CN116051315A - Intelligent hotel management system - Google Patents

Intelligent hotel management system Download PDF

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CN116051315A
CN116051315A CN202310315743.7A CN202310315743A CN116051315A CN 116051315 A CN116051315 A CN 116051315A CN 202310315743 A CN202310315743 A CN 202310315743A CN 116051315 A CN116051315 A CN 116051315A
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client
clients
customer
check
hotel
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CN116051315B (en
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徐友红
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Hefei Kunyu Intelligent Technology Co ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/12—Hotels or restaurants
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0281—Customer communication at a business location, e.g. providing product or service information, consulting
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0283—Price estimation or determination
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/16—Human faces, e.g. facial parts, sketches or expressions
    • G06V40/178—Human faces, e.g. facial parts, sketches or expressions estimating age from face image; using age information for improving recognition
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management

Abstract

The invention discloses an intelligent hotel management system, which relates to the technical field of hotel management and comprises the following components: starting a reception robot to receive clients, collecting the requirement information of the clients and establishing a characteristic image library; judging the consumption capacity and the check-in safety of the client, and recommending corresponding rooms to the client; when a customer is about to get out of a house, collecting the information of the customer, and guiding the customer to transact the house-going procedure before arranging the receiving robot closest to the customer; according to the distribution of the acquisition coefficient Rz, the safety coefficient Aq and the client economic evaluation value JPz, determining an invited client, and sending an acquisition invitation to the invited client; and determining a discount scheme, and sending the discount scheme to the invited clients according to the client reservation information, and collecting comments from part of the invited clients if the invited clients are still not in the home. According to the consumption capability and the safety of the clients, the clients are recommended and selected to be suitable for the clients, the actual revenue of the hotel is improved, the safety of the clients is ensured, and the hidden danger of personal safety after the clients check in is avoided.

Description

Intelligent hotel management system
Technical Field
The invention relates to the technical field of hotel management, in particular to an intelligent hotel management system.
Background
The hotel in the modern society provides comfortable environment for clients, meets various requirements of the clients, and meanwhile needs to reduce operation cost of the hotel to the maximum extent, and improves efficiency and benefit of the hotel.
In the actual operation of a hotel, in order to save the cost of people as much as possible, the staff in the reception area of the hotel is usually not more, and even only individual staff can be left in the foreground, so once the staff in the reception area are not enough, and when a customer enters the hotel, unmanned reception can occur, and the situation of losing the customer can occur.
In order to avoid the problem, the existing hotel, even a bank, is generally equipped with a robot for reception and inquiry in a hall, receives or assists a reception client by using the robot, and combines the robot with a hotel management system to reduce the operation pressure of the hotel, but the existing hotel management system only has a guiding function when the existing hotel management system is operated, and the reception robot can improve the reception of the hotel from the viewpoint of reducing the labor cost, but has limited functions when receiving the client, and can increase the reception.
For this purpose, a smart hotel management system is provided.
Disclosure of Invention
(one) solving the technical problems
Aiming at the defects of the prior art, the invention provides an intelligent hotel management system which is used for receiving clients by starting a receiving robot, collecting the requirement information of the clients and establishing a characteristic image library; judging the consumption capacity and the check-in safety of the client, and recommending corresponding rooms to the client; when a customer is about to get out of a house, collecting the information of the customer, and guiding the customer to transact the house-going procedure before arranging the receiving robot closest to the customer; according to the distribution of the acquisition coefficient Rz, the safety coefficient Aq and the client economic evaluation value JPz, determining an invited client, and sending an acquisition invitation to the invited client; and determining a discount scheme, and sending the discount scheme to the invited clients according to the client reservation information, and collecting comments from part of the invited clients if the invited clients are still not in the home. According to the consumption capability and the safety of the clients, the clients are recommended and selected to be suitable for the clients, the actual revenue of the hotel is improved, the safety of the clients is ensured, and the problems in the background technology are solved.
