Internet of Things equipment and intelligent home system

Abstract

The invention discloses Internet of Things equipment and a smart home system. The Internet of Things equipment comprises a main control chip; the communication module is coupled to the main control chip, a processor core is arranged in the communication module, the communication module is used for receiving the data sent by the main control chip and carrying out logic data processing on the data, and the logic data processing at least comprises packet loss retransmission and / or flow control. In this way, the requirement for the hardware specification of the main control chip can be lowered.

Description

Technical Field

[0001] The present application relates to the technical field of Internet of Things, and in particular to Internet of Things devices and smart home systems. Background Art

[0002] In the current IoT device architecture, the interaction mode between the communication module and the main control chip is relatively traditional. Usually, the main control chip, as the core processor, controls the operation rhythm of the entire system. When it comes to network connection requirements, the communication module starts the initialization process under the instructions of the main control chip.

[0003] The current technology has the following shortcomings: on the one hand, it has high performance requirements for the main control chip and high hardware costs; on the other hand, it has limited scalability. Summary of the invention

[0004] The Internet of Things device and smart home system provided by this application can reduce the requirements for the hardware specifications of the main control chip.

[0005] In a first aspect, the present application provides an Internet of Things device, which includes: a main control chip; a communication module, coupled to the main control chip, wherein a processor core is provided in the communication module for receiving data sent by the main control chip and performing logical data processing on the data, wherein the logical data processing includes at least packet loss retransmission and / or flow control.

[0006] A further technical solution is that the processor core in the communication module is also used to enter a standby mode when no data transmission is detected.

[0007] A further technical solution is that the processor core in the communication module is also used to reduce the data transmission rate when it is detected that the load is greater than a threshold.

[0008] A further technical solution is that the processor core in the communication module is also used to adjust the queue order according to the priority of the data packet, wherein the queue order is arranged in descending order of priority.

[0009] A further technical solution is that a hardware encryption engine is provided in the communication module for encrypting and decrypting the transmitted data in real time.

[0010] A further technical solution is that the processor core in the communication module is also used to restart the hardware corresponding to the fault when a hardware fault in the communication module is detected.

[0011] Its further technical solution is that the IoT device also includes a cloud server, which is connected to the communication module; wherein the communication module interacts with the cloud server, regularly checks firmware update information, and when a new version of the firmware is detected, the firmware is updated through dual backup partition technology.

[0012] Its further technical solution is that the Internet of Things device also includes a cloud server, which is connected to the communication module; wherein the communication module is used to receive a first control instruction sent by the cloud server, and when it is detected that the first control instruction is reasonable, the first control instruction is sent to the main control chip, so that the main control chip directly executes the first control instruction.

[0013] Its further technical solution is that after the main control chip executes the first control instruction, it collects current data and sends the current data to the communication module; the communication module encrypts and packages the current data and sends it to the cloud server.

[0014] In a second aspect, the present application provides a smart home system, which includes the Internet of Things device provided in the first aspect.

[0015] The beneficial effect of the present application is as follows: different from the prior art, the IoT device and smart home system provided by the present application, the communication module can have some functions of the main control chip, and thus some logic data processing of the main control chip can be deployed in the communication module for implementation, which is equivalent to the IoT device having two main control chips, thereby effectively releasing the logic data processing pressure of the main control chip, and reducing the requirements for the hardware specifications of the main control chip, that is, the IoT device can use a main control chip with low logic data processing capability in conjunction with a communication module with a processor core to realize all functions of the IoT device, which can effectively reduce the hardware cost of the main control chip. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0017] Figure 1 It is a structural diagram of an embodiment of an Internet of Things device provided by the present application;

[0018] Figure 2 It is a structural schematic diagram of another embodiment of the Internet of Things device provided by the present application;

[0019] Figure 3 It is a structural diagram of an embodiment of a smart home system provided by the present application;

[0020] Figure 4 It is a flow chart of an embodiment of a control method for a clothes drying device provided by the present application;

[0021] Figure 5 is a flow chart of an embodiment after step 43;

[0022] Figure 6 is a flow chart of another embodiment of the control method for clothes drying equipment provided by the present application;

[0023] Figure 7 is a flow chart of an embodiment after step 63;

[0024] Figure 8 is a flow chart of another embodiment of the control method for clothes drying equipment provided by the present application;

[0025] Fig. 9 It is a structural diagram of an embodiment of a cloud server provided by the present application;

[0026] Fig.10 is a flow chart of another embodiment of the control method for clothes drying equipment provided by the present application;

[0027] Fig.11 It is a structural schematic diagram of an embodiment of the clothes drying equipment provided in the present application. DETAILED DESCRIPTION

[0028] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. It will be understood that the specific embodiments described herein are only used to explain the present application, rather than to limit the present application. It should also be noted that, for ease of description, only some but not all structures related to the present application are shown in the drawings. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present application.

[0029] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0030] In the current IoT device architecture, the interaction mode between the communication module and the main control chip is relatively traditional. Usually, the main control chip, as the core processor, controls the operation rhythm of the entire system. When it comes to network connection requirements, the communication module starts the initialization process under the instructions of the main control chip.

[0031] The current technology has the following shortcomings: on the one hand, it has high performance requirements for the main control chip and high hardware costs; on the other hand, it has limited scalability.

