CN109744580B - Intelligent smoking control method and device - Google Patents
Intelligent smoking control method and device Download PDFInfo
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- CN109744580B CN109744580B CN201910026598.4A CN201910026598A CN109744580B CN 109744580 B CN109744580 B CN 109744580B CN 201910026598 A CN201910026598 A CN 201910026598A CN 109744580 B CN109744580 B CN 109744580B
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Abstract
The embodiment of the invention provides an intelligent smoking control method and device. The method comprises the following steps: detecting an energy value of a target heat source signal; judging whether the heat energy value is in a preset range or not, wherein the preset range is determined according to the heat energy value of cigarette combustion; if the heat energy value is in a preset range, detecting whether smoking action exists or not according to the change of the heat energy value in a first preset time; if the smoking action is judged to exist, evaluating the tobacco leaf quality of the target cigarette based on an intelligent smoking control formula; and if the tobacco leaf quality of the target cigarette is lower than a preset threshold value, reminding the user to stop smoking. The embodiment of the invention has the beneficial effects of providing better smoking experience for users and simultaneously ensuring the health of the users.
Description
Technical Field
The embodiment of the invention relates to the technical field of health management, in particular to an intelligent smoking control method and device.
Background
Tobacco quality is an important indicator of smoker health today, and low quality tobacco can both affect the smoker experience and even destroy the smoker health.
The variety, producing area, position, growing environment, climate condition and other factors of the leaves can have great influence on the quality of the tobacco leaves. At present, the quality of tobacco leaves is mainly evaluated from four aspects of sensory quality, appearance quality, chemical components and physical properties. The sensory quality and the appearance quality are mainly evaluated by professional staff, the steps are complicated, sensory fatigue is easy to generate due to large workload, subjective errors may exist in evaluation results, the repeatability is unstable, the preference and the evaluation score gradient among different evaluation individuals are difficult to be consistent, and large fluctuation of product quality may be caused. Therefore, the quality of the tobacco leaves is evaluated by using the chemical index data of the tobacco leaves, and the problems of unstable quality of finished cigarettes and the like caused by quality mixing of the tobacco leaves can be effectively avoided.
However, the conventional intelligent smoking control method cannot perform control based on the evaluation result of tobacco quality, and is not accurate and reasonable.
Disclosure of Invention
Embodiments of the present invention provide an intelligent smoking control method and apparatus that overcomes, or at least partially solves, the above-mentioned problems.
In a first aspect, an embodiment of the present invention provides an intelligent smoking control method, including: detecting an energy value of a target heat source signal;
judging whether the heat energy value is in a preset range or not, wherein the preset range is determined according to the heat energy value of cigarette combustion; if the heat energy value is in a preset range, detecting whether smoking action exists or not according to the change of the heat energy value in a first preset time;
if the smoking action is judged to exist, evaluating the tobacco leaf quality of the target cigarette based on an intelligent smoking control formula;
if the tobacco leaf quality of the target cigarette is lower than a preset threshold value, reminding a user to stop smoking;
wherein, intelligence smoking control formula obtains through following mode: obtaining various chemical indexes of the sample tobacco leaves; screening a plurality of chemical indexes according to the correlation coefficient of each chemical index and the sensory quality evaluation score to obtain chemical component evaluation indexes; establishing a corresponding fitting score function for each chemical component evaluation index to obtain a corresponding fitting score; and setting a corresponding weight value for each chemical evaluation index according to the correlation coefficient of the fitting score and the sensory evaluation score, and obtaining an intelligent smoking control formula in a weighting summation mode.
In a second aspect, an embodiment of the present invention provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the program, the steps of the intelligent smoking control method in the first aspect are implemented.
In a third aspect, embodiments of the present invention provide a non-transitory computer-readable storage medium on which is stored a computer program, which when executed by a processor implements the steps of the intelligent smoking control method of the first aspect.
