Internet data intelligent service-based hotel online reservation service system and intelligent terminal

Abstract

The invention discloses a hotel online reservation service system based on Internet data intelligent service and an intelligent terminal, and belongs to the field of hotel reservation service. The hotel online reservation service system based on the Internet data intelligent service comprises a reservation management module, a guest room management module and a customer information management module. The method solves a problem that the customer distribution efficiency is affected because reasonable distribution cannot be carried out according to demands of different customers in the prior art, can automatically distribute hotel guest rooms according to customer preference factors, reduces manual communication errors, ensures that the check-in experience accords with expectations, improves the service response speed, improves the utilization rate and the room distribution efficiency, and improves the user experience. By evaluating the running state of the equipment of the hotel guest room, potential faults can be found in advance, the maintenance process can be automatically triggered, the situation that guests encounter equipment faults when checking in is avoided, the satisfaction degree is improved, the situation that the hotel guest room is temporarily non-sold due to sudden faults is avoided by eliminating equipment hidden dangers in advance, and the room resource utilization rate is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of hotel reservation services, and in particular to an online hotel reservation service system and an intelligent terminal based on internet data intelligent services. Background Art

[0002] As a place that provides direct services to guests, hotels also need to provide more personalized services in this market context, allowing customers to experience the comfort and convenience brought by high-tech. The existing hotel check-in methods are for guests to make reservations online or check in directly in person. However, online reservations may result in the guest not being able to check in in person, which brings inconvenience to hotel management. In addition, online reservations and the check-in process may result in guests defaulting on their reservations, which also brings inconvenience to hotel operations.

[0003] Chinese patent publication number CN117035137A discloses a platform and intelligent system for self-service check-in, including an online reservation module, a hotel online platform, a third-party monitoring module, a backend center module, and an offline check-in processing module. The online reservation module is bidirectionally connected to the hotel online platform. In the present invention, an online reservation module is provided, which can be any of a mobile phone or a tablet computer. The camera module and the fingerprint collection module can respectively collect the guest's facial information and fingerprint information, and import this information into the identity information entry module. The guest can then enter their ID information, contact information, and payment information through the identity information entry module. Finally, after the identity information entry module obtains all the information, it connects to the hotel online platform through the hotel platform connection module, allowing the guest to reserve a hotel room online through their mobile phone or tablet computer.

[0004] In actual use of the above patent, when reserving hotel rooms, the allocation of hotel rooms cannot be reasonably allocated according to the needs of different customers, thereby affecting the efficiency of customer allocation. Summary of the Invention

[0005] The purpose of the present invention is to provide a hotel online reservation service system and intelligent terminal based on Internet data intelligent service, which can automatically allocate hotel rooms according to customer preference factors, ensure that the check-in experience meets expectations, improve service response speed, improve operational reliability, shorten hotel room turnover gaps, and improve utilization and room allocation efficiency. By evaluating the operating status of the equipment in the hotel room, potential faults can be discovered in advance and the maintenance process can be automatically triggered to avoid equipment failures when guests check in. The maintenance is automatically completed in the gap between the reservation and the check-in period. When guests check in, they can directly enjoy the equipment in good condition, which improves satisfaction. By eliminating equipment hidden dangers in advance, it is avoided that the hotel room is temporarily unsaleable due to sudden failures, the room utilization rate is improved, and the problems raised in the above background technology are solved.

[0006] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a hotel online reservation service system and intelligent terminal based on Internet data intelligent service, comprising:

[0007] The reservation management module is used to receive and integrate hotel room reservation information from multiple channels, synchronize the integrated hotel room reservation information in real time, and allocate hotel rooms based on the synchronized hotel room reservation information;

[0008] The room management module is used to obtain the status of reserved hotel rooms, execute cleaning plans and facility maintenance according to the hotel room status, and interact with smart devices in the hotel rooms to update the hotel room status in real time and provide network connections for customers;

[0009] Get the status of the reserved hotel room, including:

[0010] Extract the hotel room status of the customer's reservation, as well as the customer's historical reservation and accommodation records;

[0011] If the customer has a history of reservations and accommodation records, the state transition probability corresponding to the hotel room state reserved by the customer is obtained using the customer's history of reservations and accommodation records;

[0012] The customer information management module is used to record customer preferences and historical consumption records, and provide customized welcome gifts and service arrangements based on customer preferences and historical consumption records.

