Hotel guest room control method and system based on AI model driving

Abstract

The embodiment of the invention provides a hotel guest room control method and system based on AI model driving, and the method comprises the steps: enabling a server to receive environment data collected by a sensor, and calling an AI model to carry out the analysis and understanding of the environment data, and obtaining an analysis result; the AI model generates a control instruction corresponding to the analysis result according to the analysis result; and the server inquires according to the control instruction to obtain equipment corresponding to the control instruction, and sends the control instruction to the equipment to realize intelligent control of the hotel customer or the smart home.

Description

Technical Field

[0001] The present application belongs to the field of smart home and hotel room intelligent control, and specifically relates to a hotel room control method and system driven by an AI model. Background Art

[0002] The basic definition of a hotel (also known as a guesthouse, inn, hostel, hotel, business travel, inn, inn, etc.) is a commercial institution that provides safe and comfortable space for users to rest or sleep for a short period of time. With the development of the domestic tourism industry, more and more services are provided in hotel rooms, and users' requirements are increasing. With the continuous development of science and technology, the demand for smart homes and hotel rooms is increasing. Traditional control methods have problems such as inconvenient operation and low intelligence, which cannot meet people's pursuit of convenient, efficient and intelligent life. In addition, the current intelligent control does not have the ability to understand intentions, scene understanding and reasoning, and can only achieve simple logical control. In this case, it cannot meet the personalized needs of users, which reduces the user's experience of staying. Summary of the invention

[0003] The present application provides a hotel room control method and system driven by an AI model, which can automatically control the hotel rooms and improve the user's accommodation experience.

[0004] In a first aspect, the present application provides a hotel room control method based on AI model driving, characterized in that the method comprises the following steps:

[0005] The server receives environmental data collected by the sensor, and calls the AI ​​model to analyze and understand the environmental data to obtain analysis results;

[0006] The AI ​​model generates control instructions corresponding to the analysis results according to the analysis results;

[0007] The server obtains the device corresponding to the control instruction according to the control instruction query, and sends the control instruction to the device to realize intelligent control of the hotel guests or smart homes.

[0008] In a second aspect, a hotel room control system driven by an AI model is provided, the system comprising:

[0009] A sensor unit for collecting environmental data;

[0010] An AI model unit is used to analyze and understand the environmental data to obtain an analysis result; and to generate a control instruction corresponding to the analysis result according to the analysis result;

[0011] The control execution unit is used to query and obtain the device corresponding to the control instruction according to the control instruction, and send the control instruction to the device to realize intelligent control of hotel guests or smart homes.

[0012] In a third aspect, the present application provides a computer storage medium storing a computer program for electronic data exchange, wherein the computer program enables a computer to execute some or all of the steps described in the first aspect of the present application.

[0013] The embodiments of the present application have the following beneficial effects:

[0014] The technical solution provided by this application provides a hotel room intelligent control and smart home integrated control method and system based on AI big model drive. By using AI big model to analyze and make decisions on environmental data, intelligent control of hotel rooms and smart homes is realized, the accuracy and convenience of control are improved, and a more comfortable and intelligent living environment is provided for users. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. 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 paying creative work.

[0016] Figure 1 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application;

[0017] Figure 2 This is a flowchart of a hotel room control method based on AI model drive provided in Example 1 of the present application;

[0018] Figure 3 This is a structural diagram of a hotel room control system driven by an AI model provided in an embodiment of the present application. DETAILED DESCRIPTION

[0019] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution 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, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0020] The terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, systems, products or devices.

[0021] 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.

[0022] The following is a schematic diagram of the structure of an electronic device involved in an embodiment of the present application.

[0023] This application also provides a hotel control system, such as Figure 1 As shown, the hotel control system includes: a server and a plurality of sensors connected to the server, the sensors include but are not limited to: a door card sensor, a camera, etc., the sensors are connected to the server in communication, and the communication connection can be a wired connection or a wireless connection. The server includes at least one processor (processor) 11 and a memory (memory) 12, and can also include a communication interface (CommunicationsInterface) 14, a display screen 16 and a bus 13. Among them, the processor 11, the memory 12, the display screen 16 and the communication interface 14 can complete the communication with each other through the bus 13. The communication interface 14 can transmit information, and the communication interface 14 can have a wireless communication function, and the wireless communication function can be a short-range wireless communication or a long-range communication function (such as LTE or NR mode). The processor 11 can call the logic instructions in the memory 12 to execute or support the method in the embodiment of the present application.