The embodiment of the invention detects the energy value of the target heat source signal; judging whether the heat energy value is in a preset range or not, wherein the preset range is determined according to the heat energy value of cigarette combustion; if the heat energy value is in a preset range, detecting whether smoking action exists or not according to the change of the heat energy value in a first preset time; if the smoking action is judged to exist, evaluating the tobacco leaf quality of the target cigarette based on an intelligent smoking control formula; if the tobacco leaf quality of the target cigarette is lower than a preset threshold value, reminding a user to stop smoking; wherein, intelligence smoking control formula obtains through following mode: obtaining various chemical indexes of the sample tobacco leaves; screening a plurality of chemical indexes according to the correlation coefficient of each chemical index and the sensory quality evaluation score to obtain chemical component evaluation indexes; establishing a corresponding fitting score function for each chemical component evaluation index to obtain a corresponding fitting score; and setting a corresponding weight value for each chemical evaluation index according to the correlation coefficient of the fitting score and the sensory evaluation score, and obtaining an intelligent smoking control formula in a weighting summation mode. The embodiment of the invention has the beneficial effects of providing better smoking experience for users and simultaneously ensuring the health of the users.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
Fig. 1 is a schematic flow chart of an intelligent smoking control method according to an embodiment of the present invention;
fig. 2 is a schematic physical structure diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a schematic flow chart of an intelligent smoking control method according to an embodiment of the present invention. As shown in fig. 1, the intelligent smoking control method includes:
s1, the energy value of the target heat source signal;
s2, judging whether the heat energy value is in a preset range or not, wherein the preset range is determined according to the heat energy value of cigarette combustion; if the heat energy value is in a preset range, detecting whether smoking action exists or not according to the change of the heat energy value in a first preset time;
s3, evaluating the tobacco leaf quality of the target cigarette based on an intelligent smoking control formula if the smoking action exists;
s4, if the tobacco leaf quality of the target cigarette is lower than a preset threshold value, reminding a user to stop smoking;
wherein, intelligence smoking control formula obtains through following mode: 101, obtaining various chemical indexes of sample tobacco leaves; 102, screening a plurality of chemical indexes according to the correlation coefficient of each chemical index and the sensory quality evaluation score to obtain chemical component evaluation indexes; 103, establishing a corresponding fitting score function for each chemical component evaluation index to obtain a corresponding fitting score; and 104, setting a corresponding weight value for each chemical evaluation index according to the correlation coefficient of the fitting score and the sensory evaluation score, and obtaining an intelligent smoking control formula in a weighted summation mode.
Specifically, in step 101, a tobacco sample of a production area or type to be tested is selected, and various chemical indexes of each tobacco raw material are extracted from the tobacco sample. The chemical indexes can be used for evaluating the quality of the tobacco leaves.
And 102, screening the multiple chemical indexes selected in the step 101 according to the correlation coefficient of each chemical index and the sensory quality evaluation score, and taking the screened chemical indexes as chemical component evaluation indexes. For example, a chemical index having a correlation coefficient with the sensory quality evaluation score larger than a preset value is screened as a chemical composition evaluation index.
And 103, establishing a corresponding fitting score function for each chemical component evaluation index screened in the step 102, and obtaining a fitting score corresponding to the corresponding fitting score function. For example, the chemical component evaluation indexes to be screened are the sugar nitrogen ratio, the nitrogen-base ratio, the nicotine ratio, and the potassium-chlorine ratio, respectively. And for the sugar-nitrogen ratio, setting a fitting function type according to the distribution trend of the scatter diagram of the sugar-nitrogen ratio and the sensory quality evaluation score, and obtaining a fitting score function of the sugar-nitrogen ratio by adopting a hook function, wherein the fitting score function comprises the following steps:
wherein, y1Fitting score, x, for sugar to nitrogen ratio1Is a numerical value of sugar nitrogen ratio.