[0013] Preferably, the reservation management module includes:

[0014] A receiving unit, configured to receive hotel room reservation information from multiple channels and integrate the received hotel room reservation information from multiple channels;

[0015] An allocation unit is used to synchronize the integrated hotel room reservation information in real time, extract customer preference factors, and automatically allocate the best hotel room based on hotel room status and customer preference factors;

[0016] The confirmation unit is used to confirm the reservation success notification corresponding to the hotel room reservation order, and send the confirmed reservation success notification and the interior display picture of the hotel room to the customer in the form of email and text message.

[0017] Preferably, the distribution unit includes:

[0018] Determine whether the hotel room reservation order is a quota room reservation order, wherein a quota room reservation order is used to request a quota room reservation, and a non-quota room reservation order can be used to request a quota room or a non-quota room reservation;

[0019] If the hotel room reservation order is a quota room reservation order, a reservation success notification corresponding to the hotel room reservation order is generated;

[0020] In the case where the hotel room reservation order is a non-quota room reservation order, the integrated hotel room reservation information is synchronized in real time to extract customer preference factors from the integrated hotel room reservation information;

[0021] Preprocessing customer preference factors to obtain preprocessed data, and forming the preprocessed data into a data set;

[0022] Construct a neural network, train and verify the neural network model based on the data set, and obtain a neural network model based on hotel room allocation;

[0023] Re-extract customer preference factors, input the re-collected customer preference factors into the neural network model based on hotel room allocation, obtain the hotel room allocation results, and generate a successful booking notification corresponding to the hotel room reservation order.

[0024] Preferably, the guest room management module includes:

[0025] An order acquisition unit is used to obtain the status of the hotel room reserved by the customer, determine a cleaning plan based on the status of the hotel room, and clean the hotel room according to the cleaning plan;

[0026] The equipment management unit is used to obtain the usage of hotel room equipment, evaluate the operating status of equipment, formulate maintenance plans for faulty equipment, and conduct risk assessments on abnormal equipment that has not failed;

[0027] Intelligent gateway unit, used to provide customers with encrypted networking plug-ins.

[0028] Preferably, determining the cleaning plan according to the hotel room status includes:

[0029] If the customer has no previous reservation or accommodation record, the room will be cleaned the day before the customer's arrival date.

[0030] Comparing the state transition probability corresponding to the hotel room state reserved by the customer with a preset probability threshold;

[0031] When the state transition probability corresponding to the hotel room state reserved by the customer exceeds a preset probability threshold, it is determined that the room will be cleaned on the date of the customer's arrival;

[0032] When the state transition probability corresponding to the hotel room state reserved by the customer does not exceed a preset probability threshold, it is determined that the room will be cleaned one day before the customer's arrival date.

[0033] Preferably, the state transition probability corresponding to the hotel room state reserved by the customer is obtained by utilizing the customer's historical reservation and accommodation records, including:

[0034] Retrieve the customer's historical reservation and accommodation records;

[0035] Equipment operating parameters from the customer during their stay at the house, wherein the equipment operating parameters include current waveform distortion, temperature drift, and humidity drift;

[0036] Acquiring multimodal comprehensive data corresponding to each stay of the customer based on the equipment operating parameters of the customer during the stay;

[0037] Retrieve the number of hotel room status changes that appear in the customer's historical reservation and accommodation records;

[0038] Retrieving the time interval between the reservation time of the reserved hotel room status and the time when the hotel room status changes each time in the customer's historical reservation and accommodation records;

[0039] Obtaining an average time interval by using the time interval between the reservation time of the hotel room status corresponding to each hotel room status change and the status change time of the hotel room status change;

[0040] The state movement probability corresponding to the customer is obtained based on the average number of hotel room state changes and time intervals appearing in the customer's historical reservation and accommodation records and the multimodal comprehensive data corresponding to each accommodation of the customer.

[0041] Preferably, the intelligent gateway unit specifically includes:

[0042] When the gateway is connected to the client terminal device, receiving the network deployment authorization of the client terminal device;

[0043] According to the network deployment authorization, deploy the encrypted networking plug-in in the customer terminal device;

[0044] The encrypted networking plug-in is configured with an encryption sub-plug-in, a network connection rotor plug-in, and a network switching sub-plug-in;

[0045] The encryption sub-plug-in is used to encrypt the device information of the client terminal device and generate the corresponding encrypted network number;

[0046] The rotor plug-in in the network connection is used to connect to the client terminal device through the encrypted network number, and establish a main network link with the client terminal device and a branch network link with the network switching sub-plug-in, the branch network link including a first branch network link and a second branch network link;

[0047] The network switching sub-plug-in is used to detect the main network strength of the main network link of the client terminal device, and when the first branch network link is connected to the main network link, search for the gateway device through the second branch network link connection, and switch the branch network link when the network strength of the gateway device is greater than the main network strength.

