Intelligent refrigerator control system and method based on Internet of Things technology

Abstract

The present invention belongs to the field of smart refrigerators and the Internet of Things (IoT) technology. A smart refrigerator control system and method based on IoT technology are provided. The method comprises: the smart refrigerator detects and evaluates the network status of a first IoT network; when the network status of the first IoT network meets the connectivity conditions, the smart refrigerator maintains a login status with the first IoT network to accept remote monitoring from a user's IoT terminal device; when the network status of the first IoT network does not meet the connectivity conditions, the smart refrigerator sends a network request signal to a target IoT terminal device via a second IoT network; and the smart refrigerator logs into a third IoT network to accept remote monitoring from the user's IoT terminal device. When a fault occurs in a predetermined IoT network, the smart refrigerator of the present invention can still maintain an online status by sending a network request to other terminal devices, thereby effectively implementing remote monitoring of the smart refrigerator by the user.

Description

Technical Field

[0001] The present invention relates to the field of smart refrigerators and the technical field of the Internet of Things, and in particular to a smart refrigerator control system and method based on the Internet of Things technology. Background Art

[0002] With technological advancements, refrigerators are becoming increasingly intelligent. Many refrigerators now utilize the Internet of Things (IoT) technology. Once connected to an IoT network, users can remotely monitor and control their refrigerators. A search revealed numerous patents related to smart refrigerators using IoT technology.

[0003] CN117469915A discloses a remote control method for a smart refrigerator, comprising the following steps: Step S1: confirming the maximum synchronization time t0 of the electronic control state, i.e., the time from when the user completes the modification of the function state on the refrigerator to when the APP is successfully synchronized; Step S2: confirming the time t1 from when the setting command is sent from the APP to when it is received by the Internet of Things module and sent to the control board and then to the dedicated zone board; Step S3: after the APP sends the setting command, synchronization is not performed immediately, but after a delay of t2, where t2 ≥ t0 + t1; Step S4: comparing the electronic control report data received by the APP within t2, and if the data is the same as the setting data, state synchronization is performed; if the data is different, state synchronization is performed using the data reported by the electronic control after t2. The present invention avoids the problem of state jumps on the APP caused by delayed electronic control state reporting due to a long communication link by not changing the software and hardware state of the refrigerator electronic control system, and only performs software processing on the mobile phone APP end, thereby improving the user experience.

[0004] CN117128704A discloses a smart refrigerator control method based on the Internet of Things, which is applied to a smart refrigerator comprising a plurality of storage bins for storing items. The method comprises: parsing an acquired item search request to obtain target item information; determining whether the smart refrigerator currently stores a target item corresponding to the target item information based on the target item information; and if the target item exists in the smart refrigerator, locating the storage bin corresponding to the target item to provide the target item to the user. The smart refrigerator control method based on the Internet of Things provided in the embodiment of the present application can help users quickly find the specific location of the target item in the refrigerator, and by allocating independent storage bins for each type of item, each type of item is neatly arranged and not easily overlooked.

[0005] CN115790060A discloses a refrigerator temperature monitoring system based on narrowband Internet of Things, which is characterized by comprising a computer server and multiple refrigerator temperature monitoring modules, each of which is in communication connection with the computer server; the refrigerator temperature monitoring module comprises a first temperature sensor, a second temperature sensor, a central processing unit, a power module, and a narrowband Internet of Things NB-IoT communication module; the first temperature sensor, the second temperature sensor, the power module, and the narrowband Internet of Things NB-IoT communication module are respectively connected to the central processing unit; the first temperature sensor, the second temperature sensor, and the narrowband Internet of Things NB-IoT communication module are also connected to the power module; the first temperature sensor is arranged near the refrigerator door, and the second temperature sensor is arranged away from the refrigerator door The refrigerator temperature monitoring module includes two temperature sensors, which can improve the reliability of temperature monitoring. On the other hand, it can also use a variable sampling frequency method when only one temperature sensor exceeds the limit to determine whether there is a short-term local temperature rise caused by opening the refrigerator door, thereby avoiding false alarms of temperature exceeding the limit caused by opening the refrigerator door. This invention has better temperature monitoring reliability and network communication functions than the temperature sensor modules currently used in hospitals, and can determine false alarms of temperature exceeding the limit caused by opening the refrigerator door to take out items through a software algorithm.