[0032] For example, in smart home devices such as smart light bulb systems, the main control chip is responsible for the basic electrical control of the device, such as adjusting the brightness of the light, switching colors and other functions. When the remote control function needs to be realized and the device is connected through a mobile phone APP (application), the main control chip first detects the networking command triggered by the user on the APP. It will send a series of configuration commands to the traditional communication module connected to it, including setting the network access mode (such as STA (Station) mode to access a home router), transmitting SSID (Service Set Identifier, wireless network service set identifier) ​​and password and other information. After receiving these instructions, the communication module starts the RF circuit according to the built-in driver, searches for available networks around, and attempts to authenticate the connection.

[0033] In terms of data interaction, once the connection is successful, if the main control chip wants to report the current status information of the device (such as the brightness value of the bulb, the current color code, etc.) to the cloud server, it will package the prepared data according to the preset data format, and then send it to the communication module through communication buses such as SPI (Serial Peripheral Interface) or UART (Universal Asynchronous Receiver / Transmitter). After receiving the data, the communication module encapsulates it layer by layer according to the network protocol (such as the TCP / IP protocol stack), adds the necessary header information, and then sends the data packet to the target server.

[0034] In terms of the logic data processing function, the main control chip undertakes most of the decision-making tasks. For example, when receiving a control instruction from the server, the main control needs to parse the instruction content to determine whether to adjust the brightness or switch the color. If it is to adjust the brightness, it will calculate the corresponding PWM (Pulse Width Modulation) signal duty cycle based on its built-in dimming algorithm, and then drive the bulb's driving circuit to achieve brightness changes. The communication module is more of a data transmission channel, and only performs some basic verification, retransmission and other simple logic at the network communication level to ensure the reliability of data transmission. This traditional interaction method and function allocation gradually exposed many defects in the face of growing performance requirements and cost control challenges. 1. With the vigorous development of the Internet of Things market, a large number of electronic devices pursue low cost and miniaturization, which makes the main control often use low-cost and low-performance chips. In this case, there are obvious problems with the combination of traditional communication modules and main controls.

[0035] On the one hand, the computing power of low-cost and low-performance main control is limited. In complex network application scenarios, such as processing connection requests from multiple devices at the same time and dealing with frequent data transmission tasks, the main control is prone to processing delays. Like the smart security camera system, the main control is responsible for image acquisition and encoding, as well as processing data interaction with the communication module and network protocol-related logic. When multiple mobile phones try to connect to view real-time images at the same time, the main control may be overwhelmed, resulting in image freezes, severe delays, and even connection loss.

[0036] On the other hand, ordinary communication modules have single functions and are highly dependent on the main control chip for complex logic data processing. This not only increases the burden on the main control chip, but also causes the overall power consumption of the system to be high. Because the main control chip is busy with data processing and logic judgment, it is in a high-load operation state for a long time and consumes a lot of electricity. Moreover, since the resources of the main control chip are occupied by network-related logic, the resources left for the core functions of the device (such as intelligent image analysis of security cameras) are relatively insufficient, which greatly reduces the professional performance of the device.

[0037] In addition, the scalability of the system is limited. When network functions need to be updated, such as upgrading to a new encryption protocol to enhance security, or supporting a more efficient OTA (Over-the-Air) update mechanism, due to the traditional architecture of the main control chip and the WiFi module (communication module) being tightly coupled, the main control chip software needs to be modified on a large scale, which results in a long development cycle and high cost, and is not conducive to rapid product iteration and upgrade.

[0038] Based on this, the present application proposes that the communication module can have some functions of the main control chip, and then some logic data processing of the main control chip can be deployed in the communication module for implementation, which is equivalent to the IoT device having two main control chips, which can effectively release the logic data processing pressure of the main control chip and reduce the demand for the hardware specifications of the main control chip, that is, the IoT device can use the main control chip with low logic data processing capability to cooperate with the communication module with the processor core to realize all the functions of the IoT device, which can effectively reduce the hardware cost of the main control chip. For details, please refer to the technical solution of any of the following embodiments.

[0039] See also Figure 1 , Figure 1 1 is a schematic diagram of the structure of an embodiment of an Internet of Things device provided by the present application. The Internet of Things device 100 includes: a main control chip 10 and a communication module 20.

[0040] The communication module 20 is coupled to the main control chip 10. The communication module 20 is provided with a processor core for receiving data sent by the main control chip 10 and performing logical data processing on the data, wherein the logical data processing at least includes packet loss retransmission and / or flow control. In some embodiments, the communication module 20 may be a WiFi module and / or a Bluetooth module, etc.

[0041] In the present application, the communication module 20 may have some functions of the main control chip 10, and thus some logic data processing of the main control chip 10 may be deployed in the communication module 20 for implementation, which is equivalent to the Internet of Things device 100 having two main control chips 10, thereby effectively releasing the logic data processing pressure of the main control chip 10, and reducing the requirements for the hardware specifications of the main control chip 10, that is, the Internet of Things device 100 may use a main control chip 10 with low logic data processing capability in conjunction with a communication module 20 with a processor core to implement all functions of the Internet of Things device 100 in the related technology, and thus effectively reduce the hardware cost of the main control chip 10.

[0042] In some embodiments, the communication module 20 provided by the IoT device 100 in the present application may have functions such as logic decision processing function, networking communication function, protocol parsing function, data encryption function, and OTA remote update program function.