(II) technical scheme
In order to achieve the above purpose, the invention is realized by the following technical scheme: an intelligent hotel management system comprises the following steps that when the number of staff in a hotel is insufficient, a reception robot is started and moves in a reception area of the hotel, a customer entering the reception area is received and guided, when the customer is received, the demand information of the customer is collected, the image of the customer is collected, and a characteristic image library is built;
judging the consumption capacity and the check-in safety of the clients according to the information acquisition of the receiving robot to the clients, and recommending corresponding rooms to the clients by combining the formed judging results with the distribution of the residual rooms in the hotel; after handling the check-in procedure for the client, guiding the client to check in; when a customer is about to get out of a house, acquiring the information of the customer about to get in the house after the information of the customer about to get out of the house, arranging a reception robot closest to the customer about to get in the house, guiding the customer to transact the procedure of the house, forming an in-house coefficient Rz according to the information of the in-house, and forming an evaluation on the service difficulty of the customer;
after the expected time, if the customer does not check in again, the consumption data of the customer during check in is called, and a customer economic evaluation value JPz is established; according to the distribution of the acquisition coefficient Rz, the safety coefficient Aq and the client economic evaluation value JPz, determining an invited client, and sending an acquisition invitation to the invited client; sending a check-in invitation to the client, and determining a standard of continuously sending out an offer to the client according to the historical check-in information of the client if the client can be recommended to not check in after the preset time; and determining a discount scheme according to the client reservation information and sending the discount scheme to the invited clients in combination with the evaluation made to the invited clients, and collecting comments from part of the invited clients if the invited clients are still not in the home.
Further, a movable reception robot is arranged in a reception area of a hotel lobby, and when a guest is judged to enter the reception area based on machine vision, the reception robot sends a voice query to the guest, wherein the query information at least comprises whether to check in, check in time and the number of check-in persons;
when the client is judged to be in, guiding the client to rest in a rest area, and when the client is judged to be in, guiding the client to move towards the foreground; the reception robot accesses the guest room management system, inquires about the current guest room free condition and corresponding price and discount in the hotel, and when the current hotel guest room is remained, acquires images of the clients to be received, wherein the image content at least comprises wearing and wearing, and constructs a client image feature library.
Further, after the customer image feature library is obtained, when a plurality of customers exist, age information and dressing information of the plurality of customers are obtained, and the values of wearing and accessories of the customers are inquired and judged through the inquiry module to form external prices; selecting the highest value from a plurality of external prices, taking the corresponding client as a target client, and outputting the position information of the target client; determining a consumption coefficient Xf of the client according to the ratio relation between the highest value and a preset value threshold;
acquiring position information of a client, enabling the reception robot to talk with the target client before moving to the target client, collecting emotion characteristics of the client, performing character analysis, and determining a safety coefficient Aq of the target client according to emotion stability;
when the safety coefficient Aq of the target client is larger than a threshold value, the region is not limited when recommending the guest room to the target client; when the safety coefficient Aq of the client is smaller than the threshold value, when recommending the guest room to the target client, the guest room recommended to the target client preferentially is not in the non-proximity of the old and the child.
Further, according to the relation between the consumption force coefficient Xf of the customer and the corresponding value threshold, matching the number of the customers to be received and the price of the hotel guest room, and recommending at least one guest room corresponding to the price to the target customer; when the safety coefficient Aq and the consumption coefficient Xf are used as the reference standard of the recommended client, the priority of the safety coefficient Aq is higher than that of the consumption coefficient Xf; therefore, when the guest room recommendation is carried out, the security of the check-in clients in the hotel is prioritized;
after the target client selects a corresponding guest room, the reception robot handles the check-in procedure for the target client and guides the target client to the selected guest room; before a customer enters a guest room, a reception robot accesses a hotel equipment management system, checks whether equipment in the guest room is good, and if the equipment is good, guides the customer to check in.
Further, after the room-returning information of the client is obtained, the reception robot closest to the room-returning distance is moved to the room-returning position according to the position information of the room-returning, so that the room-returning procedure is handled for the client, and the client is guided to the reception area of the hotel lobby; after the completion of the procedure of the room return,
the reception robot returns to the living room, acquires images of the living room, and establishes a living image feature library; and identifying a guest room image in the image feature library, acquiring the cleanliness of the guest room, forming a living coefficient Rz according to the cleanliness, and informing a cleaning person to clean the guest room before.