[0006] However, IoT networks have a probability of failure. When the network is poor or even disconnected, remote monitoring and operation of the refrigerator cannot be implemented. The above-mentioned existing patent documents do not involve solutions or improvements to this technical problem. Summary of the Invention

[0007] In this regard, the present invention provides a smart refrigerator control method, system, electronic device, computer storage medium and computer program product based on Internet of Things technology to solve the above technical problems.

[0008] The present invention discloses a smart refrigerator control method based on Internet of Things technology, which includes the following steps: the smart refrigerator detects and evaluates the network status of a first Internet of Things network, and when the network status of the first Internet of Things network meets the connection conditions, the smart refrigerator maintains a login state with the first Internet of Things network to accept remote monitoring of a user's Internet of Things terminal device; when the network status of the first Internet of Things network does not meet the connection conditions, the smart refrigerator sends a network request signal to a target Internet of Things terminal device through a second Internet of Things network; the network request signal is used to trigger the target Internet of Things terminal device to open a third Internet of Things network; the smart refrigerator logs in to the third Internet of Things network to accept remote monitoring of the user's Internet of Things terminal device.

[0009] In some embodiments, the smart refrigerator detects and evaluates the network status of the first Internet of Things network, including: obtaining historical operation record information for remote monitoring of the smart refrigerator, and determining the minimum number of operations based on the historical record information; obtaining the number of remote operations of the user Internet of Things terminal device in the current time period; when the number of remote operations is less than the minimum number of operations, determining that the network status of the first Internet of Things network is abnormal.

[0010] In some embodiments, determining the minimum number of operations based on the historical record information includes: dividing the historical record information into several groups according to date attributes and time period attributes, performing statistical calculations on the historical remote operation times in each group, and obtaining the remote operation statistical times for each time period to which the corresponding date belongs; sorting the remote operation statistical times for each corresponding date according to the time period order, and performing curve fitting and smoothing on the sorted data to obtain the remote operation statistical curve for the corresponding date; segmenting the remote operation statistical curve according to the time period, and determining the minimum value of the vertical coordinate in each segmented curve as the minimum number of operations for each time period to which the corresponding date belongs.

[0011] In some embodiments, the statistical calculation of the historical remote operation times in each group to obtain the remote operation statistical times for each time period to which the corresponding date belongs includes: statistical calculation of the historical remote operation times in each group to obtain the first remote operation statistical times for each time period to which the corresponding date belongs, and the number of the user IoT terminal devices; determining an amplification coefficient based on the number, and using the amplification coefficient to adjust the first remote operation statistical times to obtain the second remote operation statistical times, that is, obtaining the remote operation statistical times.

[0012] In some embodiments, the smart refrigerator sends a network request signal to the target IoT terminal device through the second IoT network, including: the smart refrigerator turns on the second IoT network to send a network request signal to the outside, and the network request signal includes the terminal device ID, the judgment information of the abnormal network status of the first IoT network and the network start request information; wherein, the terminal device ID is obtained based on the connection record information of the first IoT network.

[0013] In some embodiments, the target IoT terminal device turns on the third IoT network, including: the target IoT terminal device parses the judgment information of the abnormal network status of the first IoT network to obtain a judgment method for the abnormal network status; if the abnormal network status is determined based on the minimum number of operations, the target IoT terminal device switches its own network from the first IoT network to a fourth IoT network that belongs to the same network device as the first IoT network but has a different network frequency band, and then turns on the third IoT network; if the abnormal network status is directly determined based on the network operation parameters of the first IoT network, the target IoT terminal device first turns on the mobile communication network, and then turns on the third IoT network.