[0043] For the logic decision processing function, the communication module 20 has an independent microprocessor core and can run a lightweight real-time operating system (Real Time Operate System, RTOS), such as FreeRTOS. The communication module 20 can use the microprocessor core to determine whether it is due to excessive load or hardware failure, and try to reduce the transmission rate or restart some hardware modules according to the preset strategy. In the allocation of data transmission tasks, the communication module 20 can use the microprocessor core to reasonably arrange the queue order according to the priority of the data packet (such as real-time control instructions are high priority, and the device status is regularly reported as low priority) to optimize the transmission efficiency. That is, the processor core in the communication module 20 is also used to reduce the data transmission rate when the load is detected to be greater than the threshold. And the processor core in the communication module 20 is also used to adjust the queue order according to the priority of the data packet, wherein the queue order is arranged in descending order of priority. And the processor core in the communication module 20 is also used to restart the hardware corresponding to the fault when a hardware fault in the communication module is detected.

[0044] For networking communication functions, the communication module 20 integrates a high-performance radio frequency chip, supports multiple frequency bands (2.4GHz, 5GHz and possible 6GHz bands in the future), and improves data throughput. The communication module 20 can automatically search and connect to available wireless networks, encrypt protocol authentication, and ensure connection security.

[0045] Regarding the protocol parsing function, the communication module 20 has the ability to fully parse mainstream protocol stacks such as TCP / IP, UDP, HTTP, MQTT, etc. It can accurately extract the payload from the received data packets, quickly assemble and send data packets according to the target application, accurately encapsulate the data into data that is adapted to the MQTT topic format, and efficiently transmit it to the cloud server for big data analysis.

[0046] For the data encryption function, the communication module 20 has a built-in hardware encryption engine that supports multiple encryption algorithms such as AES (Advanced Encryption Standard, symmetric encryption algorithm), RSA, ECC (elliptic curve encryption), etc., which can encrypt and decrypt the transmitted data in real time, automatically adopt high-intensity encryption methods to prevent data leakage, and the encryption process does not affect the overall transmission rate. That is, the communication module 20 is provided with a hardware encryption engine for real-time encryption and decryption of the transmitted data.

[0047] For the OTA remote update program function, the communication module 20 establishes a reliable connection with the cloud server, regularly checks the firmware update information, and effectively optimizes and avoids some legacy market problems. Once a new version is found, the dual backup partitions ensure that the upgrade can be rolled back if it fails.

[0048] In some embodiments, the main control chip 10 provided in the present application may have the functions of receiving and responding to control instructions and reporting current information of the device.

[0049] For the function of receiving and responding to control instructions, the main control chip 10 can be connected to the WiFi module (communication module 20) through a communication method such as a serial port protocol, and quickly receive control instructions using an interrupt drive method. After receiving the control instruction, the instruction type is quickly identified based on the built-in instruction parsing table, and the corresponding actuator is driven. For example, in the clothes drying machine system, when the "lower the clothes drying rod" instruction is received, the motor drive circuit is immediately started to control the clothes drying rod to descend at a uniform speed, ensuring timely response and meeting the user's real-time control needs.

[0050] For the function of reporting the current information of the device, the main control chip 10 can regularly collect key parameters of the device, such as the operating status of the clothes drying rod, the switch status of lighting, disinfection and other functions, organize them in a concise and efficient data format, and quickly transmit them through the communication protocol agreed with the WiFi module. The main control chip 10 is only responsible for the original collection and preliminary arrangement of data, and does not involve complex logical data processing, which reduces its own burden.

[0051] The processor core in the communication module 20 is also used to enter the standby mode when no data transmission is detected.

[0052] See also Figure 2 , Figure 2FIG. 1 is a schematic diagram of another embodiment of an Internet of Things device provided by the present application. The Internet of Things device 100 includes: a main control chip 10 , a communication module 20 and a cloud server 30 .

[0053] In some embodiments, the cloud server 30 is connected to the communication module 20; wherein the communication module 20 interacts with the cloud server 30, regularly checks for firmware update information, and when a new version of firmware is detected, performs firmware updates through dual backup partition technology.

[0054] In some embodiments, the communication module 20 is used to receive a first control instruction sent by the cloud server 30, and when it is detected that the first control instruction is reasonable, the communication module 20 sends the first control instruction to the main control chip 10 so that the main control chip 10 directly executes the first control instruction.

[0055] In some embodiments, after executing the first control instruction, the main control chip 10 collects current data and sends the current data to the communication module 20; the communication module 20 encrypts and packages the current data and sends it to the cloud server 30. For example, the main control chip 10 regularly collects key parameters of the equipment, such as the operating status of the clothes drying rod, the switch status of lighting, disinfection and other functions of the clothes drying machine, organizes them in a concise and efficient data format, and quickly transmits them through the communication protocol agreed with the communication module 20. The main control chip 10 is only responsible for the original collection and preliminary arrangement of data, and does not involve complex logical data processing, which reduces its own burden.

[0056] See also Figure 3 , Figure 3 2 is a schematic diagram of a structure of an embodiment of a smart home system provided by the present application. The smart home system 200 includes an Internet of Things device 100. The Internet of Things device 100 can be applied to many smart home systems such as a smart clothes drying system, a smart air conditioning system, a smart refrigerator system, and a smart washing machine system, and cooperate with smart home appliances to achieve more intelligent control.

