Field electric appliance monitoring system combined with sound detection, field electric appliance monitoring method and socket device

Abstract

A field electric appliance monitoring system combined with sound detection is suitable for monitoring electric appliances in a field and comprises a socket device and a cloud management server to execute a field electric appliance monitoring method. The socket device generates sound characteristic data according to the sound detection data, and transmits generated event data to the cloud management server according to the current characteristic data, the current detection data and the sound characteristic data. The cloud management server determines whether the event data matches at least one of a plurality of behavior features by using a behavior feature identification model. When it is determined that the event data does not match the behavior characteristics, a warning message is transmitted to at least one user-side electronic device. Therefore, the living condition of the user can be estimated by monitoring the use condition of the electric appliance.

Description

Technical Field

[0001] The present invention relates to a monitoring system and a monitoring method, and in particular to a field electrical appliance monitoring system and a field electrical appliance monitoring method based on electrical appliance usage and combined with sound detection. Background Art

[0002] For the elderly who are in good health, have the ability to take care of themselves and attach great importance to maintaining their personal privacy, they often choose to live by themselves. However, people's memory, perception and motor ability will gradually decline with age, which increases the probability of accidents happening to the elderly living alone at home (such as falls, electrical equipment not properly turned off after use, etc.). Moreover, due to living alone, after an accident, it is usually impossible for relevant people (such as relatives, friends, and staff of care institutions) to be informed immediately and provide care and follow-up assistance and treatment.

[0003] Therefore, how to develop a system to effectively estimate the user's daily life by monitoring the use of electrical appliances has become an issue that the relevant industry players want to solve. Summary of the invention

[0004] The object of the present invention is to provide a field appliance monitoring system that can estimate the user's daily living conditions by monitoring the use of appliances and combining sound detection.

[0005] Therefore, the field electrical appliance monitoring system combined with sound detection of the present invention is suitable for monitoring electrical equipment used in the field, and includes a socket device and a cloud management server.

[0006] The socket device includes a socket module, a storage module, a current detection module, a sound receiving module, and a socket processing module. The socket module is used to electrically connect the electrical device and is operable to allow power to be supplied to the electrical device or to interrupt the supply of the power. The storage module stores current characteristic data. The current characteristic data is related to multiple reference working currents of the electrical device in different operation modes. The current detection module is electrically connected to the socket module and is used to detect the current flowing through the electrical device and generate current detection data. The sound receiving module is used to detect the sound of the field and generate sound detection data. The socket processing module is electrically connected to the socket module, the storage module, the current detection module and the sound receiving module. The socket processing module generates sound characteristic data according to the sound detection data, and generates event data about the use of the electrical device according to the current characteristic data, the current detection data and the sound characteristic data.

[0007] The cloud management server includes a database, a storage unit, and a processing unit. The database stores user data of at least one user in the field, and device data and historical usage data of the electrical device. The storage unit stores a behavior feature recognition model for identifying multiple behavior features of the at least one user in the use behavior of the electrical device. The behavior feature recognition model is established based on multiple feature parameters associated with the at least one user, the electrical device, and the environment in which the electrical device is located, and uses a machine learning algorithm to analyze the user data and the historical usage data to summarize the behavior features.

[0008] The processing unit is connected to the socket processing module via communication, and is electrically connected to the database and the storage unit. The socket processing module transmits the event data to the processing unit, and the processing unit uses the behavior feature recognition model to determine whether the received event data matches at least one of the behavior features. When it is determined that the event data does not match the behavior features, a warning message is transmitted to at least one user-end electronic device related to the at least one user.

[0009] In some implementations, the processing unit also stores the event data received each time in the database, and incorporates the event data into the historical usage data. The processing unit also determines whether the reference operating current of the electrical device needs to be adjusted based on the event data and the device data. When the processing unit determines that at least one of the reference operating currents needs to be adjusted, it generates corresponding adjusted current characteristic data, and transmits and updates the adjusted current characteristic data to the current characteristic data stored in the storage module of the socket device.

[0010] In some implementations, the storage module of the socket device further stores an event recognition model for identifying a plurality of sound features, wherein the event recognition model is established based on a plurality of sound parameters associated with the environment in which the socket device is located and by analyzing the sound detection data using the machine learning algorithm or another machine learning algorithm to summarize the sound features. The socket processing module uses the event recognition model to determine which of the sound features the sound detection data detected by the sound receiving module matches, thereby becoming the sound feature data.

