CN112218406B

CN112218406B - Hotel personalized intelligent lighting system based on user identity automatic identification

Info

Publication number: CN112218406B
Application number: CN202011175538.8A
Authority: CN
Inventors: 邹细勇; 张维特; 井绪峰; 李晓艳; 陈亮; 石岩
Original assignee: China Jiliang University
Current assignee: China Jiliang University
Priority date: 2018-11-02
Filing date: 2019-04-03
Publication date: 2023-06-02
Anticipated expiration: 2039-04-03
Also published as: CN109890106A; CN112218401A; CN109890106B; CN112218402A; CN112218406A

Abstract

The invention provides a hotel personalized intelligent lighting system based on automatic user identity recognition, which comprises a host unit, a user interface unit, a dimmable lamp set and a server. The host unit obtains the characteristic membership value according to fuzzy classification on personal characteristic data of the user after identity authentication, analyzes the dimming instruction to obtain each lamp modulation value, compares the lamp modulation vector with historical user data in a database based on the characteristic membership value vector of the user, and presumes the lamp modulation vector preferred by the user according to the similarity among the vectors, and sends the presumption result to the user after confirmation to the lamp group to execute dimming. According to the invention, 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 lighting parameter recommendation and one-key scene lighting are realized.

Description

Hotel personalized intelligent lighting system based on user identity automatic identification

The application is a divisional application of application number 201910287078.9, application date 2019, month 06 and 14, and invention name of hotel personalized intelligent lighting device, system and method based on user identity automatic identification.

Technical Field

The invention relates to a hotel personalized intelligent lighting system based on user identity automatic identification, 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 stronger need for 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 hotel personalized intelligent lighting system and a hotel personalized intelligent lighting method based on automatic identification of user identities, which integrate the advantages of intelligent lighting equipment and personalized recommendation functions and provide more personalized lighting experience for hotel check-in users.

The invention provides a hotel personalized intelligent lighting device based on automatic user identity recognition, which comprises a host unit and a user interface unit, wherein the host unit comprises an input module, an identity authentication 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, a display screen and a user identity recognition module are arranged in the user interface unit;

the host unit is configured to:

based on the user identification characteristic information acquired by the user identification module, the identification module judges whether the user is a legal user or not and identifies the user identity according to the comparison of the information and the pre-stored data in the external server database,

the legal user inputs the registration information such as personal characteristic parameters of the user from the user interface unit, and can also input the dimming instruction for modulating the color temperature and brightness of the adjustable lamp group in the hotel guest room, 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 by 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 user interface unit 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 user interface unit,

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 in, the necessary identity information, including the ID card number, the guest room number, etc., is stored in the database and transmitted by the database to the host unit in the guest room in which the user is in,

the user interface unit is provided with three interfaces, namely a login interface, a registration interface and a lamp modulation interface, after the login interface carries out identity authentication on the user, the user enters a subsequent interface according to the identified user identity,

the legal user can send information to the host unit through the registration interface and the lamp modulation interface, so that the personal characteristic parameters of the user are perfected, and the lamps in the guest room are 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 registers through the user interface unit, the illumination recommendation module compares the characteristic membership value vector of the user with the characteristic membership value vectors of other history 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.

Preferably, the host unit is further configured to:

for the non-first-time user, when the user u modulates the color temperature and brightness of the lamp through the user interface unit, the modulation information is recorded, and the illumination recommendation module establishes a lamp modulation vector [ X ] according to the modulation value _u ，Y _u ]：

wherein ,X_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,

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 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;

the output module outputs the brightness modulation value x' _u，i And a color temperature modulation value y' _u，i Send to the user interface unit and send the confirmed modulation number returned by the user interface unitThe data is stored in a database and is simultaneously transmitted to the driver of the lamp group through the 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 registers for the first time through the user interface unit, classifying the new user u by a fuzzy classification method according to the user registration information, and calculating the classification of the new 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 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 user interface unit.

