CN112734600B - Hotel personalized intelligent lighting method based on mobile phone APP - Google Patents
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Abstract
The application provides a hotel personalized intelligent lighting method based on a mobile phone APP, which comprises the steps of carrying out fuzzy classification on personal characteristic data of a user to obtain characteristic membership value after check-in registration and information acquisition, analyzing a dimming instruction to obtain each lamp modulation value, comparing the lamp modulation vector with historical check-in user data in a database based on a user characteristic membership value vector, and carrying out speculation on a lamp modulation vector preferred by the user according to similarity among vectors, wherein the speculation result is pushed to the user, and after confirmation, sending the dimming instruction to a dimmable lamp group through an output module. According to the application, the dimming preference of the lamp which is not operated in the guest room is deduced according to the individual characteristics of the user and the similarity of the dimming operation, and the lighting effect which the user is likely to be interested in can be quickly pushed to the user, so that personalized intelligent lighting recommendation and decision are realized.
Description
The application discloses a division application of application number 201910287080.6, application date 2019, 04 month 03 and application name of a hotel personalized intelligent lighting device, system and method based on mobile phone APP.
Technical Field
The invention relates to a hotel personalized intelligent lighting method based on a mobile phone APP, and belongs to the field of intelligent lighting.
Background
With the gradual maturity of the intelligent LED lighting technology, the popularization rate of the intelligent LED lighting is higher. The intelligent LED lamp has the advantages of high efficiency, energy saving, more diversified illumination modes, capability of switching illumination effects in real time according to different scene requirements and more humanization. The hotel industry is a representative service industry and is concerned with the check-in experience of customers. Because the primary use area of the customer is concentrated indoors and the use time is concentrated at night, the industry has a greater interest in efficient, practical and personalized intelligent lighting devices.
Meanwhile, with the continuous development of the internet industry and the arrival of big data age, the personalized recommendation function is taken as a product and service recommendation function capable of automatically eliminating redundant information and searching optimal results according to user characteristics, and the application range of the product and service recommendation function is becoming wider.
However, for the hotel industry, the intelligent lighting devices currently used in the industry are often limited to simple infrared, voice-controlled switch devices, or wireless remote control devices, and the like, so that the pertinence is not high, and the lighting experience with higher applicability cannot be provided for the user according to the personalized lighting of the user.
SUMMARY OF THE PATENT FOR INVENTION
The invention aims to provide a hotel personalized intelligent lighting device, a system and a method based on a mobile phone APP, which integrate the advantages of intelligent lighting equipment and personalized recommendation function and provide more personalized lighting experience for hotel check-in users.
The technical scheme of the invention is that the hotel personalized intelligent lighting device based on the mobile phone APP comprises a host unit and a user interface unit, wherein the host unit comprises an input module, a user characteristic analysis module, a user modulation analysis module, a lighting recommendation module, an output module and a storage module, and an operation panel is arranged in the user interface unit;
the host unit is configured to:
the user inputs registration information such as personal characteristic parameters of the user from the mobile phone APP terminal, and simultaneously inputs a dimming instruction for modulating the color temperature and the brightness of the adjustable lamp group in the hotel room through the mobile phone APP terminal, the information and the instruction are transmitted to the host unit through the input module and are transferred to the database of the external server through the host unit,
the personal characteristic parameters of the user comprise categories such as age, gender, region, occupation, favorite color temperature, favorite brightness, number of persons in the residence, trip purpose and the like,
The user characteristic analysis module processes and analyzes the personal characteristic data of the user according to categories, firstly, a fuzzy variable set is established for each category in the range of the discourse domain, and a membership function is established for each fuzzy variable in the set; then, according to the membership function, calculating the membership value of each piece of data in the personal characteristic data of the user corresponding to each fuzzy variable in the category of the user, and sequentially arranging all membership values into a characteristic membership value vector; then, the characteristic membership value vectors are respectively stored in a storage module and an external database,
the user modulation analysis module processes the dimming signals of the lamps in the corresponding dimmable lamp group in the dimming command input by the user through the APP terminal to obtain corresponding modulation values, the modulation values are sequentially arranged into a lamp modulation vector and then are respectively stored in the storage module and the external database,
the illumination recommendation module compares the characteristic membership value vector and the lamp modulation vector of the user with other historical user data in an external database, predicts the final lamp modulation vector of the user according to the similarity among the vectors, recommends the final lamp modulation vector to the user through a mobile phone APP terminal,
And after the user confirms the recommendation, a dimming instruction is sent to the dimmable lamp set through the output module.
Preferably, when the user's foreground registers the user, the necessary identity information, including the ID card number, the guest room number, etc., is stored in the database and transmitted from the database to the host unit in the guest room,
the mobile phone APP terminal is provided with three interfaces, namely a login interface, a registration interface and a lamp modulation interface, when a user logs in through the login interface of the mobile phone APP terminal, the host unit judges whether to allow the user to log in and enter a subsequent interface by comparing whether the identity information input by the user is in accordance with the foreground registration information,
after the login of the user is successful, information can be sent to the host unit through the registration interface and the lamp modulation interface, so that personal characteristic parameters of the user are perfected, and the lamp in the guest room is subjected to switching and brightness and color temperature modulation operation.
Preferably, the host unit is further configured to:
when a new check-in user u checks in the hotel for the first time and opens a mobile phone APP terminal for registration, the illumination recommendation module compares the characteristic membership value vector of the user with the characteristic membership value vectors of other historical check-in users v in the database according to the user registration information, calculates the similarity between the two vectors,
Wherein sim i (u, v) is the characteristic similarity of the users u, v in the dimension of the ith parameter category, I is the category set of the ages and the like, j is the number of fuzzy variable sets in the ith parameter category, mu ik (u i )、μ ik (v i ) The parameter values of users u, v on the i-th class correspond to the membership value of the k-th fuzzy variable in that class, k=1, 2.
For example, for an age parameter category, 4 fuzzy variables of teenagers, young, middle-aged, elderly, etc. may be set; for the color temperature parameter class, 3 blur variables of low color temperature, medium color temperature, high color temperature, and the like can be set.
Preferably, the favorite color temperature may be a color temperature list according to time periods of morning, afternoon and evening; the travel purpose can be travel, work, meeting friends and the like, and the work can be subdivided into activities such as business, engineering, technical service and the like.