[0048] Preferably, the device management unit specifically includes:

[0049] The data acquisition unit is used to collect data from hotel room equipment and extract representations of the collected data after data processing and data fusion;

[0050] An evaluation unit, configured to use the representation as a state characteristic quantity of the hotel room equipment, perform a state evaluation based on the state characteristic quantity of the hotel room equipment, determine the faulty equipment, and perform a risk evaluation on the abnormal equipment that has not failed;

[0051] The maintenance unit is used to determine the fault type and cause of the faulty equipment and make fault repair decisions.

[0052] Preferably, the risk assessment for abnormal equipment that has not failed specifically includes:

[0053] Obtaining operational data of abnormal equipment that has not experienced a failure and baseline operational data of abnormal equipment that has not experienced a failure;

[0054] Combine the operating data of abnormal equipment with the baseline operating data to conduct a risk assessment on the abnormal equipment. If the assessment result is low risk, no maintenance decision is required.

[0055] If the assessment result is high risk, fault prediction is performed for the hotel room equipment with high risk assessment result;

[0056] Predict the future health status of hotel room equipment and make maintenance decisions based on the future health status of hotel room equipment;

[0057] Obtain the maintenance category of the hotel room equipment, and make maintenance plans for different maintenance categories, maintenance restrictions, mutually exclusive maintenance restrictions, maintenance resources and power grid operations of the hotel room equipment to obtain a maintenance plan.

[0058] The invention relates to an intelligent terminal for hotel online reservation service based on Internet data intelligent service, comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the functions of the hotel online reservation service system based on Internet data intelligent service.

[0059] Compared with the prior art, the present invention has the following beneficial effects:

[0060] The present invention automatically allocates hotel rooms according to customer preference factors, reduces manual communication errors, ensures that the check-in experience meets expectations, improves service response speed, and improves operational reliability. It reduces the need for room changes due to preference mismatch through intelligent matching, shortens the turnover gap of hotel rooms, and improves utilization and room allocation efficiency. Through the online reservation system, it reduces manual management costs, can directly obtain customer reservation data, facilitates the construction of customer portraits to implement precision marketing, and further increases revenue. Online reservations can ensure the accuracy and real-time nature of information, can automatically process reservation requests, track reservation status, manage cancellation and modification requests, and ensure the smooth progress of the reservation process. By evaluating the operating status of the equipment in the hotel guest rooms, it can detect potential faults in advance and automatically trigger the maintenance process to avoid equipment failures when guests check in. The maintenance is automatically completed in the gap between the reservation and check-in. When guests check in, they can directly enjoy the equipment in good condition, which improves satisfaction. By eliminating equipment hidden dangers in advance, it can avoid the temporary unsale of hotel rooms due to sudden failures, and improve the utilization rate of room resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 This is a schematic diagram of the hotel online reservation service system module based on Internet data intelligent service of the present invention;

[0062] Figure 2 This is a flow chart of the hotel online reservation service system based on Internet data intelligent service of the present invention. DETAILED DESCRIPTION

[0063] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0064] In order to solve the problem that the existing technology cannot reasonably allocate hotel rooms according to the needs of different customers when reserving hotel rooms, thereby affecting the efficiency of customer allocation, please refer to Figure 1-Figure 2 , this embodiment provides the following technical solutions:

[0065] Hotel online reservation service system and intelligent terminal based on Internet data intelligent service, including:

[0066] The reservation management module is used to receive and integrate hotel room reservation information from multiple channels, synchronize the integrated hotel room reservation information in real time, and allocate hotel rooms based on the synchronized hotel room reservation information;

[0067] The room management module is used to obtain the status of reserved hotel rooms, execute cleaning plans and facility maintenance based on the hotel room status, and interact with smart devices in the hotel rooms to update the hotel room status (such as whether it is occupied and whether it has been cleaned) in real time, greatly improving the accuracy and efficiency of hotel room management and providing customers with network connectivity;

[0068] The customer information management module is used to record customer preferences and historical consumption records, and provide customized welcome gifts and service arrangements based on customer preferences and historical consumption records to improve customer satisfaction and loyalty.

