An article detection method and device applied to a vehicle-mounted refrigerator

Abstract

The application relates to the field of refrigerator article detection, and particularly discloses an article detection method applied to a vehicle-mounted refrigerator; the method comprises the following steps: acquiring article weight data K0 in a refrigerator drawer; comparing and analyzing the acquired article weight data K0 with preset comparison factors; and determining whether to start an alarm or to remind a user according to the comparison analysis result. The application also provides a device applying the above-mentioned article detection method of the vehicle-mounted refrigerator. The method and the device have the advantages of good application effect, rich functions, high intelligentization, advanced technology and strong practicability.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of refrigerator article detection, and in particular to an article detection method and device applied to a vehicle-mounted refrigerator. BACKGROUND

[0002] At present, the development of passenger cars is very rapid, especially with the development of new energy passenger cars, users have higher and higher requirements for vehicle life configuration. Vehicle-mounted refrigerators have become an indispensable configuration, enriching the user's vehicle life experience.

[0003] Users are used to placing beverages and other commonly used articles in vehicle-mounted refrigerators. Investigation has found that the detection of these commonly used articles to remind users of article-related information is a very popular function of vehicle-mounted refrigerators. However, at present, there are few vehicle-mounted refrigerators that set up article detection, and even if there are, the function is very simple, only detecting whether there are articles in the vehicle-mounted refrigerator, which cannot meet the actual use requirements of users, and therefore, further improvement is needed. SUMMARY

[0004] To solve the above problems in the prior art, the present application provides, in one aspect, an article detection method applied to a vehicle-mounted refrigerator, comprising:

[0005] acquiring article weight data K0 in a refrigerator drawer;

[0006] comparing and analyzing the acquired article weight data K0 with a preset comparison factor;

[0007] determining whether to start an alarm or remind a user according to the comparison and analysis result.

[0008] In another aspect, the present application also provides a device, comprising:

[0009] a first acquisition module for acquiring article weight data K0 in a refrigerator drawer;

[0010] a first comparison and analysis module for comparing and analyzing the acquired article weight data K0 with a preset comparison factor;

[0011] an alarm module for determining whether to start an alarm or remind a user according to the comparison and analysis result.

[0012] In the application, the weight data of the articles in the drawer of the refrigerator can be acquired, the weight data is compared and analyzed with various comparison factors, so as to judge and give an alarm or remind the user; and in the application, the weight data of the articles acquired for multiple times can be analyzed by big data, so as to summarize and analyze the use habits of the user, so as to give more targeted reminders; again, in the application, the external mobile terminal can be connected, the article information in the refrigerator on vehicle can be sent, and the instructions of the external mobile terminal can be received; therefore, the method and the device of the application have good application effect, rich functions and strong practicability. BRIEF DESCRIPTION OF DRAWINGS

[0013] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.

[0014] Figure 1 The flowchart of the first embodiment of the application of the article detection method applied to the refrigerator on vehicle;

[0015] Figure 2 The flowchart of the second embodiment of the application of the article detection method applied to the refrigerator on vehicle;

[0016] Figure 3 The flowchart of the third embodiment of the application of the article detection method applied to the refrigerator on vehicle;

[0017] Figure 4 The flowchart of the fourth embodiment of the application of the article detection method applied to the refrigerator on vehicle;

[0018] Figure 5 The flowchart of the fifth embodiment of the application of the article detection method applied to the refrigerator on vehicle;

[0019] Figure 6 The structural diagram of the first embodiment of the device of the present application;

[0020] Figure 7 The structural diagram of the second embodiment of the device of the present application;

[0021] Figure 8 The structural diagram of the third embodiment of the device of the present application;

[0022] Figure 9 The structural diagram of the fourth embodiment of the device of the present application. DETAILED DESCRIPTION

[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] Method First Embodiment

[0025] like Figure 1 The diagram shown is a flowchart illustrating the first embodiment of the item detection method for a vehicle-mounted refrigerator according to the present invention. The method includes:

[0026] Step S1: Obtain the weight data K0 of the items in the refrigerator drawer;

[0027] Step S2: Compare and analyze the obtained item weight data K0 with the preset comparison factors;

[0028] Step S3: Based on the comparison and analysis results, determine whether to activate the alarm or notify the user.