Preferably, the host unit is further configured to:
for a non-first user, when the user u modulates the color temperature and brightness of the lamp through the mobile phone APP terminal, the modulation information is recorded, and meanwhile, the illumination recommendation module establishes a lamp modulation vector [ X ] according to the modulation value u ,Y u ]:
Wherein X is u Representing the brightness modulation value of user u to part of lamps, such as m lamps, in the adjustable light group in guest room, wherein the corresponding value is x 1 To x m ,Y u Color temperature modulation values of users u for m lamps in guest rooms are represented, and the corresponding values are y 1 To y m ,
Then, based on the lamp modulation vector, comparing the lamp modulation vector with the lamp modulation vector of the historical entering user stored in the database, and calculating the vector similarity one by one:
sim(u,v)=α·sim x +(1-α)·sim y
wherein m represents the number of lamps commonly modulated by the users, and x i,u 、y i,u 、x i,v 、y i,v Representing the luminance and color temperature modulation values of the luminaire by the incumbent users u and v respectively,respectively represent the average value of the corresponding modulation values, +.>For the arithmetic mean of the luminance modulation values of user u for m modulated lamps,
simx(u,v)、sim y (u, v) and sim (u, v) represent the luminance similarity, the color temperature similarity and the overall vector similarity of u and v, respectively, the overall similarity is a weighted sum of the luminance similarity and the color temperature similarity, and α is a weight of the luminance similarity.
Preferably, the host unit is further configured to:
after vector similarity calculation is completed, taking K historical check-in users with highest similarity as neighbors of u and forming a neighbor set of u, and then presuming a recommended brightness modulation value x 'of a lamp i in a guest room of the check-in user u according to historical modulation information of the check-in users in the neighbor set' u,i And a color temperature modulation value y' u,i :
Wherein i=1, 2..n, n is the number of lights in the living room where the user u has not yet determined the modulation value;
the output module outputs the brightness modulation value x' u,i And a color temperature modulation value y' u,i And sending the modulation data to the mobile phone APP terminal, storing the modulation data returned by the mobile phone APP terminal after confirmation into a database, and sending the modulation data to a driver of the lamp bank through an output module.
Preferably, the lamps i are lamps which are not modulated by the user u and confirm the operation in the guest room.
In another embodiment of the present invention, the host unit may be further configured to:
when a new user u enters and opens a mobile phone APP terminal for registration for the first time, classifying the new user u by a fuzzy classification method according to user registration information, and calculating the classification:
F=S+N+Y+D
wherein S is the sex of the living user, such as 0 for men and 1 for women; n is the number of people in the house, and the general values are 1,2, 3 and the like; y is the age of the user, ten digits of the actual age value minus 20 are taken and cut off to be 0 to 4; d is for trip purpose, and its numerical value is from 0 to 6, and corresponds to business, travel, reception, leisure, meeting, office and long renting respectively. F is a classification value for the living users, and the users that get the same score are classified into the same category, which may take a value of 1 to 14, i.e., all historical living users are classified into 14 categories.
After the user enters a guest room, the illumination recommendation module compares the F value of the user with F values of other historical living users in an external database, combines the users with the same value into a neighbor set of the user, calculates average values of the final lamp modulation vectors of the user according to the lamp modulation values of all the users in the neighbor set, uses the average values as a presumption value, combines the presumption value into a modulation vector, and recommends the modulation vector to the user through a mobile phone APP terminal.
In yet another embodiment of the present invention, there is also provided a smart lighting system for a hotel individuation based on a mobile APP, comprising an adjustable light color lamp set having light properties of which both brightness and color temperature are adjustable, a user interface unit for performing parameter input and dimming operations, a mobile APP terminal, a server, and a host unit respectively connected to the lamp set, the user interface unit, the mobile APP terminal and the server,
the host unit includes an input module, a user characteristic analysis module, a user modulation analysis module, a lighting recommendation module, an output module, and a storage module, and is configured to:
the user inputs registration information such as personal characteristic parameters of the user from the mobile phone APP terminal, and simultaneously inputs a dimming instruction for modulating the color temperature and brightness of the lamp set in the hotel room through the mobile phone APP terminal, the information and the instruction are transmitted to the host unit through an input module in the control unit and are transferred to a database of the server through the host unit,
The personal characteristic parameters of the user comprise categories such as age, gender, region, occupation, favorite color temperature, favorite brightness, number of persons in the residence, trip purpose and the like,
when a new check-in user u checks in a hotel for the first time, the user characteristic analysis module processes and analyzes the personal characteristic data of the user according to categories, firstly, a fuzzy variable set is established for each category in the range of the domain of the user, and a membership function is established for each fuzzy variable in the set; then, according to the membership function, calculating the membership value of each piece of data in the personal characteristic data of the user corresponding to each fuzzy variable in the category of the user, and sequentially arranging all membership values into a characteristic membership value vector; then, the characteristic membership value vector is respectively stored in a storage module and a server database,
the user modulation analysis module processes the dimming signals of the lamps in the corresponding dimmable lamp group in the dimming command input by the user through the APP terminal to obtain corresponding modulation values, the modulation values are sequentially arranged into a lamp modulation vector and then are respectively stored in the storage module and the server database,
the illumination recommendation module compares the characteristic membership value vector and the lamp modulation vector of the user with other historical check-in user data in a server database, predicts the final lamp modulation vector of the user according to the similarity among the vectors, recommends the final lamp modulation vector to the user through a mobile phone APP terminal,
After the user confirms the recommendation, a dimming instruction is sent to the dimmable lamp set through the output module,
the similarity of the characteristic membership value vector is calculated according to the following formula:
wherein,,
sim i (u, v) is the characteristic similarity between the new living user u and the historical living user v in the database in the dimension of the ith parameter category, I is the category set of the age and the like, j is the number of fuzzy variable sets in the ith parameter category, mu ik (u i )、μ ik (vi) The parameter values of users u, v on the i-th class correspond to the membership value of the k-th fuzzy variable in that class, k=1, 2.
Preferably, the lamp group is composed of a plurality of dimmable LED lamps and is distributed on the ceiling of a hotel, the driver of the LED lamps is connected with a host unit through a communication interface, the host unit changes the driving current of each driving channel in the LED lamps through the driver according to the instruction sent by the mobile phone APP terminal to realize the modulation of the brightness and the color temperature,
the modulation value is the PWM wave duty ratio value of the driving current of each driving channel,
the mobile phone APP terminal can be connected with the host unit through a wireless route in the guest room, and meanwhile, the host unit is connected with the light color adjustable LED lamp set and the server through a wired connection mode.