[0069] Through multi-channel hotel room reservation information, customers can make reservations anytime and anywhere, reducing the time spent on telephone or offline communication. The operation is fast and available 24 hours a day. Through the online reservation system, customers can view room status, select dates, compare prices and confirm instantly in real time. The average reservation time is greatly reduced. Room status information can be updated in real time, and hotel room inventory, prices and room type changes can be displayed simultaneously to avoid overbooking or information delays. Through data analysis functions, hotels can dynamically adjust pricing strategies, reasonably allocate rooms, and reduce manual management costs. Direct online reservations can directly obtain customer reservation data, facilitate the construction of customer portraits, implement precision marketing, and further increase revenue. Online reservations can ensure the accuracy and real-time nature of information, automatically process reservation requests, track reservation status, manage cancellation and modification requests, and ensure a smooth reservation process.

[0070] Appointment management module, including:

[0071] A receiving unit is used to receive and integrate hotel room reservation information from multiple channels, including official website, OTA platform and telephone reservation;

[0072] The allocation unit is used to synchronize the integrated hotel room reservation information in real time, extract customer preference factors, and automatically allocate the best hotel room according to the hotel room status and customer preference factors, thereby reducing manual intervention and improving work efficiency.

[0073] The confirmation unit is used to confirm the reservation success notification corresponding to the hotel room reservation order, and send the confirmed reservation success notification and the interior display picture of the hotel room to the customer in the form of email and text message to improve the response speed.

[0074] Distribution unit, comprising:

[0075] Determine whether the hotel room reservation order is a quota room reservation order, wherein a quota room reservation order is used to request a quota room reservation, and a non-quota room reservation order can be used to request a quota room or a non-quota room reservation;

[0076] If the hotel room reservation order is a quota room reservation order, a reservation success notification corresponding to the hotel room reservation order is generated;

[0077] In the case where the hotel room reservation order is a non-quota room reservation order, the integrated hotel room reservation information is synchronized in real time to extract customer preference factors from the integrated hotel room reservation information;

[0078] Preprocessing customer preference factors to obtain preprocessed data, and forming the preprocessed data into a data set;

[0079] Construct a neural network, train and verify the neural network model based on the data set, and obtain a neural network model based on hotel room allocation;

[0080] Re-extract customer preference factors, input the re-collected customer preference factors into the neural network model based on hotel room allocation, obtain the hotel room allocation results, and generate a successful booking notification corresponding to the hotel room reservation order.

[0081] By automatically allocating hotel rooms based on historical customer preferences (such as floor, bed type, and view requirements) or special requests specified during reservations (such as non-smoking rooms and accessibility), the system reduces manual communication errors and ensures the check-in experience meets expectations. It can automatically identify membership levels and historical preferences (such as quiet rooms and specific orientations) based on customer preferences, prioritize high-quality room types or provide upgrades, strengthening customers' sense of belonging. It automatically screens eligible hotel rooms (such as those requiring cribs or extra beds), avoiding manual oversights, improving service response times, and shortening check-in times, significantly reducing front desk pressure during peak hours. It can integrate room status, cleaning progress, and maintenance status data in real time based on the hotel's room allocation structure to ensure that assigned rooms are immediately available, avoiding conflicts caused by information lags. Automated processes reduce manual errors such as duplicate reservations and mismatched room types, improving operational reliability. Intelligent matching reduces the need for room changes due to preference discrepancies, shortens hotel room turnover, and improves utilization and room allocation efficiency. By extracting customer preference data, it assists in formulating precise pricing strategies (such as a premium for preferred room types) and optimizing room allocation. By recording and analyzing customer preferences, it can automatically provide more personalized service for the next reservation. For example, if a customer prefers to stay in a high-rise room or a room near an elevator, the corresponding room can be automatically arranged when the customer makes his next reservation, improving the customer's accommodation experience. The system can automatically save the customer's preference information, such as bed type and floor, and quickly match the corresponding room when the customer makes another reservation, reducing manual operation time and significantly improving business processing efficiency. The system can dynamically adjust room allocation strategies based on customer preferences and historical behavior data, reasonably allocate rooms, reduce manual management costs and error rates, and by providing personalized services, hotels can establish long-term relationships with customers and increase customer return rates. For example, when a frequent guest makes another reservation, the system will automatically remind the front desk staff of the customer's preferences and arrange a room in advance, thereby improving customer loyalty and satisfaction.

[0082] Room management module, including:

[0083] An order acquisition unit is used to obtain the status of the hotel room reserved by the customer, determine a cleaning plan based on the status of the hotel room, and clean the hotel room according to the cleaning plan;

[0084] The equipment management unit is used to obtain the usage of hotel room equipment, evaluate the operating status of equipment, formulate maintenance plans for faulty equipment, and conduct risk assessments on abnormal equipment that has not failed;

[0085] Intelligent gateway unit, used to provide customers with encrypted networking plug-ins.

