Item detection method and device for vehicle-mounted refrigerator

Abstract

The present invention relates to the field of item detection in refrigerators, and in particular discloses an item detection method for vehicle-mounted refrigerators, which method includes obtaining item weight data K0 in a refrigerator drawer, performing a comparison analysis with preset comparison elements based on the obtained item weight data K0, and determining whether to activate an alarm or alert the user based on the comparison analysis result. The present invention also provides an apparatus for applying the above-mentioned item detection method for vehicle-mounted refrigerators. The method and apparatus of the present invention have excellent application effects, rich functions, a high level of intelligence, advanced technology, and high practicality.

Description

[Technical Field]

[0001] The present invention relates to the field of article detection in refrigerators, and more particularly to an article detection method and device for vehicle-mounted refrigerators. [Background technology]

[0002] At present, passenger cars are developing very rapidly, and with the development of new energy passenger cars in particular, the need for installation related to the way users spend time in their cars is increasing. The installation of in-car refrigerators has become indispensable, and the way users spend time in their cars is becoming more diverse.

[0003] Users are accustomed to placing everyday items such as beverages in their car refrigerators, and research has shown that detecting these everyday items is used to inform users of information about the items and is a very popular feature of car refrigerators. However, currently, item detection is rarely set up in car refrigerators, and even if it is set up, the function is very simple and simply detecting whether or not an item is present in the car refrigerator does not meet the actual usage needs of users, so improvements are being made. Summary of the Invention

[0004] In order to solve the above problems existing in the prior art, according to one aspect of the embodiment of the present invention, Acquiring data K0 on the weight of items in a refrigerator drawer; Based on the acquired item weight data K0, perform a comparison analysis with preset comparison factors; and determining whether to activate an alarm or give a warning to a user based on the comparison and analysis result.

[0005] According to another aspect, an embodiment of the present invention further comprises: a first acquisition module that acquires weight data K0 of items in a drawer of the refrigerator; a first comparison analysis module that performs a comparison analysis using preset comparison elements based on the acquired item weight data K0; and an alarm module for determining whether to activate an alarm or alert a user based on the comparison and analysis result.

[0006] The present invention can obtain data on the weight of items in refrigerator drawers, and based on the weight data, perform comparative analysis using multiple comparison factors, thereby making a judgment and sending an alarm or warning the user. In addition, the present invention can perform big data analysis based on multiple obtained item weight data, thereby collectively analyzing the user's usage habits and more accurately warning the user. Furthermore, the present invention can connect to an external mobile terminal, transmit information on items in the vehicle refrigerator, and receive commands from the external mobile terminal. Therefore, the method and device of the present invention have excellent application effects, rich functions, and high practicality. [Brief explanation of the drawings]

[0007] In order to more clearly describe the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces drawings necessary for describing the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention, and those skilled in the art can obtain other drawings based on these drawings without any creative efforts.

[0008] [Figure 1] 1 is a flowchart of a first embodiment of an article detection method for a vehicle-mounted refrigerator according to the present invention. [Figure 2] 10 is a flowchart of a second embodiment of the object detection method for a vehicle-mounted refrigerator according to the present invention. [Figure 3] 10 is a flowchart of a third embodiment of the object detection method for a vehicle-mounted refrigerator of the present invention. [Figure 4] 10 is a flowchart of a fourth embodiment of the object detection method for a vehicle-mounted refrigerator of the present invention. [Figure 5]10 is a flowchart of a fifth embodiment of the object detection method for a vehicle-mounted refrigerator of the present invention. [Figure 6] 1 is a structural schematic diagram of a first embodiment of the device of the present invention; [Figure 7] FIG. 2 is a structural schematic diagram of a second embodiment of the device of the present invention. [Figure 8] FIG. 10 is a structural schematic diagram of a third embodiment of the device of the present invention. [Figure 9] FIG. 10 is a structural schematic diagram of a fourth embodiment of the device of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0009] The technical solutions in the embodiments of the present invention will be described clearly and completely below with reference to the drawings in the embodiments of the present invention, but it is obvious that the described embodiments are only some of the embodiments of the present invention, and not all of the embodiments, and all other embodiments obtained by those skilled in the art based on the embodiments of the present invention without any creative efforts shall fall within the protection scope of the present invention.