In still another embodiment of the present invention, there is also provided a hotel personalized intelligent lighting method based on a mobile phone APP, comprising the steps of:
s1, initializing, registering and information collecting the user,
the system receives registration information such as personal characteristic parameters of a user through a mobile phone APP terminal, and the registration information is transferred to a database of a server by a host unit, wherein the personal characteristic parameters of the user comprise categories such as age, gender, area, occupation, favorite color temperature, favorite brightness, number of people in the house, trip purpose and the like,
establishing fuzzy variable sets in the range of the discourse domain for each user personal characteristic parameter category, establishing membership functions for each fuzzy variable in the sets,
s2, a host unit in the hotel room judges whether a user first check-in and builds a user personality vector, if the user first check-in, the process goes to S3, otherwise, a mobile phone APP terminal receives a dimming instruction for modulating the color temperature and the brightness of a dimmable lamp group in the hotel room by the user, processes dimming signals of lamps in the corresponding dimmable lamp group in the dimming instruction to obtain corresponding modulation values, and sequentially arranges the modulation values into a lamp modulation vector serving as the user personality vector, then goes to S4,
S3, for the first-time user, firstly, calculating membership value corresponding to the personal characteristic parameter value of the user based on membership function of each fuzzy variable of the category of the parameter for each personal characteristic parameter, and sequentially arranging all the membership values into a characteristic membership value vector as a user personality vector,
s4, respectively storing the user personality vectors into a storage module of the host unit and a server database,
s5, comparing the user personality vector of the user with other historical check-in user data in a server database, according to the similarity between the vectors, presuming the lamp modulation vector preferred by the user,
s6, recommending the presumption result to a user through the mobile phone APP terminal, after the user confirms or adjusts the recommendation, transmitting the confirmed lamp modulation vector to the dimmable lamp group through an output module of the host unit to dim, and simultaneously storing the lamp modulation vector into a server database.
Preferably, the step S1 further includes:
when the user foreground registers in the living, the registered necessary identity information including the ID card number, the guest room number and the like is stored in the server database and transmitted to the host unit in the living room by the database,
Setting three interfaces, namely a login interface, a registration interface and a lamp modulation interface, on the mobile phone APP terminal, when a user logs in through the login interface of the mobile phone APP terminal, the host unit judges whether to allow the user to log in and enter a subsequent interface by comparing whether the identity information input by the user is in accordance with the foreground registration information,
after the login of the user is successful, information can be sent to the host unit through the registration interface and the lamp modulation interface, so that personal characteristic parameters of the user and the modulation operation of brightness and color temperature on lamps in a guest room are perfected.
Preferably, in the step S1, the server adopts a cloud server, and after the system receives registration information such as personal characteristic parameters of the user through the mobile phone APP terminal, the mobile phone APP terminal directly stores the information into a database of the cloud server.
Preferably, the step S2 further includes:
for a non-first-time user, when the user u modulates the color temperature and brightness of the lamp through the mobile phone APP terminal, the modulation information is recorded, and a lamp modulation vector [ X ] is established according to the modulation value u ,Y u ]:
Wherein X is u The brightness modulation value of the user u to part of m lamps in the adjustable lamp group in the hotel room is represented by x 1 To x m ,Y u Representing the color temperature modulation value of the user u to the m lamps, wherein the corresponding value is y 1 To y m ;
The step S5 further includes:
based on the lamp modulation vectors of the m lamps, comparing the lamp modulation vectors with the lamp modulation vectors of the historical entering users stored in the database, and calculating vector similarity one by one:
sim(u,v)=α·sim x +(1-α)·sim y
wherein m represents the number of lamps commonly modulated by the users, and x i,u 、y i,u 、x i,v 、y i,v Representing the luminance and color temperature modulation values of the luminaire by the incumbent users u and v respectively,respectively represent the average value of the corresponding modulation values, +.>For the arithmetic mean of the luminance modulation values of user u for m modulated lamps,
sim x (u,v)、sim y (u, v) and sim (u, v) represent the luminance similarity, the color temperature similarity and the overall vector similarity of u and v, respectively, the overall similarity is a weighted sum of the luminance similarity and the color temperature similarity, and α is a weight of the luminance similarity.
Preferably, the step S5 further includes:
for the first-time user u, comparing the characteristic membership value vector of the user with the characteristic membership value vectors of other historical user v in the database, calculating the similarity between the two vectors,
wherein sim is i (u, v) is the characteristic similarity of the users u, v in the dimension of the ith parameter category, I is the category set of the ages and the like, j is the number of fuzzy variable sets in the ith parameter category, mu ik (u i )、μ ik (vi) The parameter values of users u, v on the i-th class correspond to the membership value of the k-th fuzzy variable in that class, k=1, 2.
Preferably, the step S5 further includes:
after the vector similarity is calculatedAfter the processing, taking K historical check-in users with highest similarity as neighbors of u and forming a neighbor set of u, and then presuming a recommended brightness modulation value x 'of a lamp i in a guest room of the check-in user u according to the historical modulation information of the check-in users in the neighbor set' u,i And a color temperature modulation value y' u,i :
Wherein i=1, 2, n;
the step S6 includes:
the host unit modulates the brightness modulation value x' u,i And a color temperature modulation value y' u,i And sending the modulation data to the mobile phone APP terminal, storing the modulation data returned by the mobile phone APP terminal after confirmation into a database, and sending the modulation data to a driver of the adjustable light group through an output module.
Preferably, the lamps i are lamps which are not modulated by the user u and confirm the operation in the guest room.
Preferably, the method further comprises the following steps:
the PWM wave duty ratio value of the driving current of each driving channel in the adjustable light lamp group is used as a modulation value, the modulation value is transmitted in the dimming command,
an operation panel is arranged in a hotel room to input parameters, meanwhile, the parameters are displayed in an auxiliary mode through a display screen, and after a user confirms the light modulation vector, the vector is displayed on the display screen in a list mode.
In yet another embodiment of the present invention, the step S3 employs the following process:
when a new check-in user u checks in for the first time and opens a mobile phone APP terminal to register, firstly classifying the new check-in user u by adopting a fuzzy classification method according to user registration information, and calculating the classification of the new check-in user u:
F=S+N+Y+D
wherein S is the sex of the living user, such as 0 for men and 1 for women; n is the number of people in the house, and the general values are 1, 2, 3 and the like; y is the age of the user, ten digits of the actual age value minus 20 are taken and cut off to be 0 to 4; d is for trip purpose, and its numerical value is from 0 to 6, and corresponds to business, travel, reception, leisure, meeting, office and long renting respectively. F is the classification value of the living users, the users with the same score are classified into the same class, the numerical value of the users can be 1 to 14, namely, all the historical living users are classified into 14 classes;
step S5 employs the following processing:
after the first user enters the guest room, comparing the F value with F values of other historical user entering in a server database, combining the users with the same value into a neighbor set of the user, calculating average numbers of lamp modulation vectors preferred by the user according to the lamp modulation values of all users in the neighbor set, then using the average numbers as the estimated values, combining the estimated values into a modulation vector, and recommending the modulation vector to the user through a mobile phone APP terminal.