[0057] The practical application process of this application is explained by taking the intelligent clothes drying system as an example.

[0058] Step 1: When the smart clothes drying system is started, the internal power management chip of the WiFi module (such as the communication module 20) in the IoT device starts to provide stable power supply for each component, and the clock circuit starts to work synchronously to provide a precise clock reference for RF transceiver and digital logic operation. Subsequently, the self-test program sequentially detects key parts such as the RF link, storage chip, encryption module, etc. If there is a fault, it will alarm the main control chip of the IoT device; if there is no abnormality, the WiFi module sends an initialization completion signal to the main control chip.

[0059] Step 2: After receiving the initialization completion signal, the main control chip reads the device identification code, SN code and other information stored locally.

[0060] Step 3: The main control chip transmits the device identification code, SN code and other information to the WiFi module via the serial port. The WiFi module uses this information to complete the authentication connection, and returns the network parameters (such as the assigned IP address and gateway address) to the main control chip after the connection is successful. Among them, the authentication connection can be an authentication connection between the cloud server and the application on the mobile terminal.

[0061] Step 4: When the cloud server sends the command to control the pole to rise, the WiFi module receives the data packet corresponding to the command, and uses the built-in protocol parsing module to extract the key content of the command. The processor core in the WiFi module determines the rationality of the command based on the preset logic (such as the pole is not at the highest point). If it is reasonable, it transmits the rising command to the main control chip through the serial port. After receiving it, the main control chip drives the electrode according to the rated current, changes the device state of the pole, and then collects data.

[0062] Step 5: The main control chip packages the data and sends it back to the WiFi module. The WiFi module is responsible for encrypting the data, encapsulating it into network data packets and sending it to the cloud server, completing a complete interactive cycle.

[0063] For example, when performing an OTA upgrade, as in step 6: the WiFi module background regularly "shakes hands" with the cloud server, and after detecting the firmware update notification, it downloads the firmware in segments from the cloud server, downloads, verifies, and upgrades to ensure that the upgrade is reliable and convenient.

[0064] The IoT device provided by this application demonstrates the advantages of this application in optimizing interaction, improving performance, and facilitating upgrades through full-process implementation in multiple scenarios, providing solid technical support for the innovative development of IoT devices.

[0065] That is, this application replans the interaction mode and functional layout between the WiFi module and the main control chip in the IoT device, transfers the key logic functions to the WiFi module, thereby resolving the relevant technical difficulties, and has the following effects:

[0066] First, improve system performance and response speed. By letting the WiFi module take on the responsibility of network logic data processing, the main control chip resources are released to focus on the core business logic of IoT devices. For example, in the field of smart cameras, the main control chip can focus on image acquisition, encoding optimization, and fast processing of video frame data, while the WiFi module is independently responsible for packet loss retransmission and flow control in network transmission, ensuring stable video stream upload, reducing screen freezes, and improving user viewing experience.

[0067] The second is to reduce power consumption and extend battery life. The WiFi module intelligently adjusts its own power consumption according to the network activity status, enters low-power standby mode when there is no data transmission, and wakes up related modules on demand when there is data interaction. The main control chip can also sleep at the right time after not having to process complex network logic, reducing unnecessary energy consumption. Taking the application of IoT devices in smart door locks as an example, most of the time it is in standby monitoring state, the WiFi module only maintains a weak heartbeat connection, and the main control chip is dormant. When an opening command is transmitted through the network, the WiFi module quickly wakes up the main control chip for collaborative processing, greatly extending the battery replacement cycle.

[0068] The third is to accelerate product iteration and upgrade. Encapsulate network-related functions in the WiFi module, and subsequent upgrades only require firmware updates for the WiFi module. For example, if IoT medical devices need to comply with new data privacy regulations and upgrade encryption algorithms, only the WiFi module program needs to be updated, and the main control chip does not need to be changed, shortening the time from R&D to market and enhancing product competitiveness.

[0069] Fourth, it meets the needs of cost control and performance balance. Using WiFi modules for logical decision processing can reduce many performance requirements for the main control chip. If the performance requirements for the main control chip are reduced, a lower-cost main control chip can be replaced.

[0070] In some embodiments, the above-mentioned smart home system can be applied to a clothes drying system. In the current smart clothes drying system, the communication module and the main control chip work together to realize remote control and intelligent interaction functions. Generally, the communication module is mainly responsible for network connection and data transmission, and the detection means for abnormal and faulty main control functions are relatively limited.

[0071] When a problem occurs with the clothes drying equipment, the communication module first relies on the error reporting mechanism of the main control chip itself. During the operation of the main control chip, if some key register values ​​inside are wrong, the clock signal is abnormal, or some hardware modules fail the self-test, a simple fault code will be sent to the communication module. For example, if the main control detects that the motor driver chip is overheating, it will send a specific binary code "001" to the communication module. After receiving it, the communication module will judge that the motor drive part may be overheating according to the fault code table pre-stored in its internal firmware. However, this method can only detect fault types that are known to the main control and have a pre-set feedback mechanism.

[0072] Another common detection method is based on data transmission verification. The communication module and the main control chip transmit data through the serial port. When transmitting instructions or status information, a simple check bit, such as parity check, is attached. When the main control sends data to the communication module, it calculates the parity of the data and adds a check bit. After receiving the data, the communication module recalculates the check. If it does not match, it is judged that an error has occurred in the data transmission, which may indicate that there is a problem with the data processing or transmission interface of the main control chip. However, this verification method can only detect errors at the data transmission level. It is difficult to effectively identify deep-level functional failures of the main control, such as erroneous instruction output caused by program runaway, confusion of motor control logic under complex working conditions, etc.