[0086] Specifically, the cleaning plan is determined based on the status of the hotel room reserved by the customer, including:

[0087] Extract the hotel room status of the customer's reservation, as well as the customer's historical reservation and accommodation records; the hotel room status of the customer's reservation includes but is not limited to basic reservation completion status, reservation cancellation status, and reservation of special items (such as cribs, fitness equipment, chess and card game equipment, etc.);

[0088] If the customer has a history of reservations and accommodation records, the state transition probability corresponding to the hotel room state reserved by the customer is obtained using the customer's history of reservations and accommodation records;

[0089] If the customer has no previous reservation or accommodation record, the room will be cleaned the day before the customer's arrival date.

[0090] The state transition probability corresponding to the hotel room state reserved by the customer is compared with a preset probability threshold; wherein, the experience-based probability threshold setting method is mainly to summarize the correlation between the customer reservation status and the actual arrival situation in the hotel's historical operating data, combined with the actual needs of the room cleaning resource scheduling, and the operation management personnel set a probability critical value for judging whether to adjust the cleaning timing based on experience. In general, the method of obtaining the probability threshold includes but is not limited to the following methods: statistically analyzing the probability distribution of the customer's actual arrival at the hotel after making a reservation in the historical data, and setting the threshold at a critical point that can effectively distinguish between "high probability arrival" and "low probability arrival" (for example, if historical data shows that the customer arrival rate increases significantly when the state transition probability exceeds 70%, then the threshold is set to 70%).

[0091] When the state transition probability corresponding to the hotel room state reserved by the customer exceeds a preset probability threshold, it is determined that the room will be cleaned on the date of the customer's arrival;

[0092] When the state transition probability corresponding to the hotel room state reserved by the customer does not exceed a preset probability threshold, it is determined that the room will be cleaned one day before the customer's arrival date.

[0093] The technical benefits of the above-mentioned technical solution are as follows: Based on multiple dimensions of room status, including basic reservation status, cancellation status, and special amenity requests, and in combination with historical guest reservation records, the solution constructs a state transition probability model. For guests with historical data, this model probabilistically quantifies room status trends (e.g., reservation stability for guests with frequent cancellations) to accurately determine cleaning timing. If the probability exceeds a threshold, the room is cleaned on arrival, minimizing secondary contamination and resource waste caused by pre-emptive cleaning. If the probability does not exceed the threshold, the room is cleaned one day in advance to ensure cleanliness. For new guests, a guaranteed cleaning schedule of one day in advance is implemented, balancing efficiency and reliability. This optimizes the allocation of human and material resources (e.g., avoiding duplicated work and unused linens caused by premature cleaning). By making cleaning timing decisions tailored to guest behavior, the solution reduces costs and user experience issues caused by inappropriate cleaning timing (e.g., wasted resources caused by guest cancellations after pre-emptive cleaning, or cleaning too late, which impacts the guest experience). This improves hotel management refinement and resource utilization efficiency, enhancing the consistency of the guest experience.

[0094] Specifically, the state transition probability corresponding to the hotel room state reserved by the customer is obtained by using the customer's historical reservation and accommodation records, including:

[0095] Retrieve the customer's historical reservation and accommodation records;

[0096] Equipment operating parameters during the client's stay at the residence, wherein the equipment operating parameters include but are not limited to current waveform distortion, temperature drift, humidity drift, etc.;

[0097] Acquiring multimodal comprehensive data corresponding to each stay of the customer based on the equipment operating parameters of the customer during the stay;

[0098] The multimodal comprehensive data corresponding to each housing stay of the customer is obtained by the following formula:

[0099]

[0100] Among them, F represents the multimodal comprehensive data corresponding to each customer's stay; n represents the number of types of equipment operating parameters corresponding to each customer's stay; w i Represents the weight value corresponding to the operating parameters of the i-th type of equipment; r i Indicates the modal sensitivity coefficient corresponding to the operating parameters of the i-th type of equipment, with a value range of 0.2-1.4; ΔX i Indicates the average deviation of the numerical values ​​corresponding to the operating parameters of the i-th type of equipment; X refi Indicates the numerical reference value corresponding to the operating parameter of the i-th type of equipment (set based on experience); specifically, The exponential function is used to quantify the degree of influence of abnormal / deviation of equipment parameters on the guest room status. iApproaching 0 (equipment is close to normal operation), the result of this formula approaches 0, indicating that the impact on the guest room status is small; when ΔX i The result approaches 1, which reflects the significant interference of abnormal equipment parameters on the guest room status (such as customer behavior and environmental stability). Finally, the multimodal comprehensive data F is obtained by summing up, which integrates the comprehensive impact of multiple equipment parameters on the guest room status.