[0014] The present invention also discloses an intelligent refrigerator control system based on Internet of Things technology, wherein the system includes a network module, a processing module, and a storage module, wherein the processing module is electrically connected to the network module and the storage module respectively; the network module is used to receive remote monitoring operations of user Internet of Things terminal devices; and, detect the operating parameters of the first Internet of Things network and transmit them to the processing module; and, according to the control instructions sent by the processing module, send a network request signal to the target Internet of Things terminal device through the second Internet of Things network and switch access to the third Internet of Things network; the storage module is used to store computer programs; it is characterized in that: the processing module is used to respond to receiving remote monitoring operations of user Internet of Things terminal devices; and retrieve and execute the computer program in the storage module to execute any of the methods described above to evaluate and generate control instructions for controlling the network module based on the network status of the first Internet of Things network.

[0015] The present invention also discloses an electronic device, which is applied to a smart refrigerator, 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 aforementioned embodiment.

[0016] 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 any of the above methods.

[0017] The present invention also discloses a computer program product. When the computer program product is run on a terminal, the terminal implements any of the above methods when executing the computer program product.

[0018] The beneficial effect of the present invention is that when a predetermined Internet of Things network fails, the smart refrigerator of the present invention can still maintain an online state by sending network borrowing to other terminal devices, thereby enabling users to effectively implement remote monitoring of the smart refrigerator. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0020] Figure 1 This is a flow chart of a smart refrigerator control method based on Internet of Things technology disclosed in an embodiment of the present invention.

[0021] Figure 2 This is a structural diagram of an intelligent refrigerator control system based on Internet of Things technology disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0022] The following specific embodiments illustrate the implementation of this application. Those familiar with the art can easily understand the other advantages and functions of this application from the content disclosed in this specification. Obviously, the described embodiments are part of the embodiments of this application, but not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this 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 1As shown, an embodiment of the present invention discloses a smart refrigerator control method based on Internet of Things technology, which includes the following steps: the smart refrigerator detects and evaluates the network status of a first Internet of Things network, and when the network status of the first Internet of Things network meets the connection conditions, maintains a logged-in state with the first Internet of Things network to accept remote monitoring of the user's Internet of Things terminal device; when the network status of the first Internet of Things network does not meet the connection conditions, the smart refrigerator sends a network request signal to the target Internet of Things terminal device through the second Internet of Things network; the network request signal is used to trigger the target Internet of Things terminal device to open a third Internet of Things network; the smart refrigerator logs in to the third Internet of Things network to accept remote monitoring of the user's Internet of Things terminal device.

[0025] In an embodiment of the present invention, the smart refrigerator of the present invention is equipped with an Internet of Things communication module, which can log in to the first Internet of Things network in the area where it is located, so that the user can remotely monitor the smart refrigerator in an online state. The smart refrigerator can also monitor the network status of the currently logged-in Internet of Things network. When it finds that the network status is not good, it determines that it may be in a situation where it cannot be remotely monitored by the user. At this time, it sends a network request signal to the target Internet of Things terminal device through the second Internet of Things network. After receiving the network request signal, the target Internet of Things terminal device in the area can turn on its own third Internet of Things network signal, and the smart refrigerator can maintain an online connection with the user through the network of the target Internet of Things terminal device. Therefore, when the predetermined Internet of Things network fails, the smart refrigerator of the present invention can still maintain an online state by sending a network borrowing to other terminal devices, thereby realizing the effective implementation of remote monitoring of the smart refrigerator by the user.

[0026] Among them, user IoT terminal devices can be smartphones, tablets, computers, smart wearable devices, virtual reality devices, etc. Target IoT terminal devices can also be terminals of the above types, but they need to be equipped with independent networks, such as 2G, 3G, 4G, 5G, 6G and other mobile communication networks.

