Wireless guest control method and system based on edge computing gateway and medium

Abstract

The invention relates to a wireless guest control method and system based on an edge computing gateway and a medium, and relates to the technical field of Internet of Things control, and the method comprises the steps: sharing the state information and customer demand information of each device in a room through the edge computing gateway; establishing a demand constraint model based on the customer demand information, and minimizing a preset energy consumption function by using the demand constraint model; based on the minimization result of the energy consumption function, adjusting the state information of each device; and controlling the corresponding equipment based on the adjusted state information. The method is used for cooperative control of multiple devices of the guest room so as to save energy consumption of the guest room on the basis of meeting customer requirements.

Description

Technical Field

[0001] The present invention relates to the field of Internet of Things control technology, and in particular to a wireless customer control method, system and medium based on edge computing gateway. Background Art

[0002] An edge computing gateway is a device that integrates computing, storage, and network functions and is located at the edge of the network close to the data source or terminal device. It processes and analyzes data locally, reducing dependence on remote data centers, network latency, and bandwidth consumption. Edge computing gateways are often used in the Internet of Things and smart systems to manage and control connected devices in real time, and support local processing and remote synchronization of data to improve system response speed and efficiency while ensuring data privacy and security.

[0003] Guest room control refers to a system that uses intelligent technology to centrally manage and control various devices in hotel guest rooms. It can realize remote or automatic operation of lighting, air conditioning, curtains, door locks, televisions and other facilities to enhance the guest experience.

[0004] The current edge guest control system is mainly used as a controller to individually control the equipment in the room, such as air conditioners and lights, but its functions are relatively limited. It mainly executes preset tasks and lacks the ability to intelligently coordinate between devices. It is unable to optimize energy consumption based on the mutual influence between devices. For example, when the curtains are closed, the air conditioner power cannot be automatically reduced or the TV brightness cannot be lowered, resulting in insufficient overall energy efficiency management and difficulty in achieving energy saving goals. Summary of the invention

[0005] In view of the shortcomings of the prior art described above, the object of the present invention is to provide a wireless guest control method, system and medium based on edge computing gateway, which are used for collaborative control of multiple devices in guest rooms to save guest room energy consumption while meeting customer needs.

[0006] To achieve the above purpose, the present invention adopts the following technical solution.

[0007] In a first aspect, the present invention provides a wireless customer control method based on an edge computing gateway, which adopts the following technical solution: A wireless customer control method based on an edge computing gateway, comprising: Through the edge computing gateway, the status information of each device in the room and customer demand information are shared; Establishing a demand constraint model based on the customer demand information, and minimizing a preset energy consumption function with the demand constraint model; adjusting the status information of each device based on the result of minimizing the energy consumption function; And, controlling the corresponding device based on the adjusted status information.

[0008] Furthermore, in the wireless customer control method based on edge computing gateway, the customer demand information at least includes the air conditioning temperature variable T desired , light brightness variable L desired , curtain opening and closing state variable C desired And the TV switch state variable S desired .

[0009] Furthermore, in the above-mentioned wireless customer control method based on edge computing gateway, the demand constraint model is established based on the customer demand information, and the preset energy consumption function is minimized by the demand constraint model, including: Based on the customer demand information, define the demand range of each device to form the demand constraint model; According to the energy consumption characteristics of each device, define the energy consumption function of each device; Combine the energy consumption functions of all devices into a total energy consumption objective function, and combine it with customer demand constraints to form an optimization problem; The energy consumption objective function is solved using an optimization algorithm to find the equipment operating state that meets customer needs and has the lowest energy consumption.

[0010] Furthermore, in the above-mentioned wireless customer control method based on edge computing gateway, the optimization algorithm includes a linear programming algorithm.

[0011] Furthermore, the above-mentioned wireless customer control method based on edge computing gateway also includes: The collected equipment operation data, energy consumption data and environmental change data are regularly uploaded to the cloud server through the edge computing gateway; the cloud server updates the energy consumption function and sends it to the edge computing gateway through a preset update algorithm.