[0073] In addition, in some smart clothes drying systems, the communication module will send a "heartbeat" command to the main control chip at a certain time interval (such as every 10 minutes), and the main control chip will reply with a confirmation message after receiving it. If the communication module does not receive a reply for many consecutive times, it will determine that the main control chip may have crashed or seriously failed, but this also cannot accurately locate the root cause of the failure, and is only a relatively rough abnormal judgment method.

[0074] That is, in the relevant technology, the clothes drying equipment mainly has problems such as uneven lifting speed of the clothes drying rod, stroke deviation, excessive noise, and reduced load-bearing capacity.

[0075] The clothes drying system provided in the present application includes a clothes drying device and a cloud server. The clothes drying device can communicate with the communication module of the cloud server through the communication module to complete data interaction. The specific implementation method can refer to any of the following embodiments.

[0076] See also Figure 4 , Figure 4 1 is a flow chart of an embodiment of a control method for a clothes drying device provided by the present application. The method is applied to a cloud server, and the method includes:

[0077] Step 41: Receive target data of the target clothes drying device sent by the target communication module.

[0078] The target data includes basic data and operation data. The basic data includes at least one of the equipment model, motor model, load-bearing information, and usage date corresponding to the target clothes drying equipment. The operation data includes at least one of the noise data and usage times corresponding to the target clothes drying equipment.

[0079] Among them, the target data is sent from the main control chip of the target clothes drying device to the target communication module.

[0080] In some embodiments, the target communication module, such as the communication module in any of the above implementations, has partial logic data processing capabilities.

[0081] In some embodiments, the cloud server can interact with at least one clothes drying device, that is, the cloud server can interact with at least one communication module to control the corresponding clothes drying device.

[0082] In some embodiments, a deep data interaction channel is established inside the target communication module with the main control chip to receive basic data reported by the main control chip at a fixed period (e.g., once per second), including fixed parameters such as clothes drying machine model, motor model, main control version, equipment use date, etc., as well as real-time motor current and voltage, current position of the drying rod, etc., and actively request key dynamic data from the main control chip. After preliminary processing, the collected data is uploaded to the cloud server in real time through the network connection of the target communication module.

[0083] In some embodiments, after receiving massive data from many smart clothes drying machines, the cloud server uses a fault diagnosis model based on big data and artificial intelligence for analysis. The model builds a correlation model between various fault scenarios and equipment operating parameters through deep learning of massive historical data (covering normal operation data and fault data).

[0084] When the target communication module of a clothes drying device uploads data, the cloud server quickly compares and analyzes it. Once abnormal data is found, such as the motor current exceeds the normal range for a long time and the weight of the clothes drying rod is light, it is judged that the motor drive module may be faulty or the main control chip has errors in the control parameters of the motor; for example, the program running status flag reported by the main control chip frequently shows abnormal values, indicating that the main control program may have a risk of deadlock or memory leakage. The cloud server immediately feeds back the diagnosis results to the user's mobile phone APP in the form of early warning information through the target communication module, informing the user of the potential risk of failure, and recommending suspension of use or taking corresponding maintenance measures to prevent problems before they occur.

[0085] Step 42: Obtain control parameters of the target clothes drying equipment according to the target data.

[0086] The control parameters include the voltage and current corresponding to the motor of the target clothes drying device.

[0087] In some embodiments, the cloud server can calculate the control parameters based on at least one of the noise data, device model, motor model, load-bearing information, number of times used, and date of use to obtain the control parameters. The control parameters include the voltage and current corresponding to the motor of the target clothes drying device. The main control chip in the target clothes drying device can generate corresponding control signals based on the corresponding voltage and current to control the motor of the target clothes drying device.

[0088] Step 43: Send the control parameters to the target communication module, so that the target communication module sends the control parameters to the main control chip.

[0089] Among them, the main control chip is used to control the target clothes drying equipment according to the control parameters, such as controlling the motor rotation in the clothes drying equipment to make the clothes rise or fall. For example, the fan in the clothes drying equipment is controlled to start and provide corresponding wind to accelerate the reduction of moisture in the target to be dried.

[0090] In some embodiments, see Figure 5 , after step 43, the following process may be performed:

[0091] Step 431: Receive current noise data of the target clothes drying device sent by the target communication module.

[0092] In some embodiments, the rotation of the motor and the fan will generate corresponding noise, so a corresponding noise collection component can be set on the target clothes drying device, and the noise collection component is connected to the main control chip to send the collected current noise data to the main control chip. After receiving the current noise data, the main control chip can filter it to improve the accuracy of the current noise data, and then send the filtered current noise data to the cloud server through the target communication module.

[0093] Step 432: When the current noise data exceeds the threshold, re-optimize the control parameters according to the current noise data.

[0094] In some embodiments, when the current noise data exceeds the threshold, the control parameters may be re-optimized according to the proportion of the current noise data exceeding the threshold, such as proportionally reducing the control parameters, specifically, proportionally reducing the voltage and / or current.