In the lighting system, the mobile phone APP terminal is connected with the host unit through wireless communication such as a WIFI interface, and the mobile phone APP terminal can send user registration information and regulation and control instructions to the host unit through the WIFI network of the hotel guest room. The host unit is connected with the LED strings of the adjustable light color LED lamps through the driver, the brightness and color temperature of the adjustable light color LED lamp group are modulated according to the regulation and control instruction of the mobile phone APP terminal, meanwhile, the user is input with information and the regulation and control instruction to enter a database, the user is compared with other histories, the user regulation and control parameters are presumed according to the characteristics of the user and the similarity of the modulation values of the lamps in the regulation and control instruction, and the parameters are recommended to the user through the mobile phone APP terminal so as to meet the personalized lighting requirements of the user.
The utility model provides an adjustable photochromic LED banks comprises a plurality of luminance, colour temperature adjustable LED lamp, to the hotel of transformation can be according to the original lamps and lanterns overall arrangement of hotel and set up on the hotel's ceiling to link to each other with the host unit, the host unit contains WIFI communication module, wireless router and the cell-phone APP terminal realization communication in the guest room environment are linked to this module to accessible, simultaneously through wired connection's mode, link to each other with adjustable photochromic LED lamp and server. After recommending the presumed lamp modulation vector to the user, the host unit controls the driver to correspondingly change the driving current of each driving channel of the adjustable light color LED lamp by changing the duty ratio of PWM waves according to the confirmation instruction sent by the mobile phone APP terminal, so as to realize the brightness and color temperature modulation of each LED lamp in the guest room.
Recommended brightness modulation value x' u,i And a color temperature modulation value y' u,i And after the calculation is completed, combining the lamp modulation vectors into lamp modulation vectors, transmitting the lamp modulation vectors to the mobile phone APP terminal, and displaying the lamp modulation vectors on an interface of the mobile phone APP terminal. The user can directly confirm the modulation parameter list corresponding to the vector, and can also modify the modulation parameters of part of the LED lamps. After the user clicks on the APP interface to confirm, the mobile phone APP terminal sends a lamp modulation instruction to the host unit according to various modulation parameters on the interface; and the host unit stores the lamp modulation vector into a database of the server, and simultaneously sends corresponding PWM duty cycle modulation values to each driver of the LED lamp through the output module, so that scene illumination in the guest room is realized.
The invention has the advantages that:
1. the similarity calculation is carried out according to the category analysis of the user characteristics, so that the lighting requirement of the user is presumed to be checked for the first time, and the problem of cold start of recommended application is solved;
2. after the user modulates part of the lamplight, the system can utilize the similar modulation of the historical entering user to infer the modulation requirement of the system on other lamplight, and the lighting effect is more targeted;
3. the invention uses the mobile phone APP to control, can realize remote control, single-lamp dimming and one-key switch of recommended scenes, and is simple and convenient.
Drawings
FIG. 1 is a workflow diagram of a hotel personalized intelligent lighting method based on a mobile phone APP;
fig. 2 is a block diagram of a hotel personalized intelligent lighting system based on a mobile phone APP by adopting the lighting method of the invention;
FIG. 3 is a schematic illustration of a hotel personalized intelligent lighting system application environment;
FIG. 4 is a schematic diagram of an attribute membership function;
fig. 5 is a lamp modulation parameter personalization recommendation signal flow diagram.
Wherein:
1000 mobile phone APP based hotel personalized intelligent lighting system, 100 host units, 200 adjustable light groups, 300 user interface units, 400 mobile phone APP terminals, 500 servers, 800 mobile phone APP based hotel personalized intelligent lighting devices,
110 input module, 120 user characteristic analysis module, 130 illumination recommendation module, 140 output module, 150 storage module, 160 user modulation analysis module,
210, the driver, 220LED lamp,
310 display screen, 320 operation panel.
Detailed Description
The preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings, but the present invention is not limited to these embodiments only. The invention is intended to cover any alternatives, modifications, equivalents, and variations that fall within the spirit and scope of the invention.
In the following description of preferred embodiments of the invention, specific details are set forth in order to provide a thorough understanding of the invention, and the invention will be fully understood to those skilled in the art without such details.
The invention is more particularly described by way of example in the following paragraphs with reference to the drawings. It should be noted that the drawings are in a simplified form and are not to scale precisely, but rather are merely intended to facilitate and clearly illustrate the embodiments of the present invention.
Example 1
As shown in fig. 1, the hotel personalized intelligent lighting method based on the mobile phone APP provided by the invention comprises the following steps:
s1, initializing, registering and information collecting the user,
the system receives registration information such as personal characteristic parameters of a user through a mobile phone APP terminal, and the registration information is transferred to a database of a server by a host unit, wherein the personal characteristic parameters of the user comprise categories such as age, gender, area, occupation, favorite color temperature, favorite brightness, number of people in the house, trip purpose and the like,
establishing fuzzy variable sets in the range of the discourse domain for each user personal characteristic parameter category, establishing membership functions for each fuzzy variable in the sets,
S2, a host unit in the hotel room judges whether a user first check-in and builds a user personality vector, if the user first check-in, the process goes to S3, otherwise, a mobile phone APP terminal receives a dimming instruction for modulating the color temperature and the brightness of a dimmable lamp group in the hotel room by the user, processes dimming signals of lamps in the corresponding dimmable lamp group in the dimming instruction to obtain corresponding modulation values, and sequentially arranges the modulation values into a lamp modulation vector serving as the user personality vector, then goes to S4,
s3, for the first-time user, firstly, calculating membership value corresponding to the personal characteristic parameter value of the user based on membership function of each fuzzy variable of the category of the parameter for each personal characteristic parameter, and sequentially arranging all the membership values into a characteristic membership value vector as a user personality vector,
s4, respectively storing the user personality vectors into a storage module of the host unit and a server database,
s5, comparing the user personality vector of the user with other historical check-in user data in a server database, according to the similarity between the vectors, presuming the lamp modulation vector preferred by the user,
S6, recommending the presumption result to a user through the mobile phone APP terminal, after the user confirms or adjusts the recommendation, transmitting the confirmed lamp modulation vector to the dimmable lamp group through an output module of the host unit to dim, and simultaneously storing the lamp modulation vector into a server database.