[0029] For example, in step S1 of this embodiment, the method of obtaining the weight data K0 of the items in the refrigerator drawer includes:

[0030] Four half-bridge resistive sensors are arranged at the four corners of the bottom of the refrigerator drawer. They are connected in parallel to form a full-bridge circuit. Support plates are installed on the four sensors, and items are placed on the support plates. The weight of the items acts on the support plates, and the support plates transmit the force to the deformation part of the sensors, causing a change in resistance. Through the AD circuit, the resistance value is converted into a weight value, and the weight data K0 is obtained.

[0031] Alternatively, the vehicle refrigerator may be equipped with a beverage section and a fruit section, and the quantity of items in the beverage section and the fruit section may be obtained respectively;

[0032] The method of obtaining the quantity status of items in the beverage section and fruit section respectively includes setting up a camera device to identify the quantity of items in the beverage section and fruit section of the refrigerator through the captured images.

[0033] In step S2, the comparison factors may include a variety of factors, such as weight value, quantity value, and time value.

[0034] Method Second Embodiment

[0035] like Figure 2 The diagram shown is a flowchart of a second embodiment of the item detection method for a vehicle-mounted refrigerator according to the present invention. The method includes:

[0036] Step S4: Set the shortest detection time T0 and the no-change detection time T1;

[0037] Step S1: Obtain the weight data K0 of the items in the refrigerator drawer;

[0038] In this embodiment, in step S1, obtaining the item weight data K0 means obtaining the item weight data that exceeds the shortest detection time T0;

[0039] For example, if the shortest detection time T0 is set to 2 seconds, then in step S1, the item weight data K0 is only valid if the item data takes more than 2 seconds to obtain. This is mainly to prevent errors caused by the weight change due to the item bouncing briefly inside the refrigerator caused by the vehicle's movement.

[0040] Step S2: Compare and analyze the obtained item weight data K0 with the preset comparison factors;

[0041] This step is based on the same principle as the corresponding step in the first embodiment of the method, and will not be described again.

[0042] Step S3: Based on the comparison and analysis results, determine whether to activate the alarm or notify the user.

[0043] This step is based on the same principle as the corresponding step in the first embodiment of the method, and will not be described again.

[0044] In this embodiment, if the change in the item weight data K0 exceeds the no-change detection period T1 and the change value is less than the preset change threshold, an alarm is triggered or a reminder is sent to the user, indicating that the item has not been used for a long time. For example, the no-change detection period T1 is set to 10 days or 15 days, etc.; the preset change threshold can be set to 200g or 500g, etc. Therefore, if the item weight data K0 exceeds 10 days and the change value is within 200g, it means that most of the items in the refrigerator may not have been used and there is a risk of expiration, so they need to be cleaned up in time.

[0045] Method Third Embodiment

[0046] like Figure 3 The diagram shown is a flowchart of a third embodiment of the item detection method for a vehicle-mounted refrigerator according to the present invention. The method includes:

[0047] Step S5: Set the first preset weight threshold K1 and the second preset weight threshold K2;

[0048] Step S4: Set the shortest detection time T0 and the no-change detection time T1;

[0049] This step is based on the same principle as the corresponding step in the second embodiment of the method, and will not be described again.

[0050] Step S1: Obtain the weight data K0 of the items in the refrigerator drawer;

[0051] This step is based on the same principle as the corresponding step in the second embodiment of the method, and will not be described again.

[0052] Step S2: Compare and analyze the obtained item weight data K0 with the preset comparison factors;

[0053] In this embodiment, step S2 includes:

[0054] If the item weight data K0 is less than the first preset weight threshold K1, an alarm will be triggered or a reminder will be sent to the user that the item is insufficient.

[0055] If the item weight data K0 is greater than the second preset weight threshold K2, an alarm will be triggered, or a reminder will be sent to the user that the item is full.

[0056] Step S3: Based on the comparison and analysis results, determine whether to activate the alarm or notify the user.

[0057] In this embodiment, for example, the first preset weight threshold K1 is set to 300g, because a small bottle of cola or other beverage is generally about 350ml, or an apple weighs 100g, etc. If the detected item weight data K0 is less than 300g, it means that there is no water in the car refrigerator, so an alarm is triggered, or the user is reminded that there are not enough items.

