Real-time monitoring method for smart refrigerator and smart refrigerator

Abstract

The present invention belongs to the field of computer technology. A real-time monitoring method for a smart refrigerator and a smart refrigerator are provided. The method comprises: obtaining the door opening and closing history data of the refrigerator, determining the opening time data set and the closing time data set according to the door opening and closing history data; calculating the matching degree between the current time period and the opening time data set and the closing time data set, and determining the target device for detecting the freshness of the food stored in the refrigerator according to the matching degree; sending a control instruction to the target device, and determining the freshness of the food stored in the refrigerator according to the detection data of the target device. The present invention effectively reduces the detection load of the freshness detection device that can emit light signals by using a camera device to detect the freshness of the food in the refrigerator in some time periods. Since the detection principle of the camera device does not need to emit light signals to the food, the power consumption of the refrigerator can be effectively reduced.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a real-time monitoring method for a smart refrigerator and a smart refrigerator. Background Art

[0002] With the advancement of technology, more and more families are beginning to choose smart refrigerators with food freshness monitoring functions. These refrigerators can analyze the freshness of the food stored inside and output the corresponding freshness analysis results to users.

[0003] There are several typical implementations of existing food freshness detection methods: Existing patent document 1 (CN113218878A) discloses a method for judging the freshness of food in a refrigerator, comprising the following steps: scanning spectral data of food of the same type in the refrigerator at different freshness; establishing a freshness model based on the spectral data, wherein the freshness model includes multiple freshness levels of the food; scanning spectral data of new food of the same type in the refrigerator, and obtaining a measured freshness level through the freshness model; judging whether the actual freshness level of the new food is consistent with the measured freshness level; if it is consistent, increasing the weight of the spectral data judging as the measured freshness level, and if it is not consistent, increasing the weight of the spectral data judging as the actual freshness; repeatedly placing food of the same type with multiple freshness levels in the refrigerator, scanning the spectral data, judging whether the actual freshness is consistent with the measured freshness and increasing the corresponding weight according to the result; adjusting the freshness model according to the correspondence between the spectral data with the highest weight and the freshness level.

[0004] Existing patent document 2 (CN116429733A) discloses a freshness detection device for egg food, including: a fixing device for placing egg food; a light source module, which is arranged on one side of the fixing device and is used to emit a light source signal; a light sensor, which is arranged on the other side of the fixing device and is used to receive a transmitted light source passing through the egg food; a controller is configured to: in response to a freshness detection operation, control the light source module to emit an incident light source that meets a preset light intensity; obtain the light intensity of the transmitted light source detected by the light sensor; calculate the transmittance of the egg food according to the light intensity of the incident light source and the light intensity of the transmitted light source; compare the transmittance with a plurality of preset light transmittance intervals, and obtain the freshness of the egg food according to the comparison result.

[0005] It can be seen that the existing food freshness detection is mostly based on spectral data, light data and other methods, specifically through the light source device and photosensitive device arranged in the refrigerator. However, none of the above existing patent documents optimize the timing of food freshness detection. The light source device and photosensitive device need to work synchronously according to fixed rules to realize the detection function, which will increase the energy consumption of smart refrigerators. This is a technical problem that needs to be solved at present. Summary of the invention

[0006] In this regard, the present invention provides a real-time monitoring method for a smart refrigerator, a smart refrigerator, an electronic device and a computer storage medium to solve the above technical problems.

[0007] The first aspect of the present invention also discloses a real-time monitoring method for a smart refrigerator, comprising the following steps: obtaining the refrigerator door opening and closing history data, and determining an opening time data set and a closing time data set based on the door opening and closing history data; calculating the matching degree between the current time period and the opening time data set and the closing time data set, and determining a target device for detecting the freshness of food stored in the refrigerator based on the matching degree; wherein the target device includes a camera device and a freshness detection device that can emit light signals; sending a control instruction to the target device, and determining the freshness of the food stored in the refrigerator based on the detection data of the target device.