[0010] First embodiment of the method As shown in FIG. 1, this is a flowchart of a first embodiment of an article detection method for a vehicle refrigerator of the present invention, which includes: Step S1: acquiring data K0 on the weight of items in a refrigerator drawer; Step S2: performing a comparison analysis with preset comparison factors based on the acquired item weight data K0; and step S3 of determining whether to activate an alarm or alert the user based on the comparison and analysis result.

[0011] For example, in step S1 of this embodiment, the method for acquiring the item weight data K0 in the refrigerator drawer is as follows: The method includes installing four half-bridge resistive sensors at the four corners of the bottom of a refrigerator drawer and connecting them in parallel to form a full-bridge circuit, attaching a support plate on which an item is placed to the four sensors, the gravity of the item acting on the support plate and being transmitted to a deformation part of the sensor by the support plate, causing a change in the resistance value, and converting the resistance value into a gravity value by an AD circuit to obtain weight data K0.

[0012] In another embodiment, the vehicle-mounted refrigerator may be provided with a beverage area and a fruit area, and the number of items in the beverage area and the fruit area may be acquired, respectively; The method for acquiring the status of the number of items in the beverage area and the fruit area respectively includes installing a photographing device and identifying the number of items in the beverage area and the fruit area in the refrigerator based on the photographed image.

[0013] In step S2, the comparison element may include multiple elements such as, for example, a weight value, a quantity value, and a time value.

[0014] Second embodiment of the method As shown in FIG. 2, this is a flowchart of a second embodiment of the object detection method for a vehicle refrigerator of the present invention, which includes steps S4, S1, S2 and S3, In step S4, the shortest detection time T0 and the no-change detection time T1 are set. In step S1, data K0 on the weight of items in a refrigerator drawer is acquired. In this embodiment, in step S1, the item weight data K0 exceeding the shortest detection time T0 is acquired, For example, the shortest detection time T0 is set to 2 seconds, and it is effective to acquire item data in step S1 when the item weight data K0 exceeds 2 seconds. This is mainly to prevent errors caused by the vehicle shaking while the vehicle is moving, which causes the items in the refrigerator to bounce back in a short period of time and cause changes in weight.

[0015] In step S2, a comparison analysis is performed using preset comparison factors based on the acquired item weight data K0. This step is the same in principle as the corresponding step in the first embodiment of the method, so the description thereof will be omitted.

[0016] In step S3, based on the result of the comparison and analysis, it is determined whether to activate an alarm or to alert the user.

[0017] This step is the same in principle as the corresponding step in the first embodiment of the method, so the description thereof will be omitted.

[0018] In this embodiment, if the change value of the item weight data K0 exceeds the no-change detection time T1 and the change value is smaller than the preset change threshold, an alarm is activated or the user is notified that the item has not been removed for a long time. For example, the no-change detection time T1 can be set to 10 days or 15 days, and the preset change threshold can be set to 200g or 500g. Therefore, if the item weight data K0 exceeds 10 days and its weight change value is within the 200g range, it means that most of the items in the refrigerator have not yet been removed, are at risk of expiring, and need to be put away immediately.

[0019] Third embodiment of the method As shown in FIG. 3, this is a flowchart of a third embodiment of the object detection method for a vehicle refrigerator of the present invention, which includes steps S5, S4, S1, S2 and S3, In step S5, a first preset weight threshold K1 and a second preset weight threshold K2 are set, In step S4, the shortest detection time T0 and the no-change detection time T1 are set. This step is the same in principle as the corresponding step in the second embodiment of the method, so the description thereof will be omitted.

[0020] In step S1, data K0 on the weight of items in a refrigerator drawer is acquired. This step is the same in principle as the corresponding step in the second embodiment of the method, so the description thereof will be omitted.

[0021] In step S2, a comparison analysis is performed using preset comparison factors based on the acquired item weight data K0. In this embodiment, in step S2, If the item weight data K0 is smaller than the first preset weight threshold K1, activate an alarm or alert the user to indicate that the item is missing; If the item weight data K0 is greater than the second preset weight threshold K2, an alarm is activated or a user is notified that the item is full.

[0022] In step S3, based on the result of the comparison and analysis, it is determined whether to activate an alarm or to alert the user.