[0101] Retrieve the number of hotel room status changes that appear in the customer's historical reservation and accommodation records;

[0102] Retrieving the time interval between the reservation time of the reserved hotel room status and the time when the hotel room status changes each time in the customer's historical reservation and accommodation records;

[0103] Obtaining an average time interval by using the time interval between the reservation time of the hotel room status corresponding to each hotel room status change and the status change time of the hotel room status change;

[0104] The state movement probability corresponding to the customer is obtained based on the average number of hotel room state changes and time intervals appearing in the customer's historical reservation and accommodation records and the multimodal comprehensive data corresponding to each accommodation of the customer.

[0105] The state transition probability is obtained by the following formula:

[0106]

[0107] Among them, A represents the state movement probability of the customer; N represents the number of hotel room state changes in the customer's historical reservation and accommodation records; F j represents the multimodal comprehensive data corresponding to the jth hotel room status change; t p represents the average value of the time interval; α represents the preset abnormal response coefficient, and the value range of the abnormal response coefficient is 1.2-1.8; β represents the preset time decay coefficient, and the value range of the time decay coefficient is 0.1-0.3. Specifically, In the time interval t p The longer, The smaller, The closer it is to 1, the weaker the impact of historical state changes on the current "state transition probability" is over time, which is consistent with the rule in actual scenarios that "customer recent behavior is more relevant to current predictions."

[0108] The technical effects of the above technical solution are: on the one hand, it deeply mines the historical housing records of customers, cuts in from the equipment operation parameters (electricity current waveform distortion, temperature and humidity drift, etc.), uses the multimodal comprehensive data formula F, and integrates the equipment parameter weight wi , modal sensitivity coefficient r i , numerical deviation ΔX i With reference value X refi , accurately depicting the customer behavior and environmental status behind the operation of the equipment at each stay, providing fine-grained, multi-dimensional data support for state transition analysis; on the other hand, combined with the number of room state changes and the average time interval, through the state movement probability formula A, the abnormal response coefficient α is introduced to capture sudden state changes, and the time decay coefficient β reflects the attenuation law of the impact of time on state transition, and a correlation model is constructed from "equipment micro-operation" to "room state macro-transfer". Ultimately, the scientific calculation of the probability of guest room state transition is achieved, helping hotels to accurately predict the evolution of customer reservation status, providing data basis for dynamic decision-making on cleaning plans (such as flexibly adjusting cleaning timing based on probability thresholds), improving the intelligence and refinement of room operation management, optimizing resource allocation, and reducing cost waste or poor service experience caused by errors in state prediction.

[0109] The above technical solution also focuses on analyzing equipment micro-operating parameters (e.g., current distortion, temperature and humidity drift). Formula F integrates multi-dimensional data to explore the correlation between equipment parameters and customer behavior and room status, upgrading room status analysis from "coarse recording" to "fine-grained quantification." For example, current waveform distortion can be used to identify customers using high-power appliances, predicting the need for linen replacement and better aligning cleaning plans with actual consumption. Furthermore, dynamic modeling of historical behavior is performed, integrating "state change frequency, time interval, and anomaly intensity" using Formula A to construct a dynamic probabilistic model of customer behavior. Compared to the traditional approach of solely focusing on reservation fulfillment rates, this solution can more accurately distinguish between "stable customers" (who have a low probability of state transition and are therefore more reliant on pre-cleaning) and "volatile customers" (who have a high probability of state transition and are therefore more likely to receive a same-day cleaning). This shifts cleaning timing decisions from "experience-based" to "data-driven." By accurately predicting room state transitions, cleaning plans can be dynamically adjusted. For customers with a high probability of state transition, cleaning can be delayed to avoid wasting resources if they cancel after a pre-cleaning session. For customers with a low probability of state transition, pre-cleaning can ensure a clean room. Compared to existing technologies that "unify cleaning times" (e.g., uniformly starting cleaning one day in advance), this approach can reduce the loss of resources such as manpower and linens, while also reducing negative reviews due to "rooms not being cleaned promptly upon arrival," balancing operating costs with the service experience. Through multimodal data quantification and dynamic probabilistic modeling, this solution addresses the challenges of traditional hotel room management, such as "narrow data dimensions, low prediction accuracy, and poor resource adaptation." This makes room cleaning plans more intelligent, more aligned with customer behavior and actual needs, and enhances hotel management refinement and resource utilization efficiency.