[0027] In some embodiments, the smart refrigerator detects and evaluates the network status of the first Internet of Things network, including: obtaining historical operation record information for remote monitoring of the smart refrigerator, and determining the minimum number of operations based on the historical record information; obtaining the number of remote operations of the user Internet of Things terminal device in the current time period; when the number of remote operations is less than the minimum number of operations, determining that the network status of the first Internet of Things network is abnormal.

[0028] In an embodiment of the present invention, a user's remote operations on a smart refrigerator are regular. By analyzing the historical operation records of the smart refrigerator's remote monitoring, it is possible to determine the minimum number of operations performed by the user on the smart refrigerator within a specific time period. The minimum number of operations is the minimum number of operations performed by the user on the smart refrigerator within a specific time period (weekdays, weekends, holidays, and daily time periods). Therefore, if the number of remote operations within the current time period is found to be less than the minimum number of operations, it can be determined that the first IoT network connected to the smart refrigerator may have a network anomaly, preventing the user from performing remote monitoring operations.

[0029] Among them, the minimum number of operations and the number of remote operations include viewing operations and adjustment operations. The viewing operation can be the viewing of working parameters such as temperature, voltage, current, etc. in the refrigerator. The adjustment operation can be the adjustment and control of the working status such as temperature, working mode, and sterilization function on / off of each storage room of the refrigerator.

[0030] Furthermore, the above-described solution of the present invention can supplement a method for directly determining the network status of the first IoT network. This direct determination method involves directly analyzing network operating parameters such as information transmission rate, information transmission time rate, and information transmission packet loss rate to determine the network status. As this relates to mature prior art, the present invention will not elaborate on the detection principles.

[0031] In some embodiments, determining the minimum number of operations based on the historical record information includes: dividing the historical record information into several groups according to date attributes and time period attributes, performing statistical calculations on the historical remote operation times in each group, and obtaining the remote operation statistical times for each time period to which the corresponding date belongs; sorting the remote operation statistical times for each corresponding date according to the time period order, and performing curve fitting and smoothing on the sorted data to obtain the remote operation statistical curve for the corresponding date; segmenting the remote operation statistical curve according to the time period, and determining the minimum value of the vertical coordinate in each segmented curve as the minimum number of operations for each time period to which the corresponding date belongs.

[0032] In an embodiment of the present invention, all the historical record information obtained is first grouped according to date attributes and time period attributes, wherein the date attributes include weekdays, weekends, holidays, etc., and the time period is the time period of each day of the above-mentioned various types of dates, for example, each day is evenly or unevenly divided into 12 time periods. In addition, it is preferred to make the length of the division of the noon period and the evening period shorter, such as 11:00-11:30, 11:30-12:00, and 16:30-17:00, because the probability of users remotely monitoring the smart refrigerator during the above-mentioned rest periods is greater. Dividing the rest periods more densely can increase the frequency of monitoring the network status of the first Internet of Things network. By statistically calculating the number of historical remote operations in each of the above-mentioned groups, the statistical number of remote operations corresponding to each time period can be obtained.

[0033] At the same time, the statistically derived remote operation counts actually represent the equivalent value of the number of times a user remotely operated the smart refrigerator during the corresponding time period, i.e., an average or weighted average. To minimize the probability of misjudging the network status of the first IoT network, it is necessary to determine an appropriate minimum value. To this end, the present invention sorts the aforementioned remote operation counts by time period and then fits them into a smooth curve, thereby taking the minimum ordinate value of the curve within each time period as the minimum operation count. Obviously, the minimum operation count may or may not be the aforementioned remote operation counts, depending primarily on the curve trends constructed from the two remote operation counts for the preceding and subsequent time periods. Directly using the minimum value recorded in the historical remote operation counts for the corresponding time period as the minimum operation count would easily lead to overly strict determination of abnormal network status. However, the method for determining the minimum operation count described above in the present invention achieves a relatively reasonable level of strictness in determining abnormal network status.