And for the nitrogen-base ratio, setting the type of a fitting function according to the distribution trend of a fitting graph of the nitrogen-base ratio and the sensory quality evaluation score, and obtaining a fitting score function of the nitrogen-base ratio by adopting a hook function, wherein the fitting score function is as follows:
wherein, y2Fitting score, x, for the nitrogen to base ratio2Is a numerical value of the nitrogen-base ratio.
For nicotine, the type of a fitting function is set according to the distribution trend of a fitting graph of the nicotine and the sensory quality evaluation score, and a fitting score function of nicotine is obtained by adopting a quadratic function as follows:
y3＝-15x3 2+90x3-40， (3)
wherein, y3Is the fit score, x, of nicotine3Is the value of nicotine.
And for the potassium-chlorine ratio, setting the type of a fitting function according to the distribution trend of a fitting graph of the potassium-chlorine ratio and the sensory quality evaluation score, and obtaining a fitting score function of the potassium-chlorine ratio by adopting a piecewise linear function, wherein the fitting score function comprises the following steps:
wherein, y4Fitting score, x, for the potassium to chloride ratio4Is a numerical value of the ratio of potassium to chlorine.
And substituting each chemical evaluation index of each selected sample into a corresponding fitting scoring function to obtain a corresponding fitting score. For example, if the number of samples selected is 100, then fitting each chemical evaluation index for each sample into the corresponding fitting score function yields 100 corresponding fitting scores for each chemical evaluation index.
And step 104, performing relevance analysis on the fitting score and the sensory evaluation score obtained in the step 103, setting a corresponding weight value for each chemical evaluation index according to the corresponding relevance coefficient and the size of the relevance coefficient, and performing weighted summation on the fitting score function corresponding to each chemical component evaluation index obtained in the step 103 to obtain a formula for evaluating the quality of the tobacco leaves. For example: according to the correlation coefficient of the fitting score and the sensory evaluation score, the weight values of the sugar-nitrogen ratio, the nitrogen-alkali ratio, the nicotine ratio and the potassium-chlorine ratio are set to be 0.4, 0.3, 0.2 and 0.1 respectively in a manual or software calculation mode, and then a formula for evaluating the tobacco quality is obtained in a weighting summation mode, and the following formula is obtained:
wherein Y is a fitting value of the tobacco leaf quality; x is the number of1Is the numerical value of the sugar nitrogen ratio; x is the number of2Is the numerical value of the nitrogen-base ratio; x is the number of3Is the value of nicotine; x is the number of4Is a numerical value of the ratio of potassium to chlorine.
According to the embodiment of the invention, the chemical indexes are screened according to the correlation coefficient of each chemical index and the sensory quality evaluation value by acquiring various chemical indexes of the tobacco leaf raw material, and the chemical component evaluation indexes are reasonably and comprehensively set; and establishing a corresponding fitting scoring function for each chemical component evaluation index to obtain a corresponding fitting score, reasonably setting a corresponding weight value of each chemical evaluation index according to a correlation coefficient of the fitting score and the sensory evaluation score, and finally obtaining a formula for evaluating the quality of the tobacco leaves in a weighted summation mode. The obtained formula for evaluating the quality of the tobacco leaves is more accurate, and the quality of the tobacco leaves can be effectively evaluated, so that the long-term sustainable stable development of the quality of tobacco leaf products is promoted.
On the basis of the above embodiment, as an alternative embodiment, the chemical indexes include: chemical composition indices and chemical composition derivative indices; accordingly, various chemical indexes of the tobacco leaves are obtained, including: acquiring near infrared spectrum data of tobacco leaves, and constructing a near infrared quantitative mathematical model of the near infrared spectrum data; calculating to obtain various chemical component indexes through a near infrared quantitative mathematical model; and calculating to obtain various chemical derivative indexes according to the chemical component indexes.