[0008] Furthermore, the refrigerator door opening and closing history data is obtained, and an opening time data set and a closing time data set are determined based on the door opening and closing history data, including: obtaining working signal data of a passive pressing button of the refrigerator door or air pressure change data detected by an air pressure sensor in the refrigerator contained in the door opening and closing history data, and determining the opening and closing state of the door based on the working signal data or the air pressure change data; completing binary classification of the door opening and closing history data based on the opening and closing state, and generating the opening time data set and the closing time data set based on the classification data corresponding to the binary classification result.

[0009] Furthermore, the opening time data set and the closing time data set are generated according to the classified data corresponding to the binary classification results, including: performing clustering calculations on the two groups of classified data corresponding to the binary classification results respectively to obtain a first opening time data set and a first closing time data set; wherein the clustering calculations are implemented based on period characteristics; determining the corresponding first opening time data and first closing time data based on the period characteristics, and determining the overlapping time data through overlap calculation, and determining the second opening time data and the second closing time data according to the overlapping time data; wherein the second opening time data has the overlapping time data added compared to the first opening time data, and the second closing time data lacks the overlapping time data compared to the first closing time data; repeating the above steps to obtain a plurality of the second opening time data and the second closing time data; constructing a second opening time data set according to each of the second opening time data, and constructing a second closing time data set according to each of the second closing time data, that is, generating the opening time data set and the closing time data set.

[0010] Furthermore, second opening time data and second closing time data are determined based on the overlap time data, including: controlling the camera device to capture food image data in the door, and obtaining the number of food types from the food image data; determining a weight coefficient based on the number of food types, and multiplying the weight coefficient by the overlap time data to obtain new overlap time data; and determining the second opening time data and the second closing time data based on the new overlap time data.

[0011] Furthermore, a target device for detecting the freshness of food stored in the refrigerator is determined based on the matching degree, including: if the matching degree representation is associated with any of the second closing time data in the closing time data set, the freshness detection device that can emit a light signal is determined as the target device; if the matching degree representation is associated with any of the second opening time data in the opening time data set, the camera device is determined as the target device.

[0012] Furthermore, after sending a control instruction to the target device, the method also includes: when detecting that the refrigerator door is opened, obtaining the opening rate of the door, and determining the capture frequency according to the opening rate; according to the capture frequency, controlling the camera device to capture a number of food image data; wherein the capture frequency is positively correlated with the opening rate.

[0013] Furthermore, the camera device is controlled to capture a number of food image data according to the capture frequency, including: determining a capture waiting time according to the opening rate, and after the capture waiting time is reached, controlling the camera device to capture a number of food image data according to the capture frequency.

[0014] The second aspect of the present invention provides a smart refrigerator, including a communication device, a processing device, a storage device, a camera device, and a freshness detection device that can emit light signals, wherein the processing device is electrically connected to the storage device, the communication device, the camera device, and the freshness detection device that can emit light signals, respectively; the communication device is used to obtain the door opening and closing history data of the smart refrigerator, the working signal of the door passive pressing button or the air pressure change data detected by the air pressure sensor in the refrigerator, and the detection data of the target device, and transmit them to the processing device; the storage device is used to store computer programs; the processing device is used to call and execute the computer program in the storage device to execute the method as described in any of the preceding items, so as to determine the camera device or the freshness detection device that can emit light signals as the target device, and send a control instruction to the target device for controlling the target device to detect the freshness of the food stored in the refrigerator; and determine the freshness of the food stored in the refrigerator according to the detection data of the target device.

[0015] The third aspect of the present invention also discloses an electronic device, comprising: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, wherein the processor executes the computer program to implement the method described in any of the preceding items.

[0016] A fourth aspect of the present invention further discloses a computer storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the method as described in any of the preceding items.

[0017] The fifth aspect of the present invention further discloses a computer program product, which, when executed on a terminal, enables the terminal to implement the method as described in any of the preceding items.

[0018] The beneficial effect of the present invention is that the present invention uses a camera device to detect the freshness of food in the refrigerator during part of the time period, thereby effectively reducing the detection load of the freshness detection device that can emit light signals. Since the detection principle of the camera device does not require the emission of light signals to the food, the power consumption of the refrigerator can be effectively reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0020] Figure 1 It is a flow chart of a real-time monitoring method for a smart refrigerator disclosed in an embodiment of the present invention.