[0023] In this embodiment, for example, the first preset weight threshold K1 is set to 300g. Generally, one small bottle of cola or other beverage weighs about 350ml, or one apple weighs 100g, etc. Therefore, if the detected item weight data K0 is less than 300g, it means that there is not even one bottle of water in the vehicle refrigerator. At this time, an alarm will be activated to alert the user and indicate that there is a shortage of items. For example, the maximum capacity of the vehicle refrigerator is set to the second preset weight threshold K2, which can generally hold 6 to 10 bottles of beverage or 3 to 5 jin (1 jin = 500g) of fruit such as apples. If K2 is set to 3000g, when the detected item weight data K0 exceeds 3000g, an alarm will be activated or the user will be notified that the refrigerator is full and there is no need to purchase new items.

[0024] Fourth embodiment of the method As shown in FIG. 4, this is a flowchart of a fourth embodiment of the object detection method for a vehicle-mounted refrigerator of the present invention, and the method includes steps S5, S4, S1, S6, S7, S8, S2 and S3, In step S5, a first preset weight threshold K1 and a second preset weight threshold K2 are set, This step is the same in principle as the corresponding step in the third embodiment of the method, so the description thereof will be omitted.

[0025] In step S4, the shortest detection time T0 and the no-change detection time T1 are set. This step is the same in principle as the corresponding step in the second embodiment of the method, so the description thereof will be omitted.

[0026] In step S1, data K0 on the weight of items in a refrigerator drawer is acquired. This step is the same in principle as the corresponding step in the first embodiment of the method, so the description thereof will be omitted.

[0027] In step S6, the change value of the most recent N times of the item weight data K0 is obtained, In step S7, based on the change parameters at the time of the most recent N changes in the item weight data K0, the user's habit factors including the time period during which K0 changed or the number of changes in K0 are analyzed and acquired; For example, in this embodiment, the change values ​​of the most recent 20 changes in the item weight data K0 are acquired, and big data analysis is performed. For example, if 10 of the most recent 20 changes were between 1:00 PM and 2:00 PM or between 5:00 PM and 6:00 PM, this indicates that the user of the vehicle often takes out items from the refrigerator between 1:00 PM and 2:00 PM or between 5:00 PM and 6:00 PM. For example, if the weight change of an item is a decrease of 700g in 10 of the last 20 trips, this indicates that the user of the vehicle often takes out two bottles of water each time, and that there may always be two people in the vehicle.

[0028] In step S8, the cooling system of the vehicle refrigerator is automatically started in advance based on the habit factor, or the user is prompted to check whether the number of items is sufficient based on the habit factor.

[0029] In this step, operations are performed based on the analysis results of step S7, for example, the cooling system of the vehicle refrigerator is automatically started 30 minutes before 1:00 PM and 5:00 PM, or if the weight of the items in the vehicle refrigerator is less than 700 g or less than 1,400 g (less than four bottles of water, which can only be used once by two people), a warning is given to the user or an alarm is activated.

[0030] In step S2, a comparison analysis is performed using preset comparison factors based on the acquired item weight data K0.

[0031] This step is the same in principle as the corresponding step in the first embodiment of the method, so the description thereof will be omitted.

[0032] In step S3, based on the result of the comparison and analysis, it is determined whether to activate an alarm or to alert the user.

[0033] This step is the same in principle as the corresponding step in the first embodiment of the method, so the description thereof will be omitted.

[0034] In this embodiment, steps S7 and S8 are executed simultaneously with steps S1 and S2.

[0035] Fifth embodiment of the method As shown in FIG. 5, this is a flowchart of a fourth embodiment of the object detection method for a vehicle refrigerator of the present invention, and the method includes steps S91, S1, S92, S93, S2 and S3, In step S91, the vehicle-mounted refrigerator wirelessly connects to the external mobile terminal, In step S1, data K0 on the weight of items in a refrigerator drawer is acquired. In step S92, the external mobile terminal acquires item weight data K0 of the vehicle-mounted refrigerator, In step S93, the external mobile terminal prompts the user as to whether an item needs to be added based on the item weight data K0, or sends a command to the vehicle-mounted refrigerator; In step S2, a comparison analysis is performed using preset comparison factors based on the acquired item weight data K0. This step is the same in principle as the corresponding step in the first embodiment of the method, so the description thereof will be omitted.

[0036] In step S3, based on the result of the comparison and analysis, it is determined whether to activate an alarm or to alert the user.

[0037] This step is the same in principle as the corresponding step in the first embodiment of the method, so the description thereof will be omitted.

[0038] In this embodiment, step S93 and step S2 can be executed simultaneously.