[0011] In some implementations, the socket device further includes an output module electrically connected to the socket processing module. The socket processing module of the socket device further determines whether the electrical device is operating in a normal state or an abnormal state based on the current characteristic data, the current detection data, and the sound characteristic data, and when it is determined that the electrical device is operating in the abnormal state, the output module generates a warning output for indicating the abnormal state, or the socket module interrupts the power supply to the electrical device.

[0012] The present invention combines a field electrical appliance monitoring method with sound detection, and is implemented through a field electrical appliance monitoring system. The field electrical appliance monitoring system is suitable for monitoring electrical equipment located in a field, and includes a socket device and a cloud management server. The socket device stores current characteristic data. The current characteristic data is related to multiple reference working currents of the electrical equipment in different operating modes. The cloud management server stores user data of at least one user of the field, device data and historical usage data of the electrical equipment, and a behavior characteristic recognition model for identifying multiple behavior characteristics of at least one user of the field in the use behavior of the electrical equipment.

[0013] The field electrical appliance monitoring method includes: the cloud management server analyzes the user data and the historical usage data according to a plurality of characteristic parameters associated with the at least one user, the electrical device, and the environment in which the electrical device is located and uses a machine learning algorithm to summarize a plurality of behavioral characteristics of the field on the use behavior of the electrical device, and establishes a behavioral characteristic recognition model for identifying the behavioral characteristics. The socket device continuously detects the current flowing through the electrical device to generate current detection data, and detects the sound of the field to generate sound detection data; the socket device generates sound characteristic data according to the sound detection data, and generates event data related to the use of the electrical device according to the current characteristic data, the current detection data, and the sound characteristic data; the cloud management server receives the event data from the socket device, and uses the behavioral characteristic recognition model to determine whether the received event data matches at least one of the behavioral characteristics; and when it is determined that the event data and the behavioral characteristics do not match, a warning message is sent to at least one user-end electronic device related to the at least one user.

[0014] In some implementations, the field appliance monitoring method further includes: each time the cloud management server receives the event data from the socket device, it stores the event data and incorporates the event data into the historical usage data; the cloud management server determines whether the reference working current of the electrical device needs to be adjusted based on the event data and the device data; when the cloud management server determines that at least one of the reference working currents needs to be adjusted, it generates corresponding adjusted current characteristic data and transmits the adjusted current characteristic data to the socket device; and when the socket device receives the adjusted current characteristic data from the cloud management server, it updates the current characteristic data with the adjusted current characteristic data.

[0015] In some embodiments, the field appliance monitoring method further includes: the socket device also stores an event recognition model for identifying multiple sound features, the event recognition model is established based on multiple sound parameters associated with the environment in which the socket device is located and uses the machine learning algorithm or another machine learning algorithm to analyze the sound detection data to summarize the sound features, and the socket device uses the event recognition model to determine which of the sound features the detected sound detection data matches to become the sound feature data.

[0016] In some implementations, the field appliance monitoring method further includes: the socket device also determines whether the electrical equipment is operating in a normal state or an abnormal state based on the current characteristic data, the current detection data and the sound characteristic data; when it is determined that the electrical equipment is operating in the abnormal state, the socket device generates a warning output to indicate the abnormal state, or interrupts the power supply to the electrical equipment.

[0017] The socket device of the present invention is suitable for a field electrical appliance monitoring system, which is suitable for monitoring electrical equipment located in a field and includes a cloud management server. The socket device includes: a socket module, which is used to electrically connect the electrical equipment and can be operated to allow power to be supplied to the electrical equipment or to interrupt the supply of the power; a storage module, which stores current characteristic data, and the current characteristic data is related to multiple reference working currents of the electrical equipment in different operating modes; a current detection module, which is electrically connected to the socket module and is used to continuously detect the current flowing through the electrical equipment and generate current detection data; a sound receiving module, which is used to detect sound located in the field and generate sound detection data; and a socket processing module, which is electrically connected to the socket module, the storage module, the current detection module and the sound receiving module, the socket processing module generates sound characteristic data according to the sound detection data, and generates event data according to the current characteristic data, the current detection data and the sound characteristic data, and transmits the event data to the cloud management server.