Further, when the client does not live in again after exceeding the preset time, acquiring a live-in coefficient Rz and a safety coefficient Aq of the client, and when the live-in coefficient Rz and the safety coefficient Aq are both larger than a corresponding threshold value, indicating that the self condition of the client is relatively good, and marking the live-in client as a recommendable client;
summarizing recommended clients in the previous period when the room occupancy rate of the hotel in the current period is less than expected, and establishing a recommended client set; selecting clients from the recommended clients, obtaining the duration Ct of the clients, extra consumption Ex in the hotel and the price Fj of the resident clients, and obtaining the economic evaluation value JPz of the clients in a related manner after dimensionless processing;
acquiring a plurality of client economic evaluation values JPz, sequencing from high to low to form a recommendation sequence, and sequentially sending out a check-in invitation to the clients by the reception robot through reserved contact ways; the living offer at least comprises a living room price, and the living room price is at least not more than the last living price.
Further, the customer economic evaluation value JPz is obtained as follows:
Figure SMS_1
wherein (1)>
Figure SMS_2
Is weight(s)>
Figure SMS_3
，
Figure SMS_4
And->
Figure SMS_5
1, the specific value can be adjusted and set by a user, and n is the number of times of entering and holding;
wherein the economic evaluation value of clients is used
Figure SMS_6
The importance of recommending rooms to customers is evaluated by the following characterization modes:
Figure SMS_7
wherein (1)>
Figure SMS_8
For the first consumption intermediate value,/->
Figure SMS_9
Is a second consumption intermediate value.
Further, acquiring regression information of recommended tenants in a preset period, acquiring total revenue brought by the client re-check-in the period after the client re-check-in, and if the total revenue reaches the expectation, not continuing to send out check-in invitations; when the total revenue does not reach the expectation, a regression analysis prediction model is established according to a plurality of groups of historical check-in data, and prediction is formed on the guest room surplus at the recommended date; if the residual guest room exceeds a preset threshold, continuing to send out a check-in invitation; if it is lower than expected, it is not recommended.
Further, selecting clients from the set of recommendable clients that have not issued invitations, and determining corresponding client economic evaluation values JPz; determining a discount scheme for the client according to the distribution of the economic evaluation values JPz of the client to form a marketing strategy; wherein, marketing strategy is as follows:
when the customer economic rating value JPz is greater than the second threshold, providing the invited customer with a first level of discount; providing the invited customer with a second level of discount when the customer economic rating value JPz is between the first threshold and the second threshold; when the customer economic rating value JPz is less than the first threshold, providing the invited customer with a third level of discount; wherein the second threshold is greater than the first threshold, and wherein the first level discount is superior to the second level discount and the third level discount.
Further, after the discount scheme is sent to the invited clients, if the clients receiving the first-level discount are not yet in the home, the receiving robot which receives the corresponding invited clients and has a name carries out voice return visit to the invited clients in the form of voice; and collecting the reason that the client is no longer in the house, and establishing an opinion collecting system.
(III) beneficial effects
The invention provides an intelligent hotel management system, which has the following beneficial effects:
after the labor consumption coefficient Xf and the safety coefficient Aq are obtained under the condition of a reception robot, the clients are recommended and selected to be suitable according to the consumption capacity and the safety of the clients, the actual revenue of a hotel is improved, the safety of the clients is ensured on the basis of combining the information of the checked-in clients, and the hidden danger of personal safety after the clients check in is avoided.
Based on the formed economic evaluation value JPz, after the recommendable clients are selected based on the check-in coefficient Rz and the safety coefficient Aq, the recommendation sequence is determined, when the empty room rate of the hotel is higher, based on the consumption condition of the guest room during check-in, check-in invitations are orderly sent to the recommendable clients by the reception robot, the check-in rate of the hotel is improved, the check-in is improved, a certain screening effect is formed for the clients based on the check-in coefficient Rz and the safety coefficient Aq, and the operation cost is reduced.
The client sends out invitation or return visit again in a layered way to the previous client, the check-in rate of the hotel is increased under the assistance of the standby robot by means of the formulated marketing strategy and return visit strategy, and if the income of the guest room given by the hotel is not increased, the return visit strategy is adopted at the moment, so that the improvement of the hotel can be facilitated; the reception robot of the previous reception user performs a return visit, the image of the client is increased, and the hotel is also propaganda and marketing functions.