[0095] In some embodiments, the main control chip works closely with the target communication module to control the motor operation according to the optimization parameters sent by the cloud server. When the load increases, the main control chip appropriately reduces the motor speed according to the feedback from the cloud server, and fine-tunes the smoothness of the PWM signal to avoid vibration caused by sudden current changes.

[0096] In addition, the whole machine has a built-in noise monitoring function, which uses a microphone array or a vibration sensor coupled to the outer shell of the clothes drying equipment to monitor the motor running noise in real time. Once the noise exceeds the preset threshold, the data is immediately uploaded to the cloud server. The algorithm in the cloud server recalculates and optimizes the motor control parameters based on the current working conditions, such as fine-tuning the current size, adjusting the phase sequence (for three-phase motors), etc., and feeds back to the main control chip through the target communication module to control the noise within an acceptable range, for example, to keep the noise value below 45 decibels.

[0097] In some embodiments, real-time remote monitoring of the clothes drying equipment is achieved by connecting the target communication module to the cloud server. Users or after-sales technicians can view the real-time operating status of the clothes drying equipment at any time through the cloud platform interface, including key parameters such as the lifting speed of the clothes drying rod, the motor current curve, and the main control temperature. When an abnormality is found, the technician can also use the cloud server to send remote debugging instructions to the main control chip through the communication module to force the main control chip to execute specific test programs, such as restarting the motor drive module, refreshing the main control program cache, etc., to quickly find the root cause of the fault without on-site disassembly and maintenance, greatly improving the efficiency of after-sales maintenance.

[0098] In one application scenario, the cloud server uses a big data algorithm to calculate the optimal motor control parameters for the current working conditions in real time based on the multiple data uploaded by the target communication module, such as the clothes drying machine model, motor model, load-bearing capacity, number of uses, and date of use. The algorithm is built on a deep neural network and is trained on massive data of clothes drying machines of different brands and models in various actual usage scenarios to accurately grasp the influence of different factors on the operation of the motor.

[0099] For example, when the pole is 10 kg in weight, used 500 times, and used for one year after purchase, the cloud server algorithm takes into account factors such as motor aging and mechanical parts wear, and calculates that the optimal voltage to be applied to the motor is 15V and the current is 2.5A, and sends these parameters to the main control chip in real time through the target communication module. Based on the feedback, the main control chip accurately adjusts the PWM (pulse width modulation) signal of the motor driver chip to ensure that the pole can be raised and lowered at a relatively stable speed (such as the lifting speed error is controlled within ±0.03 m / s) under different working conditions to avoid large speed fluctuations.

[0100] In this embodiment, the control parameters (motor operating parameters) of the target clothes drying equipment are optimized in real time through the big data algorithm of the cloud server to ensure that the clothes drying equipment can operate smoothly, quietly and efficiently under various complex working conditions, greatly extending the service life of the equipment and significantly improving the user experience.

[0101] See also Figure 6 , Figure 6 1 is a flow chart of another embodiment of the control method of the clothes drying device provided by the present application. The method is applied to a cloud server, and the method includes:

[0102] Step 61: Receive target data of the target clothes drying device sent by the target communication module.

[0103] Among them, the target data includes at least one of the noise data, equipment model, motor model, load-bearing information, number of uses, and usage date corresponding to the target clothes drying equipment; the target data is sent to the target communication module by the main control chip of the target clothes drying equipment.

[0104] Step 62: Input the target data into the deep neural network to obtain the control parameters of the target clothes drying device output by the deep neural network.

[0105] The control parameters include the voltage and current corresponding to the motor of the target clothes drying device.

[0106] In this embodiment, a deep neural network is deployed in the cloud server, and the deep neural network can be trained using big data related to the clothes drying equipment.

[0107] Step 63: Send the control parameters to the target communication module, so that the target communication module sends the control parameters to the main control chip.

[0108] Among them, the main control chip is used to control the target clothes drying equipment according to the control parameters.

[0109] In some embodiments, see Figure 7 , after step 63, the following process may be performed:

[0110] Step 631: Receive the travel deviation data of the target clothes drying device sent by the target communication module.

[0111] Step 632: Optimize the deep neural network using the travel deviation data.

[0112] In one application scenario, the target communication module cooperates with the main control chip and the Hall sensor or photoelectric sensor installed at the starting and ending points of the clothes drying rod to accurately measure the actual travel of the clothes drying rod in real time. Before starting the lifting operation each time, the main control chip first requests the target communication module for the latest travel correction data sent by the cloud server, and replans the travel based on factors such as the current load and number of uses.

[0113] If the pole travel deviation is found, such as the rise does not reach the specified height, the main control chip will adjust the motor running direction and number of turns in time according to the sensor feedback, and perform a second rise to ensure that the pole can accurately reach the predetermined position every time, and the deviation is controlled within ±0.5 cm. At the same time, the target communication module uploads each travel deviation and related working condition data to the cloud server, and the cloud server uses this data to continuously learn and optimize the algorithm to continuously improve the travel control accuracy. In other words, the travel deviation data can be used to optimize the deep neural network.

[0114] See also Figure 8 , Figure 8 1 is a flow chart of another embodiment of the control method of the clothes drying device provided by the present application. The method is applied to a cloud server, and the method includes:

[0115] Step 81: Receive load-bearing warning information sent by the target communication module.

[0116] Step 82: Optimize the control parameters of the target clothes drying equipment according to the load-bearing warning information.

[0117] Step 83: Push reminder information corresponding to the load-bearing warning information to the mobile terminal.