[0018] The beneficial effect of the present invention is that: the socket device continuously sends the event data about the usage of the electrical equipment and the characteristics of the surrounding audio to the cloud management server, and the cloud management server uses the behavior feature recognition model to determine whether the received event data matches at least one of the behavior features to infer whether the user's usage behavior of the electrical equipment in the field (such as a household) is normal, that is, to estimate the user's daily life, and achieve the purpose of household monitoring while taking into account the user's privacy. Furthermore, the processing unit incorporates the event data into the historical usage data, so that the processing unit can update the behavior feature recognition model, and then the processing unit can use the behavior feature recognition model to determine whether the received event data matches at least one of the behavior features more accurately. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 is a block diagram of an embodiment of a field electrical appliance monitoring system combined with sound detection of the present invention;

[0020] Figure 2 It is a flow chart of an embodiment of the field electrical appliance monitoring method combined with sound detection of the present invention. DETAILED DESCRIPTION

[0021] Before the present invention is described in detail, it should be noted that, if not specifically defined, the "electrical connection" described in this patent specification generally refers to the "wired electrical connection" achieved by connecting multiple electronic devices / devices / components to each other through conductive materials, and the "radio connection" for single / bidirectional wireless signal transmission through wireless communication technology. In addition, if not specifically defined, the "electrical connection" described in this patent specification also generally refers to the "direct electrical connection" formed by directly connecting multiple electronic devices / devices / components to each other, and the "indirect electrical connection" formed by indirectly connecting multiple electronic devices / devices / components to each other through other electronic devices / devices / components.

[0022] The present invention is described in detail below with reference to the accompanying drawings and embodiments.

[0023] See also Figure 1 An embodiment of the field appliance monitoring system 100 combined with sound detection of the present invention is suitable for monitoring at least one electrical device 200 used in a field, and includes at least one socket device 1 and a cloud management server 2. That is, the at least one electrical device 200 and the at least one socket device 1 are used in a one-to-one configuration. The field is, for example, a household.

[0024] Each of the socket devices 1 includes a socket module 11, a storage module 12, a current detection module 13, a sound receiving module 14, an output module 15 and a socket processing module 16. The components of the socket device 1 will be described in further detail below.

[0025] The socket module 11 is used to electrically connect the electrical device 200, and can be operated to allow a power supply to the electrical device 200 or interrupt the supply of the power supply. Specifically, the socket device 1 is used to electrically connect the corresponding electrical device 200 (for example, a refrigerator, an electric cooker). The socket module 11 can be designed to have a pin portion (not shown) that can be plugged into a socket (i.e., an existing socket in the field) that is connected to a power grid (not shown in the figure), and a slot portion (not shown) that allows the wire plug of the electrical device 200 to be inserted. In this way, the socket module 11 obtains the power supply through the existing socket in the field and the power grid, but is not limited to this example. However, if the socket module 11 is directly electrically connected to the power grid, the above-mentioned pin portion can be omitted. The socket module 11 can be operated to allow the power supply to the electrical device 200, or interrupt the supply of the power supply, for example, by manually inserting the wire plug into the socket module 11 to make the current conduct or pulling the wire plug out of the socket module 11 to make the current non-conducting. Alternatively, the socket module 11 may include a controlled switch component (not shown) so as to be operable in a normal conducting state or a non-conducting state.

[0026] The current detection module 13 is electrically connected to the socket module 11 and is used to continuously detect the current flowing through the electrical device 200 and generate a current detection data. The sound receiving module 14 is used to detect the sound of the field and generate a sound detection data. The output module 15 is used to generate an output that can be perceived visually or auditorily, and the output module 15 can be, for example, an LED module and / or a buzzer (not shown), but is not limited to the examples shown here.

[0027] The storage module 12 stores a current characteristic data, which is related to a plurality of reference operating currents of the electrical device 200 in different operating modes. In the present embodiment, the storage module 12 also stores a household identification code corresponding to the household and having a uniqueness. It should be particularly noted that the household identification code and the current characteristic data are obtained by inputting registration and downloading a software application program related to the socket device 1 when the household first uses it, and may include the category and model of the electrical device 200, the reference operating current (or reference current threshold) corresponding to each operating mode, the reference operating current range, etc. For example, if the electrical device 200 is a refrigerator, the reference operating current of the general power saving mode is about 30mA, the reference operating current of the operating mode when the refrigerator door is opened is about 130mA, and the reference operating current of the operating mode when the compressor is running is about 1500mA, so the corresponding reference operating current range is, for example, 30 to 1500mA.

