CN115493169A - Intelligent smoke exhaust ventilator device and intelligent control and food material recommendation method - Google Patents
Intelligent smoke exhaust ventilator device and intelligent control and food material recommendation method Download PDFInfo
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- CN115493169A CN115493169A CN202211041728.XA CN202211041728A CN115493169A CN 115493169 A CN115493169 A CN 115493169A CN 202211041728 A CN202211041728 A CN 202211041728A CN 115493169 A CN115493169 A CN 115493169A
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24C—DOMESTIC STOVES OR RANGES ; DETAILS OF DOMESTIC STOVES OR RANGES, OF GENERAL APPLICATION
- F24C15/00—Details
- F24C15/20—Removing cooking fumes
- F24C15/2021—Arrangement or mounting of control or safety systems
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/60—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to nutrition control, e.g. diets
Abstract
The scheme discloses an intelligent smoke exhaust ventilator device and an intelligent control and food material recommendation method, wherein a first monitoring module of the intelligent smoke exhaust ventilator device is used for monitoring the temperature of a target in a pot; the first confirming module is used for comparing the temperature information with the set temperature, and if the temperature information is greater than the set temperature, the second monitoring module is informed to enter a monitoring state; the second monitoring module is used for monitoring the oil smoke concentration; the second confirmation module is used for comparing the oil smoke concentration with the first set concentration, and if the oil smoke concentration is greater than the first set concentration, the second confirmation module informs the control module to start the range hood; the timing control module is used for starting timing when the concentration of the oil smoke is less than a second set concentration and informing the control module to close the range hood after timing to a set time; and the control module is used for controlling the opening, closing and working rotating speed of the range hood. This scheme can avoid indoor environmental pollution or the energy is extravagant, promotes smoke ventilator intelligent control's accurate nature and stability.
Description
Technical Field
The invention belongs to the technical field of kitchen appliances, and particularly relates to an intelligent range hood device and an intelligent control and food material recommendation method.
Background
The range hood plays a very important role in our lives, and the existence of the range hood greatly improves the quality of our lives and the cleanness degree of air. When people cook, a large amount of waste gas can be generated, the generated waste gas is hot air and can float to the upper part of the cooker, and the range hood is placed above the cooker, so that the waste gas can enter the range hood more easily. But present beam-pumping unit has not intelligent problem enough, and at first, smoke ventilator's opening or close all needs manual operation, often can appear forgetting the condition of opening smoke ventilator during the in-service use, if the smoke ventilator is not opened in time when culinary art, will lead to the oil smoke to get into at home, harm healthy. And when the cooking is finished, the energy is wasted if the range hood is not closed for a long time. Closing the range hood immediately after cooking will result in oil smoke residue, again be unfavorable for health and cleanness.
In addition, the existing oil pumping unit has the problem of single function, and along with the improvement of the living standard of people, intelligent, environment-friendly, healthy and diversified foods are the targets which are increasingly pursued by people. Most people in life are often puzzled by what to eat, and diversified diet is popular with general healthy pursuit users. If can utilize smoke ventilator to carry out the collection of food information, carry out the more balanced edible material of nutrition and recommend to the recipe that will correspond edible material, will be favorable to more solving the puzzlement among people's daily life, and the selection of more balanced edible material of nutrition.
Disclosure of Invention
The invention aims to solve the problems and provides an intelligent smoke exhaust ventilator device and an intelligent control and food material recommendation method.
In order to achieve the purpose, the invention adopts the following technical scheme:
an intelligent control method for a range hood comprises the following steps:
SA1, monitoring the temperature of a target in a pot;
SA2, when the temperature of the target in the pot exceeds a set temperature, starting to monitor the concentration of the oil smoke;
SA3, when the concentration of the oil smoke is greater than the first set concentration, starting the oil smoke exhauster;
SA4, continuously monitoring the oil smoke concentration, and starting timing when the oil smoke concentration is less than a second set concentration;
and SA5, closing the range hood after timing to a set time.