[0021] Figure 2 It is a structural schematic diagram of a smart refrigerator disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0022] The following is a description of the implementation of the present application by specific specific embodiments. People familiar with the technology can easily understand other advantages and effects of the present application from the contents disclosed in this specification. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0023] In addition, the technical features involved in the different embodiments of the present application described below can be combined with each other as long as they do not conflict with each other.

[0024] like Figure 1 As shown, an embodiment of the present invention discloses a real-time monitoring method for a smart refrigerator, the method comprising the following steps: acquiring the door opening and closing history data of the refrigerator, and determining an opening time data set and a closing time data set according to the door opening and closing history data; calculating the matching degree between the current time period and the opening time data set and the closing time data set, and determining a target device for detecting the freshness of food stored in the refrigerator according to the matching degree; wherein the target device comprises a camera device and a freshness detection device capable of emitting a light signal; sending a control instruction to the target device, and determining the freshness of the food stored in the refrigerator according to the detection data of the target device.

[0025] In an embodiment of the present invention, the smart refrigerator in the present invention is equipped with two freshness detection devices, a camera device and a freshness detection device that can emit light signals. The camera device is a conventional camera, and the freshness detection device that can emit light signals can be a combination of a spectrometer or a light source module and a light sensor involved in the background technology. In the specific implementation, the present invention conducts an in-depth analysis of the refrigerator door opening and closing historical data, determines the opening time data set and the closing time data set, and obtains the refrigerator door opening and closing law; based on the opening and closing law, the above two types of target devices can be scheduled to perform freshness detection operations in different time periods, thereby effectively reducing the operating load of the freshness detection device that can emit light signals, and then reducing the energy consumption of the refrigerator. Therefore, the present invention uses a camera device to detect the freshness of the food in the refrigerator in some time periods, which effectively reduces the detection load of the freshness detection device that can emit light signals. Since the detection principle of the camera device does not need to emit light signals to the food, the power consumption of the refrigerator can be effectively reduced.

[0026] The above two target devices in the present invention are installed in the storage compartment of the smart refrigerator, that is, the refrigerator compartment and the freezer compartment of the refrigerator. The present invention does not limit the layout position and specific installation method of the two devices in the refrigerator.

[0027] Furthermore, the refrigerator door opening and closing history data is obtained, and an opening time data set and a closing time data set are determined based on the door opening and closing history data, including: obtaining working signal data of a passive pressing button of the refrigerator door or air pressure change data detected by an air pressure sensor in the refrigerator contained in the door opening and closing history data, and determining the opening and closing state of the door based on the working signal data or the air pressure change data; completing binary classification of the door opening and closing history data based on the opening and closing state, and generating the opening time data set and the closing time data set based on the classification data corresponding to the binary classification result.

[0028] A door passive press button is arranged at the contact position between the refrigerator body and the door when it is closed. When the door is open, the door passive press button is in an extended state, and when the door is closed, the door passive press button is in a pressed state. The open and closed state of the door can be determined based on the working signal of the button. Alternatively, an air pressure sensor is arranged in each room of the refrigerator, which can detect the air pressure data in the corresponding room. The opening and closing of the door will change the air pressure data detected by the air pressure sensor. Specifically, when the door is opened and closed, the detected air pressure data will decrease and increase for a short time respectively, and the open and closed state of the door can also be determined based on this.

[0029] After determining the open and closed status of the door, we can make appropriate expansions based on the time when these states occur (i.e., the time when they are detected) to obtain the corresponding opening time data and closing time data, and finally construct the above-mentioned data set.

[0030] Furthermore, the opening time data set and the closing time data set are generated according to the classified data corresponding to the binary classification results, including: performing clustering calculations on the two groups of classified data corresponding to the binary classification results respectively to obtain a first opening time data set and a first closing time data set; wherein the clustering calculations are implemented based on period characteristics; determining the corresponding first opening time data and first closing time data based on the period characteristics, and determining the overlapping time data through overlap calculation, and determining the second opening time data and the second closing time data according to the overlapping time data; wherein the second opening time data has the overlapping time data added compared to the first opening time data, and the second closing time data lacks the overlapping time data compared to the first closing time data; repeating the above steps to obtain a plurality of the second opening time data and the second closing time data; constructing a second opening time data set according to each of the second opening time data, and constructing a second closing time data set according to each of the second closing time data, that is, generating the opening time data set and the closing time data set.