[0028] The storage module 12 also stores an event recognition model for identifying multiple sound features. The event recognition model is established based on multiple sound parameters associated with the environment in which the socket device 1 is located and using a machine learning algorithm (such as a neural network regression algorithm, but not limited to this) to analyze the sound detection data to summarize the sound features. More specifically, the sound detection data generated by the sound receiving module 14 includes a sound wave voltage signal and a corresponding occurrence time. The sound features include the occurrence time, a duration, a volume, and a corresponding event. In addition, it should be specifically noted that the cloud management server 2 can transmit at least one model parameter to the socket processing module 16 via a communication connection, so that the socket processing module 16 can train or fine-tune the event recognition model through the at least one model parameter and update the event recognition model.

[0029] The socket processing module 16 is electrically connected to the socket module 11, the storage module 12, the current detection module 13, the sound receiving module 14 and the output module 15. The function and operation of the socket processing module 16 will be described in detail in the following paragraphs.

[0030] The cloud management server 2 includes a database 21, a storage unit 22, and a processing unit 23 electrically connected to the storage unit 22 and the database 21 and connected to the socket processing module 16 via communication. For example, the cloud management server 2 can be implemented as a single computer or a computer system composed of multiple computer hosts.

[0031] The database 21 stores a device data and a historical usage data about each of the electrical devices 200, and user data about one or more users in the field (such as the household). For example, for each of the electrical devices 200, the device data may include data such as the electrical category, model, reference operating current range corresponding to different operating modes (especially, the reference operating current range of the same electrical category and model collected in large quantities), and the historical usage data may include relevant data such as each use of the device every day during a predetermined historical period (for example: sound characteristics corresponding to the ambient sound, usage time, operating mode and duration, daily cumulative usage time, etc.); the user data may include data such as the gender and age of the at least one user, the geographical area and / or location of the household, the household identification code, and one or more user-end electronic devices 300 ( Figure 1 Only one piece of communication data (eg, mobile phone numbers of relatives, friends, emergency contacts, or staff of a care institution of the at least one user) is depicted.

[0032] The storage unit 22 stores a behavior feature recognition model for identifying multiple behavior features of the at least one user in the field in the use behavior of the at least one electrical device 200. In the present embodiment, for each of the electrical devices 200, the behavior feature recognition model is established by the processing unit 23 according to multiple characteristic parameters associated with the at least one user, the electrical device 200 and the environment in which the electrical device 200 is located (for example, the age and gender of each user, the geographical area where the household is located, the type and characteristics of the electrical device 200, the use time of the electrical device 200, the use duration of the electrical device 200, the cumulative use time of the electrical device 200 on the day, the sound characteristics of the environment, etc.) and using a machine learning calculation method (for example, a neural network regression algorithm, but not limited thereto) to analyze the user data and the historical usage data to summarize the behavior features. The storage unit 22 and / or the storage module 12 can be implemented using a non-volatile storage medium such as a hard disk, a flash memory, etc.

[0033] The socket processing module 16 and / or the processing unit 23 may include (but not limited to) at least one of a multi-core processor, a dual-core mobile phone processor, a microprocessor, a microcontroller, a digital signal processor (DSP), a field programmable gate array (FPGA), an application specific integrated circuit (ASIC) and a radio frequency integrated circuit (RFIC).

[0034] See also Figure 2 , an embodiment of a field electrical appliance monitoring method executed by the field electrical appliance monitoring system 100 of the present invention is described below.

[0035] First, in step S01, the current detection module 13 continuously detects the current flowing through the electrical device 200 to generate the current detection data, and transmits the current detection data to the socket processing module 16. At the same time, the sound receiving module 14 continuously receives the sound in the field to generate the sound detection data, and transmits the sound detection data to the socket processing module 16. The socket processing module 16 also generates a sound feature data according to the sound detection data. In this embodiment, the socket processing module 16 uses the event recognition model to determine which of the sound features the sound detection data detected by the sound receiving module 14 matches, and becomes the sound feature data. That is to say, the socket processing module 16 uses the event recognition model to determine whether there is at least one repeated and identical or similar (i.e., a predetermined degree of identity) sound in the sound detection data and matches the at least one sound feature. For example, at 3 pm (i.e., the occurrence time), water comes out of the thermos (i.e., the corresponding event) for 15 seconds (i.e., the duration) and the volume is 50 decibels (i.e., the sound size).