[0024] The memory 12, as a computer-readable storage medium, can be configured to store software programs, computer executable programs, such as program instructions or modules corresponding to the method in the embodiment of the present disclosure. The processor 11 executes functional applications and data processing by running the software programs, instructions or modules stored in the memory 12, that is, implementing or supporting the method in the embodiment of the present application.

[0025] The following introduces the main technical application scenarios of the embodiments of this application.

[0026] The first thing a hotel provides is a privacy-protected check-in environment, and some users also require personalized services. Taking current hotel services as an example, air conditioning, television, charging, and shopping have become very common functions. However, since existing hotels are unable to collect corresponding data and do not have the analysis and processing capabilities of large AI models, they are unable to achieve intelligent control of hotel rooms based on the hotel's scenarios.

[0027] The specific methods are introduced in detail below.

[0028] Embodiment 1

[0029] Embodiment 1 of the present application provides a hotel room control method based on AI model driving, and the above method is as follows Figure 1 The hotel control system shown executes, Figure 2 A flowchart of a hotel room control method driven by an AI model is provided in Example 1 of the present application, such as Figure 2 As shown, the above method comprises the following steps:

[0030] Step S201: The server receives environmental data collected by the sensor, and calls the AI ​​model to analyze and understand the environmental data to obtain analysis results;

[0031] Step S202: the AI ​​model generates a control instruction corresponding to the analysis result according to the analysis result;

[0032] Step S203: The server obtains the device corresponding to the control instruction according to the control instruction query, and sends the control instruction to the device to realize intelligent control of the hotel customer or smart home.

[0033] Optionally, the calling of the AI ​​model to analyze and understand the environmental data to obtain the analysis result specifically includes:

[0034] The AI ​​model generates input data of the AI ​​model based on the environmental data, inputs the input data into the AI ​​model for calculation to obtain a calculation result, and obtains the analysis result based on the calculation result.

[0035] The technical solution provided by this application provides a hotel room intelligent control and smart home integrated control method and system based on AI big model drive. By using AI big model to analyze and make decisions on environmental data, intelligent control of hotel rooms and smart homes is realized, the accuracy and convenience of control are improved, and a more comfortable and intelligent living environment is provided for users.

[0036] For example, the above control instruction may be a control instruction of a socket, specifically:

[0037] The server detects the status of the room card socket in the hotel room. If the room card socket status is inserted, the power status of all power sockets is periodically collected. Each time the data is collected, a state vector of the user socket is generated. When the power status of the socket is power on, the element value corresponding to the state vector is 1, otherwise it is 0. If the room card socket status is not inserted, the server extracts the first state vector corresponding to the previous sampling period, extracts the socket identifier with an element value of 1 in the first state vector, and determines the position corresponding to the socket identifier based on the mapping relationship between the socket identifier and the position relationship. If the position belongs to the range of sockets used by the user, the server controls the socket corresponding to the socket identifier to maintain power supply.

[0038] The following takes 4 plugs as an example, which are bedside socket 1, bedside socket 2, TV socket, and sideboard socket in order; if the power usage states are: power on, no power on, no power on, power on, the corresponding state vector is: 1001; if the power usage states corresponding to the next collection cycle are: no power on, power on, power on, power on, the corresponding state vector is: 0111; the above collection cycle can be set by the hotel itself, and generally does not need to be very frequent, for example, collection once every 5 minutes or 10 minutes is sufficient.

[0039] The above method may further include:

[0040] Combine multiple state vectors into a state matrix in the order of collection time; the server detects the row number or column number in the state matrix where the value of each row or column element is 1, and extracts the socket corresponding to the row number or column number according to a preset mapping relationship. If the location of the socket is not within the user's range, the server sends an alarm message to the hotel service system.