In the above intelligent control method for the range hood, in step SA4, the oil smoke concentration is continuously monitored during a timing period, and if the oil smoke concentration is greater than a first set concentration, the timing is ended until the oil smoke concentration is again less than a second set concentration, and the timing is restarted;
in step AS1, the temperature of the target in the pan is monitored by:
SA11, acquiring image information of a target in the pan;
SA12, acquiring a thermal image based on the image information by using an infrared thermal imaging technology, thereby acquiring the temperature of the target in the pan;
in the step SA2, the oil smoke concentration is monitored through an oil smoke sensor, and the oil smoke sensor is a particulate matter concentration sensor or a VOC gas sensor;
and in the step SA3, judging the current cooking mode according to the recipe selected by the user, and controlling the low-speed operation, the medium-speed operation or the high-speed operation of the range hood according to the cooking mode.
A cooking fume exhauster food material recommending method based on intelligent control of an oil pumping machine comprises the following steps:
SB1, in the cooking process of starting the range hood, acquiring image information of a target in the cooker, and analyzing the image information to determine food material information corresponding to the image information;
SB2, converting the food material information into information codes corresponding to the nutrient elements for storage;
SB3, recommending food materials to the user by using the stored historical information codes; the stored historical information codes comprise a large number of information codes stored in steps SB1 and SB2.
And SB4, saving the recommended food materials selected by the user, and recommending the recipe to the user based on the recommended food materials selected by the user.
In the above cooking fume exhauster food material recommending method based on intelligent control of the oil pumping unit, in step SB3, the food material is recommended to the user by the following method:
SB31, analyzing the nutrition balance degree of the user according to the user-food material preference scoring matrix; the user-food material preference scoring matrix is established based on historical information codes of the user;
calculating the similarity between the target user and other users according to the user-food material preference scoring matrix, and acquiring an adjacent user group of the target user according to the similarity;
selecting a plurality of users with nutrition balance degree higher than a balance threshold value from an adjacent user group as a neighbor set of a target user;
SB34, calculating the food material preference scores of which the preference scores are not scored by the target user or are lower than the preference score threshold value according to the existing preference scores of the neighbor sets, and sequencing;
and SB35, recommending the N or M food materials with the highest calculation scores to the target user, and taking N when N is less than M, or taking M which is the number of the food materials subjected to the food material preference scoring in the step SB34.
In the cooking fume exhauster food material recommending method based on the intelligent control of the oil pumping unit, in the step SB1, an infrared thermal imager is used for acquiring the image information of a target in a cooker;
and in the step SB4, the recommended recipes are pushed to the user client, and the recommended recipes selected by the user are displayed on a display screen of the range hood.
The utility model provides an intelligence smoke ventilator device, includes first monitoring module, first affirmation module, second monitoring module, second affirmation module and control module, wherein:
the first monitoring module is used for monitoring the temperature of the target in the pot and transmitting the temperature information to the first confirming module;
the first confirmation module is used for comparing the received temperature information with the set temperature, and if the monitored temperature information is greater than the set temperature, the second monitoring module is informed of entering a monitoring state;
the second monitoring module is used for monitoring the oil smoke concentration and transmitting the information of the oil smoke concentration to the second confirming module;
the second confirmation module is used for comparing the received oil smoke concentration with the first set concentration, and informing the control module to start the range hood if the monitored oil smoke concentration is greater than the first set concentration;
the control module is also used for continuously monitoring the oil smoke concentration when the range hood is in the opening state, starting timing when the oil smoke concentration is less than a second set concentration, and informing the control module to close the range hood after the timing reaches a set time;
and the control module is used for controlling the opening, closing and working rotating speed of the range hood.
In the above-mentioned intelligent smoke exhaust ventilator device, the temperature information transmitted by the first monitoring module to the first confirming module is the highest temperature of the target in the pan in the current detection;
or the temperature information transmitted to the first confirmation module by the first monitoring module is the average temperature of the target in the pot in the current detection;
or the temperature information transmitted to the first confirming module by the first monitoring module is the temperature distribution in the current detection, and the first confirming module selects the highest temperature or calculates the average temperature from the temperature distribution to compare with the set temperature.
In the above-mentioned intelligent smoke ventilator device, the second monitoring module continues to monitor the oil smoke concentration within the timing time period, and the second confirming module is further configured to end the timing when the oil smoke concentration is greater than the first set concentration within the timing time period, and restart the timing until the oil smoke concentration is again less than the second set concentration;
the first monitoring module comprises an infrared thermal imager, and the temperature of the target in the pan is acquired by acquiring the image information of the target in the pan and acquiring a thermal image based on the image information;
the second monitoring module comprises an oil smoke sensor, and the oil smoke sensor monitors the oil smoke concentration.