[0036] Next, as shown in step S02, the socket processing module 16 generates an event data about the electrical device 200 and corresponding to the usage status in each specific time period according to the current characteristic data and the current detection data and the sound characteristic data, for example, in each specific time period (which can be determined or changed according to actual conditions). In other words, the event data can be continuously generated in each specific time period. The event data can include, for example, the household identification code, the type and model of the electrical device 200, the start time, operating current and duration of each operating mode, and the sound characteristic data corresponding to the sound of the field detected by the sound receiving module 14, etc., but is not limited to this example.

[0037] Next, as shown in step S03 , the socket processing module 16 transmits the event data to the processing unit 23 via the communication network.

[0038] Next, as shown in step S04, the processing unit 23 uses the behavior feature recognition model to determine whether the received event data matches at least one of the behavior features. If the determination is no, step S05 is executed, and if the determination is yes, the process ends.

[0039] In this embodiment, the processing unit 23 also stores the event data received each time in the database 21, and incorporates the event data into the historical usage data (corresponding to the electrical device 200). In this way, the processing unit 23 can analyze the historical usage data incorporated into the event data to summarize the behavior characteristics that may be the same or different from the previous ones, so that when the at least one user's usage behavior of the electrical device 200 changes, the processing unit 23 can update the behavior characteristic recognition model in a preset period (for example, a few days or weeks), so that the processing unit 23 can use the behavior characteristic recognition model to determine whether the received event data matches at least one of the behavior characteristics more accurately.

[0040] Step S05 is when the processing unit 23 determines that the received event data does not match any of the behavior characteristics using the behavior characteristic recognition model, the processing unit 23 sends a warning message to the at least one user-end electronic device 300 related to the at least one user. The process ends. That is to say, when the processing unit 23 determines that the received event data does not match any of the behavior characteristics using the behavior characteristic recognition model, it can be inferred that the at least one user of the household has abnormal behavior in the use behavior of the electrical device 200 that does not conform to the behavior characteristics. For example, for the electrical device 200 is a refrigerator, if the event data on the same day indicates that the freezer door and the refrigerator door of the refrigerator are not opened, the event data will be determined to not match any of the behavior characteristics, that is, it is inferred that the use behavior of the refrigerator has abnormal behavior that does not conform to the behavior characteristics. As another example, if the electrical device 200 is an electric water bottle, if the event data on the same day indicates that the electric water bottle has not been pressed to release water, the event data will be determined to not match any of the behavioral characteristics, that is, it is estimated that the use behavior of the electric water bottle has abnormal behavior that does not conform to the behavioral characteristics. It should be noted that the electric water bottle needs to be kept warm for a long time, so the current value will often continue to maintain a high current state. It is difficult to judge the indicated use behavior only by the change in the current value when pressing to release water, so the water sound (that is, the sound characteristic data) is used to assist in judging the indicated use behavior. When the use behavior of the electrical device 200 is estimated to be abnormal behavior, the processing unit 23 will transmit the warning message to the at least one user-end electronic device 300 related to the at least one user to remind the relatives and friends of the household, emergency contacts or staff of the care and care agency of this abnormal situation, so as to carry out subsequent related processing.

[0041] It should be supplemented that, when the processing unit 23 uses the behavior feature recognition model to determine that the received event data matches at least one of the behavior features, this situation can be inferred that the at least one user of the household has shown normal behavior in using the electrical device 200 that conforms to at least one of the behavior features. At this time, the processing unit 23 will not send any message to the at least one user-end electronic device 300 related to the at least one user.