[0058] For example, the maximum capacity of the car refrigerator is the second preset weight threshold K2, which can generally hold 6-10 bottles of beverages or 3-5 jin of fruits such as apples. If K2 is set to 3000g, then if the detected item weight data K0 is greater than 3000g, an alarm will be triggered or a reminder will be sent to the user that the refrigerator is full and that the user does not need to purchase new items to put in the refrigerator.

[0059] Method Fourth Embodiment

[0060] like Figure 4 The diagram shown is a flowchart of the fourth embodiment of the item detection method applied to a vehicle refrigerator according to the present invention. The method includes:

[0061] Step S5: Set the first preset weight threshold K1 and the second preset weight threshold K2;

[0062] This step is based on the same principle as the corresponding step in the third embodiment of the method, and will not be described again.

[0063] Step S4: Set the shortest detection time T0 and the no-change detection time T1;

[0064] This step is based on the same principle as the corresponding step in the second embodiment of the method, and will not be described again.

[0065] Step S1: Obtain the weight data K0 of the items in the refrigerator drawer;

[0066] This step is based on the same principle as the corresponding step in the first embodiment of the method, and will not be described again.

[0067] Step S6: Obtain the change values ​​of the weight data K0 of the item in the most recent N changes;

[0068] Step S7: Analyze and obtain user habit factors based on the change parameters of the most recent N changes in the item weight data K0; the habit factors include the time period of K0 change or the number of K0 changes;

[0069] For example, in this embodiment, the change values ​​of the item weight data K0 in the last 20 times are obtained and big data analysis is performed; for example, if 10 of the last 20 times the change occurred between 1 pm and 2 pm, or between 5 pm and 6 pm, it indicates that the user of the vehicle often takes out the refrigerator items between 1 pm and 2 pm or between 5 pm and 6 pm.

[0070] For example, if the weight of the item decreased by 700g in 10 out of the last 20 times, it means that the user of the car often takes 2 bottles of water each time, and there may be 2 people riding in the car frequently.

[0071] Step S8: Based on user habits, automatically start the vehicle refrigerator's cooling system in advance; or based on user habits, remind the user whether there are enough items.

[0072] In this step, operations are performed based on the analysis results of step S7; for example, the vehicle refrigerator cooling system is automatically turned on half an hour before 1 p.m. and 5 p.m.; or when the weight of the items in the vehicle refrigerator is less than 700g, or less than 1400g (less than 4 bottles of water, enough for only two people to use once), the user is reminded or an alarm is triggered.

[0073] Step S2: Compare and analyze the obtained item weight data K0 with the preset comparison factors;

[0074] This step is based on the same principle as the corresponding step in the first embodiment of the method, and will not be described again.

[0075] Step S3: Based on the comparison and analysis results, determine whether to activate the alarm or notify the user.

[0076] This step is based on the same principle as the corresponding step in the first embodiment of the method, and will not be described again.

[0077] It should be noted that in this embodiment, steps S7 and S8 are executed simultaneously with steps S1 and S2.

[0078] Fifth embodiment of the method

[0079] like Figure 5 The diagram shown is a flowchart of the fourth embodiment of the item detection method applied to a vehicle refrigerator according to the present invention. The method includes:

[0080] Step S91: The vehicle refrigerator connects to an external mobile terminal wirelessly;

[0081] Step S1: Obtain the weight data K0 of the items in the refrigerator drawer;

[0082] Step S92: The external mobile terminal acquires the weight data K0 of the items in the vehicle refrigerator;

[0083] Step S93: The external mobile terminal reminds the user whether to add items or sends a command to the vehicle refrigerator based on the item weight data K0.

[0084] Step S2: Compare and analyze the obtained item weight data K0 with the preset comparison factors;

[0085] This step is based on the same principle as the corresponding step in the first embodiment of the method, and will not be described again.

[0086] Step S3: Based on the comparison and analysis results, determine whether to activate the alarm or notify the user.

[0087] This step is based on the same principle as the corresponding step in the first embodiment of the method, and will not be described again.

[0088] It should be noted that in this embodiment, steps S93 and S2 can be run simultaneously.