For the first invitation, if not enough results are received, the invitation needs to be sent out again for other clients, on the basis of the first invitation, a marketing policy is formulated according to the distribution of the economic evaluation values JPz of the clients, and under the condition that the enterprise income is not low, a certain discount is given, so that the probability of the invited clients to check in is increased.
Drawings
FIG. 1 is a flow chart of the intelligent hotel management system of the present invention when applied;
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Examples
Referring to fig. 1, the present invention provides a smart hotel management system, which comprises the following steps:
step one, when the number of staff in a hotel is insufficient, starting a reception robot and enabling the reception robot to move in a reception area of the hotel, receiving and guiding clients entering the reception area, collecting client demand information and collecting client images when the clients are received, and establishing a characteristic image library;
the first step comprises the following steps:
step 101, setting a movable reception robot in a reception area of a hotel lobby, and sending a voice query to a client by the reception robot when a guest is judged to enter the reception area based on machine vision, wherein the query information at least comprises whether to check in, check in time and the number of check in;
102, guiding the client to rest in a rest area when the client is not checked in, and guiding the client to move towards a foreground when the client is checked in;
accessing a guest room management system by a reception robot, and inquiring the current guest room free condition in the hotel and the corresponding price and discount;
when the current hotel guest room remains, the image is acquired for the customer to be treated, and the image content at least comprises wearing and wearing, so that a customer image feature library is constructed.
When the robot is used, when the manpower of the hotel is insufficient, the reception robot intervenes in the reception process, so that the problem of the insufficient manpower is solved, and the phenomenon that the client does not check in the hotel any more due to the fact that no reception is performed at present is avoided; meanwhile, the image characteristics and clothing wearing information of the clients are collected based on machine vision, so that the economical capacity of the users is judged, and the later living room entry is conveniently recommended.
Step two, judging the consumption capacity and the check-in safety of the clients according to the information acquisition of the clients by the reception robot, and recommending corresponding rooms to the clients by combining the formed judging results with the distribution of the residual rooms in the hotel; after handling the check-in procedure for the client, guiding the client to check in;
the second step comprises the following steps:
step 201, after obtaining a customer image feature library, when a plurality of customers exist, obtaining age information and dressing information of a plurality of customers, inquiring and judging the values of wearing and accessory of the customers through an inquiry module, and forming external prices;
selecting the highest value from a plurality of external prices, taking the corresponding client as a target client, and outputting the position information of the target client; determining a consumption coefficient Xf of the client according to the ratio relation between the highest value and a preset value threshold;
when the hotel management system is used, the recommended guest rooms can be matched with the consumption capacity of the clients as much as possible by determining the consumption coefficient Xf of the clients, so that the hotel revenue is increased.
Step 202, acquiring position information of a client, enabling a reception robot to talk with the target client before moving to the target client, collecting emotion characteristics of the client, performing character analysis, and determining a safety coefficient Aq of the target client according to emotion stability;
when the safety coefficient Aq of the target client is larger than a threshold value, namely the safety is higher, the region limitation is not carried out when the guest room is recommended to the target client; when the safety coefficient Aq of the client is smaller than a threshold value, namely, the safety is possibly insufficient, recommending the guest room to the target client, wherein the guest room recommended to the target client is not adjacent to the old and children preferentially;
when the intelligent safety system is used, based on the collection of the emotion characteristics of the client, the emotion state of the client, such as extremely violent character of the client, can be judged that the client has certain potential safety hazard, so that after the client is in life, the safety of other in-life clients is ensured.
Step 203, recommending at least one guest room corresponding to the price to the target client according to the relation between the client consumption force coefficient Xf and the corresponding value threshold and the number of the receiving clients and the price of the hotel guest room;
for example, the user's effort consumption coefficient Xf is greater than the corresponding value threshold, recommending the customer room with the highest gear in price to the user;
or after displaying the image and video information of the recommended guest room of the corresponding price, selecting at least one of the image and video information by the client;
when the safety coefficient Aq and the consumption coefficient Xf are used as reference standards of recommended clients, the priority of the safety coefficient Aq is higher than that of the consumption coefficient Xf; therefore, when the guest room recommendation is carried out, the security of the check-in clients in the hotel is prioritized;
step 204, after the target client selects the corresponding guest room, the reception robot handles the living procedure for the target client and guides the target client to the selected guest room;
before a customer enters a guest room, the guest room is accessed into a hotel equipment management system by a reception robot, whether equipment in the guest room is good is checked, if the equipment is good, the customer is guided to check in, and if the equipment cannot be used immediately, the guest room is replaced again.