[0012] Furthermore, in the wireless customer control method based on the edge computing gateway, the state information of each device is adjusted based on the result of minimizing the energy consumption function, including: According to the calculation results of the minimization energy consumption function, the optimal working state of each device is determined; Verify whether the optimal working state meets the demand constraint model, and adjust the state information of each device after successful verification.

[0013] Furthermore, in the wireless customer control method based on the edge computing gateway, the controlling of the corresponding device based on the adjusted state information includes: Adjusting the status information into corresponding device adjustment instructions; The device adjustment instruction is sent to the corresponding device via the Bluetooth Mesh network.

[0014] In a second aspect, the present invention provides a wireless customer control system based on an edge computing gateway, which adopts the following technical solution: A wireless customer control system based on an edge computing gateway, built into a wireless router, includes: A data acquisition module, at least for sharing status information of each device in the room and customer demand information; A data calculation module, at least used to establish a demand constraint model based on the customer demand information, and minimize a preset energy consumption function with the demand constraint model; A data adjustment module, at least used to adjust the status information of each device based on the energy consumption function minimization result; And, a data execution module is at least used to control a corresponding device based on the adjusted state information.

[0015] Furthermore, the wireless customer control system of the edge computing gateway further includes: The cloud update module is at least used to update the energy consumption function through a preset update algorithm and send it to the edge computing gateway.

[0016] In a third aspect, the present invention provides a readable storage medium, which adopts the following technical solution: A readable storage medium stores computer instructions, and when the computer instructions are executed by a processor, a wireless customer control method based on an edge computing gateway as described in any one of the first aspects above is implemented.

[0017] In summary, compared with the prior art, the present invention includes at least one of the following beneficial technical effects: The present invention realizes intelligent collaborative control among various devices, which can not only meet the personalized needs of customers, but also maximize the energy saving effect while ensuring comfort. In addition, the present invention realizes refined management by dynamically adjusting the device status in real time, improves the energy efficiency and operation efficiency of the equipment, and reduces the overall energy consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0019] Figure 1 It is a flowchart of a specific embodiment of a wireless customer control method based on an edge computing gateway of the present invention.

[0020] Figure 2It is a flowchart of another specific embodiment of a wireless customer control method based on an edge computing gateway of the present invention.

[0021] Figure 3 It is a flowchart of another specific embodiment of a wireless customer control method based on an edge computing gateway of the present invention.

[0022] Figure 4 It is a structural schematic diagram of a specific embodiment of a wireless customer control system based on an edge computing gateway of the present invention.

[0023] Figure 5 It is a structural schematic diagram of another specific embodiment of a wireless customer control system based on an edge computing gateway of the present invention. DETAILED DESCRIPTION

[0024] 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. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present application. In addition, it should be understood that the specific implementation methods described herein are only used to illustrate and explain the present application, and are not used to limit the present application.

[0025] It should be noted that the description order of the following embodiments is not intended to limit the preferred order of the embodiments of the present application. In addition, in the following embodiments, the description of each embodiment has its own emphasis, and for parts not described in detail in one embodiment, reference can be made to the relevant description of other embodiments.

[0026] The method steps described in the embodiments of the present invention may be executed in the order described in the specific implementation manner, or the execution order of each step may be adjusted according to actual needs and on the premise that the technical problem can be solved, which will not be listed here one by one.

[0027] Reference Figure 1 The embodiment of the present invention discloses a wireless customer control method based on an edge computing gateway, comprising: S1, shares the status information of each device in the room and customer demand information through the edge computing gateway; S2, establishing a demand constraint model based on the customer demand information, and minimizing a preset energy consumption function with the demand constraint model; S3, adjusting the status information of each device based on the result of minimizing the energy consumption function; S4, controlling the corresponding device based on the adjusted status information.