[0041] The following takes the above two vectors as an example. In other application scenarios, the number of vectors in the above state matrix will be larger. The above vectors, 1001, and 0111 form a state matrix;

[0042]

[0043] Then extract column number 4 where the value of each column element is 1. The socket corresponding to column number 4 is the sideboard socket. Assuming that the sideboard socket is not within the user's range, an alarm message is issued. If the sideboard socket is within the user's range (it is within the user's range based on the location), no alarm is issued.

[0044] The above-mentioned user-use socket range and non-user-use socket range can be determined by the hotel itself. For example, the sockets near the bedside cabinet and other locations can be the user-use socket range, the TV socket can be the non-user-use socket range, and so on.

[0045] For rooms with illegal devices installed, there are two characteristics. One is that as long as the room card is powered, the illegal device must be in continuous working state, that is, powered state. Another characteristic is that the socket from which it draws power must be a relatively hidden socket (that is, a socket that users will not use, such as a TV socket, etc.). Based on such characteristics, the above technical solution extracts the sockets that are always in power from the state matrix. In order to avoid false alarms, some sockets commonly used by users are determined as normal power supply. In this way, illegal devices can be effectively alarmed without generating too many false alarms. This solution can protect the privacy of users.

[0046] The hotel service system may be a server or a mobile terminal. For example, an alarm message may be directly sent to the terminal device of the hotel service personnel. The alarm message may carry the socket location and the room number, which makes it convenient for the hotel service personnel to check the same.

[0047] For example, the above method may further include:

[0048] The server records the status and status parameters of all devices in the room corresponding to the room card, and constructs a mapping relationship between the status and status parameters of all devices in the room and the user's identity information. The server collects the user's first facial data, and when determining the user's identity information based on the first facial data, extracts the status and status parameters of all devices in the room based on the mapping relationship, and determines whether to adjust all devices in the room to the said status and status parameters based on the camera position of the collected user's first facial data.

[0049] For example, the above-mentioned determination of whether to adjust all the devices in the room to the state and the state parameters based on the camera position of the collected first face data of the user may specifically include:

[0050] The server obtains the first position of the camera for collecting the first facial data of the user, calculates the first distance between the first position and the room position, obtains the second position of the camera for collecting the second facial data of the user, calculates the second distance between the second position and the room position, and if the second distance is less than the first distance, adjusts all the devices in the room to the state and state parameters; if the second distance is greater than the first distance, does not adjust all the devices in the room to the state and state parameters; the camera for the second facial data is a camera for identifying the user's identity information.

[0051] The above technical solution determines whether to adjust the equipment in the room to the state required by the user by identifying the user's identity information. The above equipment and status parameters include, for example, TV (whether it is used, the corresponding channel (i.e., status parameter)), air conditioning (temperature value), curtains (curtain opening distance), etc. If the distance decreases (corresponding to the second distance < the first distance), it is determined that the user is walking towards the room, which requires the use of the equipment in the room. Otherwise, the equipment in the room does not need to be used. It should be noted that the above distance is the walking distance, not the straight-line distance, and the floor information needs to be taken into account. The specific distance calculation method can be determined by referring to the technical solution of indoor positioning. It does not involve the improvement of the indoor positioning solution and will not be repeated here. This method can improve the user's hotel usage effect and facilitate the user to experience the specific usage effect.

[0052] For example, the above method may further include:

[0053] The server obtains the first mobile phone number and the first room number registered by the user, and receives a wifi login request sent by the mobile phone terminal, the wifi login request including: all searched wifi names and the first mobile phone number, the server queries whether the above wifi name contains the first room number corresponding to the first mobile phone number, if the query above wifi name contains the first room number corresponding to the first mobile phone number, the wifi login request is received, and the mobile phone terminal is allowed to log in to the wifi without a password.

[0054] When logging into the hotel's wifi, users usually log in with the username and password on the room card or room paper. This method cannot achieve seamless login for users. However, if users are allowed to log in directly, many users will log in to the same wifi, causing the wifi signal to deteriorate, insufficient wifi data channels, etc. In this way, it is necessary to distinguish the wifis logged in with different room numbers and achieve seamless login. Here, all searched wifi names and the first mobile phone number are carried in the wifi login request. In this way, it is possible to determine whether the user (i.e., the mobile phone terminal) is near the room number matched by the user by whether the first mobile phone number and the first room number of the level correspond. If so, the mobile phone terminal is allowed to log in to the wifi without a password. In this way, password-free login to the wifi is achieved, and seamless wifi login is achieved, which improves the hotel experience.