Specifically, the chemical indexes of the tobacco leaves comprise chemical component indexes and chemical component derivative indexes. As an alternative embodiment, the chemical composition indicators include: total sugar, total nitrogen, nicotine, total potassium, and total chloride. As an alternative embodiment, the chemical derivation indicators include: sugar nitrogen ratio, nitrogen-base ratio, potassium-chlorine ratio.
Selecting tobacco leaf samples of a production area or type to be detected, scanning all the samples by using a near-infrared instrument, acquiring near-infrared spectrum data of tobacco leaf raw materials, and constructing a near-infrared quantitative mathematical model of the near-infrared spectrum data. As an alternative embodiment, after acquiring the near infrared spectrum data of the tobacco leaf raw material, the method further includes: the near infrared spectral data is preprocessed using a derivation and smoothing process. As an alternative embodiment, the spectral range of the near infrared spectral data comprises: 4000-8000 cm.
For example, collecting 465 parts of near infrared spectrum data of tobacco leaves in total in 2014 and 2015 years, namely Liangshan, Panzhihua, Luzhou, Yibin and Guangyuan areas; and establishing a near-infrared quantitative mathematical model of the contents of total sugar, total nitrogen, nicotine, organic potassium and total chlorine, limiting the near-infrared spectrum range to 4000-8000 cm during modeling, and preprocessing the spectrum by using a first derivative and 15-point smoothing. Analyzing the total sugar, total nitrogen, nicotine, organic potassium and total chlorine contents of 200 tobacco leaf samples in total in 2016 and 2017 years of summer hills, climbing rosewood, Luzhou, Yibin and Guangyuan areas by using the constructed near-infrared quantitative mathematical model; and calculating the numerical values of the sugar-nitrogen ratio, the nitrogen-alkali ratio and the potassium-chlorine ratio of the tobacco leaf sample.
According to the embodiment of the invention, the near infrared quantitative mathematical model of the near infrared spectrum data is constructed by selecting the tobacco leaf sample of the production area or type to be detected and acquiring the near infrared spectrum data of the tobacco leaf raw material. Corresponding chemical component indexes and chemical derivative indexes can be conveniently and quickly obtained by directly inputting the near infrared spectrum data of the tobacco leaf samples in the same production area or type into the near infrared quantitative mathematical model.
On the basis of the above embodiments, as an optional embodiment, screening multiple chemical indexes according to the correlation coefficient between each chemical index and the sensory quality evaluation score to obtain chemical component evaluation indexes, including: fitting the sensory quality evaluation values and the chemical indexes by a linear function fitting method to obtain corresponding correlation coefficients, screening the chemical indexes according to the correlation coefficients, and selecting the chemical indexes of which the correlation coefficients reach a set threshold value as chemical component evaluation indexes.
Specifically, the tobacco leaves have various chemical indexes, and the influence of each chemical index on the quality of the tobacco leaves is different, so that the various chemical indexes of the tobacco leaves need to be screened. Fitting the existing sensory quality evaluation values and the correlation of various chemical indexes of the tobacco leaves by a linear function fitting method, obtaining correlation coefficients by fitting, comprehensively considering the conditions of co-correlation and the like among the indexes, and screening out the chemical indexes of which the correlation coefficients reach a set threshold value from the various chemical indexes of the tobacco leaves as chemical component evaluation indexes. For example, 2016 sensory quality evaluation values and various chemical indexes of tobacco leaves are fitted by a linear function fitting method to obtain correlation coefficients between the 2016 sensory quality evaluation values and the various chemical indexes, and sugar-nitrogen ratio, nitrogen-base ratio, nicotine and potassium-chlorine ratio are screened out as the chemical component evaluation indexes according to the magnitude of the correlation coefficients and by comprehensively considering the co-correlation and other conditions between the indexes.
According to the embodiment of the invention, the chemical indexes are screened according to the sensory quality evaluation score and the correlation coefficient of the chemical indexes, so that the corresponding chemical component evaluation indexes are obtained. The chemical component evaluation indexes for evaluating the quality of the tobacco leaves can be set more comprehensively and reasonably.