[0031] In the embodiment of the present invention, based on the above determined open and closed state of the refrigerator door, the door opening and closing history data can be divided into two groups of data: the opening period and the closing period. At the same time, the rules of users opening and closing the refrigerator door in different periods are quite different. Therefore, the present invention performs clustering calculation on the above two groups of data (i.e., the two groups of classified data corresponding to the binary classification results) based on the period characteristics. Taking the period as working day and non-working day as an example, the following is explained: ;in, is a data matrix of users opening and closing refrigerator doors during a certain period of time (e.g. 10:00-12:00), where Indicates The refrigerator door opening time data for the working days of the week, Indicates The refrigerator door opening time data of non-working days (i.e. weekends) in a week will be These data are clustered to obtain , which represents the rule of users opening the refrigerator door during the above period (e.g. 10:00-12:00) on weekdays, that is, the first opening time data set (which contains multiple corresponding to different time periods) is obtained. , for example, corresponding to 8:00-10:00, 10:00-12:00, 12:00-17:00, 17:00-22:00 respectively); and These data are clustered to obtain , which represents the pattern of users closing the refrigerator door during the above period (e.g. 10:00-12:00) on non-working days, i.e. weekends, that is, the first closing time dataset (which contains multiple corresponding to different time periods) is obtained. , for example, corresponding to 8:00-10:00, 10:00-12:00, 12:00-17:00, 17:00-22:00 respectively).

[0032] The above clustering calculation involved in the present invention can be directly obtained by , The average value of , but it is preferred to use an unsupervised ML clustering algorithm, namely DBSCAN (density-based spatial clustering of noise applications), which can avoid the influence of outliers compared to the traditional K-means clustering algorithm. The process of clustering the two groups of classified data corresponding to the binary classification results based on the DBSCAN algorithm is roughly as follows: First, a random point with at least minPts (minimum points) within its radius is selected. Then each point in the neighborhood of the core point is evaluated to determine whether it has minPts (minPts includes the point itself) within the epsilon distance (maximum radius of the community). If the point meets the minPts criterion, it will become another core point and the cluster will expand. If a point does not meet the minPts criterion, it becomes a boundary point. When a cluster is surrounded by boundary points, this cluster has been searched completely because there are no more points within the distance, a new random point is selected, and the process is repeated to identify the next cluster until the clustering of each group of classified data is completed.

[0033] In addition, the time characteristics in the present invention are not limited to different time periods in a week or a day, but can also be different months in a year, or even weekdays, weekends, holidays, etc.

[0034] At the same time, since the user does not have an absolute limit on the opening and closing rules of the refrigerator door, it is very likely that there will be overlapping areas in time. In this regard, the present invention determines the overlapping area of ​​the first opening time data and the first closing time data corresponding in time in the above-mentioned preliminary opening time data set and closing time data set, and divides the overlapping area into the first opening time data. Thus, a more accurate opening time data set and closing time data set can be generated.

[0035] Furthermore, second opening time data and second closing time data are determined based on the overlap time data, including: controlling the camera device to capture food image data in the door, and obtaining the number of food types from the food image data; determining a weight coefficient based on the number of food types, and multiplying the weight coefficient by the overlap time data to obtain new overlap time data; and determining the second opening time data and the second closing time data based on the new overlap time data.