In yet another embodiment of the present invention, there is also provided a hotel personalized intelligent lighting system based on automatic user identification, comprising an adjustable light color lamp set having adjustable light properties of both brightness and color temperature, a user interface unit for parameter input and dimming operations, a server, and a host unit respectively connected to the lamp set, the user interface unit, and the server,

the user interface unit is provided with an operation panel, a display screen and a user identity recognition module;

the host unit includes an input module, an identity authentication 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:

based on the user identification characteristic information acquired by the user identification module, the identification module judges whether the user is a legal user or not and identifies the user identity according to the comparison of the information and the pre-stored data in the server database,

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 user interface unit 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, the lamp modulation vector and other historical check-in user data in the 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 user interface unit,

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 (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 lamp group is composed of a plurality of dimmable LED lamps and is distributed on the ceiling of the hotel, the driver of the LED lamps is connected with the host unit through the 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 user interface unit 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 user interface unit can be connected with the host unit through a wireless route in the guest room, and meanwhile, the host unit is also connected with the adjustable light color LED lamp group and the server through a wired connection mode.

Preferably, the operation panel is provided with a plurality of scene mode keys,

in the debugging stage: after a user presses a scene mode key, the brightness and color temperature of each lamp in customer service under the mode are modulated, the formed lamp modulation vector is supplemented with the mode mark, when the lamp modulation vector is compared, the illumination recommendation module only compares the vector with the mode mark, the estimated and confirmed final lamp modulation vector is supplemented with the mode mark,

in the application stage: the user presses a scene mode key, and the host unit sends a dimming command to the dimmable light group through the output module based on the final light modulation vector confirmed by the user in the corresponding mode.

In still another embodiment of the present invention, there is provided a hotel personalized intelligent lighting method based on automatic user identity identification, comprising the steps of:

s1, initializing, establishing a user check-in and fuzzy classification standard,

registering the identity of the user and the identification characteristic information in the hotel foreground and inputting the identification characteristic information into a server database,

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, identity authentication and information acquisition,

in hotel rooms, based on the acquired user identification characteristic information, the host unit compares the information with the information prestored in the server database, judges whether the user is a legal user and identifies the user identity,

the user interface unit receives the registration information such as personal characteristic parameters of the user, which include the categories of age, sex, area, occupation, favorite color temperature, favorite brightness, number of people in the house, trip purpose and the like, and the registration information is transferred to the database of the server by the host unit,

s3, the host unit judges whether the user first check-in and builds a user personality vector, if the user first check-in, the S4 is switched, otherwise, the user interface unit receives a dimming instruction for modulating the color temperature and the brightness of the dimmable lamp group in the hotel room by the user, processes the dimming signals of the lamps in the dimming instruction, which correspond to the dimmable lamp group, to obtain corresponding modulation values, and sequentially arranges the modulation values into a lamp modulation vector as the user personality vector, and then the S5 is switched,

s4, 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,

S5, respectively storing the user personality vectors into a storage module of the host unit and a server database,

s6, 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,

s7, recommending the presumption result to the user through the user interface unit, after the user confirms or adjusts the recommendation, transmitting the confirmed lamp modulation vector to the dimmable lamp group through the output module of the host unit for dimming, and simultaneously storing the lamp modulation vector into the 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,

three interfaces, namely a login interface, a registration interface and a lamp modulation interface, are arranged on the user interface unit, after the user is logged in the login interface for identity authentication, the user enters a subsequent interface according to the identified user identity,

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 user interface unit, the user interface unit directly stores the information into a database of the cloud server.

Preferably, the step S3 further includes:

wherein ,X_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 step S6 further includes:

based on the lamp modulation vector, comparing the lamp modulation vector with the lamp modulation vector of the historical check-in user stored in the database, and calculating vector similarity one by one:

sim(u，v)＝α·sim _x +(1-α)·sim _y

respectively represent the average value of the corresponding modulation values, +. >

Preferably, the step S6 further includes:

when the first user u is checked in, the characteristic membership value vector of the user is compared with the characteristic membership value vectors of other historical user v in the database, the similarity between the two vectors is calculated,

/>

Preferably, the step S6 further includes:

Wherein i=1, 2, n;

the output module outputs the brightness modulation value x' _u，i And a color temperature modulation value y' _u，i And the modulation data is transmitted to the user interface unit, and the modulation data returned by the user interface unit after confirmation is stored in the database and is simultaneously transmitted to the driver of the lamp group through the output module.

Preferably, it further comprises 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,

the lamp modulation vectors are displayed in list form on a display screen in the user interface unit.