Fig. 2 is a schematic physical structure diagram of an electronic device according to an embodiment of the present invention. As shown in fig. 2, the electronic device includes: a processor (processor)310, a communication Interface (communication Interface)320, a memory (memory)330 and a communication bus 340, wherein the processor 310, the communication Interface 320 and the memory 330 communicate with each other via the communication bus 340. The processor 310 may call logic instructions in the memory 330 to perform the following method: detecting an energy value of a target heat source signal; judging whether the heat energy value is in a preset range or not, wherein the preset range is determined according to the heat energy value of cigarette combustion; if the heat energy value is in a preset range, detecting whether smoking action exists or not according to the change of the heat energy value in a first preset time; if the smoking action is judged to exist, evaluating the tobacco leaf quality of the target cigarette based on an intelligent smoking control formula; if the tobacco leaf quality of the target cigarette is lower than a preset threshold value, reminding a user to stop smoking; wherein, intelligence smoking control formula obtains through following mode: obtaining various chemical indexes of the sample tobacco leaves; screening a plurality of chemical indexes according to the correlation coefficient of each chemical index and the sensory quality evaluation score to obtain chemical component evaluation indexes; establishing a corresponding fitting score function for each chemical component evaluation index to obtain a corresponding fitting score; and setting a corresponding weight value for each chemical evaluation index according to the correlation coefficient of the fitting score and the sensory evaluation score, and obtaining an intelligent smoking control formula in a weighting summation mode.
In addition, the logic instructions in the memory 330 may be implemented in the form of software functional units and stored in a computer readable storage medium when the software functional units are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
An embodiment of the present invention provides a non-transitory computer-readable storage medium, where the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions enable a computer to execute the intelligent smoking control method provided in the foregoing embodiment, for example, the method includes: detecting an energy value of a target heat source signal; judging whether the heat energy value is in a preset range or not, wherein the preset range is determined according to the heat energy value of cigarette combustion; if the heat energy value is in a preset range, detecting whether smoking action exists or not according to the change of the heat energy value in a first preset time; if the smoking action is judged to exist, evaluating the tobacco leaf quality of the target cigarette based on an intelligent smoking control formula; if the tobacco leaf quality of the target cigarette is lower than a preset threshold value, reminding a user to stop smoking; wherein, intelligence smoking control formula obtains through following mode: obtaining various chemical indexes of the sample tobacco leaves; screening a plurality of chemical indexes according to the correlation coefficient of each chemical index and the sensory quality evaluation score to obtain chemical component evaluation indexes; establishing a corresponding fitting score function for each chemical component evaluation index to obtain a corresponding fitting score; and setting a corresponding weight value for each chemical evaluation index according to the correlation coefficient of the fitting score and the sensory evaluation score, and obtaining an intelligent smoking control formula in a weighting summation mode.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods of the various embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (9)
1. An intelligent smoking control method is characterized by comprising the following steps:
detecting the heat energy value of a target heat source signal;
judging whether the heat energy value is in a preset range or not, wherein the preset range is determined according to the heat energy value of cigarette combustion; if the heat energy value is in a preset range, detecting whether smoking action exists or not according to the change of the heat energy value in a first preset time;
if the smoking action is judged to exist, evaluating the tobacco leaf quality of the target cigarette based on an intelligent smoking control formula;
if the tobacco leaf quality of the target cigarette is lower than a preset threshold value, reminding a user to stop smoking;
wherein, intelligence smoking control formula obtains through following mode: obtaining various chemical indexes of the sample tobacco leaves; screening a plurality of chemical indexes according to the correlation coefficient of each chemical index and the sensory quality evaluation score to obtain chemical component evaluation indexes; establishing a corresponding fitting score function for each chemical component evaluation index to obtain a corresponding fitting score; and setting a corresponding weight value for each chemical component evaluation index according to the correlation coefficient of the fitting score and the sensory quality evaluation score, and obtaining an intelligent smoking control formula in a weighting summation mode.