In use, in combination with the contents of steps 201 to 204,
after the labor consumption coefficient Xf and the safety coefficient Aq are obtained under the condition of the reception robot, the clients adapting to the consumption capacity and the safety of the clients can be recommended and selected for the clients, when the reception robot receives the reception, the actual reception of the hotel is improved as much as possible, meanwhile, the safety of the clients is ensured on the basis of combining the information of the checked-in clients, and the hidden danger of personal safety after the clients check in is avoided.
Step three, when a customer is about to get out of a house, after the information of the customer about to get out of the house is obtained, the information of the customer about to get in the house is collected, the customer is guided to transact the procedure of getting out of the house before arranging a receiving robot closest to the customer, and a check-in coefficient Rz is formed according to the information of getting in the house, so that evaluation is formed on the service difficulty of the customer;
the third step comprises the following steps:
step 301, after obtaining the room-return information of the customer, moving the reception robot most connected with the distance from the room-return room to the room-return room according to the position information of the room-return room, handling the room-return procedure for the customer, and guiding the customer to the reception area of the hotel lobby;
step 302, after the completion of the room return procedure, returning the reception robot to the living room, and detecting whether the electrical equipment in the living room is good; after the electrical equipment is intact, acquiring an image of a living room, and establishing a living image feature library;
and identifying a guest room image in the image feature library, acquiring the cleanliness of the guest room, forming a living coefficient Rz according to the cleanliness, and informing a cleaning person to clean the guest room before.
When the check-in coefficient Rz is lower than the clean threshold value, a certain cleaning difficulty exists when the client is not checked in any more, when the check-in system is used, after the check-in robot is used for handling the check-out information for the client, the personal service difficulty of the client can be evaluated based on the formed check-in coefficient Rz, the client with better communication or the client with lower cleaning difficulty can be better evaluated, the reception cost of hotel investment is relatively lower, and the reception is relatively higher.
Step four, after the expected time, if the customer does not check in again, the consumption data of the customer during check in is called, and a customer economic evaluation value JPz is established; according to the distribution of the acquisition coefficient Rz, the safety coefficient Aq and the client economic evaluation value JPz, determining an invited client, and sending an acquisition invitation to the invited client;
the fourth step comprises the following steps:
step 401, when the client does not live in again after exceeding the preset time, acquiring a live-in coefficient Rz of the client, a safety coefficient Aq, and when the live-in coefficient Rz and the safety coefficient Aq are both larger than a corresponding threshold value, indicating that the self condition of the client is relatively good, and marking the live-in client as a recommendable client;
summarizing recommended clients in the previous period when the room occupancy rate of the hotel in the current period is less than expected, and establishing a recommended client set; when the client is used, the client can be timely selected and input and output invitations through the established recommended client set.
Step 402, selecting clients from the recommended clients, obtaining the duration Ct of the clients, the extra consumption Ex in the hotel, and the price Fj of the resident clients, wherein when the number of times of the client's check-in is one or more, for example n times, the duration is recorded as
Figure SMS_10
The extra consumption in hotel is recorded as +.>
Figure SMS_11
The guest room prices are recorded as +.>
Figure SMS_12
；
Acquiring duration of life
Figure SMS_13
Extra consumption in hotel>
Figure SMS_14
Guest room price->
Figure SMS_15
After dimensionless treatment, acquiring a customer economic evaluation value JPz in a correlation way;
the customer economic evaluation value JPz is obtained as follows:
Figure SMS_16
wherein (1)>
Figure SMS_17
Is weight(s)>
Figure SMS_18
，
Figure SMS_19
And->
Figure SMS_20
The specific value can be set by the user;
wherein the economic evaluation value of clients is used
Figure SMS_21
The importance of recommending rooms to customers is evaluated by the following characterization modes:
Figure SMS_22
wherein (1)>
Figure SMS_23
For the first consumption intermediate value,/->
Figure SMS_24
Is a second consumption intermediate value; />
Economic evaluation value of clients
Figure SMS_25
Comparing with corresponding threshold value, if the economic evaluation value of the customer is
Figure SMS_26
Below the corresponding recommendation threshold, the corresponding client has no great recommendation value;
step 403, acquiring a plurality of economic evaluation values JPz of clients, sorting from high to low to form a recommendation sequence, and sequentially sending out a check-in invitation to the clients by the reception robot through reserved contact ways; wherein the offer for check-in includes at least a room price, the room price being at least not greater than a last check-in price;
when the intelligent hotel management system is used, based on the formed economic evaluation value JPz, after a recommended client is selected based on the check-in coefficient Rz, the safety coefficient Aq determines the recommendation sequence, so that when the room rate of a hotel is higher, check-in invitations can be orderly sent to the recommended client by the reception robot based on the consumption condition of the room in the check-in period, the check-in rate of the hotel is improved, and the check-in rate is improved.