Preferably, it further comprises the steps of:

a plurality of scene mode keys are provided on an operation panel in the user interface unit,

in the debugging stage, after a user presses a scene mode key, the brightness and color temperature of each lamp in customer service under the mode are modulated, the formed lamp modulation vectors are supplemented with the mode marks, when the lamp modulation vectors are compared, the illumination recommendation module only compares the vectors with the same mode marks, the estimated and confirmed final lamp modulation vectors are also supplemented with the mode marks,

In the application phase, the user presses a scene mode key, and the host unit sends a dimming instruction to the dimmable lamp group through the output module based on the final lamp modulation vector confirmed by the user in the corresponding mode.

In yet another embodiment of the present invention, the step S4 employs the following process:

F＝S+N+Y+D

Step S6 employs the following processing:

after the user enters a guest room, the illumination recommendation module compares the F value of the user with F values of other historical entering users in a server 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 user interface unit.

In the lighting system, the user interface unit is connected with the host unit through a wired interface or a wireless WIFI interface, and the user interface unit can send user registration information and regulation 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 the color temperature of the adjustable light color LED lamp group are modulated according to the regulation and control instruction of the user interface unit, meanwhile, the user input information and the regulation and control instruction are input into the database, the user input information and the regulation and control instruction are 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 user regulation and control parameters are recommended to the user through the user interface unit so as to meet the personalized lighting requirements of the user.

The utility model provides a but 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 computer unit, the host computer unit contains WIFI communication module, wireless router and the user interface unit realization communication in the guest room environment are linked to this module, 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 user interface unit, 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 After the calculation is completed, the combined lamp modulation vector is sent to the user interface unit and displayed on the interface thereof. 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 the operation panel for confirmation, the user interface unit sends a lamp modulation instruction to the host unit according to each modulation parameter 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. according to the invention, through panel operation, single-lamp dimming and one-key switching of recommended scenes can be realized, and the method is simple and convenient.

Drawings

FIG. 1 is a workflow diagram of a hotel personalized intelligent lighting method based on automatic user identity identification;

FIG. 2 is a block diagram of the components of a hotel personalized intelligent lighting system based on automatic user identity identification;

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 personalized recommendation signal flow diagram;

fig. 6 is a scene lighting operation interface.

wherein ：

1000 hotel individuation intelligent lighting system based on user identity automatic identification, 100 host units, 200 adjustable light groups, 300 user interface units, 400 servers, 800 hotel individuation intelligent lighting devices based on user identity automatic identification,

110 input module, 120 user characteristic analysis module, 130 illumination recommendation module, 140 output module, 150 storage module, 160 user modulation analysis module, 170 identity authentication module,

210, the driver, 220LED lamp,

310 display screen, 320 operation panel, 330 user identification module.

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 automatic identification of the user identity, provided by the invention, comprises the following steps:

s2, identity authentication and information acquisition,

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 user identity automatic identification adopting the method in the invention comprises a hotel personalized intelligent lighting device 800 based on the user identity automatic identification, a tunable light group 200 with adjustable brightness and color temperature and a server 400.

Wherein, the hotel personalized intelligent lighting device 800 based on the user identity automatic recognition comprises a host unit 100 and a user interface unit 300; an input module 110, an identity authentication module 170, 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 disposed in the host unit 100.

In the hotel room lighting system, the hotel personalized intelligent lighting device 800 based on the user identity automatic identification is respectively connected with the adjustable light lamp set 200 with adjustable brightness and color temperature and the server 400.

The user interface unit 300 is provided with an operation panel 320 for parameter input and a display screen 310 for display and auxiliary input operations. The user interface unit 300 is 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 400.

The user identification module 330 is used to enter user identification features for authentication and identification. Preferably, the user identification module 330 can adopt one or several of the following identification modes: fingerprint recognition, iris recognition, voice recognition, and face recognition.

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 contains a WIFI communication module through which a wireless router in the guest room environment can be connected to enable its communication with the user interface unit 300. Meanwhile, the host unit 100 is also connected to the database of the server 400 by a wired connection. The host unit 100 changes the PWM wave duty ratio value transmitted to the LED lamp driver through the output module according to the operation signal transmitted from the user interface unit 300, 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 corresponding to the lamps in the dimmable lamp set 200 in the dimming command input by the user through the user interface unit 300 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.

As shown in fig. 2, 3 and 5, 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, the driver 210 are placed in a suspended ceiling of a bathroom, the user interface unit 300 is placed at the entrance of the bathroom, and the server 400 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. And simultaneously, the biological characteristics of the user are input into a database through an identity recognition module such as a fingerprint recognition module, and the characteristics of the user are used for recognizing the user by the identity recognition module in the host unit in the guest room.