[0036] In an embodiment of the present invention, a variety of food materials can be stored in a refrigerator, and the more types of food materials there are, the higher the probability that the user takes food materials outside the above-stated opening time data set; on the contrary, it means that the probability that a certain cold storage room or freezer of the refrigerator is dedicated to the user is greater, for example, it is dedicated to storing fruits, tomatoes, fresh meat, etc. In this case, the probability that the user takes food materials outside the above-stated opening time data set is lower. Therefore, the present invention uses a camera device installed in the refrigerator to shoot food images in the refrigerator, and the number of types of stored food materials can be statistically obtained by analyzing the food image, for example, it is recognized that three types of food materials, apples, tomatoes, and carrots, are stored; then, a weight coefficient is determined according to the number of food types, and the weight coefficient (greater than 1) is positively correlated with the number of food types; finally, the aforementioned coincidence time data is adjusted according to the weight coefficient, thereby realizing the adaptive expansion of the coincidence time data, which can adapt to the situation that the user takes food materials outside the above-stated opening time data set, so that the working switching timing of the camera device is more appropriate.

[0037] It should be noted that the camera device can capture image data of food inside the refrigerator door when the door is opened, so there is no need to use lighting to assist in capturing food images after closing the door, which can further reduce the power consumption of the refrigerator.

[0038] Furthermore, a target device for detecting the freshness of food stored in the refrigerator is determined based on the matching degree, including: if the matching degree representation is associated with any of the second closing time data in the closing time data set, the freshness detection device that can emit a light signal is determined as the target device; if the matching degree representation is associated with any of the second opening time data in the opening time data set, the camera device is determined as the target device.

[0039] In an embodiment of the present invention, when the above-determined matching degree determines that the current time period is in the regular closing period of the refrigerator door, the freshness detection device that can emit light signals can be determined as the target device. During this door closing period, the light in the refrigerator is dim, and it is difficult to accurately detect the freshness through the camera device. The above-mentioned type of device that can emit light signals is preferentially used to detect the freshness of the food in the refrigerator. When the above-determined matching degree determines that the current time period is in the regular opening period of the refrigerator door, the camera device can be determined as the target device. During this door opening period, the light in the refrigerator is sufficient, and the camera device is sufficient to accurately detect the freshness. During this period, the freshness detection device that can emit light signals is controlled to suspend work and switch to the camera device, which can effectively reduce the power consumption when the light signal is emitted.

[0040] It should be noted that the two existing patent documents attached to the background technology have explained in detail the basic principle of the freshness detection device that can emit light signals to detect the freshness of food. The present invention introduces the content related to its detection principle into the present invention, which will not be repeated here. In addition, the technology of using camera equipment to analyze the freshness of food is relatively mature. Generally, the appearance image features of the food are matched and calculated with the preset freshness template images of different freshness levels to determine the corresponding freshness level. The details will not be repeated here.

[0041] Furthermore, after sending a control instruction to the target device, the method also includes: when detecting that the refrigerator door is opened, obtaining the opening rate of the door, and determining the capture frequency according to the opening rate; according to the capture frequency, controlling the camera device to capture a number of food image data; wherein the capture frequency is positively correlated with the opening rate.

[0042] In the embodiment of the present invention, in order to prevent the camera equipment from occupying the storage space in the refrigerator, it is preferred to place the camera equipment on the inner side of the door, because the inner side of the door generally has a concave structure, which is conducive to placing the relatively small camera equipment therein without occupying too much space in the box. However, when the camera equipment is placed in this way, when the door is opened, the shooting angle of the camera equipment will change with the opening of the door. The camera equipment needs to capture as many images as possible to obtain more appropriate images of the food. At the same time, too many captures are also useless, and a trade-off needs to be made.

[0043] In this regard, when it is determined that the current period corresponds to the opening time data set, the refrigerator can be controlled to enter the refrigerator door opening monitoring state, for example, the aforementioned door passive pressing button or the air pressure sensor in the refrigerator can be controlled to enter a continuous monitoring state, and the working signal data of the door passive pressing button or the air pressure data detected by the air pressure sensor in the refrigerator can be used to accurately detect whether the refrigerator door is opened. Then, the capture rate of the camera device is determined according to the rate at which the refrigerator door is opened. Obviously, the faster the door opening rate, the higher the capture frequency of the camera device, so that there is a greater chance of capturing more complete and clearer food image data in the refrigerator; correspondingly, the slower the door opening rate, the lower the capture frequency of the camera device, so that while ensuring a greater chance of capturing more complete and clearer food image data in the refrigerator, it can also effectively reduce useless capture.

