PM2.5 data taken within a certain 1 minute at that moment and the PM2.5 baseline value.

4. The method for intelligently judging smoking behavior based on changes in indoor air composition according to claim 1, characterized in that: The method for judging whether there is smoking behavior based on the TVOC value-added and PM2.5 value-added results in step 4 is to judge the calculated PM2.5 value-added and TVOC value-added at any time. Only when PM2.5 value-added ≥ H and TVOC value-added ≥ L are simultaneously satisfied, it is considered that there is smoking behavior, where H and L are manually set values.

5. The method for intelligently judging smoking behavior based on changes in indoor air composition according to any one of claims 1 to 4, characterized in that: A system for implementing a monitoring method for intelligently judging smoking behavior based on changes in indoor air composition is provided, the system comprising a PM2.5 sensor (1), a VOC sensor group (2), a data processing module (3) and a communication module (4) arranged indoors, the PM2.5 sensor (1), the VOC sensor group (2) and the communication module (4) all being connected to the data processing module (3); The PM2.5 sensor (1) is used to collect indoor PM2.5 data in real time; The VOC sensor group (2) is used to collect indoor TVOC data in real time; The data processing module (3) is used to receive and process data from the PM2.5 sensor (1) and the VOC sensor group (2), and upload the data to the monitoring cloud through the communication module (4); when smoking behavior is detected, the monitoring cloud sends a smoking alarm reminder to the user APP and web terminal.

6. The method for intelligently judging smoking behavior based on changes in indoor air composition according to claim 5, characterized in that: It also includes an alarm module (5) connected to the data processing module (3), and when smoking behavior is detected, the alarm module (5) issues a reminder warning message.

Images