[0039] Therefore, in the present invention, a mobile phone can be wirelessly connected to the vehicle refrigerator, for example, by WIFI, Bluetooth (registered trademark) or mobile communication traffic, and after the connection is established, the vehicle refrigerator will send data on the refrigerator's items, such as the number of drinks or fruits, to the mobile phone, so that the user can know whether the items need to be replenished, or the user can send a command to the vehicle refrigerator via the mobile phone to start the cooling system of the vehicle refrigerator.

[0040] First embodiment of the device As shown in FIG. 6, this is a structural schematic diagram of the first embodiment of the device of the present invention. In this embodiment, the device of the item detection method for vehicle refrigerators is as follows: a first acquisition module 1 that acquires weight data K0 of items in a drawer of the refrigerator; a first comparison analysis module 2 that performs a comparison analysis using preset comparison elements based on the acquired item weight data K0; and an alarm module 3 for determining whether to activate an alarm or alert a user based on the comparison and analysis result.

[0041] The first acquisition module 1 acquires the item weight data K0 in the refrigerator drawer as follows: The method includes installing four half-bridge resistive sensors at the four corners of the bottom of a refrigerator drawer and connecting them in parallel to form a full-bridge circuit, attaching a support plate on which an item is placed to the four sensors, the gravity of the item acting on the support plate and being transmitted to a deformation part of the sensor by the support plate, causing a change in the resistance value, and converting the resistance value into a gravity value by an AD circuit to obtain weight data K0.

[0042] In another embodiment, the vehicle-mounted refrigerator may be provided with a beverage area and a fruit area, and the number of items in the beverage area and the fruit area may be acquired, respectively; The method for acquiring the status of the number of items in the beverage area and the fruit area respectively includes installing a photographing device and identifying the number of items in the beverage area and the fruit area in the refrigerator based on the photographed image.

[0043] In the first comparison analysis module 2, the comparison element may include multiple elements such as, for example, a weight value, a quantity value, and a time value.

[0044] In another embodiment, in this embodiment, the first acquisition module 1 can acquire the status of the number of items in the beverage area and the fruit area respectively, for example, by taking an image through a photographing unit, and then identifying and analyzing the number of items in the beverage area and the fruit area in the refrigerator through an analysis unit.

[0045] Second embodiment of the device As shown in FIG. 7, this is a structural schematic diagram of the second embodiment of the device of the present invention, in this embodiment, before the first acquisition module, the device further includes a first setting module 4 and a second setting module 5; The first setting module 4 is A shortest detection time T0 and a no-change detection time T1 are set, and item weight data that exceeds the shortest detection time T0 acquired by item weight data K0 is acquired. In this embodiment, if the change in the item weight data K0 is less than the preset change threshold after the no-change detection time T1 has elapsed, an alarm is triggered or the user is alerted to indicate that the item has not been removed for a long period of time.

[0046] The second setting module 5 is A first preset weight threshold K1 and a second preset weight threshold K2 are set. Therefore, in this embodiment, if the item weight data K0 is smaller than the first preset weight threshold K1, an alarm is activated or a user is notified that an item is missing; If the item weight data K0 is greater than the second preset weight threshold K2, an alarm will be activated or a user will be notified that the item is full. The first acquisition module 1 acquires weight data K0 of items in a drawer of the refrigerator, The first comparison analysis module 2 performs a comparison analysis using preset comparison factors based on the acquired item weight data K0; The alarm module 3 determines whether to activate an alarm or give a warning to the user based on the comparison and analysis result.

[0047] Here, the operation principles of the first acquisition module 1, the first comparison and analysis module 2 and the alarm module 3 are the same as the corresponding structures of the device in the first embodiment, so the description thereof will be omitted.

[0048] Third embodiment of the device As shown in FIG. 8, this is a structural schematic diagram of the third embodiment of the device of the present invention. In this embodiment, the first setting module 4 includes: A shortest detection time T0 and a no-change detection time T1 are set, and item weight data that exceeds the shortest detection time T0 acquired by item weight data K0 is acquired. The second setting module 5 is A first preset weight threshold K1 and a second preset weight threshold K2 are set. The first acquisition module 1 acquires weight data K0 of items in a drawer of the refrigerator, Here, the operation principles of the first setting module 4, the second comparison and analysis module 5 and the first acquisition module 1 are the same as the corresponding structures of the device in Example 2, so the description thereof will be omitted.