The intelligent range hood device further comprises an image processing module, a first monitoring module and a second monitoring module, wherein the image processing module is used for analyzing the image information acquired by the first monitoring module to determine food material information corresponding to the image information; the food material conversion module is used for converting the food material information into information codes of corresponding nutrient elements and storing the information codes in the storage module; the food material recommending module is used for recommending food materials to the user by utilizing the stored historical information codes and storing the recommended food materials selected by the user in the storage module; the pushing module is used for recommending recipes to the user client based on recommended food materials selected by the user; and the communication module is used for communicating with the user client.
In the above-mentioned intelligent smoke exhaust ventilator device, also include the display screen used for revealing the menu, the said control module is also used for controlling the working speed according to the menu revealed by the display screen;
the image processing module comprises a trained image recognition model, and training data used for the image recognition model comprises pictures of various food materials and food material information thereof;
the food material conversion module comprises a trained food material conversion model, and the training data for training the food material conversion model comprises various food material information and information codes of corresponding nutrient elements thereof;
the food material recommending module recommends food materials to the user through steps SB31-SB 35.
The invention has the advantages that:
1. the range hood can be opened and closed in time, and indoor environmental pollution or energy waste caused by forgetting to open or close the range hood by a user is avoided;
2. the delayed closing is adopted in the process of closing the range hood, so that indoor oil smoke can be sucked and removed as much as possible, the lifting is realized, and a healthier indoor environment is created;
3. the range hood is started by adopting a two-step monitoring mode, the oil smoke concentration is monitored and reacted after the temperature of food in the cooker reaches a set temperature, and at the moment, the oil smoke concentration is relatively high, a more reliable monitoring result can be realized, and the accuracy and the stability of intelligent control of the range hood are improved;
4. recommend the edible material that the user probably likes and nutrition collocation is even for the user according to user's dietary habit, can solve the puzzlement that the user does not know to eat at ordinary times, can also cater to user's hobby, promote the balanced degree of nutrition of the whole dietary habit of user simultaneously to promote user's quality of life.
Drawings
Fig. 1 is a block diagram of a module structure of an intelligent range hood device;
fig. 2 is a block diagram of a module structure of the intelligent range hood device;
FIG. 3 is a schematic view of the structure of a range hood in the intelligent range hood device;
fig. 4 is a flow chart of the intelligent control of the rotation speed in the intelligent range hood device;
fig. 5 is a first flowchart of an intelligent control method in an intelligent range hood device;
fig. 6 is a second flowchart of the intelligent control method in the intelligent range hood device;
fig. 7 is a flow chart of the intelligent control of the rotation speed in the intelligent range hood device;
fig. 8 is a flowchart of a food material recommendation method in the intelligent range hood device.
Reference numerals are as follows: a first monitoring module 1; a first confirmation module 2; a second monitoring module 3; a second validation module 4; a control module 5; an image processing module 6; a food material conversion module 7; a push module 8; a display screen 9.
Detailed Description
The invention is described in further detail below with reference to the drawings and the detailed description.
A first aspect of this scheme provides an intelligence smoke ventilator device, as shown in fig. 1, this device includes first monitoring module 1, first affirmation module 2, second monitoring module 3, second affirmation module 4 and control module 5, wherein:
the first monitoring module 1 is mainly used for monitoring the image information of food materials in the pot by utilizing an image acquisition device, wherein the food materials comprise main materials and auxiliary materials. Detecting an image of food materials in the pot, monitoring the temperature in the pot based on image information by utilizing an infrared thermal imaging technology, and transmitting the temperature information to a first confirmation module 2; can install smoke ventilator below with image acquisition device, the pot face top carries out the acquirement of eating the material image, and in this embodiment, utilize infrared thermal imager, both can acquire the interior material image of pot and can directly utilize infrared thermal imaging technique based on image information monitoring pot temperature again.
The first confirming module 2 is used for comparing the received temperature information with a set temperature, if the highest temperature of the monitored temperature in the cooker does not reach the set temperature, the range hood is kept in a closed state, and if the highest temperature of the monitored temperature in the cooker reaches the set temperature, the second monitoring module 3 is informed to enter a monitoring state; even if the user is heating food materials or boiling water, the monitored temperature also reaches the preset temperature through the first confirmation module 2, no oil smoke is generated, the range hood cannot be opened, the range hood can be started more accurately through two monitoring, and user experience is improved.