[0118] In one application scenario, as the target clothes drying equipment is used, the target communication module periodically (e.g., once a quarter) requires the main control chip to perform a load-bearing self-test according to the instructions of the cloud server. The main control chip controls the motor to drive the clothes drying rod to rise slowly, gradually increasing the load during the rise until the motor becomes obviously strained (judged by monitoring the motor current and speed changes), and records the maximum load at this time.

[0119] The target communication module compares the load-bearing self-inspection results with historical data. If it is found that the load-bearing capacity has dropped by more than a certain proportion (such as 8%, 9%, 10%), the data will be uploaded to the cloud server. The cloud server will push reminder information to users through the mobile phone APP, informing users that the load-bearing capacity of the clothes drying equipment has declined and recommending reducing the weight of the clothes to be dried. At the same time, the cloud algorithm optimizes subsequent motor control parameters according to the latest load-bearing conditions, reduces the load on the motor in daily operation, and extends the service life of the clothes drying machine.

[0120] See also Fig. 9 , Fig. 9 1 is a schematic diagram of a cloud server embodiment provided by the present application. The cloud server 30 includes: a processor 32, a memory 31 coupled to the processor 32, and a communication module 33, the memory 31 stores a computer program, and the processor 32 is used to execute the computer program to implement the following method:

[0121] Receive target data of a target clothes drying device sent by a target communication module; the target data includes at least one of noise data, device model, motor model, load-bearing information, number of uses, and date of use corresponding to the target clothes drying device; wherein the target data is sent to the target communication module by a main control chip of the target clothes drying device; obtain control parameters of the target clothes drying device according to the target data; the control parameters include voltage and current corresponding to the motor of the target clothes drying device; send the control parameters to the target communication module, so that the target communication module sends the control parameters to the main control chip; wherein the main control chip is used to control the target clothes drying device according to the control parameters.

[0122] In some embodiments, the processor 32 is further configured to execute a computer program to implement the method of any of the above embodiments.

[0123] See also Fig.10 , Fig.10 1 is a flow chart of another embodiment of the control method for clothes drying equipment provided by the present application. The method is applied to clothes drying equipment, and the method includes:

[0124] Step 101: The main control chip of the clothes drying device sends target data to the cloud server through the communication module, so that the cloud server obtains the control parameters of the clothes drying device according to the target data.

[0125] The target data includes at least one of noise data, equipment model, motor model, load-bearing information, number of uses, and date of use corresponding to the target clothes drying equipment.

[0126] Step 102: The main control chip receives control parameters sent by the cloud server through the communication module; the control parameters include the voltage and current corresponding to the motor of the target clothes drying device.

[0127] Step 103: The main control chip controls the clothes drying device according to the control parameters.

[0128] The interaction between the clothes drying device and the cloud server is specifically referred to any of the above embodiments, which will not be described here.

[0129] See also Fig.11 , Fig.11 1 is a schematic diagram of a structure of an embodiment of a clothes drying device provided by the present application. The clothes drying device 400 comprises: a main control chip 402, a memory 401 and a communication module 403 coupled to the main control chip 402, the memory 401 stores a computer program, and the main control chip 402 is used to execute the computer program to implement the following method:

[0130] The main control chip of the clothes drying equipment sends target data to the cloud server through the communication module, so that the cloud server obtains the control parameters of the clothes drying equipment according to the target data; the target data includes at least one of the noise data, equipment model, motor model, load-bearing information, number of uses, and use date corresponding to the target clothes drying equipment; the main control chip receives the control parameters sent by the cloud server through the communication module; the control parameters include the voltage and current corresponding to the motor of the target clothes drying equipment; the main control chip controls the clothes drying equipment according to the control parameters.

[0131] In some embodiments, the main control chip 402 is further used to execute a computer program to implement the method of any of the above embodiments.

[0132] In some embodiments, a household smart clothes drying machine is used as an example to illustrate the actual application process.

[0133] Step 1: After the system is powered on and initialized, the main control chip reports the initial information of the clothes dryer, such as model, motor model, main control version, purchase date, etc., to the WiFi module.

[0134] Step 2: Upload the WiFi module device parameters to the cloud server synchronously.

[0135] Step 3: Then, the main control chip reports the real-time operation data of the device to the WiFi module at a frequency of once a minute, including the current position of the drying rod, motor current, voltage, noise volume, etc. The WiFi module encrypts and transmits it to the cloud server. For example: When drying clothes daily, the user hangs the clothes on the drying rod, and the pressure sensor instantly collects the load-bearing data. The main control chip immediately reports it to the WiFi module, and the WiFi module uploads it to the cloud server. Suppose at a certain moment, the user has dried a lot of heavy clothes, the load-bearing reaches 18 kilograms, the number of uses is 300 times, and it has been purchased for half a year.

[0136] Step 4: Based on this information, the big data algorithm of the cloud server takes into account factors such as motor wear and mechanical component aging, and quickly calculates the optimal operating parameters that the motor should use at this time, such as 16V voltage and 3A current. And feedback is sent to the main control chip through the WiFi module. The main control accurately adjusts the PWM signal of the motor driver chip to make the clothes drying pole rise at a stable speed of 0.25 meters per second, avoiding excessive speed fluctuations due to changes in load.