[0044] It should be noted that the opening rate of the door can be determined according to the lifting rate of the passive pressing button of the door, the rate of change of air pressure data, or the angular velocity data transmitted by the Hall sensor on the rotating shaft of the door.

[0045] Furthermore, the camera device is controlled to capture a number of food image data according to the capture frequency, including: determining a capture waiting time according to the opening rate, and after the capture waiting time is reached, controlling the camera device to capture a number of food image data according to the capture frequency.

[0046] In the embodiment of the present invention, in addition to the shooting angle, another prerequisite for the camera device to capture better food images is that the refrigerator door is opened at a sufficient angle (enough light can enter) so that the lighting conditions inside the box are sufficient. In this regard, the present invention determines the capture waiting time according to the aforementioned detected door opening rate. When the capture waiting time is reached, the opening angle of the refrigerator door is large enough (for example, 10°), and the lighting in the refrigerator has also completed the lighting start-up. At this time, the lighting conditions in the refrigerator are also sufficient. At this time, the camera is controlled to capture food images at the aforementioned determined capture frequency, so that more good images can be captured in the food images, and the shooting angle at this time is also the most favorable, which is conducive to the subsequent screening of better food images.

[0047] like Figure 2As shown, an embodiment of the present invention also discloses a smart refrigerator, including a communication device, a processing device, a storage device, a camera device, and a freshness detection device that can emit light signals, wherein the processing device is electrically connected to the storage device, the communication device, the camera device, and the freshness detection device that can emit light signals, respectively; the communication device is used to obtain the door opening and closing history data of the smart refrigerator, the working signal of the door passive pressing button or the air pressure change data detected by the air pressure sensor in the refrigerator, and the detection data of the target device, and transmit them to the processing device; the storage device is used to store computer programs; the processing device is used to retrieve and execute the computer program in the storage device to execute the method described in the aforementioned embodiment, so as to determine the camera device or the freshness detection device that can emit light signals as the target device, and send a control instruction to the target device for controlling the target device to detect the freshness of the food stored in the refrigerator; and determine the freshness of the food stored in the refrigerator according to the detection data of the target device.

[0048] An embodiment of the present invention further discloses an electronic device, comprising: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, wherein the processor executes the computer program to implement the method described in the above embodiment.

[0049] An embodiment of the present invention further discloses a computer storage medium, wherein the computer storage medium stores a computer program, and the computer program is executed by a processor to implement the method described in the above embodiment.

[0050] The embodiment of the present invention further discloses a computer program product. When the computer program product is run on a terminal, the terminal implements the method described in the above embodiment.

[0051] The steps of the method or algorithm described in conjunction with the disclosure of the present application may be implemented in hardware or by executing software instructions by a processor. The software instructions may be composed of corresponding software modules, which may be stored in a random access memory (RAM), flash memory, read-only memory (ROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), registers, hard disks, mobile hard disks, CD-ROMs, or any other form of storage medium known in the art. An exemplary storage medium is coupled to a processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium may also be a component of the processor. The processor and the storage medium may be located in an ASIC. In addition, the ASIC may be located in a core network interface device. Of course, the processor and the storage medium may also be present in a core network interface device as discrete components.

[0052] In the several embodiments provided in the present application, it should be understood that the disclosed methods and devices can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0053] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network devices. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0054] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each functional unit may exist independently, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0055] Through the description of the above implementation methods, the technicians in the relevant field can clearly understand that the present application can be implemented by means of software plus necessary general hardware, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a readable storage medium, such as a computer floppy disk, hard disk or optical disk, etc., and includes a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0056] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions within the technical scope disclosed in the present application shall be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A real-time monitoring method for a smart refrigerator, characterized in that: The method comprises the following steps: obtaining the door opening and closing history data of the refrigerator, and determining the opening time data set and the closing time data set according to the door opening and closing history data; calculating the matching degree between the current time period and the opening time data set and the closing time data set, and determining the target device for detecting the freshness of the food stored in the refrigerator according to the matching degree; wherein the target device comprises a camera device and a freshness detection device capable of emitting a light signal; sending a control instruction to the target device, and determining the freshness of the food stored in the refrigerator according to the detection data of the target device; Determining a target device for detecting the freshness of food stored in a refrigerator according to the matching degree includes: if the matching degree representation is associated with any closing time data in the closing time data set, determining the freshness detection device capable of emitting a light signal as the target device; if the matching degree representation is associated with any opening time data in the opening time data set, determining the camera device as the target device.