[0034] In some embodiments, the statistical calculation of the historical remote operation times in each group to obtain the remote operation statistical times for each time period to which the corresponding date belongs includes: statistical calculation of the historical remote operation times in each group to obtain the first remote operation statistical times for each time period to which the corresponding date belongs, and the number of the user IoT terminal devices; determining an amplification coefficient based on the number, and using the amplification coefficient to adjust the first remote operation statistical times to obtain the second remote operation statistical times, that is, obtaining the remote operation statistical times.

[0035] In an embodiment of the present invention, in addition to counting the initial remote operation statistics for each time period to which the corresponding date belongs, the present invention also performs statistical analysis on the number of user IoT terminal devices involved in each initial remote operation statistics. A household may have more than one user IoT terminal device registered for remote monitoring operations on a smart refrigerator. The greater the number of user IoT terminal devices, the greater the probability that the smart refrigerator will receive more remote monitoring operations. The present invention determines a suitable amplification coefficient based on the above number, and uses it to appropriately increase the aforementioned initial remote operation statistics. In this way, a remote operation statistics with higher fault tolerance after intervention can be obtained, so that the determined minimum number of operations can be more consistent with the actual situation of a specific household. Obviously, the amplification coefficient is positively correlated with the number of user IoT terminal devices.

[0036] In some embodiments, the smart refrigerator sends a network request signal to the target IoT terminal device through the second IoT network, including: the smart refrigerator turns on the second IoT network to send a network request signal to the outside, and the network request signal includes the terminal device ID, the judgment information of the abnormal network status of the first IoT network and the network start request information; wherein, the terminal device ID is obtained based on the connection record information of the first IoT network.

[0037] In an embodiment of the present invention, upon determining that the network status of a first IoT network is abnormal, the smart refrigerator may activate a second IoT network by sending a network request signal to a designated terminal device. The network request signal includes the terminal device ID, information determining the network status of the first IoT network, and a network activation request. Upon receiving the network request signal, the designated terminal device analyzes and determines the signal according to predetermined rules. If it determines that activation conditions are met, it then sends back relevant signals to the smart refrigerator, such as the terminal device ID, information regarding consent to activate a third IoT network, the third IoT network's identification code, and a password for joining the third IoT network. The smart refrigerator then uses this information to log in to the third IoT network and maintain an online state.

[0038] Furthermore, if a network request signal is sent to an unintended terminal device, such as one in a neighboring home, the smart refrigerator's operating data or even control permissions may be lost, resulting in adverse consequences. Therefore, after logging into the first IoT network, the smart refrigerator in the present invention requests its connection history information, which contains the IDs of terminal devices that have previously connected to the first IoT network (e.g., within the past six months). These terminal device IDs belong to terminal devices in the same home. The smart refrigerator then sends a network request signal to these terminal devices, maintaining their online status through their networks, thereby avoiding the aforementioned risks.

[0039] The second IoT network refers to a short-range wireless network, such as a Bluetooth network, ZigBee network, or WiFi network. The smaller communication range of the second IoT network effectively reduces the probability of network request signals being sent to unintended terminal devices. Furthermore, designated terminal devices are typically equipped with Bluetooth, ZigBee, or WiFi modules, facilitating the implementation of the technical solution of the present invention. Furthermore, designated terminal devices can be configured to monitor signals at a preset frequency, enabling timely detection of network request signals.

[0040] In some embodiments, the target IoT terminal device turns on the third IoT network, including: the target IoT terminal device parses the judgment information of the abnormal network status of the first IoT network to obtain a judgment method for the abnormal network status; if the abnormal network status is determined based on the minimum number of operations, the target IoT terminal device switches its own network from the first IoT network to a fourth IoT network that belongs to the same network device as the first IoT network but has a different network frequency band, and then turns on the third IoT network; if the abnormal network status is directly determined based on the network operation parameters of the first IoT network, the target IoT terminal device first turns on the mobile communication network, and then turns on the third IoT network.