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 foreground registration is completed, the user enters the guest room and is connected to the host unit 100 through the user interface unit, and at least three interfaces, namely a login interface, a registration interface and a lamp modulation interface, are arranged in an operation interface formed by the operation panel 320 and the display screen 310 on the user interface unit 300. The first interface is a login interface, where user identity authentication is to be performed. Based on the user identification feature information, such as fingerprint information, collected by the user identification module 330, the identity authentication module 170 in the host unit 100 determines whether the user is a legitimate user and identifies the user identity according to the comparison between the information and the data stored in the database of the server 400, and the legitimate user is allowed to enter the subsequent interface with the identified user identity. In the registration interface, the user perfects the personal information by checking and other operations. At the light modulation interface, when the user changes the data to perform the light parameter modulation, clicking the modification completion key triggers a setup completion event of the user interface unit, in response to which the user interface unit 300 transmits a dimming signal to the host unit 100.

Wherein the user interface unit 300 has a dimming interface for each lamp, typically, the brightness of each lamp can be represented by a sliding bar, and the brightness can be adjusted between 0% and 100% by the user 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 user interface unit 300 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 400. Meanwhile, these PWM duty ratio values are transmitted 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, thereby adjusting the brightness and color temperature of the corresponding LED lamp 220 to the set values of the user interface unit 300, respectively.

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 400, and according to the similarity between the vectors, presumes the final lamp modulation vector of the user, and recommends the final lamp modulation vector to the user through the user interface unit 300; 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 non-casesWhen a user for first check-in is used, and the check-in user u modulates the color temperature and brightness of the lamp through the user interface unit 300, the user modulation analysis module records the modulation information, and the illumination recommendation module establishes a lamp modulation vector [ X ] according to the modulation value _u ，Y _u ]：

wherein ,X_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)＝σ·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 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,

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;

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 After the calculation is completed, the combined lamp modulation vector is sent to the user interface unit and displayed on the display screen. 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 the operation panel for confirmation, the user interface unit sends a lamp modulation instruction to the host unit according to each modulation parameter 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 is logged in for the first time in the user interface unit 300, registration information including personal characteristic parameters such as age, sex, region, occupation, favorite color temperature, favorite brightness, number of people to be logged in, and traveling purpose is input in the registration interface. The database of the server 400 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_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.

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 user identity automatic identification, as shown in fig. 1 to 4, the hotel personalized intelligent lighting system 1000 based on user identity automatic identification comprises a hotel personalized intelligent lighting device 800 based on user identity automatic identification, a tunable light group 200 with adjustable brightness and color temperature and a server 400. The hotel personalized intelligent lighting device 800 based on the user identity automatic identification comprises a host unit 100 and a user interface unit 300.

The host unit 100, which is connected to the lamp group, the user interface unit, and the server, respectively, includes an input module 110, an identity authentication module 170, 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 interface unit 300 is provided with an operation panel 320 for inputting parameters, a display screen 310 for assisting in inputting operations, and a user identification module 330 for inputting user identification features for identity verification and identification.

Based on the user identification feature information collected by the user identification module 330, the identity authentication module 170 determines whether the user is a legitimate user and identifies the user's identity according to the comparison of the information with the pre-stored data in the database of the server 400,

the legitimate user inputs registration information such as personal characteristic parameters of the user from the user interface unit 300, and at the same time, can also input a dimming command for modulating the color temperature and brightness of the dimmable lamp set 200 in the hotel room. These information and instructions are all transferred to the host unit through the input module 110 in the control unit 100 and are transferred by the host unit into the database of the server 400.

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 user interface unit 300 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 400.

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 to the user through the user interface unit 300,

after the user confirms the recommendation, a dimming command is sent to the dimmable light bank 200 through the output module 140.

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.

Example 4

The embodiment provides a hotel personalized intelligent lighting method based on user identity automatic identification by one-key scene lighting, and is characterized in that a plurality of scene mode keys corresponding to guest room lighting application scenes such as guest reception, reading, office and television are arranged on an operation panel in combination with the illustration of fig. 1,2 and 6 so as to realize one-key scene lighting.