[0089] Therefore, in this invention, a mobile phone can be wirelessly connected to the car refrigerator, for example, via WIFI, Bluetooth, or mobile data traffic; after connection, the car refrigerator sends the contents data of the refrigerator to the mobile phone, such as the quantity of beverages or fruits, so that the user knows whether the items need to be replenished; or the user can send a command to the car refrigerator through the mobile phone to turn on the cooling system of the car refrigerator.

[0090] First embodiment of the device

[0091] like Figure 6 The diagram shown is a structural schematic of the first embodiment of the device of the present invention; in this embodiment, the device for the item detection method applied to a vehicle refrigerator includes:

[0092] The first acquisition module 1 is used to acquire the weight data K0 of the items in the refrigerator drawer;

[0093] The first comparison and analysis module 2 is used to compare and analyze the obtained item weight data K0 with preset comparison factors.

[0094] Alarm module 3 is used to determine whether to activate an alarm or remind the user based on the comparison and analysis results.

[0095] The first acquisition module 1 acquires the weight data K0 of the items in the refrigerator drawer in the following ways:

[0096] Four half-bridge resistive sensors are arranged at the four corners of the bottom of the refrigerator drawer. They are connected in parallel to form a full-bridge circuit. Support plates are installed on the four sensors, and items are placed on the support plates. The weight of the items acts on the support plates, and the support plates transmit the force to the deformation part of the sensors, causing a change in resistance. Through the AD circuit, the resistance value is converted into a weight value, and the weight data K0 is obtained.

[0097] Alternatively, the vehicle refrigerator may be equipped with a beverage section and a fruit section, and the quantity of items in the beverage section and the fruit section may be obtained respectively;

[0098] The method for obtaining the quantity of items in the beverage section and the fruit section respectively includes setting up a camera device to identify the quantity of items in the beverage section and the fruit section of the refrigerator through the captured images.

[0099] In the first comparison analysis module 2, the comparison factors can include a variety of factors, such as weight value, quantity value and time value.

[0100] In another implementation, in this embodiment, the first acquisition module 1 can acquire the quantity of items in the beverage section and the fruit section respectively; for example, images are captured by the camera unit, and then the quantity of items in the beverage section and the fruit section in the refrigerator is identified and analyzed by the analysis unit.

[0101] Second embodiment of the device

[0102] like Figure 7 The diagram shown is a structural schematic of a second embodiment of the device of the present invention; in this embodiment, the device further includes, before the first acquisition module:

[0103] First setting module 4, used for:

[0104] Set the shortest detection time T0 and the no-change detection time T1; acquire item weight data K0 to acquire item weight data that exceeds the shortest detection time T0;

[0105] In this embodiment, if the change value of the item weight data K0 is less than the preset change threshold after the no-change detection time T1, an alarm will be triggered or the user will be reminded that the item has not been used for a long time.

[0106] The second setting module 5 is used for:

[0107] Set a first preset weight threshold K1 and a second preset weight threshold K2.

[0108] Therefore, in this embodiment, if the item weight data K0 is less than the first preset weight threshold K1, an alarm is triggered or the user is reminded that the item is insufficient.

[0109] If the item weight data K0 is greater than the second preset weight threshold K2, an alarm will be triggered, or a reminder will be sent to the user that the item is full.

[0110] The first acquisition module 1 is used to acquire the weight data K0 of the items in the refrigerator drawer;

[0111] The first comparison and analysis module 2 is used to compare and analyze the obtained item weight data K0 with preset comparison factors.

[0112] Alarm module 3 is used to determine whether to activate an alarm or remind the user based on the comparison and analysis results.

[0113] The working principles of the first acquisition module 1, the first comparison and analysis module 2, and the alarm module 3 are the same as those of the corresponding structure in the first embodiment of the device, and will not be described again.

[0114] Third embodiment of the device

[0115] like Figure 8 The diagram shown is a structural schematic of a third embodiment of the device of the present invention; in this embodiment, the first setting module 4 is used for:

[0116] Set the shortest detection time T0 and the no-change detection time T1; acquire item weight data K0 to acquire item weight data that exceeds the shortest detection time T0;

[0117] The second setting module 5 is used for:

[0118] Set a first preset weight threshold K1 and a second preset weight threshold K2.

[0119] The first acquisition module 1 is used to acquire the weight data K0 of the items in the refrigerator drawer;

[0120] The working principles of the first setting module 4, the second setting module 5, and the first acquisition module 1 are the same as those of the corresponding structures in the second embodiment of the device, and will not be described again.