2. The real-time monitoring method for a smart refrigerator according to claim 1, characterized in that: Obtaining refrigerator door opening and closing history data, and determining an opening time data set and a closing time data set according to the door opening and closing history data, including: obtaining working signal data of a passive pressing button of the refrigerator door or air pressure change data detected by an air pressure sensor in the refrigerator contained in the door opening and closing history data, and determining the opening and closing state of the door according to the working signal data or the air pressure change data; completing binary classification of the door opening and closing history data according to the opening and closing state, and generating the opening time data set and the closing time data set according to classification data corresponding to the binary classification result.

3. The real-time monitoring method for a smart refrigerator according to claim 2, characterized in that: The opening time data set and the closing time data set are generated according to the classification data corresponding to the binary classification results, including: performing clustering calculations on the two groups of classification data corresponding to the binary classification results respectively to obtain a first opening time data set and a first closing time data set; wherein the clustering calculations are implemented based on period characteristics; determining the corresponding first opening time data and first closing time data based on the period characteristics, and determining the overlapping time data through overlap calculation, and determining the second opening time data and the second closing time data according to the overlapping time data; wherein the second opening time data has the overlapping time data added compared to the first opening time data, and the second closing time data lacks the overlapping time data compared to the first closing time data; repeating the above steps to obtain a plurality of the second opening time data and the second closing time data; constructing a second opening time data set according to each of the second opening time data, and constructing a second closing time data set according to each of the second closing time data, that is, generating the opening time data set and the closing time data set.

4. The real-time monitoring method for a smart refrigerator according to claim 3, characterized in that: Determining the second opening time data and the second closing time data according to the overlap time data includes: controlling the camera device to capture the image data of the food in the door, and obtaining the number of food types from the food image data; determining a weight coefficient according to the number of food types, and multiplying the overlap time data by the weight coefficient to obtain new overlap time data; and determining the second opening time data and the second closing time data according to the new overlap time data.

5. The real-time monitoring method for a smart refrigerator according to claim 1, characterized in that: After sending a control instruction to the target device, the method further includes: when detecting that the refrigerator door is opened, obtaining the opening rate of the door, and determining the capture frequency according to the opening rate; according to the capture frequency, controlling the camera device to capture a number of food image data; wherein the capture frequency is positively correlated with the opening rate.

6. The real-time monitoring method for a smart refrigerator according to claim 5, characterized in that: The camera device is controlled to capture a number of food image data according to the capture frequency, including: determining a capture waiting time according to the opening rate, and after the capture waiting time is reached, controlling the camera device to capture a number of food image data according to the capture frequency.

7. A smart refrigerator, comprising a communication device, a processing device, a storage device, a camera device, and a freshness detection device capable of emitting light signals, wherein the processing device is electrically connected to the storage device, the communication device, the camera device, and the freshness detection device capable of emitting light signals, respectively; the communication device is used to obtain the door opening and closing history data of the smart refrigerator, the working signal of the door passively pressing button or the air pressure change data detected by the air pressure sensor in the refrigerator, and the detection data of the target device, and transmit them to the processing device; the storage device is used to store a computer program; characterized in that: The processing device is used to retrieve and execute the computer program in the storage device to perform the method described in any one of claims 1 to 6, so as to determine the camera device or the freshness detection device that can emit light signals as a target device, and send a control instruction to the target device to control the target device to detect the freshness of food stored in the refrigerator; and determine the freshness of the food stored in the refrigerator based on the detection data of the target device.

8. An electronic device comprising: At least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, wherein the processor executes the computer program to implement the method according to any one of claims 1 to 6.

9. A computer storage medium storing a computer program, characterized in that: The computer program is executed by a processor to implement the method according to any one of claims 1 to 6.

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