[0028] Specifically, step S1 collects the status information of each device in the room (such as air conditioning, lighting, curtains, etc.) in real time through the edge computing gateway, such as temperature setting, brightness level, switch status, etc.; at the same time, receives the customer's personalized demand information, which can be obtained through various interfaces, such as instructions entered by the resident through mobile applications, smart panels or voice control devices. The edge computing gateway aggregates the real-time status of all devices and customer demand information, and shares it with the system for subsequent energy consumption optimization and equipment control.

[0029] In step S2, based on customer demand information (such as temperature, brightness, comfort, etc.), a demand constraint model is established through an algorithm to ensure that the equipment operation meets customer needs. The demand constraint model can use linear or nonlinear constraints, such as the air conditioning temperature is within the range set by the customer, and the light brightness must not be lower than the preset value. Then, combined with the energy consumption characteristics of the equipment, the preset energy consumption function is minimized using an optimization algorithm (such as linear programming, genetic algorithm, dynamic programming, etc.) to find the optimal equipment operation strategy that not only meets customer needs but also minimizes energy consumption.

[0030] Step S3 sends control instructions through the edge computing gateway to adjust the temperature setting of the air conditioner, change the brightness of the lights, open and close the curtains, etc. These adjustments can be immediate, such as adjusting the air conditioner power in real time to achieve the most energy-efficient temperature setting, or reducing the output of the lights when the brightness exceeds the demand. In addition, the adjustment method can also be dynamically updated according to changes in the external environment (such as outdoor temperature or sunlight intensity), ensuring that the equipment always works in the most energy-efficient state while meeting customer needs.

[0031] Step S4 sends control instructions to each device through the edge computing gateway based on the adjusted device status information to specifically update the device status. This can include adjusting the air conditioner to a new set temperature, changing the light brightness, changing the TV brightness, etc. Control instructions can be transmitted in a variety of ways, such as Wi-Fi, Bluetooth Mesh network, etc., to ensure that the device responds quickly and stably. In addition, the system can continuously monitor the operating status of the device to ensure that the device operates according to the latest adjustment information, and make real-time corrections or optimizations when necessary to ensure that the device is always maintained in the optimal working state.

[0032] Based on the above embodiments, intelligent collaboration and real-time energy consumption optimization between devices are achieved. First, by sharing the status of each device and customer demand information, an accurate demand constraint model is established, and then the energy consumption function is minimized based on this, and the operating status of the device is dynamically adjusted. Finally, each device is automatically controlled to ensure that energy efficiency is maximized while meeting customer needs, which significantly improves the operating efficiency of the equipment and the hotel's energy management level, while improving the customer experience.

[0033] Further, as an embodiment of the present invention, the customer demand information at least includes the air conditioning temperature variable T desired , light brightness variable L desired , curtain opening and closing state variable C desired And the TV switch state variable S desired .

[0034] Specifically, the air conditioning temperature variable T desired Indicates the temperature value desired by the customer, such as 24°C; light brightness variable L desired Represents the light brightness expected by the customer, such as 70%; Curtain opening and closing state variable C desired Indicates the opening and closing state of the curtains, for example, the customer wants the curtains to be closed; the TV switch state variable S desired Indicates the on / off status of the TV. These variables together constitute the personalized needs of customers, and the equipment will be adjusted accordingly based on these needs to ensure the customer experience while maximizing energy saving.

[0035] Further, as an embodiment of the present invention, refer to Figure 2 , step S2, establishing a demand constraint model based on the customer demand information, and minimizing a preset energy consumption function with the demand constraint model, including: S21, based on the customer demand information, defining the demand range of each device to form the demand constraint model; S22, defining an energy consumption function of each device according to the energy consumption characteristics of each device; S23, combining the energy consumption functions of all devices into a total energy consumption objective function and combining it with customer demand constraints to form an optimization problem; S24, using an optimization algorithm to solve the energy consumption objective function to find the equipment operating state that meets customer needs and has the lowest energy consumption.