Based on the embodiment 1, the hotel personalized intelligent lighting method based on the user identity automatic identification further comprises the following steps:

In the application stage, the user presses a scene mode key, and the host unit sends a dimming instruction to the dimmable lamp group through the output module based on the final lamp modulation vector confirmed by the user in the corresponding mode, so that all lamps in the guest room are synchronously switched to the confirmed brightness and color temperature, and one-key scene illumination is realized.

Preferably, the lamp modulation vectors are displayed in a list form on a display screen 310 in the user interface unit 300.

Preferably, the operation panel 320 and the display screen 310 may be combined into one touch screen.

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

1. A hotel individuation intelligent lighting system based on user identity automatic identification, which comprises an adjustable light color lamp group with adjustable light properties of brightness and color temperature, a user interface unit for parameter input and dimming operation, a server, and a host unit respectively connected with the lamp group, the user interface unit and the server,

The user interface unit is provided with an operation panel, a display screen and a user identity recognition module,

the legal user inputs the personal characteristic parameter registration information of the user from the user interface unit, and simultaneously inputs a dimming instruction for modulating the color temperature and brightness of the dimmable lamp group in the hotel room, the information and the instruction are transmitted to the host unit through the input module and are transferred to the database of the server by the host unit,

the user personal characteristic parameters include age, sex, region, occupation, favorite color temperature, favorite brightness, number of persons to check in and category of trip purpose,

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 vector is respectively stored in a storage module and a server 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 the server database, presumes the final lamp modulation vector of the user according to the similarity between the characteristic membership value vector and the lamp modulation vector, recommends the final lamp modulation vector to the user through a user interface unit,

2. The hotel personalized intelligent lighting system of claim 1, wherein the similarity of the characteristic membership value vector is calculated as follows:

wherein ,

sim _i (u, v) is the characteristic similarity of 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 age category set, 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;

when a new check-in user u checks in the hotel for the first time and registers through the user interface unit, 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, and calculates the similarity between the two vectors.

3. The hotel personalized intelligent lighting system based on the automatic identification of the user identity according to claim 1, wherein the lamp group consists of a plurality of dimmable LED lamps and is distributed on a hotel ceiling, a 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 user interface unit to realize the modulation of the brightness and the color temperature of the LED lamps,

the user interface unit is connected with the host unit through a wireless route in the guest room, and meanwhile, the host unit is connected with the adjustable light color LED lamp group and the server through a wired connection mode.

4. The hotel personalized intelligent lighting system based on the automatic identification of user's identity according to claim 1, wherein the necessary identity information for the check-in of the user's foreground, including the identification card number, the guest room number, is stored in the database and transmitted from the database to the host unit in the guest room in which the user checked in,

the legal user sends information 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 lamps in the guest room are modulated in terms of switching and brightness and color temperature.

5. The hotel personalized intelligent lighting system based on the automatic identification of user identity according to claim 1, wherein a plurality of scene mode keys are arranged on the operation panel,

in the debugging stage: after a user presses a scene mode key, the brightness and the color temperature of each lamp in the guest room under the mode are modulated, the formed lamp modulation vectors are supplemented with mode marks, when the lamp modulation vectors are compared, the illumination recommendation module only compares the vectors with the same mode marks, the estimated final lamp modulation vectors confirmed by the user are supplemented with the mode marks,

6. The hotel personalized intelligent lighting system based on automatic user identity identification of claim 1, wherein the host unit is further configured to:

wherein ,X_u Representing brightness modulation value of user u to m lamps in adjustable light group in guest room, its correspondent 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 ，

sim(u，v)＝α·sim _x +(1-α)·sim _y

wherein m represents accommodationThe number of lamps commonly modulated by the user, 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,

7. The hotel personalized intelligent lighting system based on automatic user identity identification of claim 1, wherein the host unit is further configured to:

Wherein i=1, 2, n;

8. The hotel personalized intelligent lighting system based on automatic user identity identification of claim 1, wherein the host unit is further configured to:

F＝S+N+Y+D

wherein S is the sex of the living user, and 0 for men is represented by 1 for women; n is the number of people in the house, and the value is an integer; 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, its numerical value is from 0 to 6, correspond to business, travel, guest, recreation, meeting, office and long renting separately, obtain the user of the same classification value score F to be classified into the identity classification;

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 same-class users with the same value into a neighbor set of the user, calculates average numbers of the final lamp modulation vectors of the user according to the lamp modulation values of all users in the neighbor set, uses the average numbers as a presumption value, combines the presumption value into a modulation vector, and recommends the modulation vector to the user through a user interface unit.