[0055] For example, the above method may further include:

[0056] The server extracts the data of room occupancy and check-in time within the hotel's historical time interval, and groups the data of room occupancy and check-in time by day to obtain multiple groups of data, each group of data includes the room occupancy and check-in time of the day, and uses the group data as the basic unit to fit the room occupancy and check-in time of the day to obtain the first function of room occupancy and check-in time f(t)=(at) 2 +b1; where t is the time in hours, a and b1 are the function constant variables of f(t), and the average value of a of each group of functions is extracted to obtain a 均 , calculate the average value of b1 of each group of functions to get b1 均 ; Construct the prediction function f(t)'=(a 均 -t) 2 +b1 均 ; Get the current time, estimate the room occupancy f(t1)' at the current time based on the current time t1 and the prediction function, extract the data on the number of clean rooms and time in the hotel's historical time interval, and use the data on the number of clean rooms and time to fit the second function of the data on the number of clean rooms and time f(x) = kx + b2; where x is the time in hours, k is the slope, and b2 is a constant variable. Calculate the number of clean rooms f(t1) at the current time t1 based on the current time. If f(t1)'>f(t1), send a delayed check-in message to the user.

[0057] The delayed check-in message may carry the delayed check-in time, which is equal to [f(t1)'-f(t1)] / k rounded up. Of course, the delayed check-in time may also be directly estimated as a set time, such as 1 hour or 2 hours, but when sending the message, the users are divided into multiple groups, and each group is sent a different delayed check-in time.

[0058] In the above, two functions are constructed to predict whether the hotel users will delay their check-in. In some application scenarios, such as the hotel corresponding to an amusement park, the guests staying in the rooms change with the hour in a curve. For example, hotel check-ins are generally after 13:00, so the occupancy rate is generally highest around 2:00 or 3:00. In this case, historical data is needed to fit the specific room occupancy curve, so that today's room occupancy can be predicted by time. For cleaning rooms, the change in quantity is linear, because the number of cleaners per day is fixed, and the number of rooms cleaned by one person per unit time is almost fixed, so it changes linearly. Then the number of clean rooms (that is, the number of rooms that can be occupied) can be estimated. After the estimation, if the predicted number of occupied rooms is greater than the number of clean rooms, then it is necessary to send a room delayed check-in message to the user, otherwise it may cause the user to be stranded in the hotel lobby. In layman's terms, when the user arrives at this time, there are no hotel rooms available, which greatly affects the user experience. Therefore, after notifying the user in advance of the delayed check-in, the user can arrange other matters and delay coming to the hotel to avoid being stranded in the hotel lobby. Therefore, through the above prediction, the hotel's guest rooms can be actually controlled to improve the user's hotel check-in experience.

[0059] See also Figure 3 , Figure 3 A schematic diagram of a hotel room control system driven by an AI model is provided, the system comprising:

[0060] Sensor unit 301, used for collecting environmental data;

[0061] The AI ​​model unit 302 is used to analyze and understand the environmental data to obtain an analysis result; and to generate a control instruction corresponding to the analysis result according to the analysis result;

[0062] The control execution unit 303 is used to query and obtain the device corresponding to the control instruction according to the control instruction, and send the control instruction to the device to realize intelligent control of hotel guests or smart homes.

[0063] Optional,

[0064] The AI ​​model unit 302 generates input data of the AI ​​model based on the environmental data, inputs the input data into the AI ​​model for calculation to obtain a calculation result, and obtains the analysis result based on the calculation result.

[0065] For example, the above system may further include a processing unit,

[0066] The processing unit is used to record the status and status parameters of all devices in the room corresponding to the room card, and construct a mapping relationship between the status and status parameters of all devices in the room and the user identity information. The server collects the first facial data of the user, and when it is determined that the identity information belongs to the user based on the first facial data, the status and status parameters of all devices in the room are extracted based on the mapping relationship, and it is determined whether to adjust all devices in the room to the said status and status parameters based on the camera position of the collected first facial data of the user.