[0036] Specifically, based on the customer's personalized demand information, define the demand range of each device and build a demand constraint model. desired , set the temperature range to the customer's desired temperature, such as 26°C; for the light brightness variable L desired , define the lower limit of brightness as the minimum brightness set by the customer, such as 70%; the curtain opening and closing state variable C desired Defined as 0 (off) or 1 (on); TV switch state variable S desired Defined as 0 (off) or 1 (on). These demand ranges constitute the constraints of the device, ensuring that the device optimizes energy consumption while meeting customer needs.

[0037] According to the energy consumption characteristics of each device, its energy consumption function is defined. For air conditioners, its energy consumption function can be based on the difference between the set temperature and the ambient temperature, such as E AC =k*|T desired -T env |, where k is the energy consumption coefficient; for lights, the energy consumption function can be proportional to the brightness, such as E light =c*L desired , where c is the power consumption coefficient of the light; the energy consumption of the curtain can be defined as a fixed power consumption value according to its switch state, consuming power when open and no energy consumption when closed; the energy consumption of the TV can be constructed by defining the relationship between the TV brightness and power consumption to construct an energy consumption function. For example, the energy consumption function of the TV can be expressed as E TV =d*S desired , d is the TV power consumption coefficient. Through these energy consumption functions, the power consumption of each device in different states is quantified, providing a basis for subsequent energy consumption optimization.

[0038] The energy consumption functions of each device are combined into a total energy consumption objective function, and combined with the customer's demand constraints to construct an overall optimization problem. Specifically, the energy consumption function of each device, such as the air conditioner energy consumption E AC =k*|T desired -T env |、Lighting energy consumption E light =c*L desired , Curtain energy consumption E curtain =m and TV energy consumption E TV =d*S desired Superimpose to form the total energy consumption objective function Etotal = E AC +E light +E curtain +E TV Then, combined with the customer's demand constraints (such as temperature, brightness, switch status, etc.), these conditions are used as constraints to ensure that the operating state of the equipment optimizes energy consumption while meeting customer needs. Through this total energy consumption function, a complete optimization problem can be constructed to achieve collaborative optimization among devices.

[0039] Based on the constructed energy consumption objective function and customer demand constraints, an optimization algorithm is used to solve the optimal operating state of each device. Common optimization algorithms may include linear programming, genetic algorithms, or particle swarm optimization. Through these algorithms, the system will iteratively calculate the device combination state with the lowest energy consumption while meeting customer needs (such as temperature range, brightness requirements, etc.). The final result will output the optimal setting value for each device, such as the optimal temperature of the air conditioner, the optimal brightness of the light, the switch and brightness status of the curtains and TV, so as to minimize global energy consumption.

[0040] For example, the embodiment of the present invention provides a simple code example for linear programming optimization using the SciPy library in Python. Assuming that the energy consumption function including air conditioning, lighting, curtains and television needs to be minimized and optimized in combination with the customer's demand constraints, then: from scipy.optimize import linprog #Define the coefficients of the energy consumption function (for example, k1, k2, k3, k4 are the energy consumption coefficients of air conditioning, lighting, curtains, and TV respectively) #The energy consumption of each device is assumed to be linear c=[0.5,0.2,0.1,0.3]#Energy consumption coefficient of air conditioner, lighting, curtains, and TV #Define the constraints of customer requirements #Constraint 1: 22 <= T_desired <= 26 (air conditioning temperature) #Constraint 2: 50 <= L_desired <= 100 (light brightness) #Constraint 3: 0 <= C_desired <= 1 (curtain status, 0 for closed, 1 for open) #Constraint 4: 0 <= S_desired <= 100 (TV brightness) #The matrices A_ub and b_ub of the inequality constraints are used to express the inequality A_ub@x<=b_ub A_ub=[ [-1,0,0,0], #corresponding to T_desired>=22 [1,0,0,0], #corresponding to T_desired <= 26 [0,-1,0,0], #corresponding to L_desired>=50 [0,1,0,0], #corresponding to L_desired <= 100 [0,0,-1,0],#corresponding to C_desired>=0 [0,0,1,0], #corresponding to C_desired <= 1 [0,0,0,-1], #corresponding to S_desired>=0 [0,0,0,1]#corresponds to S_desired<=100 ] b_ub=[-22,26,-50,100,0,1,0,100] #x in the objective function is [T_desired, L_desired, C_desired, S_desired] #Use linprog to find the optimal solution res=linprog(c,A_ub=A_ub,b_ub=b_ub, method='highs') # Output results if res.success: T_opt,L_opt,C_opt,S_opt=res.x print(f"Optimal air conditioning temperature:{T_opt:.2f}℃") print(f"Optimal light brightness: {L_opt:.2f}%") print(f"Optimal curtain state:{'open'if C_opt>0.5else'close'}") print(f"Optimal TV brightness: {S_opt:.2f}%") else: print("Optimization failed") Thus, the optimal solution for the equipment operating status is found, thereby minimizing energy consumption.