The set temperature can be 60 ℃, and when the temperature monitored by an infrared thermal imager facing the pan of the range hood is higher than 60 ℃, the monitoring of the oil smoke concentration is started.
And the second confirmation module 4 is used for comparing the received oil smoke concentration with the first set concentration, if the monitored oil smoke concentration is greater than the first set concentration and the range hood is in a closed state, notifying the control module 5 to start the range hood, continuously monitoring the oil smoke concentration in the open state of the range hood, starting timing when the oil smoke concentration is less than the second set concentration, and notifying the control module 5 to close the range hood after timing a set time. The first set concentration and the second set concentration may be the same concentration or different concentrations. After the range hood monitors that the concentration of surrounding oil smoke is lower than a second set concentration, the range hood is closed after a set time, the set time can be 3 minutes or 5 minutes and the like, and the range hood is closed after the set time is delayed to absorb the residual oil smoke in the air as clean as possible, so that a healthier environment is created.
And the control module 5 is used for controlling the opening, closing and working rotating speed of the range hood.
Further, the second monitoring module 3 continues to monitor the oil smoke concentration within the timing time period, and the second confirming module 4 is further configured to end timing when the oil smoke concentration is greater than the first set concentration within the timing time period, until the timing is restarted when the oil smoke concentration is again less than the second set concentration.
Specifically, the VOC value in the room specified in China is not higher than 200g/L, and the VOC requirement is required to be below 125 g/L. Therefore, the range hood is preferably started when the VOC gas sensor monitors that the VOC value is more than 125 g/L; when the VOC gas sensor monitors that the VOC value is less than 125g/L, the range hood is automatically closed after 5min, and the harmful gas in the air is ensured to be completely absorbed.
Further, as shown in fig. 2, the apparatus further includes an image processing module 6, a food material recommending module 7, a pushing module 8, a display screen, and a communication module. The image processing module 6 is configured to analyze the image information acquired by the first monitoring module 1 to determine food material information corresponding to the image information; the food material conversion module 7 is used for converting the food material information into information codes of corresponding nutrient elements and storing the information codes in the storage module; the food material recommending module 7 is used for recommending food materials to the user by using the stored historical information codes and storing the recommended food materials selected by the user in the storage module; the pushing module 8 is used for recommending recipes to the user based on the recommended food materials selected by the user; and the communication module is connected with the processor of the device and used for realizing network communication and realizing communication with an external database, a server, a user client and the like, for example, a recipe of corresponding food materials is obtained from the database so as to perfect a local recipe, a nutrition balance guide is obtained from the database, the recipe selected by the user is received from the user client and is displayed through a display screen, and the like. The food material recommending module 7 pushes recommended food materials to a user client side or a display screen of the range hood for selection of a user, the user selects food materials for use, the pushing module 8 pushes recommended recipes and recommending effects of related food materials to the user client side based on the selected food materials, the user can select one or more recipes at the user client side for storage, the recipes can be selected at the later stage when the recipes need to be used, and the range hood displays corresponding recipes on the display screen after receiving the selection of the user at the user client side. Then, as shown in fig. 3 and 4, the control module automatically adjusts the operating speed according to the recipe displayed on the display screen 9, for example, when the recipe recommends a cooking mode that generates less oil smoke such as boiling and steaming, the recipe recommends a cooking mode that generates more oil smoke such as stewing and braising, the recipe recommends a middle-speed operation, and when the recipe recommends a cooking mode that generates a large amount of oil smoke such as frying, frying and barbecuing, the control module performs a high-speed operation.
Specifically, the image processing module 6 includes an image recognition model subjected to machine learning training, and the training data for the image recognition model includes pictures of various food materials and food material information thereof, and the trained image recognition model can output the food material information according to the food material pictures.
The food material conversion module 7 includes a food material conversion model subjected to machine learning training, and the training data used for training the food material conversion model includes various food material information and information codes of corresponding nutritional elements thereof. The trained food material conversion model can output information codes of corresponding nutrient elements according to food material information.
In the scheme, the specific structures and training processes of the image recognition model, the food material conversion model, the preference scoring model and other models below are not the key points of the scheme, and can be selected by a person skilled in the art as required, and are not repeated herein.