[0121] The device also includes a big data analysis module 6, used for:

[0122] Based on the change parameters of the most recent N changes in the item weight data K0, the user's habit factors are analyzed and obtained; the habit factors include the time period of K0 change and the number of K0 changes.

[0123] Therefore, in this embodiment, the vehicle refrigerator's cooling system is automatically started in advance based on user habits; or the user is reminded whether the quantity of items is sufficient based on user habits.

[0124] The first comparison and analysis module 2 is used to compare and analyze the obtained item weight data K0 with preset comparison factors.

[0125] Alarm module 3 is used to determine whether to activate an alarm or remind the user based on the comparison and analysis results.

[0126] The working principle of the first comparison and analysis module 2 and the alarm module 3 is the same as the corresponding structure in the first embodiment of the device, and will not be described again.

[0127] Fourth embodiment of the device

[0128] like Figure 9 The diagram shown is a structural schematic of a fourth embodiment of the device of the present invention; in this embodiment, the device includes:

[0129] Communication module 7 is used for: wirelessly connecting to an external mobile terminal;

[0130] For example, wireless connection via WIFI, Bluetooth, or mobile data;

[0131] First setting module 4, used for:

[0132] Set the shortest detection time T0 and the no-change detection time T1; acquire item weight data K0 to acquire item weight data that exceeds the shortest detection time T0;

[0133] The second setting module 5 is used for:

[0134] Set a first preset weight threshold K1 and a second preset weight threshold K2.

[0135] The first acquisition module 1 is used to acquire the weight data K0 of the items in the refrigerator drawer;

[0136] The working principles of the first setting module 4, the second setting module 5, and the first acquisition module 1 are the same as those of the corresponding structures in the third embodiment of the device, and will not be described again.

[0137] The sending module 81 is used to send the weight data K0 of the items in the vehicle refrigerator to an external mobile terminal;

[0138] The receiving module 82 is used to receive instructions sent by an external mobile terminal.

[0139] Therefore, in this invention, a mobile phone can be wirelessly connected to the car refrigerator, for example, via WIFI, Bluetooth, or mobile data traffic; after connection, the car refrigerator sends the contents data of the refrigerator to the mobile phone, such as the quantity of beverages or fruits, so that the user knows whether the items need to be replenished; or the user can send a command to the car refrigerator through the mobile phone to turn on the cooling system of the car refrigerator.

[0140] Big Data Analytics Module 6 is used for:

[0141] Based on the change parameters of the most recent N changes in the item weight data K0, the user's habit factors are analyzed and obtained; the habit factors include the time period of K0 change and the number of K0 changes.

[0142] The first comparison and analysis module 2 is used to compare and analyze the obtained item weight data K0 with preset comparison factors.

[0143] Alarm module 3 is used to determine whether to activate an alarm or remind the user based on the comparison and analysis results.

[0144] The working principles of the big data analysis module 6, the first comparison analysis module 2, and the alarm module 3 are the same as the corresponding structures in the third embodiment of the device, and will not be described again.

[0145] Therefore, in this invention, the weight data of items inside the refrigerator drawer can be obtained. Based on this weight data, it can be compared and analyzed with various comparison factors to determine and issue an alarm or remind the user. Furthermore, this invention can also perform big data analysis based on multiple acquisitions of item weight data to summarize and analyze user usage habits for more targeted reminders. Additionally, this invention can connect to an external mobile terminal to send information about items inside the vehicle refrigerator and receive instructions from the external mobile terminal. Therefore, the method and apparatus of this invention have good application effects, rich functions, and strong practicality.