[0137] For example, during the rising process of the clothes-drying rod, the Hall sensors installed at the starting and ending points of the clothes-drying rod monitor the position of the clothes-drying rod in real time. If the clothes-drying rod rises to 3 cm short of the preset highest position due to mechanical wear of the motor, the main control chip will judge the travel deviation based on the feedback of the Hall sensor and the latest travel correction data obtained by the WiFi module from the cloud server, and immediately stop the current rising action, adjust the direction of the motor, and rise again until the clothes-drying rod reaches the highest position accurately to ensure that the clothes are fully dried.

[0138] For example, the WiFi module uses a built-in vibration sensor to monitor the noise of the motor. When the noise value exceeds 48 decibels, the data is immediately uploaded to the cloud server together with the current working conditions. The cloud algorithm recalculates and optimizes the motor control parameters, such as fine-tuning the current to 2.8A and adjusting the phase sequence, and then feeds back to the main control through the WiFi module to reduce the noise to below 45 decibels, creating a quiet use environment.

[0139] For example: Every quarter, the WiFi module requires the main control chip to perform a load-bearing self-test according to the instructions of the cloud server. The main control chip drives the clothes drying rod to rise slowly, gradually increasing the load until the motor current rises sharply and the speed drops significantly. It is judged that the maximum load-bearing capacity of the clothes drying machine has been reached at this time, assuming it is 26 kg. The data is reported to the WiFi module, and the WiFi module uploads it to the cloud server. The cloud server compares historical data and finds that the load-bearing capacity has dropped by 12% compared to the initial nominal value. It pushes reminder information to users through the mobile phone APP, informing users that the load-bearing capacity of the clothes drying machine has declined, and recommends reducing the weight of the clothes to be dried. The parameters in the adaptive control algorithm are adjusted accordingly to reduce the load of the motor in daily operation and extend the service life of the clothes drying machine.

[0140] That is, through the full-process implementation in multiple scenarios, the advantages of this application in optimizing detection, improving performance, etc. are demonstrated, providing solid technical support for the innovative development of smart clothes drying machines.

[0141] In summary, this application is committed to breaking through the relevant technical bottlenecks and innovatively proposes an intelligent clothes drying machine optimization solution that integrates WiFi modules, main control chips and cloud server big data algorithms, which can achieve the following goals:

[0142] Build an accurate, comprehensive and intelligent main control function abnormality and fault detection system. With the help of WiFi module and cloud algorithm collaboration, it can not only quickly capture known faults of the main control chip, but also deeply explore potential hidden faults for the overall user, provide accurate guidance for equipment maintenance and repair, and reduce after-sales costs and user risks.

[0143] We have overcome a series of technical difficulties such as uneven lifting speed of the clothes drying rod, stroke deviation, excessive noise and reduced load-bearing capacity, and optimized the motor operating parameters in real time through cloud-based big data algorithms to ensure that the clothes drying machine can operate smoothly, quietly and efficiently under various complex working conditions, greatly extending the service life of the equipment and significantly improving the user experience.

[0144] In the several embodiments provided in this application, it should be understood that the disclosed methods and devices can be implemented in other ways. For example, the device implementation described above is only illustrative, for example, the division of the modules or units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed.

[0145] If the integrated units in the above other embodiments are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) or a processing circuit component (processor) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, RandomAccess Memory), disk or optical disk and other media that can store program code.

[0146] The above description is only an implementation method of the present application, and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly used in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. An Internet of Things device, characterized in that: The IoT devices include: Main control chip; A communication module is coupled to the main control chip, wherein a processor core is provided in the communication module for receiving data sent by the main control chip and performing logical data processing on the data, wherein the logical data processing at least includes packet loss retransmission and / or flow control.

2. The IoT device according to claim 1, characterized in that: The processor core in the communication module is also used to enter a standby mode when no data transmission is detected.

3. The IoT device according to claim 1, characterized in that: The processor core in the communication module is also used to reduce the data transmission rate when it is detected that the load is greater than a threshold.

4. The Internet of Things device according to claim 1, characterized in that: The processor core in the communication module is also used to adjust the queue order according to the priority of the data packet, wherein the queue order is arranged in descending order of priority.

5. The Internet of Things device according to claim 1, characterized in that: The communication module is provided with a hardware encryption engine for encrypting and decrypting the transmitted data in real time.

6. The Internet of Things device according to claim 1, characterized in that: The processor core in the communication module is also used to restart the hardware corresponding to the fault when a hardware fault in the communication module is detected.

7. The Internet of Things device according to any one of claims 1 to 6, characterized in that: The IoT device further includes a cloud server, and the cloud server is connected to the communication module; The communication module interacts with the cloud server, regularly checks firmware update information, and when a new version of firmware is detected, performs firmware update through dual backup partition technology.

8. The Internet of Things device according to any one of claims 1 to 6, characterized in that: The IoT device further includes a cloud server, and the cloud server is connected to the communication module; The communication module is used to receive a first control instruction sent by the cloud server, and when detecting that the first control instruction is reasonable, send the first control instruction to the main control chip so that the main control chip directly executes the first control instruction.

9. The Internet of Things device according to claim 8, characterized in that: After executing the first control instruction, the main control chip collects current data and sends the current data to the communication module; The communication module encrypts and encapsulates the current data and sends it to the cloud server.

10. A smart home system, characterized in that: The smart home system includes the Internet of Things device as described in any one of claims 1-9.

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