Step five, sending a check-in invitation to the client, and determining a standard of continuously sending an offer to the client according to historical check-in information of the client if the client can be recommended to not check in after the preset time; combining the evaluation made to the invited clients, determining a discount scheme, transmitting the discount scheme to the invited clients according to the client reservation information, and collecting comments from part of the invited clients if the invited clients are still not in the home;
the fifth step comprises the following steps:
step 501, acquiring regression information of recommended tenants in a preset period, acquiring total revenue brought by the client re-check-in the period after the client re-check-in, and if the total revenue reaches the expectation, not continuing to send out check-in invitations;
when the total revenue does not reach the expectation, a regression analysis prediction model is established according to a plurality of groups of historical check-in data, and prediction is formed on the guest room surplus at the recommended date;
if the residual guest room exceeds a preset threshold, continuing to send out a check-in invitation; if it is lower than expected, it is not recommended.
When the hotel management system is used, if a customer check-in again but the business income of the hotel is still insufficient, the customer needs to be considered to continuously send out offers to the customer in order to improve the income, and if the income demand is met and the number of rooms is small, the customer can leave a plurality of spare rooms so as to cope with a large number of customers which may suddenly appear.
Step 502, selecting clients from the recommendable clients, and determining corresponding economic evaluation values JPz of the clients; determining a discount scheme for the client according to the distribution of the economic evaluation values JPz of the client to form a marketing strategy;
wherein, marketing strategy is as follows:
when the customer economic rating value JPz is greater than the second threshold, providing the invited customer with a first level of discount;
providing the invited customer with a second level of discount when the customer economic rating value JPz is between the first threshold and the second threshold;
when the customer economic rating value JPz is less than the first threshold, providing the invited customer with a third level of discount;
wherein the second threshold is greater than the first threshold, and wherein the first level discount is superior to the second level discount and the third level discount.
When the method is used, enough effects are not received aiming at the first invitation, at the moment, the invitation needs to be sent out again aiming at other clients, on the basis of the first invitation, a marketing policy is formulated according to the distribution of the economic evaluation values JPz of the clients, and certain discounts are given under the condition that the enterprise income is not lowered, so that the probability of the invited clients to check in is increased.
Step 503, after sending a discount scheme to the invited clients, if the clients receiving the first-level discount are still not in, carrying out voice return visit to the invited clients in a voice mode by the receiving robot which receives the corresponding invited clients and has a name;
and collecting the reason that the client is no longer in the house, and establishing an opinion collecting system.
When in use, if the check-in of the guest room is still insufficient based on the steps 501 and 502, the invitation is not continued at this time, the client receiving the first-level discount is revisited, and the corresponding opinion is collected, so that the hotel makes the corresponding change.
When the hotel management system is used, the contents in the steps 501 to 503 are combined, invitation or return visit is sent to the previous clients in a layered manner, the check-in rate of the hotel is increased under the assistance of the standby robot by means of the formulated marketing strategy and the return visit strategy, and if the income of the guest rooms given by the hotel is not increased, the return visit strategy is adopted at the moment, so that the improvement of the hotel can be facilitated; in addition, the reception robot of the previous reception user can also increase the image of the client, and plays a role in propaganda and marketing for the hotel.