[0041] Furthermore, as an implementation mode of the present invention, the optimization algorithm includes a linear programming algorithm.

[0042] Specifically, in edge computing gateways, due to the limitation of computing power, the use of linear programming algorithms is highly efficient and can quickly solve the optimal solution under multiple constraints, especially for linear and convex optimization problems. The linear programming method describes the problem through an accurate mathematical model, which can ensure the global optimality of the solution and avoid falling into the local optimum. In addition, it is easy to implement and has mature solving tools, can handle large-scale problems, and is suitable for optimization tasks such as resource allocation and cost minimization in many practical scenarios.

[0043] Further, as an embodiment of the present invention, refer to Figure 3 , the wireless customer control method based on edge computing gateway described in the embodiment of the present invention also includes: S5, regularly uploads the collected equipment operation data, energy consumption data, and environmental change data to the cloud server through the edge computing gateway; S6, the cloud server updates the energy consumption function through a preset update algorithm and sends it to the edge computing gateway.

[0044] Specifically, in step S5, the edge computing gateway is responsible for collecting the operating data, energy consumption data and environmental change data of each device in the room in real time. The operating data includes specific device parameters such as the set temperature of the air conditioner, the brightness of the light, the opening and closing status of the curtains, the brightness and usage of the TV; the energy consumption data is the real-time energy consumption of the device in different states, such as the power consumption of the air conditioner at different temperature settings, the power consumption of the light at different brightness, etc. Environmental change data usually involves external factors such as external temperature, humidity, and light that affect the energy consumption of the device. The edge computing gateway collects and summarizes this data regularly, and then uploads this data to the cloud server via the Internet or local area network. The frequency of data upload can be set according to application requirements, such as uploading once an hour or uploading at a fixed time every day. The upload process needs to ensure the security and integrity of data transmission, and encryption technology and data verification mechanisms are usually used to avoid data leakage or loss during the transmission process.

[0045] In step S6, after receiving the uploaded data, the cloud server dynamically updates the energy consumption function through a preset update algorithm. The update algorithm can be a model based on machine learning or a statistical analysis algorithm. The purpose is to adjust the energy consumption function of each device based on a large amount of historical data and currently collected data, so that it can more accurately reflect the energy consumption characteristics of the device under different environmental conditions. For example, the energy consumption function of the air conditioner can be adjusted with the change of seasons to better adapt to the impact of different external temperatures on the performance of the air conditioner. The cloud server will regenerate or update the energy consumption optimization model based on the new data analysis results, and send the new energy consumption function back to the edge computing gateway. After receiving the updated energy consumption function, the edge computing gateway applies it to the real-time optimization of the device control strategy. Through this cloud and edge computing collaboration, the system can continuously optimize itself to ensure that the system can always operate with the lowest energy consumption under different environmental conditions and when the needs of different residents change, while ensuring the comfort experience of the residents.