[0110] Intelligent gateway unit, specifically including:

[0111] When the gateway is connected to the client terminal device, receiving the network deployment authorization of the client terminal device;

[0112] According to the network deployment authorization, deploy the encrypted networking plug-in in the customer terminal device;

[0113] The encrypted networking plug-in is configured with an encryption sub-plug-in, a network connection rotor plug-in, and a network switching sub-plug-in;

[0114] The encryption sub-plug-in is used to encrypt the device information of the client terminal device and generate the corresponding encrypted network number;

[0115] The rotor plug-in in the network connection is used to connect to the client terminal device through the encrypted network number, and establish a main network link with the client terminal device and a branch network link with the network switching sub-plug-in, the branch network link including a first branch network link and a second branch network link;

[0116] The network switching sub-plug-in is used to detect the main network strength of the main network link of the client terminal device, and when the first branch network link is connected to the main network link, search for the gateway device through the second branch network link connection, and switch the branch network link when the network strength of the gateway device is greater than the main network strength.

[0117] In the prior art, when surfing the Internet in a hotel, due to distance, some routing devices may be far away, while others may be close. This may cause poor network signals when moving around. This may also leak the customer's terminal device information. To solve this technical problem, the present invention first obtains the customer's authorization by deploying a plug-in. Based on the customer's authorization, an encrypted networking plug-in is loaded and deployed in the terminal device. The customer's terminal device encrypts the customer's information through the encryption sub-plug-in in this plug-in, generates an encrypted networking number, and does not display the customer's device information. When connecting to the network, the network is only connected through the main network link of the rotor plug-in in the network connection. The main network link may be connected to the first branch network link or the second branch network link, but can only be connected to one branch. When the network of the branch connected in real time is too poor, the other branch automatically searches for network devices, determines a better network source routing device, and directly switches the network by switching branches. In this case, the main network link does not need to re-enter the password to connect to the new network routing device, but directly switches automatically. This ensures network continuity.

[0118] Device management unit, specifically including:

[0119] The data acquisition unit is used to collect data from hotel room equipment and extract representations of the collected data after data processing and data fusion;

[0120] An evaluation unit, configured to use the representation as a state characteristic quantity of the hotel room equipment, perform a state evaluation based on the state characteristic quantity of the hotel room equipment, determine the faulty equipment, and perform a risk evaluation on the abnormal equipment that has not failed;

[0121] The maintenance unit is used to determine the fault type and cause of the faulty equipment and make fault repair decisions.

[0122] The data acquisition unit collects data from the hotel room equipment, and extracts representations from the collected data after data processing and data fusion. The representations are used as state characteristics of the hotel room equipment. A state assessment is performed based on the state characteristics of the hotel room equipment to obtain the current health status of the hotel room equipment. If the state assessment result is normal, the entire analysis process is completed;

[0123] If the status assessment result is abnormal, perform fault diagnosis and analysis on the abnormal hotel room equipment. If the diagnosis result shows that the hotel room equipment has a fault, determine the fault type and cause, and make a fault repair decision. If the diagnosis result shows that there is no obvious fault in the hotel room equipment, then make a possible fault repair decision based on the possible cause and probability of occurrence in the diagnosis result.

[0124] Conduct risk assessments on abnormal equipment that has not experienced any failures, including:

[0125] Obtaining operational data of abnormal equipment that has not experienced a failure and baseline operational data of abnormal equipment that has not experienced a failure;

[0126] Combine the operating data of abnormal equipment with the baseline operating data to conduct a risk assessment on the abnormal equipment. If the assessment result is low risk, no maintenance decision is required.

[0127] If the assessment result is high risk, fault prediction is performed for the hotel room equipment with high risk assessment result;

[0128] Predict the future health status of hotel room equipment and make maintenance decisions based on the future health status of hotel room equipment;

[0129] Obtain the maintenance category of the hotel room equipment, and make maintenance plans for different maintenance categories, maintenance restrictions, mutually exclusive maintenance restrictions, maintenance resources and power grid operations of the hotel room equipment to obtain a maintenance plan.