The food material recommending module 7 comprises a preference scoring model which is trained through machine learning, and training data used for training the preference scoring model comprises historical information codes and user-food material bias of a plurality of usersA good scoring matrix, a trained preference scoring model capable of outputting a user-food material preference scoring matrix R (m, n; m represents m users, n represents n food materials, R m，n And (3) the preference scoring data of the user m to the food material n is represented. The food material recommending module 7 analyzes the nutrition balance degree of the user according to the user-food material preference scoring matrix and the nutrition balance guideline acquired from the cloud, and the closer to the requirement of the nutrition balance guideline, the higher the nutrition balance degree is. And calculating the similarity between the target user and other users according to the user-food material preference scoring matrix, and acquiring an adjacent user group of the target user according to the similarity. The similarity can be calculated by adopting the following similarity algorithms:
(1) Cosine similarity meter algorithm: cosine similarity is used for measuring the similarity degree between individuals by calculating the cosine value of an included angle between two vectors in a vector space. The method comprises the steps of calculating the fondness similarity between users by solving the cosine value of an included angle, namely, regarding the food material fondness of the users as a point in an n-dimensional coordinate system, forming a preference score vector of a certain user by connecting the point and the origin of the coordinate system, wherein the similarity value between two users is the cosine value of the included angle between the two preference score vectors. The smaller the included angle, the larger the cosine value, i.e. representing the more similar the preference between two users, and conversely, the larger the included angle, the smaller the cosine value, i.e. representing the greater the preference difference between two users. In the triangular coefficient, the cosine value of the angle ranges between [ -1,1], the cosine value between two coincident vectors is 1, and the cosine value between two opposite vectors is-1.
Cosine similarity formula:
and a and b are points in an n-dimensional coordinate system where the food materials are located, and a preference score vector of a user is formed by connecting the points and the origin of the coordinate system.
For two-dimensional space, let ax 1 ,y 1 ，bx 2 ,y 2 Then:
wherein x 1 ,y 1 ，x 2 ,y 2 Is the coordinate of the food material in the n-dimensional coordinate system.
For multidimensional spaces, assume aa 1 ,a 2 ,…,a n ，bb 1 ,b 2 ,…,b n And then:
wherein a is i ，b i Is the coordinates of the food material in the n-dimensional space.
(2) Modified cosine similarity meter algorithm: cosine similarity, which is to solve the difference between two individuals by using cosine distance, is substantially emphasized on the direction difference of measurement points in space, and is insensitive to the difference in value, so that the specific difference in each dimension value cannot be measured, which often results in serious inconsistency between the result and the real situation. For example, clustering analysis is performed on e-commerce users, high-value users and low-value users are distinguished through consumption times and average consumption amount, and given that consumption information of the A and B users is 4, 20, 10 and 50 respectively, the cosine similarity method is adopted to calculate that the similarity of the two users is extremely high, but the value of the B user is obviously higher than that of the A user in numerical terms. In order to effectively reduce such an error, a modified cosine similarity calculation method is provided, that is, before the cosine similarity between vectors is obtained, a difference between a value in each dimension and an average value of scores of the user regarding the preference of the food is required to be calculated. The method is verified to be more reasonable and is in line with reality.
(3) Pearson correlation coefficient: the pearson correlation coefficient describes the close relationship between two variables, and in the field of application of recommendation systems, the correlation coefficient represents the degree of similarity between two objects, and the larger the value, the more similar the objects.
Wherein I i,j Representing a set of food preference scores, R, commented on by i and j users together i,c Indicating i the user's preference score for food c,
represents the average preference score of user i for the preferred scored food,
representing the average preference score of user j for the preferred scored food.
(4) Euclidean-based similarity: namely, a similarity calculation method based on euclidean distance, which mainly calculates the distance between a point and a point in a multidimensional space by calculating euclidean distance, and the concepts of similarity and distance are mutually contradictory to a certain extent. The larger the distance is, the smaller the similarity is; conversely, the greater the similarity. When the similarity of the preference scores of the users is solved, all the food material preference scores which are evaluated by the users together are used as numerical values of all dimensions in each point, the linear distance between the points is calculated, and the similarity between the two users is reflected through the distance. Assuming x, y are two points in an n-dimensional space, the Euclidean distance between them is:
when n =2, d (x, y) is the distance between two points on the plane. The similarity calculation based on euclidean distance is as follows:
then, after obtaining an adjacent user group of the target user, the food material recommending module 7 selects a plurality of users with nutrition balance degree higher than a balance threshold value from the adjacent user group as a neighbor set of the target user, calculates a food material preference score which is not subjected to preference scoring or is lower than a preference scoring threshold value of the target user according to the existing preference score of the neighbor set by the following calculation formula, and sorts the food material preference score;
where sim (i, j) represents the similarity between user i and user j, R j,d Represents the score of food material d by the nearest neighbor user j,
and
representing user i and average score for all food items with j, respectively.