[0046] This collaborative mechanism based on cloud servers and edge computing gateways can achieve dynamic tuning of the system, so that the energy consumption optimization model not only adapts to the current equipment status, but also performs predictive optimization based on long-term data trends, thereby further improving the system's energy-saving effects and operating efficiency.

[0047] Furthermore, as an embodiment of the present invention, step S3, based on the result of minimizing the energy consumption function, adjusts the status information of each device, including: determining the optimal working state of each device according to the calculation result of minimizing the energy consumption function; verifying whether the optimal working state satisfies the demand constraint model, and adjusting the status information of each device after successful verification.

[0048] Specifically, based on the calculation results of minimizing the energy consumption function, the optimal working state of each device is determined, such as the optimal temperature setting of the air conditioner, the optimal brightness of the light, the opening and closing state of the curtains, and the brightness of the TV. The optimal state of these devices is calculated by the optimization algorithm, aiming to meet the goal of minimum energy consumption. Next, these optimal states are verified to ensure that they meet the constraints of customer needs. For example, the air conditioner temperature must be within the range set by the customer, the light brightness cannot be lower than the brightness value required by the customer, and the curtain and TV status must also meet the user's expectations. If the verification is successful, the control command is sent through the edge computing gateway to adjust each device to the corresponding optimal state. These adjustments ensure that the device still meets the personalized needs of customers while minimizing energy consumption, and realizes intelligent and efficient energy consumption management.

[0049] Further, as an implementation mode of the present invention, step S4, controlling the corresponding device based on the adjusted status information, includes: adjusting the status information into a corresponding device adjustment instruction; and sending the device adjustment instruction to the corresponding device via a Bluetooth Mesh network.

[0050] Specifically, the corresponding device control instructions are generated based on the optimized and adjusted device status information. For example, the temperature setting instructions for air conditioners, the brightness adjustment instructions for lights, the opening and closing instructions for curtains, and the brightness setting instructions for TVs. These generated instructions convert the optimal working state of the device into specific operation commands. Next, these device control instructions are sent to each corresponding device through the Bluetooth Mesh network. The Bluetooth Mesh network allows multiple devices to communicate efficiently within a local area, ensuring that instructions can be delivered to each device quickly and accurately, and achieving real-time response and adjustment. After each device receives the instruction, it immediately adjusts to the optimized working state according to the instruction, thereby ensuring the lowest energy consumption and meeting customer needs.

[0051] A wireless customer control system based on an edge computing gateway is built into the edge computing gateway (wireless router). The system includes a data acquisition module 1, a data calculation module 2, a data adjustment module 3, a data execution module 4 and a cloud update module 5.

[0052] The data acquisition module 1 is at least used to share the status information of each device in the room and the customer demand information; specifically, the status information of each device in the room and the customer demand information are collected and shared in real time through the edge computing gateway. The equipment status information includes the current set temperature of the air conditioner, the brightness of the light, the opening and closing status of the curtains, the switch and brightness of the TV, etc. These status information can be transmitted and updated in real time through wireless networks (such as Wi-Fi or Bluetooth Mesh). Customer demand information can be collected through user input devices such as mobile applications, smart panels or voice control devices to collect residents' preferences for equipment, such as the desired air conditioning temperature, light brightness, curtain status, etc. Through wireless sensors and edge computing devices, the data acquisition module 1 will update the equipment status and user needs regularly or in real time, summarize and share this information to other modules of the system, to ensure that the system can reflect changes in equipment status in the shortest time, and provide an accurate data basis for subsequent energy consumption optimization and control.