[0041] In an embodiment of the present invention, after receiving the network request signal, the target IoT terminal device parses the network request signal to derive a method for the smart refrigerator to determine the abnormal network status of the first IoT network, namely, the aforementioned determination based on the minimum number of operations or direct determination based on network operating parameters.

[0042] When the abnormal network status is determined based on the minimum number of operations, since the network anomaly is determined indirectly, the target IoT terminal device first switches its connected network to a fourth IoT network that is connected to the same network device as the first IoT network but has a different network frequency band. The first and fourth IoT networks can be different network frequency bands of a router, for example, the first IoT network is on the 2.4 GHz band and the fourth IoT network is on the 5 GHz band. Initially, both the target IoT terminal device and the smart refrigerator are connected to the 2.4 GHz band. When the smart refrigerator indirectly determines that a network anomaly exists in the 2.4 GHz band through the aforementioned method, the target IoT terminal device switches its own network from the 2.4 GHz band to the 5 GHz band and then activates the hotspot, i.e., the third IoT network, for the smart refrigerator to connect to. Of course, after switching to the 5 GHz network, the target IoT terminal device can also analyze and determine the network status of the 5 GHz network. If the 5 GHz network is also abnormal, it indicates a router malfunction. In this case, the target IoT terminal device then activates its own mobile communication network and the hotspot, i.e., the third IoT network, for the smart refrigerator to connect to.

[0043] When the abnormal network status is directly determined based on the network operating parameters of the first IoT network, since the network abnormality is directly determined, it can be basically determined that the router is faulty. At this time, the target IoT terminal device can directly turn on its own mobile communication network, and then turn on the network hotspot, that is, the third IoT network, for the smart refrigerator to connect to.

[0044] like Figure 2 As shown, an embodiment of the present invention also discloses an intelligent refrigerator control system based on Internet of Things technology, wherein the system includes a network module, a processing module, and a storage module, wherein the processing module is electrically connected to the network module and the storage module respectively; the network module is used to receive remote monitoring operations of a user Internet of Things terminal device; and, detect the operating parameters of a first Internet of Things network and transmit them to the processing module; and, according to the control instructions sent by the processing module, send a network request signal to a target Internet of Things terminal device through a second Internet of Things network and switch access to a third Internet of Things network; the storage module is used to store computer programs; the processing module is used to respond to receiving remote monitoring operations of a user Internet of Things terminal device; and retrieve and execute the computer program in the storage module to execute the method described in the aforementioned embodiment to evaluate and generate control instructions for controlling the network module according to the network status of the first Internet of Things network.

[0045] An embodiment of the present invention also discloses an electronic device, which is applied to a smart refrigerator, comprising: at least one processor, a memory, and a computer program stored in the memory and capable of running on the at least one processor, characterized in that: the processor executes the computer program to implement the method described in the aforementioned embodiment.

[0046] An embodiment of the present invention further discloses a computer storage medium, wherein the computer storage medium stores a computer program, and is characterized in that the computer program is executed by a processor to implement the method described in the above embodiment.

[0047] 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.

[0048] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0049] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0050] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The steps for the function specified in one or more boxes.

[0051] The above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention.