[0042] Incidentally, in this embodiment, the socket processing module 16 of the socket device 1 also determines whether the electrical device 200 is operating in a normal state or an abnormal state according to the current characteristic data, the current detection data and the sound characteristic data. When it is determined that the electrical device 200 is operating in the abnormal state, the output module 15 generates a warning output for indicating the abnormal state (for example, the LED flashes as a warning or a buzzer sounds), or the socket module 11 interrupts the power supply to the electrical device 200. That is, if the socket processing module 16 determines that the operating current included in the current detection data exceeds the reference operating current range included in the current characteristic data, the socket processing module 16 will determine the operation of the electrical device 200 as the abnormal state related to overcurrent, or if the socket processing module 16 determines that the corresponding event of the sound characteristic data is one of a plurality of preset events, and the volume is greater than a preset threshold corresponding to one of them, and the duration is greater than another preset threshold corresponding to one of them, the preset events include, for example, refrigerators, thermos bottles, air conditioning equipment, computer hosts, etc. For example, if the electrical device 200 is a refrigerator, if an abnormal sound occurs when the compressor is running, it means that it may be in a fault or the equipment itself is not running in a normal state, but its own operating current may not exceed the reference operating current range. In this way, it can be more accurately determined whether the equipment needs to be repaired. It should be noted that the difference between this function and step S05 is that step S05 uses the behavior feature recognition model to determine whether the received event data matches at least one of the behavior features, and is used to determine whether the usage behavior within each specific time period is abnormal, and to estimate the living conditions of the at least one user in the corresponding household; while this function is that the socket processing module 16 determines whether the electrical device 200 has the abnormal state during operation, such as abnormal current (such as overcurrent) or abnormal sound (such as making an abnormal sound).

[0043] In summary, each socket device 1 continuously sends event data about the usage of the electrical device 200 to the cloud management server 2, and the cloud management server 2 uses the behavior feature recognition model to determine whether the received event data matches at least one of the behavior features to infer whether the user in the household in the field is normal in using the electrical device 200, that is, to infer the user's daily life, and achieve the purpose of household monitoring while taking into account the user's privacy. Furthermore, the processing unit 23 incorporates the event data into the historical usage data, so that the processing unit 23 can update the behavior feature recognition model at the preset period, so that the processing unit 23 can use the behavior feature recognition model to determine whether the received event data matches at least one of the behavior features more accurately, so the purpose of the present invention can be achieved.

Claims

1. A field electrical appliance monitoring system combined with sound detection, suitable for monitoring electrical equipment used in a field; characterized by: The field electrical appliance monitoring system combined with sound detection comprises: Socket device, including a socket module for electrically connecting the electrical device and operable to allow power to be supplied to the electrical device or to interrupt the supply of power, A storage module stores current characteristic data, wherein the current characteristic data is related to a plurality of reference working currents of the electrical device in different operation modes, A current detection module is electrically connected to the socket module and is used to continuously detect the current flowing through the electrical device and generate current detection data. a sound receiving module, used to detect the sound in the field and generate sound detection data, and a socket processing module, electrically connected to the socket module, the storage module, the current detection module and the sound receiving module, wherein the socket processing module generates sound characteristic data according to the sound detection data, and generates event data related to the use of the electrical device according to the current characteristic data, the current detection data and the sound characteristic data; and Cloud management server, including a database storing user data of at least one user of the field, and device data and historical usage data of the electrical device; A storage unit storing a behavior feature recognition model for identifying a plurality of behavior features of the at least one user in the use behavior of the electrical device, wherein the behavior feature recognition model is established based on a plurality of characteristic parameters associated with the at least one user, the electrical device, and the environment in which the electrical device is located and using a machine learning algorithm to analyze the user data and the historical usage data to summarize the behavior features; The processing unit is connected to the socket processing module via communication and is electrically connected to the database and the storage unit. The socket processing module transmits the event data to the processing unit. The processing unit uses the behavior feature recognition model to determine whether the received event data matches at least one of the behavior features. When it is determined that the event data does not match the behavior features, a warning message is sent to at least one user-end electronic device related to the at least one user.

2. The field electrical appliance monitoring system combined with sound detection according to claim 1, characterized in that: The processing unit also additionally stores the event data received each time in the database and incorporates the event data into the historical usage data; The processing unit further determines whether the reference working current of the electrical device needs to be adjusted according to the event data and the device data; When the processing unit determines that at least one of the reference working currents needs to be adjusted, the processing unit generates corresponding adjusted current characteristic data, and transmits and updates the adjusted current characteristic data to the current characteristic data stored in the storage module of the socket device.

3. The field electrical appliance monitoring system combined with sound detection according to claim 1, characterized in that: The storage module of the socket device also stores an event recognition model for identifying multiple sound features. The event recognition model is established based on multiple sound parameters associated with the environment in which the socket device is located and uses the machine learning algorithm or another machine learning algorithm to analyze the sound detection data to summarize the sound features. The socket processing module uses the event recognition model to determine which of the sound features the sound detection data detected by the sound receiving module matches to become the sound feature data.