And finally recommending the N or M food materials with the highest calculation scores to the target user, and taking N when N is less than M, or taking M and taking M as the number of the food materials subjected to the food material preference score calculation.
Specifically, the equilibrium threshold may be a fixed value, or may be determined according to each target user, for example, taking the nutrition equilibrium degree of the target user as the equilibrium threshold, that is, taking all other users in the adjacent user group whose nutrition equilibrium degree is higher than that of the target user as neighbor users of the target user, and recommending food materials for the target user according to the neighbor users of the target user. The recommended food materials are not only biased to the favor of the target user, but also can improve the nutrition balance degree of the target user.
The food material recommending module 7 is mainly used for finding out neighbor users with similar eating habits and balanced nutrition according to the matching information of the users on food materials, and recommending the food materials of nutritional elements lacking in the target users in the eating habits of the neighbor users to the target users. For example, the collocation conditions of ABC three users on M, N, P and Q foods are known, wherein the user A likes to eat the food A and the food P, the user B prefers the food N, the user C likes to eat the food M, P and Q, the nutrition collocation of the user A is unbalanced, and the nutrition collocation of the user C is balanced, so that the history records of the users can find that the user A and the user C have similar preferences, and the food material Q lacking in the user A in the user C can be recommended to the user A.
As shown in fig. 3, the first monitoring module 1 is installed outside the range hood, the second monitoring module 3 can be installed at the entrance of the oil screen, and when the range hood sucks indoor lampblack gas into the range hood, the lampblack gas is filtered by the oil screen and is monitored before first lampblack separation.
The various modules can be connected with or embedded into a processor of the range hood, the processor can adopt MT7688 chips and 128Mbytes DDR memory; the embedded Windows operating system is operated and can be mounted on the display screen of the range hood, as shown in fig. 3 at the mark 9.
The memory of the range hood can store menu recommendations of various food materials, the range hood can also be interconnected with an external network through the communication module, and the menu recommendations of corresponding food materials are acquired from the external network in real time or are acquired from the external network so as to update the menu recommendations in the memory.
The communication module can realize the communication of an external network through the communication connection of wireless routing equipment through wireless communication, the user client can be installed on a mobile phone of a user, and the mobile phone realizes the communication with the range hood through wireless signals.
Specifically, as shown in fig. 5, a second aspect of the present solution provides an intelligent control method for an intelligent range hood:
SA1, monitoring the temperature of a target in a pot by using an infrared thermal imager;
SA2, when the temperature of the target in the pot exceeds the set temperature, the oil smoke sensor starts to monitor the oil smoke concentration;
SA3, when the concentration of the oil smoke is greater than the first set concentration, starting the oil smoke exhauster; according to the recipe selected by the user, namely the recipe displayed on the display screen, or manual control by the user, or according to the acquired image information, judging the current cooking mode, and controlling the low-speed operation, medium-speed operation or high-speed operation of the range hood according to the cooking mode;
SA4, continuously monitoring the oil smoke concentration, and starting timing when the oil smoke concentration is less than a second set concentration;
and SA5, closing the range hood after timing to a set time.
By the method, the oil smoke in the air in the cooking process can be removed in time, and the residual oil smoke in the air after the cooking is finished can be removed. Need not the user and pay close attention to the lampblack absorber carelessly, even the user forgets to open or close the lampblack absorber and also can realize opening in time and close, promote user's quality of life. In addition, this scheme is not smoke ventilator real-time supervision oil smoke information and react, but monitors the oil smoke concentration again and reacts after the highest temperature that food temperature in the pot was monitored to smoke ventilator has reached preset temperature, and the oil smoke concentration this moment is more stable, and the reliability of monitoring result is high, can promote whole smoke ventilator intelligence control system's accuracy and stability.