The process and application of the present invention are described in detail below.
As shown in fig. 2, the hotel personalized intelligent lighting system 1000 based on the mobile phone APP adopting the lighting method of the invention comprises a hotel personalized intelligent lighting device 800 based on the mobile phone APP, a tunable light group 200 with adjustable brightness and color temperature, a server 500 and a mobile phone APP terminal 400.
The hotel personalized intelligent lighting device 800 based on the mobile phone APP comprises a host unit 100 and a user interface unit 300. An input module 110, a user characteristic analysis module 120, an illumination recommendation module 130, an output module 140, a storage module 150, and a user modulation analysis module 160 are provided in the host unit 100.
In the hotel guest room lighting system, a hotel individuation intelligent lighting device 800 based on a mobile phone APP is respectively connected with a tunable light group 200 with adjustable brightness and color temperature, a server 500 and a mobile phone APP terminal 400. The user interface unit 300 and the mobile phone APP terminal 400 can be used for inputting registration information such as personal characteristic parameters of a user and performing dimming operation on the dimmable light fixture 200 in a hotel room. And both the registration information and the dimming command are transmitted to the host unit 100 through the input module 110 and are restored by the host unit into a database within the server 500.
Referring to fig. 3, the light color adjustable lamp set 200 is an LED lamp set, which is composed of a plurality of LED lamps with adjustable brightness and color temperature. The LED lamps are arranged according to functional partitions according to the guest room structure, and for a refitted hotel with the traditional lamps replaced by the LED lamps, the LED lamps can be arranged on the ceiling of the hotel according to the original lamp layout. The LED lamps are connected to the host unit 100 by wired communication, e.g. up to 64 LED lamps can be connected to one host unit when DALI bus is used. The host unit comprises a WIFI communication module, and can be connected to a wireless router in a guest room environment through the wireless module so as to realize communication with the mobile phone APP terminal 400. Meanwhile, the host unit 100 is also connected to the user interface unit 300 and the database of the server 500 by means of a wired connection. The host unit 100 changes the duty ratio value of the PWM wave transmitted to the LED lamp driver through the output module according to the operation signal transmitted from the user interface unit 300 or the mobile phone APP terminal 400, so that the driver changes the driving current transmitted to each driving channel, and realizes the brightness and color temperature modulation of each LED lamp.
With reference to fig. 1, 2 and 5, the invention analyzes the preference of the user to the light output of each lamp in the lamp group in the guest room to modulate the guest room light, thereby realizing various scene illumination. The preference analysis is based on dimming data of a part of lamps mainly from the current user, based on the dimming data of the brightness, the color temperature and the like of the operated dimming lamps, the data are compared with the dimming data of the same lamps of the historical user recorded in the server database, the similarity degree is analyzed, and accordingly the dimming preference of the current user is extrapolated based on the dimming data of the lamp which is not operated by the historical user for the current user, and the extrapolated result is presented to the user for decision. Based on accumulation of data, when a user enters a new room type of a hotel or other hotels of a chain hotel group, dimming preference speculation in the guest room of the new hotel can be performed according to the existing modulation data of the lamp light, so that personalized intelligent lighting recommendation and decision making are realized.
For this purpose, the user modulation analysis module 160 processes the dimming signals of the lamps in the corresponding dimmable lamp set 200 in the dimming command input by the user through the APP terminal 400 to obtain corresponding modulation values, and sequentially arranges the modulation values into a lamp modulation vector, and then stores the lamp modulation vector in the storage module and the server database, respectively.
Referring to fig. 1, 2 and 3, in a hotel room, a dimmable LED lamp set 200 is composed of 11 LED lamps with adjustable brightness and color temperature, which are arranged on the ceiling of the hotel. The host unit 100 and the driver 210 are placed in a suspended ceiling of a bathroom of a guest room, and the server 500 is placed in a hotel room.
When a user registers in the foreground, according to the rule, the identity card information, the contact way and the guest room number are required to be registered, and the information can be used as a basic information table to be operated by the hotel foreground and written into a database of a server, wherein the identity card number is used as a main key ID (unique identifier) of the user.
The database of the server is also provided with a dimming information table of the LED lamps in various rooms by users, and the dimming preference of the dimming information table is stored in a lamp modulation vector format. Each record of the table comprises a user name, an identity card number and modulation parameters of each driving channel of 11 LED lamps in a guest room.
After the front-end registration is completed, the user enters the guest room and is connected to the host unit 100 through the mobile phone APP terminal 400, and the mobile phone APP terminal 400 at least comprises three interfaces, namely a login interface, a registration interface and a lamp modulation interface. Comparing the information input by the user with the information recorded in the database of the server 500 in the login interface, and if the information is matched with the information, judging the information as a compliant user and allowing the user to enter a subsequent interface; after the login of the user is successful, the user can enter a registration interface and a lamp modulation interface, and personal information is perfected through the registration interface; meanwhile, when a user enters a lamp modulation interface and operates the slider to modulate lamp parameters, and a slide rrelease () event of the mobile phone APP terminal 400 is triggered, the APP terminal 400 transmits a dimming signal to the host unit 100 in response to the event.
Wherein, the APP terminal 400 has a dimming interface for each lamp, typically, the brightness of each lamp can be represented by a sliding bar, and the user can adjust the brightness between 0% and 100% by moving the cursor of the sliding bar up and down; for the color temperature, a sector ring similar to a sector with the width of 120-150 degrees of a pointer multimeter can be used for representing the adjustable color temperature interval, and a user can move a cursor to adjust the color temperature. After the user setting is completed, the APP terminal 400 transmits the brightness and color temperature setting values to the host unit 100 through a dimming signal.
The user modulation analysis module 160 in the host unit 100 analyzes the modulated light signals, respectively converts the brightness setting value and the color temperature setting value into PWM duty ratio values, i.e. modulation values, corresponding to the driving channel currents according to the preset brightness-driving current and color temperature-driving current correspondence, respectively, and sequentially arranges the modulation values into a lamp modulation vector, and then respectively stores the lamp modulation vector in the database of the storage module 150 and the server 500. Meanwhile, the PWM duty ratio values are sent to the driver 210 of the corresponding LED lamp 220 in the dimmable lamp set 200 through the output module 140, and the driver 210 changes the driving current accordingly, so that the brightness and the color temperature of the corresponding LED lamp 220 are respectively adjusted to the set values of the APP terminal 400.