[0049] The apparatus further comprises: The device includes a big data analysis module 6 that analyzes and obtains user habit factors including the time period during which K0 changes or the number of changes in K0 based on change parameters at the time of changes in the item weight data K0 of the most recent N times.

[0050] Therefore, in this embodiment, the cooling system of the vehicle refrigerator is automatically started in advance based on the habit factor, or the user is prompted to check whether the number of items is sufficient based on the habit factor.

[0051] The first comparison analysis module 2 performs a comparison analysis using preset comparison factors based on the acquired item weight data K0; The alarm module 3 determines whether to activate an alarm or give a warning to the user based on the comparison and analysis result.

[0052] Here, the operation principles of the first comparison and analysis module 2 and the alarm module 3 are the same as the corresponding structures of the device in the first embodiment, so the description thereof will be omitted.

[0053] Fourth embodiment of the device As shown in Figure 9, this is a structural schematic diagram of the fourth embodiment of the device of the present invention. In this embodiment, the device includes: a communication module 7, a first setting module 4, a second setting module 5, a first acquisition module 1, a sending module 81, a receiving module 82, a big data analysis module 6, a first comparison analysis module 2 and an alarm module 3; The communication module 7 wirelessly connects to an external mobile terminal, A wireless connection is established, for example, via WIFI, Bluetooth, or mobile traffic; The first setting module 4 is A shortest detection time T0 and a no-change detection time T1 are set, and item weight data that exceeds the shortest detection time T0 acquired by item weight data K0 is acquired. The second setting module 5 is A first preset weight threshold K1 and a second preset weight threshold K2 are set. The first acquisition module 1 acquires weight data K0 of items in a drawer of the refrigerator, Here, the operation principles of the first setting module 4, the second setting module 5 and the first obtaining module 1 are the same as the corresponding structures of the device in the third embodiment, so the description thereof will be omitted.

[0054] The transmitting module 81 transmits the item weight data K0 of the vehicle-mounted refrigerator to an external mobile terminal, The receiving module 82 receives commands sent by external mobile terminals.

[0055] Therefore, in the present invention, a mobile phone can be wirelessly connected to the vehicle refrigerator, for example, by WIFI, Bluetooth (registered trademark) or mobile communication traffic, and after the connection is established, the vehicle refrigerator will send data on the refrigerator's items, such as the number of drinks or fruits, to the mobile phone, so that the user can know whether the items need to be replenished, or the user can send a command to the vehicle refrigerator via the mobile phone to start the cooling system of the vehicle refrigerator.

[0056] Big Data Analysis Module 6 Based on the change parameters at the time of the most recent N changes in the item weight data K0, the user's habit factors including the time periods during which K0 changed or the number of changes in K0 are analyzed and acquired.

[0057] The first comparison analysis module 2 performs a comparison analysis using preset comparison factors based on the acquired item weight data K0; The alarm module 3 determines whether to activate an alarm or give a warning to the user based on the comparison and analysis result.

[0058] Here, the operation 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 device in the third embodiment, so the description thereof will be omitted.

[0059] Therefore, the present invention can obtain data on the weight of items in refrigerator drawers, and based on the weight data, perform comparative analysis using multiple comparison factors, thereby making a judgment and sending an alarm or warning the user. In addition, the present invention can perform big data analysis based on multiple obtained item weight data, thereby collectively analyzing the user's usage habits and more accurately warning the user. Furthermore, the present invention can connect to an external mobile terminal, transmit information on items in the vehicle refrigerator, and receive commands from the external mobile terminal. Therefore, the method and device of the present invention have excellent application effects, rich functions, and high practicality.

[0060] As can be understood by those skilled in the art, all or part of the processes in the above-described method embodiments can be completed by instructing relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, which can execute the processes of the above-described method embodiments when run. Here, the storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), etc.

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

Claims

1. Acquiring item weight data (K0) in a refrigerator drawer; Based on the acquired item weight data (K0), perform a comparison analysis with preset comparison factors; and determining whether to activate an alarm or alert a user based on the comparison and analysis results.