Preferably, as shown in fig. 6, in step SA4, the soot concentration is continuously monitored during a timing period, and if the soot concentration is greater than a first set concentration, the timing is ended until the timing is restarted when the soot concentration is again less than a second set concentration;
as shown in fig. 7, a third aspect of the present disclosure provides a method for recommending range hood food materials based on intelligent control of an oil pumping unit:
in the cooking process of starting the range hood, acquiring image information of a target in the cooker by using an infrared imager, and analyzing the image information to determine food material information corresponding to the image information;
SB2, converting the food material information into information codes corresponding to the nutrient elements for storage;
SB3, recommending food materials to the user by using the stored historical information codes;
and SB4, storing the recommended food materials selected by the user, and pushing the recommended recipes to the user client based on the recommended food materials selected by the user. The user selects one or more recipes at the user client for storage, can select one recipe to be displayed on the display screen of the range hood, and at the moment, when the user cooks, the range hood controls the working rotating speed according to the recipe manufacturing method on the display screen.
Specifically, as shown in fig. 8, in step SB3, the food material is recommended to the user by the following method:
SB31, analyzing the nutrition balance degree of the user according to the user-food material preference scoring matrix; a user-food material preference scoring matrix is established based on historical information codes of users;
calculating the similarity between the target user and other users according to the user-food material preference scoring matrix, and acquiring an adjacent user group of the target user according to the similarity;
selecting a neighbor set with a nutrition balance degree higher than a balance threshold value as a target user from an adjacent user group;
SB34, calculating the food material preference scores of which the preference scores are not scored by the target user or are lower than the preference score threshold value according to the existing preference scores of the neighbor sets, and sequencing;
and SB35, recommending the N or M food materials with the highest calculation scores to the target user, and taking N when N is less than M, or taking M which is the number of the food materials subjected to the food material preference scoring in the step SB34.
Recommend the food material that the user probably likes and nutrition collocation is even for the user according to user's eating habits, can solve the user and usually not know what when perplexing, can also cater to user's hobby, promote the nutrition equilibrium degree of the whole eating habits of user simultaneously to promote user's quality of life.
The specific embodiments described herein are merely illustrative of the spirit of the invention. Various modifications or additions may be made to the described embodiments or alternatives may be employed by those skilled in the art without departing from the spirit or ambit of the invention as defined in the appended claims.
Claims (10)
1. An intelligent control method for a range hood is characterized by comprising the following steps:
SA1, monitoring the temperature of a target in a pot;
SA2, when the temperature of the target in the pot exceeds a set temperature, starting to monitor the concentration of the oil smoke;
SA3, when the concentration of the oil smoke is greater than the first set concentration, starting the oil smoke exhauster;
SA4, continuously monitoring the oil smoke concentration, and starting timing when the oil smoke concentration is less than a second set concentration;
and SA5, closing the range hood after timing to a set time.
2. The intelligent control method of the range hood according to claim 1, wherein in step SA4, the oil smoke concentration is continuously monitored during a timing period, and if the oil smoke concentration is greater than a first set concentration, the timing is ended until the timing is restarted when the oil smoke concentration is again less than a second set concentration;
in step AS1, the temperature of the target in the pan is monitored by:
SA11, acquiring image information of a target in the pan;
SA12, acquiring a thermal image based on the image information by using an infrared thermal imaging technology, thereby acquiring the temperature of the target in the pan;
in the step SA2, the oil smoke concentration is monitored through an oil smoke sensor, and the oil smoke sensor is a particulate matter concentration sensor or a VOC gas sensor;
and in the step SA3, judging the current cooking mode according to the recipe selected by the user, and controlling the low-speed operation, the medium-speed operation or the high-speed operation of the range hood according to the cooking mode.
3. A cooking fume exhauster food material recommending method based on intelligent control of an oil pumping unit is characterized by comprising the following steps:
SB1, in the cooking process of starting the range hood, acquiring image information of a target in the cooker, and analyzing the image information to determine food material information corresponding to the image information;
SB2, converting the food material information into information codes corresponding to the nutrient elements for storage;
SB3, recommending food materials to the user by using the stored historical information codes;
and SB4, storing the recommended food materials selected by the user, and recommending the recipe to the user based on the recommended food materials selected by the user.