[0053] The data calculation module 2 is at least used to establish a demand constraint model based on the customer demand information, and minimize the preset energy consumption function with the demand constraint model; specifically, a demand constraint model is established based on the customer demand information and device status information collected from the data acquisition module 1. The model includes equipment parameters such as air conditioning temperature, light brightness, curtain opening and closing status, and sets corresponding constraints according to the customer's personalized needs. Then, the data calculation module 2 calculates the energy consumption function of the device and performs energy consumption minimization calculations in combination with the constraints. For example, the energy consumption function of the air conditioner can be calculated based on the difference between the set temperature and the ambient temperature, while the lights and curtains consume energy according to the brightness and opening and closing status. The data calculation module completes these calculations locally through Bluetooth Mesh and edge computing technology to ensure that the system can adjust the device status in real time to achieve the best energy saving solution.

[0054] The data adjustment module 3 is at least used to adjust the status information of each device based on the result of minimizing the energy consumption function; specifically, based on the energy consumption minimization result generated by the data calculation module 2, the status information of each device in the room is dynamically adjusted. The data adjustment module 3 will generate corresponding device adjustment instructions through the edge computing gateway based on the calculated optimal working state, such as adjusting the set temperature of the air conditioner, the brightness of the light, or the opening and closing state of the curtains. Through the Bluetooth Mesh network, the instructions will be sent to the specific device to achieve rapid response and adjustment. The data adjustment module 3 ensures that the equipment can still meet customer needs on the basis of energy-saving optimization, and continuously optimizes the working state of the equipment through real-time status monitoring and feedback mechanism to achieve the dual goals of energy saving and comfort.

[0055] The data execution module 4 is at least used to control the corresponding device based on the adjusted status information; specifically, according to the device adjustment instructions generated by the data adjustment module 3, the data execution module 4 uses the Bluetooth Mesh network through the edge computing gateway to send these control instructions to each device in the room to ensure that the device can work according to the optimal energy consumption plan. For example, when the system decides to adjust the temperature of the air conditioner, the brightness of the lights, or the opening and closing status of the curtains, the data execution module will quickly transmit the corresponding instructions to each device to achieve accurate execution of the instructions. This module ensures that the equipment operates normally according to the optimized state, thereby saving energy while maintaining the customer's comfort experience.

[0056] The cloud update module 5 is at least used to update the energy consumption function and send it to the edge computing gateway through a preset update algorithm; specifically, the cloud update module 5 regularly obtains the operation data, energy consumption data and environmental change data of each device in the room from the edge computing gateway, and dynamically optimizes the energy consumption function through a preset update algorithm. The cloud update module 5 runs on the cloud server, using a large amount of historical data and current device status information to adjust and improve the energy consumption model through machine learning or data analysis algorithms. The updated energy consumption function can better adapt to changes in the device under different environments and usage conditions. Subsequently, the cloud update module 5 sends the optimized energy consumption function back to the edge computing gateway to ensure that the system can adjust the working status of the device according to the latest energy consumption model to achieve continuous energy efficiency optimization and energy saving goals.

[0057] Reference Figure 5 , the wireless guest control system based on the edge computing gateway described in the embodiment of the present invention has established a Bluetooth Mesh network with the lights and curtains in the hotel in advance. If the guest wants to turn off the lights or control the curtains, he only needs to press the corresponding switch in the room. The command is sent to the wireless guest control system through the wired network. The system converts the command into a Bluetooth message and sends it to the corresponding device through the Bluetooth Mesh network to control the lights or curtains. The system integrates the cloud update module, Wi-Fi AP management system, wireless guest control system and Bluetooth technology through the edge computing gateway. The cloud update module is connected to the edge computing gateway through the network to update the energy consumption function of the system; the Wi-Fi AP management system is responsible for connecting devices such as mobile phones and computers through Wi-Fi; the wireless guest control system connects to the devices in the room (such as lights, curtains, etc.) through the Bluetooth network to monitor and control the device status. The wireless guest control system is embedded in the container of the edge computing gateway to ensure that it runs independently from the Wi-Fi AP system without interfering with each other. The entire system can optimize device energy consumption through cloud updates and local control to achieve intelligent management.

[0058] The embodiment of the present invention also discloses a readable storage medium.