Claims

1. A smart refrigerator control method based on Internet of Things technology, characterized by: The method comprises the following steps: The smart refrigerator detects and evaluates the network status of the first IoT network, and when the network status of the first IoT network meets the connection conditions, maintains a login state with the first IoT network to accept remote monitoring by the user's IoT terminal device; When the network status of the first IoT network does not meet the connectivity condition, i.e., the network status is poor, the smart refrigerator sends a network borrowing request signal to the target IoT terminal device via the second IoT network; the network borrowing request signal is used to trigger the target IoT terminal device to open a third IoT network; wherein the third IoT network is a network independently equipped by the target IoT terminal device; The smart refrigerator logs into the third IoT network to accept remote monitoring by the user's IoT terminal device; The smart refrigerator detects and evaluates the network status of the first Internet of Things network, including: Acquire historical record information of remote monitoring of the smart refrigerator, and determine a minimum number of operations based on the historical record information; Obtain the number of remote operations of the user's IoT terminal device in the current time period; When the number of remote operations is less than the minimum number of operations, the network status of the first Internet of Things network is determined to be abnormal; the minimum number of operations and the number of remote operations both include viewing operations and control operations; The determining the minimum number of operations according to the historical record information includes: Divide the historical record information into several groups according to the date attribute and the time period attribute, perform statistical calculation on the number of historical remote operations in each group, and obtain the statistical number of remote operations in each time period to which the corresponding date belongs; Sorting the statistical times of the remote operations corresponding to the date in order of time periods, and performing curve fitting and smoothing on the sorted data to obtain a statistical curve of the remote operations corresponding to the date; Dividing the remote operation statistical curve into segments according to the time periods, and determining the minimum value of the vertical coordinate in each segmented curve as the minimum number of operations in each time period to which the corresponding date belongs; The statistical calculation of the number of historical remote operations in each group to obtain the statistical number of remote operations in each time period to which the corresponding date belongs includes: Statistically calculating the number of historical remote operations in each group to obtain the first remote operation statistics for each time period to which the corresponding date belongs, and the number of the user's IoT terminal devices; An amplification coefficient is determined according to the number, and the first remote operation statistical number is adjusted using the amplification coefficient to obtain a second remote operation statistical number, that is, the remote operation statistical number is obtained.

2. The method for controlling a smart refrigerator based on Internet of Things technology according to claim 1, characterized in that: The smart refrigerator sends a network borrowing request signal to a target IoT terminal device through a second IoT network, including: The smart refrigerator activates the second IoT network to send a network borrowing request signal, wherein the network borrowing request signal includes a terminal device ID, information on the abnormal network status of the first IoT network, and network activation request information. Among them, the terminal device ID is obtained based on the connection record information of the first Internet of Things network.

3. The method for controlling a smart refrigerator based on Internet of Things technology according to claim 2, wherein: The target IoT terminal device starts the third IoT network, including: The target IoT terminal device parses the abnormal network status judgment information of the first IoT network to derive a judgment method for the abnormal network status; If the abnormal network state is determined based on the minimum number of operations, the target IoT terminal device switches its own network from the first IoT network to a fourth IoT network that belongs to the same network device as the first IoT network but has a different network frequency band, and then activates the third IoT network; If the abnormal network state is directly determined based on the network operation parameters of the first Internet of Things network, the target Internet of Things terminal device first turns on the mobile communication network and then turns on the third Internet of Things network.

4. A smart refrigerator control system based on Internet of Things technology, the system comprising a network module, a processing module, and a storage module, wherein the processing module is electrically connected to the network module and the storage module respectively; The network module is configured to receive remote monitoring operations from a user's IoT terminal device; detect operating parameters of the first IoT network and transmit them to the processing module; and, based on control instructions sent by the processing module, send a network borrowing request signal to a target IoT terminal device via the second IoT network and switch access to the third IoT network. The storage module is used to store computer programs; Its characteristics are: The processing module is used to respond to receiving remote monitoring operations of the user's Internet of Things terminal device; and to call and execute the computer program in the storage module to perform the method described in any one of claims 1-3 to evaluate and generate control instructions for controlling the network module based on the network status of the first Internet of Things network.

5. An electronic device, used in a smart refrigerator, 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 3.

6. A computer storage medium storing a computer program, wherein: The computer program is executed by a processor to implement the method according to any one of claims 1 to 3.

7. A computer program product comprising a computer program stored on a non-transitory computer-readable medium, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 3 is implemented.

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