[0067] For example,

[0068] The processing unit is specifically used to obtain the first position of the camera for collecting the first facial data of the user, calculate the first distance between the first position and the room position, obtain the second position of the camera for collecting the second facial data of the user, calculate the second distance between the second position and the room position, and if the second distance is less than the first distance, adjust all the devices in the room to the state and state parameters; if the second distance is greater than the first distance, do not adjust all the devices in the room to the state and state parameters; the camera for the second facial data is a camera that recognizes the user's identity information.

[0069] For example,

[0070] The processing unit is also used to obtain the first mobile phone number and the first room number registered by the user, and receive a wifi login request sent by the mobile phone terminal, the wifi login request including: all searched wifi names and the first mobile phone number, the server queries whether the above wifi name contains the first room number corresponding to the first mobile phone number, if the query above wifi name contains the first room number corresponding to the first mobile phone number, the wifi login request is received, and the mobile phone terminal is allowed to log in to the wifi without a password.

[0071] For example, the processing unit is further used to extract the data of room occupancy and check-in time within the historical time interval of the hotel, group the data of room occupancy and check-in time by day to obtain multiple groups of data, each group of data includes the room occupancy and check-in time of the day, and use the group data as the basic unit to fit the room occupancy and check-in time of the day to obtain the first function of room occupancy and check-in time f(t)=(at) 2 +b1; where t is the time in hours, a and b1 are the function constant variables of f(t), and the average value of a of each group of functions is extracted to obtain a 均 , calculate the average value of b1 of each group of functions to get b1 均 ; Construct the prediction function f(t)'=(a 均 -t) 2 +b1 均; Get the current time, estimate the room occupancy f(t1)' at the current time based on the current time t1 and the prediction function, extract the data on the number of clean rooms and time in the hotel's historical time interval, and use the data on the number of clean rooms and time to fit the second function of the data on the number of clean rooms and time f(x) = kx + b2; where x is the time in hours, k is the slope, and b2 is a constant variable. Calculate the number of clean rooms f(t1) at the current time t1 based on the current time. If f(t1)'>f(t1), send a delayed check-in message to the user.

[0072] An embodiment of the present application also provides a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, wherein the computer program enables a computer to execute part or all of the steps of any method described in the above method embodiments, and the above computer includes an electronic device.

[0073] The embodiment of the present application also provides a computer program product, the computer program product includes a non-transitory computer-readable storage medium storing a computer program, the computer program is operable to cause a computer to execute some or all of the steps of any method described in the method embodiment. The computer program product may be a software installation package, and the computer includes an electronic device.

[0074] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0075] In the several embodiments provided in the present application, it should be understood that the disclosed methods, devices and systems can be implemented in other ways. For example, the device embodiments described above are merely schematic; for example, the division of the units is only a logical function division, and there may be other division methods in actual implementation; for example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0076] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0077] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may be physically included separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0078] The above-mentioned integrated unit implemented in the form of a software functional unit can be stored in a computer-readable storage medium. The above-mentioned software functional unit is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform some steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: a USB flash drive, a mobile hard disk, a magnetic disk, an optical disk, a volatile memory or a non-volatile memory. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM) or a flash memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM) and direct RAM RAM (DR RAM). Various media that can store program code are available.

[0079] Although the present invention is disclosed as above, the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions without departing from the spirit and scope of the present invention, and can make various changes and modifications, including the combination of the above-mentioned different functions and implementation steps, including software and hardware implementation methods, all of which are within the scope of protection of the present invention.

Claims

1. A hotel room control method based on AI model driving, characterized in that: The method comprises the following steps: The server receives environmental data collected by the sensor, and calls the AI ​​model to analyze and understand the environmental data to obtain analysis results; The AI ​​model generates control instructions corresponding to the analysis results according to the analysis results; The server obtains the device corresponding to the control instruction according to the control instruction query, and sends the control instruction to the device to realize intelligent control of the hotel guests or smart homes.