[0059] A readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the wireless customer control method based on an edge computing gateway described in any one of the above embodiments. The computer-readable storage medium may include: any entity or device capable of carrying a computer program, a recording medium, a USB flash drive, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), and a software distribution medium, etc. The computer program includes a computer program code. The computer program code may be in source code form, object code form, an executable file, or some intermediate form, etc. The computer-readable storage medium may include: any entity or device capable of carrying a computer program code, a recording medium, a USB flash drive, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), and a software distribution medium, etc.

[0060] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present invention belong.

[0061] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, apparatus or device (such as a computer-based system, a system including a processing module, or other system that can fetch instructions from an instruction execution system, apparatus or device and execute instructions), or used in combination with these instruction execution systems, apparatuses or devices.

[0062] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A wireless customer control method based on edge computing gateway, characterized in that: include: Through the edge computing gateway, the status information of each device in the room and customer demand information are shared; Establishing a demand constraint model based on the customer demand information, and minimizing a preset energy consumption function with the demand constraint model; adjusting the status information of each device based on the result of minimizing the energy consumption function; And, controlling the corresponding device based on the adjusted status information.

2. The wireless customer control method based on edge computing gateway according to claim 1 is characterized in that: The customer demand information at least includes the air conditioning temperature variable T desired , light brightness variable L desired , curtain opening and closing state variable C desired And the TV switch state variable S desired .

3. The wireless customer control method based on edge computing gateway according to claim 2 is characterized in that: The step of establishing a demand constraint model based on the customer demand information and minimizing a preset energy consumption function using the demand constraint model includes: Based on the customer demand information, define the demand range of each device to form the demand constraint model; According to the energy consumption characteristics of each device, define the energy consumption function of each device; Combine the energy consumption functions of all devices into a total energy consumption objective function, and combine it with customer demand constraints to form an optimization problem; The energy consumption objective function is solved using an optimization algorithm to find the equipment operating state that meets customer needs and has the lowest energy consumption.

4. The wireless customer control method based on edge computing gateway according to claim 3 is characterized in that: The optimization algorithm includes a linear programming algorithm.

5. The wireless customer control method based on edge computing gateway according to claim 1 is characterized in that: The method further comprises: The collected equipment operation data, energy consumption data and environmental change data are regularly uploaded to the cloud server through the edge computing gateway; the cloud server updates the energy consumption function and sends it to the edge computing gateway through a preset update algorithm.

6. The wireless customer control method based on edge computing gateway according to claim 1, characterized in that: The adjusting the status information of each device based on the result of minimizing the energy consumption function includes: According to the calculation results of the minimization energy consumption function, the optimal working state of each device is determined; Verify whether the optimal working state meets the demand constraint model, and adjust the state information of each device after successful verification.

7. The wireless customer control method based on edge computing gateway according to claim 1 is characterized in that: The controlling the corresponding device based on the adjusted state information includes: Adjusting the status information into corresponding device adjustment instructions; The device adjustment instruction is sent to the corresponding device via the Bluetooth Mesh network.

8. A wireless customer control system based on edge computing gateway, built into a wireless router, characterized in that: The system comprises: A data acquisition module, at least for sharing status information of each device in the room and customer demand information; A data calculation module, at least used to establish a demand constraint model based on the customer demand information, and minimize a preset energy consumption function with the demand constraint model; A data adjustment module, at least used to adjust the status information of each device based on the energy consumption function minimization result; And, a data execution module is at least used to control a corresponding device based on the adjusted state information.

9. The wireless customer control system of the edge computing gateway according to claim 8, characterized in that: The system also includes: a cloud update module, which is at least used to update the energy consumption function through a preset update algorithm and send it to the edge computing gateway.

10. A readable storage medium, characterized in that: The readable storage medium stores computer instructions, and when the computer instructions are executed by a processor, a wireless customer control method based on an edge computing gateway as described in any one of claims 1 to 7 is implemented.

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