The above embodiments may be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented in software, the above-described embodiments may be implemented in whole or in part in the form of a computer program product. The computer program product comprises one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the processes or functions described in accordance with the embodiments of the present application are all or partially produced. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center by wired (e.g., infrared, wireless, microwave, etc.). The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains one or more sets of available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium may be a solid state disk.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.
In the several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the elements is merely a division of some logic functions, and there may be additional divisions in actual implementation, e.g., multiple elements or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, or other various media capable of storing program codes.
The foregoing is merely specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily think about changes or substitutions within the technical scope of the present application, and the changes and substitutions are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Finally: the foregoing description of the preferred embodiments of the invention is not intended to limit the invention, but to enable any modification, equivalent or improvement to be made without departing from the spirit and principles of the invention.

Claims (10)

1. An intelligent hotel management system, which is characterized in that: comprises the following steps of the method,
when the number of staff in the hotel is insufficient, starting a reception robot and enabling the reception robot to move in a reception area of the hotel, receiving and guiding clients entering the reception area, collecting client demand information and collecting client images when the clients are received, and establishing a characteristic image library;
judging the consumption capacity and the check-in safety of the clients according to the information acquisition of the receiving robot to the clients, and recommending corresponding rooms to the clients by combining the formed judging results with the distribution of the residual rooms in the hotel; after handling the check-in procedure for the client, guiding the client to check in;
when a customer is about to get out of a house, acquiring the information of the customer about to get in the house after the information of the customer about to get out of the house, arranging a reception robot closest to the customer about to get in the house, guiding the customer to transact the procedure of the house, forming an in-house coefficient Rz according to the information of the in-house, and forming an evaluation on the service difficulty of the customer;
after the expected time, if the customer does not check in again, the consumption data of the customer during check in is called, and a customer economic evaluation value JPz is established; according to the distribution of the acquisition coefficient Rz, the safety coefficient Aq and the client economic evaluation value JPz, determining an invited client, and sending an acquisition invitation to the invited client;
sending a check-in invitation to the client, and determining a standard of continuously sending out an offer to the client according to the historical check-in information of the client if the client can be recommended to not check in after the preset time; and determining a discount scheme according to the client reservation information and sending the discount scheme to the invited clients in combination with the evaluation made to the invited clients, and collecting comments from part of the invited clients if the invited clients are still not in the home.
2. A smart hospitality management system as claimed in claim 1, wherein:
a movable reception robot is arranged in a reception area of a hotel lobby, and when a guest enters the reception area based on machine vision, the reception robot sends a voice query to the guest, wherein the query information at least comprises whether to check in, check in time and the number of check-in people;
when the client is judged to be in, guiding the client to rest in a rest area, and when the client is judged to be in, guiding the client to move towards the foreground; the reception robot accesses the guest room management system, inquires about the current guest room free condition and corresponding price and discount in the hotel, and when the current hotel guest room is remained, acquires images of the clients to be received, wherein the image content at least comprises wearing and wearing, and constructs a client image feature library.
3. A smart hospitality management system as claimed in claim 1, wherein:
after the customer image feature library is obtained, when a plurality of customers exist, age information and dressing information of the plurality of customers are obtained, and the values of wearing and accessories of the customers are inquired and judged through an inquiry module to form external prices; selecting the highest value from a plurality of external prices, taking the corresponding client as a target client, and outputting the position information of the target client; determining a consumption coefficient Xf of the client according to the ratio relation between the highest value and a preset value threshold;
acquiring position information of a client, enabling the reception robot to talk with the target client before moving to the target client, collecting emotion characteristics of the client, performing character analysis, and determining a safety coefficient Aq of the target client according to emotion stability;
when the safety coefficient Aq of the target client is larger than a threshold value, the region is not limited when recommending the guest room to the target client; when the safety coefficient Aq of the client is smaller than the threshold value, when recommending the guest room to the target client, the guest room recommended to the target client preferentially is not in the non-proximity of the old and the child.
4. A smart hospitality management system as claimed in claim 3, wherein:
according to the relation between the consumption force coefficient Xf of the customer and the corresponding value threshold, matching the number of the receiving customers and the price of hotel rooms, and recommending at least one room corresponding to the price to the target customer; when the safety coefficient Aq and the consumption coefficient Xf are used as the reference standard of the recommended client, the priority of the safety coefficient Aq is higher than that of the consumption coefficient Xf; therefore, when the guest room recommendation is carried out, the security of the check-in clients in the hotel is prioritized;
after the target client selects a corresponding guest room, the reception robot handles the check-in procedure for the target client and guides the target client to the selected guest room; before a customer enters a guest room, a reception robot accesses a hotel equipment management system, checks whether equipment in the guest room is good, and if the equipment is good, guides the customer to check in.