Then, the illumination recommendation module 130 compares the lamp modulation vector of the user with other historical user data in the database of the server 500, and according to the similarity between the vectors, presumes the lamp modulation vector preferred by the user, and recommends the lamp modulation vector to the user through the mobile phone APP terminal 400; after the user confirms the recommendation, a dimming command comprising the modulation values of all driving channels of the LED lamps or the PWM duty ratio value of the driving current in the guest room is sent to the dimmable lamp group 200 through the output module 140, so that scene illumination is realized.
For a non-first-time user, when the user u modulates the color temperature and brightness of the lamp through the mobile phone APP terminal, the user modulation analysis module records the modulation information of the user, and the illumination recommendation module establishes a lamp modulation vector [ X ] according to the modulation value of the user modulation analysis module u ,Y u ]:
Wherein X is u Representing the brightness modulation value of user u to part of lamps, such as m lamps, in the adjustable light group in guest room, wherein the corresponding value is x 1 To x m ,Y u Color temperature modulation values of users u for m lamps in guest rooms are represented, and the corresponding values are y 1 To y m 。
The m lamps in the guest room with modulation operation can be the lamps belonging to the guest room in the current check-in, or can be other lamps of the guest room with modulated light parameters in the past check-in of the user, for example, the lamps of guest rooms in other hotels in the range of the hotel which can acquire data, the lamps of guest rooms in other different room types in the current check-in hotel, or the lamps in guest rooms in the same room type but different room numbers in the current check-in hotel.
Then, based on the lamp modulation vector, the illumination recommendation module compares the lamp modulation vector with lamp modulation vectors of other users v with historic check-in stored in a server database, and calculates vector similarity one by one:
sim(u,v)=α·sim x +(1-α)·sim y
Wherein m represents the number of lamps which are modulated by the users u and v together, and x i,u 、y i,u 、x i,v 、y i,v Respectively represent intoTo maintain the brightness and color temperature modulation values of users u and v for the fixture,respectively represent the average value of the corresponding modulation values, the arithmetic mean of the brightness and color temperature modulation values of the m modulated lamps by the user u,
sim x (u,v)、sim y (u, v) and sim (u, v) respectively represent the luminance similarity, the color temperature similarity and the overall vector similarity of u and v, the overall similarity is a weighted sum of the luminance similarity and the color temperature similarity, and alpha is a weight of the luminance similarity with a value between 0 and 1.
Preferably, when the number of historic living users who have modulated m lamps together with the living user u is not enough, the number of lamps which have been modulated together may be reduced.
Preferably, when the number of historical occupancy users who have modulated m lamps together with the occupancy user u is insufficient, one or more of the lamps may be replaced with a lamp in which the occupancy user u is not modulated but the selected historical occupancy user has a modulation record for the replaced lamp, and the modulation value of the occupancy user u for the replaced lamp is set to a default initial value of the lamp, such as 80% when calculating the vector similarity.
Then, after the vector similarity calculation is completed, taking K historical check-in users with highest similarity as the neighbors of u and forming a neighbor set of u, and then, presuming the recommended brightness modulation value x 'of the lamp i in the guest room of the check-in user u according to the historical modulation information of the check-in users in the neighbor set' u,i And a color temperature modulation value y' u,i :
Wherein i=1, 2..n, n is the number of lights in the living room where the user u has not yet determined the modulation value;
the output module outputs the brightness modulation value x' u,i And a color temperature modulation value y' u,i And sending the modulation data to the mobile phone APP terminal, storing the modulation data returned by the mobile phone APP terminal after confirmation into a database, and sending the modulation data to a driver of the lamp bank through an output module.
K is preferably set to a smaller value in accordance with the richness of the data record, for example, the value is initially increased to a maximum value when the collected data record is more and more.
Because the function of some lamps is unique like that of a mirror front lamp, if all historical resident users in a neighbor set of u do not modulate a certain lamp i, if all resident users in the set are considered to be satisfied with the default initial value of the lamp modulation value, or the brightness and color temperature values of the lamp do not influence the resident experience, the default modulation value of the lamp is used as a recommended value instead of a calculated value.
Recommended brightness modulation value x' u,i And a color temperature modulation value y' u,i And after the calculation is completed, combining the lamp modulation vectors into lamp modulation vectors, transmitting the lamp modulation vectors to the mobile phone APP terminal, and displaying the lamp modulation vectors on an interface of the mobile phone APP terminal. The user can directly confirm the modulation parameter list corresponding to the vector, and can also modify the modulation parameters of part of the LED lamps. After the user clicks on the APP interface to confirm, the mobile phone APP terminal sends a lamp modulation instruction to the host unit according to various modulation parameters on the interface; and the host unit stores the lamp modulation vector into a database of the server, and simultaneously sends corresponding PWM duty cycle modulation values to each driver of the LED lamp through the output module, so that scene illumination in the guest room is realized.
The personalized lighting parameter recommendation for non-first-time-in users is achieved above, but for first-time-in users, the recommendation cannot be achieved in this way due to the lack of data that they modulate the lamp parameters. For this cold start problem, the invention solves this problem based on an analysis of the user characteristics.
As shown in fig. 1, 2 and 4, after the user logs in for the first time in the APP terminal 400, the user inputs his registration information in the registration interface, where the registration information includes personal characteristic parameters such as age, gender, area, occupation, favorite color temperature, favorite brightness, number of people to be logged in, trip purpose, and the like. The database of the server 500 is provided with a user characteristic data table for recording the user key IDs and the personal characteristic parameters of the users.
The user characteristic analysis module 120 performs a per-category processing and analysis of the user personal characteristic data. First, a fuzzy variable set is established for each category in its domain range and a membership function is established for each fuzzy variable in the set.
Referring to fig. 4, in fig. 4a, 4 fuzzy variables of teenagers, young, middle-aged, elderly, etc. are set for the age parameter categories; in fig. 4b, for the color temperature parameter class, 3 blur variables of low color temperature, medium color temperature, and high color temperature are set.
Then, according to the membership function established in fig. 4, the membership value of each data in the personal characteristic data of the user corresponding to each fuzzy variable in the category is calculated, and all membership values are sequentially arranged into a characteristic membership value vector. Meanwhile, the characteristic membership value vectors are respectively stored in a storage module and a server database.