[0146] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0147] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for detecting items in a vehicle-mounted refrigerator, characterized in that, include: Obtain the weight data (K0) of items inside the refrigerator drawer; Based on the obtained weight data (K0), perform comparative analysis with preset comparison factors; Based on the comparison and analysis results, determine whether to activate an alarm or notify the user; An apparatus for an item detection method includes: a first acquisition module for acquiring item weight data (K0) in a refrigerator drawer; a first comparison and analysis module for comparing and analyzing the acquired item weight data (K0) with preset comparison factors; and an alarm module for determining whether to activate an alarm or alert the user based on the comparison and analysis results. The apparatus further includes: a first setting module for setting a minimum detection time (T0) and a no-change detection time (T1); acquiring item weight data (K0) means acquiring item weight data exceeding the minimum detection time (T0); and a second setting module for setting a first preset weight threshold (K1) and a second preset weight threshold (K2). A big data analysis module is used to: analyze and obtain user habit factors based on the change parameters of the most recent N changes in the item weight data (K0); the habit factors include the time period of the changes in item weight data (K0) and the number of changes in item weight data (K0); the vehicle refrigerator has a beverage section and a fruit section; the first acquisition module includes: acquiring the item quantity status of the beverage section and the fruit section respectively; the method of acquiring the item quantity status of the beverage section and the fruit section respectively includes setting up a camera device to identify the item quantity of the beverage section and the fruit section in the refrigerator through the captured image; the device includes: a communication module for wirelessly connecting to an external mobile terminal; a sending module for sending the item weight data (K0) of the vehicle refrigerator to the external mobile terminal; and a receiving module for receiving instructions sent by the external mobile terminal.

2. The item detection method applied to a vehicle-mounted refrigerator as described in claim 1, characterized in that, Before the step of obtaining the weight data (K0) of the items in the refrigerator drawer, the method further includes: setting a minimum detection time (T0) and a no-change detection time (T1); obtaining the item weight data (K0) means obtaining the item weight data that exceeds the minimum detection time (T0); the step of comparing and analyzing the obtained item weight data (K0) with preset comparison factors includes: if the item weight data (K0) exceeds the no-change detection time (T1) and its change value is less than a preset change threshold, then an alarm is activated, or a reminder is given to the user that the item has not been used for a long time.

3. The item detection method applied to a vehicle-mounted refrigerator as described in claim 2, characterized in that, Before the step of obtaining the weight data (K0) of the items in the refrigerator drawer, the method further includes: setting a first preset weight threshold (K1) and a second preset weight threshold (K2); the step of comparing and analyzing the obtained weight data (K0) with preset comparison factors includes: if the weight data (K0) is less than the first preset weight threshold (K1), then an alarm is activated, or a reminder is given to the user that the items are insufficient; if the weight data (K0) is greater than the second preset weight threshold (K2), then an alarm is activated, or a reminder is given to the user that the items are full.

4. The item detection method applied to a vehicle refrigerator as described in claim 1, characterized in that, After the step of obtaining the weight data (K0) of the items in the refrigerator drawer, the method further includes: obtaining the change parameters of the most recent N changes in the weight data (K0); analyzing and obtaining user habit factors based on the change parameters of the most recent N changes in the weight data (K0); the habit factors include the time period of the changes in the weight data (K0) or the number of changes in the weight data (K0); automatically starting the vehicle refrigerator's cooling system in advance based on the habit factors; or reminding the user whether the quantity of items is sufficient based on the habit factors.

5. The method for detecting items applied to a vehicle-mounted refrigerator as described in claim 1, characterized in that, The vehicle-mounted refrigerator includes a beverage section and a fruit section, and the quantity of items in the beverage section and the fruit section are obtained respectively. The method for obtaining the quantity of items in the beverage section and the fruit section respectively includes setting up a camera device to identify the quantity of items in the beverage section and the fruit section in the refrigerator through the captured images.

6. The item detection method applied to a vehicle-mounted refrigerator as described in claim 1, characterized in that, The method for obtaining the weight data (K0) of items in the refrigerator drawer includes: arranging four half-bridge resistive sensors at the four corners of the bottom of the refrigerator drawer, forming a full-bridge circuit through parallel connection; installing support plates on the four sensors, and placing items on the support plates; the weight of the items acts on the support plates, and the support plates transmit the force to the deformation part of the sensors, causing a change in resistance; through an AD circuit, the resistance value is converted into a gravity value, and the weight data (K0) of the items is obtained.

7. The item detection method applied to a vehicle-mounted refrigerator as described in claim 1, characterized in that, The system includes a vehicle refrigerator that wirelessly connects to an external mobile terminal; the external mobile terminal acquires the weight data (K0) of the items in the vehicle refrigerator; and the external mobile terminal, based on the weight data (K0), reminds the user whether to add items or sends instructions to the vehicle refrigerator.

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