4. The field electrical appliance monitoring system combined with sound detection according to claim 1, characterized in that: The socket device also includes an output module electrically connected to the socket processing module; The socket processing module of the socket device also determines whether the electrical device is operating in a normal state or an abnormal state based on the current characteristic data, the current detection data and the sound characteristic data. When it is determined that the electrical device is operating in the abnormal state, the output module generates a warning output to indicate the abnormal state, or the socket module interrupts the power supply to the electrical device.

5. A method for monitoring field electrical appliances in combination with sound detection, implemented by a field electrical appliance monitoring system, the field electrical appliance monitoring system being suitable for monitoring electrical appliances located in a field, and comprising a socket device and a cloud management server, the socket device storing current characteristic data, the current characteristic data relating to a plurality of reference operating currents of the electrical appliance in different operating modes, the cloud management server storing user data of at least one user of the field, device data and historical usage data of the electrical appliance, and a behavior characteristic recognition model for identifying a plurality of behavior characteristics of the at least one user of the field in the use behavior of the electrical appliance, characterized in that: The field electrical appliance monitoring method combined with sound detection comprises: The cloud management server analyzes the user data and the historical usage data according to a plurality of characteristic parameters associated with the at least one user, the electrical device, and the environment in which the electrical device is located, and uses a machine learning algorithm to summarize a plurality of behavioral characteristics of the field on the usage behavior of the electrical device, and establishes a behavioral characteristic recognition model for identifying the behavioral characteristics; The socket device continuously detects the current flowing through the electrical device to generate current detection data, and detects the sound in the field to generate sound detection data; The socket device generates sound characteristic data according to the sound detection data, and generates event data related to the usage of the electrical device according to the current characteristic data, the current detection data and the sound characteristic data; The cloud management server receives the event data from the socket device and uses the behavior feature recognition model to determine whether the received event data matches at least one of the behavior features; and When it is determined that the event data and the behavior characteristics do not match, a warning message is sent to at least one user-end electronic device related to the at least one user.

6. The field electrical appliance monitoring method combined with sound detection according to claim 5, characterized in that: The field electrical appliance monitoring method combined with sound detection further comprises: The cloud management server stores the event data and incorporates the event data into the historical usage data each time the event data is received from the socket device; The cloud management server determines whether the reference working current of the electrical device needs to be adjusted according to the event data and the device data; When the cloud management server determines that at least one of the reference working currents needs to be adjusted, it generates corresponding adjusted current characteristic data and transmits the adjusted current characteristic data to the socket device; and When the socket device receives the adjusted current characteristic data from the cloud management server, it updates the current characteristic data with the adjusted current characteristic data.

7. The field electrical appliance monitoring method combined with sound detection according to claim 5, characterized in that: The field electrical appliance monitoring method combined with sound detection further comprises: The socket device also stores an event recognition model for identifying multiple sound features. The event recognition model is established based on multiple sound parameters associated with the environment in which the socket device is located and uses the machine learning algorithm or another machine learning algorithm to analyze the sound detection data to summarize the sound features. The socket device uses the event recognition model to determine which of the sound features the detected sound detection data matches and becomes the sound feature data.

8. The field electrical appliance monitoring method combined with sound detection according to claim 5, characterized in that: The field electrical appliance monitoring method combined with sound detection further comprises: The socket device also determines whether the electrical device is operating in a normal state or an abnormal state based on the current characteristic data, the current detection data and the sound characteristic data. When it is determined that the electrical device is operating in the abnormal state, the socket device generates a warning output to indicate the abnormal state, or interrupts the power supply to the electrical device.

9. A socket device, suitable for a field electrical appliance monitoring system, wherein the field electrical appliance monitoring system is suitable for monitoring electrical equipment located in a field and includes a cloud management server, characterized in that: The socket device comprises: A socket module, used for electrically connecting the electrical device and operable to allow power to be supplied to the electrical device or to interrupt the supply of power; A storage module storing current characteristic data, wherein the current characteristic data is related to a plurality of reference operating currents of the electrical device in different operation modes; A current detection module, electrically connected to the socket module and used to continuously detect the current flowing through the electrical device and generate current detection data; A sound receiving module, used to detect the sound in the field and generate sound detection data; and The socket processing module is electrically connected to the socket module, the storage module, the current detection module and the sound receiving module. The socket processing module generates sound characteristic data according to the sound detection data, and generates event data according to the current characteristic data, the current detection data and the sound characteristic data, and transmits the event data to the cloud management server.

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