The lighting recommendation module 130 then compares the characteristic membership value vector of the first-time living user u with the characteristic membership value vectors of other historic living users v in the database, calculates the similarity between the two vectors,
wherein sim is i (u, v) is the characteristic similarity of the users u, v in the dimension of the ith parameter category, I is the set of the characteristic parameter categories such as the age, j is the number of fuzzy variable sets in the ith parameter category, mu ik (u i )、μ ik (v i ) The parameter values of users u, v on the i-th class correspond to the membership value of the k-th fuzzy variable in that class, k=1, 2.
And then, according to a similar mode of the non-first-time user, calculating the recommended value of the personalized lighting parameter and pushing the recommended value to the first-time user u.
Example 2
In this embodiment, a method of fuzzy classification of users is adopted to recommend lighting parameters to the first-time user, unlike embodiment 1.
When a new user u registers for the first time, the mobile phone APP terminal 400 is opened, and classified by a fuzzy classification method according to the user registration information, and the classification is calculated:
F=S+N+Y+D
wherein S is the sex of the living user, such as 0 for men and 1 for women; n is the number of people in the house, and the general values are 1, 2, 3 and the like; y is the age of the user, ten digits of the actual age value minus 20 are taken and cut off to be 0 to 4; d is for trip purpose, and its numerical value is from 0 to 6, and corresponds to business, travel, reception, leisure, meeting, office and long renting respectively. F is a classification value for the living users, and the users that get the same score are classified into the same category, which may take a value of 1 to 14, i.e., all historical living users are classified into 14 categories.
Then, the illumination recommendation module takes all historical check-in users with the same classification value in the server database as the neighbors of u and forms a neighbor set of u, and then estimates the recommended brightness modulation value x 'of the lamp i in the guest room of the check-in user u by calculating an arithmetic average value according to the historical modulation information of the check-in users in the neighbor set' u,i And a color temperature modulation value y' u,i And pushed to the new living user u.
Example 3
The embodiment provides a hotel personalized intelligent lighting system based on a mobile phone APP, as shown in fig. 1 to 4, the hotel personalized intelligent lighting system 1000 based on the mobile phone APP comprises a hotel personalized intelligent lighting device 800 based on the mobile phone APP, a tunable light group 200 with adjustable brightness and color temperature, a server 500 and a mobile phone APP terminal 400. The hotel personalized intelligent lighting device 800 based on the mobile phone APP comprises a host unit 100 and a user interface unit 300.
The host unit 100, which is connected to the light bank, the user interface unit, the mobile APP terminal, and the server, respectively, includes an input module 110, a user characteristic analysis module 120, a lighting recommendation module 130, an output module 140, a storage module 150, and a user modulation analysis module 160.
The user inputs registration information such as personal characteristic parameters of the user from the user interface unit 300 or the mobile phone APP terminal 400, and simultaneously inputs a dimming instruction for modulating the color temperature and brightness of the dimmable lamp set 200 in the hotel room through the mobile phone APP terminal 400. These information and instructions are all transferred to the host unit through the input module 110 in the host unit 100 and are transferred by the host unit into the database of the server 500.
The personal characteristic parameters of the user comprise the categories of age, gender, region, occupation, favorite color temperature, favorite brightness, number of persons in the residence, trip purpose and the like.
When a new check-in user u first checks-in to the hotel, the user profile analysis module 120 performs a category-wise processing and analysis of the user personal profile data:
firstly, establishing a fuzzy variable set for each category in the range of the domain and establishing a membership function for each fuzzy variable in the set;
then, according to the membership function, calculating the membership value of each piece of data in the personal characteristic data of the user corresponding to each fuzzy variable in the category of the user, and sequentially arranging all membership values into a characteristic membership value vector;
And then, respectively storing the characteristic membership value vectors into a storage module and a server database.
The user modulation analysis module 160 processes the dimming signals of the lamps in the corresponding dimmable lamp group in the dimming command input by the user through the APP terminal 400 to obtain corresponding modulation values, and sequentially arranges the modulation values into a lamp modulation vector, and then stores the lamp modulation vector in the databases of the storage module 150 and the server 500.
The illumination recommendation module 130 compares the characteristic membership value vector, the lamp modulation vector of the user with other historical in-house user data in the server database, predicts the final lamp modulation vector of the user according to the similarity between the vectors, and recommends the final lamp modulation vector to the user through the mobile phone APP terminal 400,
after the user confirms the recommendation, a dimming command is sent to the dimmable light bank 200 through the output module 140.
The similarity of the characteristic membership value vector is calculated according to the following formula:
wherein,,
sim i (u, v) is the characteristic similarity between the new living user u and the historical living user v in the database in the dimension of the ith parameter category, I is the category set of the age and the like, j is the number of fuzzy variable sets in the ith parameter category, mu ik (u i )、μ ik (v i ) The parameter values of users u, v on the i-th class correspond to the membership value of the k-th fuzzy variable in that class, k=1, 2.
Preferably, the user interface unit 300 is provided with an operation panel 320 for parameter input, and a display screen 310 for assisting parameter input and displaying the processing result of the illumination recommendation module in the form of a list.
While the embodiments of the present invention have been described above, these embodiments are presented by way of example and do not limit the scope of the invention. These embodiments may be implemented in various other modes, and various omissions, substitutions, and changes may be made without departing from the spirit of the invention. These embodiments and modifications thereof are included in the scope and gist of the invention, and are also included in the invention described in the claims and their equivalents.