2. The method of claim 1, wherein the chemical indicator comprises: chemical composition indices and chemical composition derivative indices;
correspondingly, the obtaining of various chemical indexes of the tobacco leaves comprises the following steps:
acquiring near infrared spectrum data of tobacco leaves, and constructing a near infrared quantitative mathematical model of the near infrared spectrum data;
calculating and obtaining a plurality of chemical component indexes through the near infrared quantitative mathematical model;
and calculating to obtain a plurality of chemical component derivation indexes according to the chemical component indexes.
3. The method of claim 2, wherein after the obtaining of the near infrared spectral data of the tobacco leaves, further comprising:
the near infrared spectral data is pre-processed using a derivation and smoothing process.
4. The method according to claim 2, wherein the near infrared spectral data has a spectral range of 4000 to 8000 cm.
5. The method of claim 2, wherein the chemical composition indicators comprise: total sugar, total nitrogen, nicotine, total potassium, and total chloride.
6. The method of claim 2, wherein the chemical composition derived indicator comprises: sugar nitrogen ratio, nitrogen-base ratio, potassium-chlorine ratio.
7. The method according to claim 1, wherein the screening of a plurality of chemical indexes according to the correlation coefficient of each chemical index and the sensory quality evaluation score to obtain a chemical component evaluation index comprises:
fitting the sensory quality evaluation score and the chemical index by a linear function fitting method to obtain a corresponding correlation coefficient, screening the chemical index according to the correlation coefficient, and selecting the chemical index of which the correlation coefficient reaches a set threshold value as a chemical component evaluation index.
8. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method according to any of claims 1 to 7 are implemented when the processor executes the program.
9. A non-transitory computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.
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| CN110089778A (en) * | 2019-05-31 | 2019-08-06 | 合肥微纳传感技术有限公司 | A kind of electronic cigarette atomizing chip and electronic cigarette |
| CN111650133B (en) * | 2020-06-08 | 2023-11-14 | 惠州市新泓威科技有限公司 | Method for detecting and controlling harmful substances in solution to be atomized by electronic atomization equipment and electronic atomization equipment |
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| SU1396055A1 (en) * | 1984-10-05 | 1988-05-15 | Краснодарский политехнический институт | Device for testing the quality of initial tobacco materials |
| EP2813150A1 (en) * | 2013-06-10 | 2014-12-17 | Philip Morris Products S.A. | Filter quality control device |
| HUE032854T2 (en) * | 2013-08-13 | 2017-11-28 | Philip Morris Products Sa | Smoking article with dual heat-conducting elements and improved airflow |
| CN104000302B (en) * | 2014-06-17 | 2017-09-22 | 云南中烟工业有限责任公司 | A kind of tobacco juice for electronic smoke and its quality determining method |
| CN104063599B (en) * | 2014-06-26 | 2017-02-15 | 江苏中烟工业有限责任公司 | Index screening and processing method for evaluating quality of tobacco leaves |
| WO2016008067A1 (en) * | 2014-07-14 | 2016-01-21 | 惠州市吉瑞科技有限公司 | Cigarette smoking control method, cigarette smoking control circuit, and electronic cigarette |
| CN204483026U (en) * | 2015-03-04 | 2015-07-22 | 云南中烟工业有限责任公司 | A kind of electronic cigarette smoking set |
| CN205017611U (en) * | 2015-06-15 | 2016-02-03 | 深圳葆威道科技有限公司 | Temperature control system of electron cigarette heat -generating body |
| KR20240033172A (en) * | 2015-08-14 | 2024-03-12 | 필립모리스 프로덕츠 에스.에이. | An electrically operated smoking device including a system for identifying smoking articles in the device |
| CN108338414B (en) * | 2017-01-25 | 2022-05-27 | 贵州中烟工业有限责任公司 | Control method and control system of electric heating smoking system |
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