2. The hotel room control method based on AI model drive according to claim 1 is characterized in that: The calling of the AI ​​model to analyze and understand the environmental data to obtain the analysis results specifically includes: The AI ​​model generates input data of the AI ​​model based on the environmental data, inputs the input data into the AI ​​model for calculation to obtain a calculation result, and obtains the analysis result based on the calculation result.

3. The hotel room control method based on AI model drive according to claim 1 is characterized in that: The method further comprises: The server records the status and status parameters of all devices in the room corresponding to the room card, and constructs a mapping relationship between the status and status parameters of all devices in the room and the user's identity information. The server collects the user's first facial data, and when determining the user's identity information based on the first facial data, extracts the status and status parameters of all devices in the room based on the mapping relationship, and determines whether to adjust all devices in the room to the said status and status parameters based on the camera position of the collected user's first facial data.

4. The hotel room control method based on AI model drive according to claim 3 is characterized in that: The determining whether to adjust all the devices in the room to the state and the state parameters based on the camera position of the collected first face data of the user specifically includes: The server obtains the first position of the camera for collecting the first facial data of the user, calculates the first distance between the first position and the room position, obtains the second position of the camera for collecting the second facial data of the user, calculates the second distance between the second position and the room position, and if the second distance is less than the first distance, adjusts all the devices in the room to the state and state parameters; if the second distance is greater than the first distance, does not adjust all the devices in the room to the state and state parameters; the camera for the second facial data is a camera for identifying the user's identity information.

5. The hotel room control method based on AI model drive according to claim 1 is characterized in that: The method further comprises: The server obtains the first mobile phone number and the first room number registered by the user, and receives a wifi login request sent by the mobile phone terminal, the wifi login request including: all searched wifi names and the first mobile phone number, the server queries whether the above wifi name contains the first room number corresponding to the first mobile phone number, if the query above wifi name contains the first room number corresponding to the first mobile phone number, the wifi login request is received, and the mobile phone terminal is allowed to log in to the wifi without a password.

6. A hotel room control system driven by AI model, characterized in that: The system comprises: A sensor unit for collecting environmental data; An AI model unit is used to analyze and understand the environmental data to obtain an analysis result; and to generate a control instruction corresponding to the analysis result according to the analysis result; The control execution unit is used to query and obtain the device corresponding to the control instruction according to the control instruction, and send the control instruction to the device to realize intelligent control of hotel guests or smart homes.

7. The hotel room control system based on AI model drive according to claim 6 is characterized in that: The AI ​​model unit generates input data of the AI ​​model based on the environmental data, inputs the input data into the AI ​​model for calculation to obtain a calculation result, and obtains the analysis result based on the calculation result.

8. The hotel room control system based on AI model drive according to claim 6 is characterized in that: The system further comprises: a processing unit, The processing unit is also used to record the status and status parameters of all devices in the room corresponding to the room card, and construct a mapping relationship between the status and status parameters of all devices in the room and the user identity information. The server collects the first facial data of the user, and when it is determined that the identity information belongs to the user based on the first facial data, the status and status parameters of all devices in the room are extracted based on the mapping relationship, and it is determined whether to adjust all devices in the room to the status and status parameters based on the camera position of the collected first facial data of the user.

9. The hotel room control system based on AI model drive according to claim 8, characterized in that: The processing unit is specifically used to obtain the first position of the camera for collecting the first facial data of the user, calculate the first distance between the first position and the room position, obtain the second position of the camera for collecting the second facial data of the user, calculate the second distance between the second position and the room position, and if the second distance is less than the first distance, adjust all the devices in the room to the state and state parameters; if the second distance is greater than the first distance, do not adjust all the devices in the room to the state and state parameters; the camera for the second facial data is a camera that recognizes the user's identity information.

10. The hotel room control system based on AI model drive according to claim 8, characterized in that: The system further comprises: The processing unit is also used to obtain the first mobile phone number and the first room number registered by the user, and receive a wifi login request sent by the mobile phone terminal, the wifi login request including: all searched wifi names and the first mobile phone number, the server queries whether the above wifi name contains the first room number corresponding to the first mobile phone number, if the query above wifi name contains the first room number corresponding to the first mobile phone number, the wifi login request is received, and the mobile phone terminal is allowed to log in to the wifi without a password.

Images