Claims (8)
1. A hotel individuation intelligent lighting method based on a mobile phone APP comprises the following steps:
s1, initializing, registering and information collecting the user,
the system receives registration information such as personal characteristic parameters of a user through a mobile phone APP terminal, and the registration information is transferred to a database of a server by a host unit, wherein the personal characteristic parameters of the user comprise categories such as age, gender, area, occupation, favorite color temperature, favorite brightness, number of people in the house, trip purpose and the like,
Establishing fuzzy variable sets in the range of the discourse domain for each user personal characteristic parameter category, establishing membership functions for each fuzzy variable in the sets,
s2, a host unit in the hotel room judges whether a user first check-in and builds a user personality vector, if the user first check-in, the process goes to S3, otherwise, a mobile phone APP terminal receives a dimming instruction for modulating the color temperature and the brightness of a dimmable lamp group in the hotel room by the user, processes dimming signals of lamps in the corresponding dimmable lamp group in the dimming instruction to obtain corresponding modulation values, and sequentially arranges the modulation values into a lamp modulation vector serving as the user personality vector, then goes to S4,
s3, for the first-time user, firstly, calculating membership value corresponding to the personal characteristic parameter value of the user based on membership function of each fuzzy variable of the category of the parameter for each personal characteristic parameter, and sequentially arranging all the membership values into a characteristic membership value vector as a user personality vector,
s4, respectively storing the user personality vectors into a storage module of the host unit and a server database,
S5, comparing the user personality vector of the user with other historical check-in user data in a server database, according to the similarity between the vectors, presuming the lamp modulation vector preferred by the user,
if the user u is the first user:
comparing the characteristic membership value vector of the user with the characteristic membership value vectors of other historical living users v in the database, calculating the similarity between the two vectors,
wherein sim is i (u, v) is the characteristic similarity of the users u, v in the dimension of the ith parameter category, I is the category set of the ages and the like, j is the number of fuzzy variable sets in the ith parameter category, mu ik (u i )、μ ik (v i ) The parameter values of the users u, v on the i-th category correspond to the membership value of the k-th fuzzy variable in the category, k=1, 2, j;
if the user u is a non-first-time user: based on the lamp modulation vectors of m lamps, comparing the lamp modulation vectors with the lamp modulation vectors of the historical entering users stored in the database, calculating vector similarity one by one,
sim(u,v)=α·sim x +(1-α)·sim y
wherein m represents the number of lamps commonly modulated by the users, and x i,u 、y i,u 、x i,v 、y i,v Representing the luminance and color temperature modulation values of the luminaire by the incumbent users u and v respectively, Respectively represent the average value of the corresponding modulation values, +.>For the arithmetic mean of the luminance modulation values of user u for m modulated lamps,
sim x (u,v)、sim y (u, v), sim (u, v) represent the luminance similarity, the color temperature similarity and the overall vector similarity of u and v, respectively, the overall similarity is a weighted sum of the luminance similarity and the color temperature similarity, alpha is a weight of the luminance similarity,
s6, recommending the presumption result to a user through the mobile phone APP terminal, after the user confirms or adjusts the recommendation, transmitting the confirmed lamp modulation vector to the dimmable lamp group through an output module of the host unit to dim, and simultaneously storing the lamp modulation vector into a server database.
2. The hotel personalized intelligent lighting method based on the mobile phone APP as set forth in claim 1, wherein the step S1 further comprises:
when the user foreground registers in the living, the registered necessary identity information including the ID card number, the guest room number and the like is stored in the server database and transmitted to the host unit in the living room by the database,
setting three interfaces, namely a login interface, a registration interface and a lamp modulation interface, on the mobile phone APP terminal, when a user logs in through the login interface of the mobile phone APP terminal, the host unit judges whether to allow the user to log in and enter a subsequent interface by comparing whether the identity information input by the user is in accordance with the foreground registration information,
After the login of the user is successful, information can be sent to the host unit through the registration interface and the lamp modulation interface, so that personal characteristic parameters of the user and the modulation operation of brightness and color temperature on lamps in a guest room are perfected.
3. The hotel personalized intelligent lighting method based on the mobile phone APP, which is claim 1, is characterized in that,
in the step S1, the server adopts a cloud server, and after the system receives registration information such as personal characteristic parameters of a user through the mobile phone APP terminal, the mobile phone APP terminal directly stores the information into a database of the cloud server.
4. The hotel personalized intelligent lighting method according to claim 1, wherein the step S2 further comprises:
for a non-first-time user, when the user u modulates the color temperature and brightness of the lamp through the mobile phone APP terminal, the modulation information is recorded, and a lamp modulation vector [ X ] is established according to the modulation value u ,Y u ]:
Wherein X is u The brightness modulation value of the user u to part of m lamps in the adjustable lamp group in the hotel room is represented by x 1 To x m ,Y u Representing the color temperature modulation value of the user u to the m lamps, wherein the corresponding value is y 1 To y m 。
5. The hotel personalized intelligent lighting method according to claim 1, wherein the step S5 further comprises:
after vector similarity calculation is completed, taking K historical check-in users with highest similarity as neighbors of u and forming a neighbor set of u, and then presuming a recommended brightness modulation value x 'of a lamp i in a guest room of the check-in user u according to historical modulation information of the check-in users in the neighbor set' u,i And a color temperature modulation value y' u,i :
Wherein i=1, 2, n;
the step S6 includes:
the host unit modulates the brightness modulation value x' u,i And a color temperature modulation value y' u,i And sending the modulation data to the mobile phone APP terminal, storing the modulation data returned by the mobile phone APP terminal after confirmation into a database, and sending the modulation data to a driver of the adjustable light group through an output module.
6. The hotel personalized intelligent lighting method based on the mobile phone APP as claimed in claim 1, further comprising the steps of:
the PWM wave duty ratio value of the driving current of each driving channel in the adjustable light lamp group is used as a modulation value, the modulation value is transmitted in the dimming command,
an operation panel is arranged in a hotel room to input parameters, meanwhile, the parameters are displayed in an auxiliary mode through a display screen, and after a user confirms the light modulation vector, the vector is displayed on the display screen in a list mode.
7. The hotel personalized intelligent lighting method according to claim 1, wherein the step S3 is performed by:
when a new check-in user u checks in for the first time and opens a mobile phone APP terminal to register, firstly classifying the new check-in user u by adopting a fuzzy classification method according to user registration information, and calculating the classification of the new check-in user u:
F=S+N+Y+D
wherein S is the sex of the living user, such as 0 for men and 1 for women; n is the number of people in the house, and the general values are 1, 2, 3 and the like; y is the age of the user, ten digits of the actual age value minus 20 are taken and cut off to be 0 to 4; d is a trip purpose, the value of which is from 0 to 6, corresponds to business, travel, reception, leisure, conference, office and long lease respectively, F is a classification value of the living users, the users who obtain the same score are classified into the same class, the value of which may be from 1 to 14, namely, all the historical living users are classified into 14 classes.
8. The hotel personalized intelligent lighting method according to claim 1, wherein the step S5 is performed by:
after the first user enters the guest room, comparing the F value with F values of other historical user entering in a server database, combining the users with the same value into a neighbor set of the user, calculating average numbers of lamp modulation vectors preferred by the user according to the lamp modulation values of all users in the neighbor set, then using the average numbers as the estimated values, combining the estimated values into a modulation vector, and recommending the modulation vector to the user through a mobile phone APP terminal.
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CN109886841B (en) | 2020-12-22 |
CN112419102A (en) | 2021-02-26 |
CN112734600A (en) | 2021-04-30 |
CN109886841A (en) | 2019-06-14 |
CN112419101A (en) | 2021-02-26 |
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