4. The cooking fume exhauster food material recommending method based on intelligent oil pumping unit control of claim 3, wherein in step SB3, the food material is recommended to the user by the following method:
SB31, analyzing the nutrition balance degree of the user according to the user-food material preference scoring matrix; a user-food material preference scoring matrix is established based on historical information codes of users;
calculating the similarity between the target user and other users according to the user-food material preference scoring matrix, and acquiring an adjacent user group of the target user according to the similarity;
selecting a neighbor set with a nutrition balance degree higher than a balance threshold value as a target user from an adjacent user group;
SB34, calculating the food material preference scores of which the preference scores are not scored by the target user or are lower than the preference score threshold value according to the existing preference scores of the neighbor sets, and sequencing;
and SB35, recommending the N or M food materials with the highest calculated scores to the target user, and if N is less than M, taking N, otherwise, taking M, wherein M is the number of the food materials subjected to food material preference scoring in the step SB34.
5. The range hood food recommendation method based on intelligent pumping unit control of claim 4,
in the step SB1, an infrared thermal imager is used for acquiring image information of a target in the pan;
and in the step SB4, the recommended recipes are pushed to the user client, and the recommended recipes selected by the user are displayed on a display screen of the range hood.
6. The utility model provides an intelligence smoke ventilator device, characterized in that includes first monitoring module (1), first affirmation module (2), second monitoring module (3), second affirmation module (4) and control module (5), wherein:
the first monitoring module (1) is used for monitoring the temperature of a target in the pan and transmitting the temperature information to the first confirming module (2);
the first confirmation module (2) is used for comparing the received temperature information with the set temperature, and if the monitored temperature information is greater than the set temperature, the second monitoring module (3) is informed to enter a monitoring state;
the second monitoring module (3) is used for monitoring the oil smoke concentration and transmitting the information of the oil smoke concentration to the second confirming module (4);
the second confirmation module (4) is used for comparing the received oil smoke concentration with the first set concentration, and if the monitored oil smoke concentration is greater than the first set concentration, the second confirmation module informs the control module (5) to start the range hood;
the automatic control system is also used for continuously monitoring the oil smoke concentration when the range hood is in the opening state, starting timing when the oil smoke concentration is less than a second set concentration, and informing the control module (5) to close the range hood after the timing reaches a set time length;
and the control module (5) is used for controlling the opening, closing and working rotating speed of the range hood.
7. The intelligent range hood device according to claim 6, wherein the temperature information transmitted by the first monitoring module (1) to the first confirmation module (2) is the highest temperature of the target in the pan in the current detection;
or the temperature information transmitted to the first confirmation module (2) by the first monitoring module (1) is the average temperature of the target in the pot in the current detection;
or the temperature information transmitted to the first confirming module (2) by the first monitoring module (1) is the temperature distribution in the current detection, and the first confirming module (2) selects the highest temperature from the temperature distribution or calculates the average temperature to compare with the set temperature.
8. The intelligent range hood device according to claim 6, wherein the second monitoring module (3) continues to monitor the soot concentration during the timing period, and the second confirming module (4) is further configured to end the timing when the soot concentration is greater than the first set concentration during the timing period until the timing is restarted when the soot concentration is less than the second set concentration again;
the first monitoring module (1) comprises an infrared thermal imager, and the temperature of the target in the pan is obtained by obtaining image information of the target in the pan and obtaining a thermal image based on the image information;
the second monitoring module (3) comprises an oil smoke sensor, and the oil smoke sensor monitors the oil smoke concentration.
9. The intelligent range hood device according to claim 8, further comprising an image processing module (6) for analyzing the image information obtained by the first monitoring module (1) to determine the food material information corresponding to the image information; the food material conversion module (7) is used for converting the food material information into information codes corresponding to the nutrient elements and storing the information codes in the storage module; the food material recommending module (7) is used for recommending food materials to the user by utilizing the stored historical information codes and storing the recommended food materials selected by the user in the storage module; the pushing module (8) is used for recommending recipes to the user client based on recommended food materials selected by the user; and the communication module is used for communicating with the user client.
10. The intelligent range hood device according to claim 9, further comprising a display screen for displaying recipes, wherein the control module (5) is further configured to control the operating speed according to the recipes displayed by the display screen;
the image processing module (6) comprises a trained image recognition model, and training data for the image recognition model comprises pictures of various food materials and food material information thereof;
the food material conversion module (7) comprises a trained food material conversion model, and the training data for training the food material conversion model comprises various food material information and information codes of corresponding nutrient elements thereof;
the food material recommending module (7) recommends food materials to the user through steps SB31-SB 35.
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