2. Before the step of acquiring the item weight data (K0) in the drawer of the refrigerator, Setting a minimum detection time (T0) and a no-change detection time (T1); Acquiring item weight data in which the item weight data (K0) exceeds the shortest detection time (T0), The step of performing a comparison analysis with preset comparison elements based on the acquired item weight data (K0) includes:

2. The item detection method for a vehicle-mounted refrigerator according to claim 1, further comprising the step of activating an alarm or alerting a user to indicate that an item has not been removed for a long period of time when the change in the item weight data (K0) is less than a preset change threshold value after the no-change detection time (T1) has elapsed.

3. Before the step of acquiring the item weight data (K0) in the drawer of the refrigerator, setting a first preset weight threshold (K1) and a second preset weight threshold (K2); The step of performing a comparison analysis with preset comparison elements based on the acquired item weight data (K0) includes: If the item weight data (K0) is less than the first preset weight threshold (K1), activate an alarm or alert the user to indicate that the item is missing; 3. The item detection method for a vehicle-mounted refrigerator according to claim 2, further comprising: activating an alarm or alerting a user to indicate that the refrigerator is full of items when the item weight data (K0) is greater than the second preset weight threshold (K2).

4. After the step of acquiring the item weight data (K0) in the drawer of the refrigerator, Obtaining change parameters when the item weight data (K0) changes the most recent N times; Analyzing and acquiring habit factors of the user, including a time period during which the item weight data (K0) changes or a number of changes in the item weight data (K0), based on change parameters at the time of the most recent N changes in the item weight data (K0); The item detection method for a vehicle-mounted refrigerator according to claim 1, further comprising: automatically starting the cooling system of the vehicle-mounted refrigerator in advance based on the habit factor; or prompting the user to check whether the number of items is sufficient based on the habit factor.

5. The vehicle-mounted refrigerator is provided with a beverage area and a fruit area, and acquiring the status of the number of items in the beverage area and the fruit area, respectively; 2. The item detection method for an in-vehicle refrigerator according to claim 1, wherein the method for acquiring the status of the number of items in the beverage area and the fruit area respectively comprises setting up a photographing device and identifying the number of items in the beverage area and the fruit area in the refrigerator based on the photographed images.

6. The method for acquiring the item weight data (K0) in the refrigerator drawer includes:

2. The object detection method for a vehicle-mounted refrigerator according to claim 1, comprising: installing four half-bridge resistive sensors at four corners of the bottom of a refrigerator drawer and connecting them in parallel to form a full-bridge circuit; attaching a support plate on which an object is placed to the four sensors; the gravity of the object acting on the support plate and being transmitted to a deformation portion of the sensor by the support plate to cause a change in resistance value; and converting the resistance value into a gravity value by an AD circuit to obtain object weight data (K0).

7. The in-vehicle refrigerator is wirelessly connected to an external mobile terminal; The external mobile terminal acquires item weight data (K0) of the vehicle-mounted refrigerator; The item detection method for a vehicle-mounted refrigerator as described in claim 1, characterized in that the external mobile terminal prompts a user as to whether an item needs to be added or sends a command to the vehicle-mounted refrigerator based on the item weight data (K0).

8. 10. An apparatus for applying the method of claim 1, comprising: a first acquisition module for acquiring weight data (K0) of items in a drawer of the refrigerator; a first comparison analysis module that performs a comparison analysis using preset comparison elements based on the acquired item weight data (K0); and an alarm module for determining whether to activate an alarm or alert a user based on the comparison and analysis result.

9. The device comprises: moreover, a first setting module that sets a shortest detection time (T0) and a no-change detection time (T1) and acquires item weight data (K0) that exceeds the acquired shortest detection time (T0); a second setting module for setting a first preset weight threshold (K1) and a second preset weight threshold (K2); a big data analysis module that analyzes and acquires user habit factors including a time period during which the item weight data (K0) changes or a number of changes in the item weight data (K0) based on change parameters at the time of the most recent N changes in the item weight data (K0), The vehicle refrigerator is provided with a beverage area and a fruit area, The first acquisition module is used to acquire the status of the number of items in the beverage area and the fruit area respectively; The device of claim 8, wherein the method for acquiring the status of the number of items in the beverage area and the fruit area respectively comprises installing a photographing device and identifying the number of items in the beverage area and the fruit area in the refrigerator through the photographed image.

10. The device comprises: a communication module for wirelessly connecting to an external mobile terminal; a transmitting module that transmits item weight data (K0) of the vehicle-mounted refrigerator to an external mobile terminal; 9. The device according to claim 8, further comprising: a receiving module for receiving commands sent by an external mobile terminal.

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