5. A smart hospitality management system as claimed in claim 1, wherein:
after the room-returning information of the client is acquired, the reception robot which is most connected with the room-returning distance moves to the room-returning position according to the position information of the room-returning, handles the room-returning procedure for the client, and guides the client to the reception area of the hotel lobby; after the completion of the procedure of the room return,
the reception robot returns to the living room, acquires images of the living room, and establishes a living image feature library; and identifying a guest room image in the image feature library, acquiring the cleanliness of the guest room, forming a living coefficient Rz according to the cleanliness, and informing a cleaning person to clean the guest room before.
6. A smart hospitality management system as claimed in claim 1, wherein:
when the client does not get in again after exceeding the preset time, acquiring an in-house coefficient Rz and a safety coefficient Aq of the client, and when the in-house coefficient Rz and the safety coefficient Aq are both larger than corresponding thresholds, indicating that the client self conditions are relatively good, and marking the in-house client as a recommendable client;
summarizing recommended clients in the previous period when the room occupancy rate of the hotel in the current period is less than expected, and establishing a recommended client set; selecting clients from the recommended clients, obtaining the duration Ct of the clients, extra consumption Ex in the hotel and the price Fj of the resident clients, and obtaining the economic evaluation value JPz of the clients in a related manner after dimensionless processing;
acquiring a plurality of client economic evaluation values JPz, sequencing from high to low to form a recommendation sequence, and sequentially sending out a check-in invitation to the clients by the reception robot through reserved contact ways; the living offer at least comprises a living room price, and the living room price is at least not more than the last living price.
7. The intelligent hotel management system of claim 6, wherein:
the customer economic evaluation value JPz is obtained as follows:
Figure QLYQS_1
wherein (1)>
Figure QLYQS_2
Is weight(s)>
Figure QLYQS_3
，/>
Figure QLYQS_4
And->
Figure QLYQS_5
The specific value can be adjusted and set by a user, and n is the number of times of entering and holding; wherein the economic evaluation value of clients is used
Figure QLYQS_6
The importance of recommending rooms to customers is evaluated by the following characterization modes:
Figure QLYQS_7
wherein (1)>
Figure QLYQS_8
For the first consumption intermediate value,/->
Figure QLYQS_9
Is a second consumption intermediate value.
8. A smart hospitality management system as claimed in claim 1, wherein:
acquiring regression information of recommended tenants in a preset period, acquiring total revenue brought by the client in the period after the client re-registers, and if the total revenue reaches the expectation, not continuing to send the registering invitation; when the total revenue does not reach the expectation, a regression analysis prediction model is established according to a plurality of groups of historical check-in data, and prediction is formed on the guest room surplus at the recommended date; if the residual guest room exceeds a preset threshold, continuing to send out a check-in invitation; if it is lower than expected, it is not recommended.
9. The intelligent hotel management system of claim 8, wherein:
selecting clients from the set of recommendable clients that have not issued invitations and determining corresponding client economic evaluation values JPz; determining a discount scheme for the client according to the distribution of the economic evaluation values JPz of the client to form a marketing strategy; wherein, marketing strategy is as follows:
when the customer economic rating value JPz is greater than the second threshold, providing the invited customer with a first level of discount; providing the invited customer with a second level of discount when the customer economic rating value JPz is between the first threshold and the second threshold; when the customer economic rating value JPz is less than the first threshold, providing the invited customer with a third level of discount;
wherein the second threshold is greater than the first threshold, and wherein the first level discount is superior to the second level discount and the third level discount.
10. The intelligent hotel management system of claim 9, wherein:
after giving a discount scheme to the invited clients, if the clients receiving the first-level discount are still not in the home, carrying out voice return visit to the invited clients in a voice form by a receiving robot which receives the corresponding invited clients and has a name; and collecting the reason that the client is no longer in the house, and establishing an opinion collecting system.
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