[0130] By evaluating the operating status of the equipment in the hotel guest rooms, potential faults can be discovered in advance and the maintenance process can be automatically triggered to avoid equipment failures when guests check in. The maintenance is automatically completed in the gap between the reservation and check-in. Guests can directly enjoy the equipment in good condition when they check in, which improves satisfaction. Preventive maintenance is cheaper than emergency repairs after a failure, and avoids loss of hotel room revenue due to equipment outage. It automatically evaluates the operating status of the equipment and formulates maintenance plans for faulty equipment, reducing the workload of manual inspections. By eliminating equipment hidden dangers in advance, it avoids the temporary unsale of hotel rooms due to sudden failures, thereby improving room utilization.

[0131] The hotel online reservation service intelligent terminal based on Internet data intelligent service includes a memory and a processor, wherein the memory is used to store programs; the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the functions of the hotel online reservation service system based on Internet data intelligent service.

[0132] Working principle: When using the hotel online reservation service system based on Internet data intelligent service of the present invention, according to Figure 1 and Figure 2 , including the following steps:

[0133] S1: Receive hotel room reservation information from multiple channels, integrate the received hotel room reservation information from multiple channels, and synchronize the integrated hotel room reservation information in real time;

[0134] S2: Extract customer preference factors, automatically assign the best hotel room based on hotel room status and customer preference factors, confirm the corresponding hotel room reservation order and send the confirmed reservation success notification and hotel room interior display pictures to the customer via email and text message;

[0135] S3: Obtain the status of the hotel room reserved by the customer, determine a cleaning plan based on the hotel room status, and clean the hotel room according to the cleaning plan;

[0136] S4: Obtain the usage of hotel room equipment, evaluate the operating status of the equipment, formulate maintenance plans for faulty equipment, and conduct risk assessments on abnormal equipment that has not failed. Based on the risk assessment results, fault predictions are made for high-risk hotel room equipment.

[0137] S5: Record customer preferences and historical spending records, and provide customized welcome offers and service arrangements based on those preferences and historical spending records.

[0138] In summary, the hotel online reservation service system and intelligent terminal based on Internet data intelligent service of the present invention automatically allocates hotel rooms according to customer preference factors, reduces manual communication errors, ensures that the check-in experience meets expectations, strengthens customer sense of belonging, avoids manual omissions, improves service response speed, shortens check-in processing time, and significantly reduces front desk pressure during peak hours. It can integrate room status, cleaning progress and maintenance status data in real time according to the structure of hotel room allocation. The automated process can reduce manual errors such as repeated reservations and mismatched room types, improve operational reliability, reduce the need for room changes due to preference mismatches through intelligent matching, shorten the hotel room turnover gap, and improve utilization and room allocation efficiency. Through online reservations, customers can make reservations anytime and anywhere, reducing the time for telephone or offline communication. The operation is fast and available 24 hours a day. Through the online reservation system, manual management costs are reduced and can be directly obtained. Obtaining customer reservation data facilitates the construction of customer portraits, the implementation of precision marketing, and further increases revenue. Online reservations can ensure the accuracy and real-time nature of information, automatically process reservation requests, track reservation status, manage cancellation and modification requests, and ensure a smooth reservation process. By evaluating the operating status of the equipment in the hotel guest rooms, potential faults can be discovered in advance and the maintenance process can be automatically triggered to avoid equipment failures when guests check in. The maintenance is automatically completed in the gap between the reservation and check-in. Guests can directly enjoy the equipment in good condition when they check in, which improves satisfaction. Preventive maintenance is cheaper than emergency repairs after a failure, and avoids loss of hotel room revenue due to equipment outages. It automatically evaluates the operating status of the equipment and formulates maintenance plans for faulty equipment, reducing the workload of manual inspections. By eliminating equipment hazards in advance, it avoids the temporary unsale of hotel rooms due to sudden failures, thereby improving room utilization.

[0139] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0140] While the embodiments of the present invention have been shown and described, it will be apparent to those skilled in the art that various changes, modifications, substitutions, and alterations can be made to the embodiments without departing from the principles and spirit of the invention.

Claims

1. The hotel online reservation service system based on Internet data intelligent service is characterized by: include: The reservation management module is used to receive and integrate hotel room reservation information from multiple channels, synchronize the integrated hotel room reservation information in real time, and allocate hotel rooms based on the synchronized hotel room reservation information; The room management module is used to obtain the status of reserved hotel rooms, execute cleaning plans and facility maintenance according to the hotel room status, and interact with smart devices in the hotel rooms to update the hotel room status in real time and provide network connections for customers; Get the status of the reserved hotel room, including: Extract the hotel room status of the customer's reservation, as well as the customer's historical reservation and accommodation records; If the customer has a history of reservations and accommodation records, the state transition probability corresponding to the hotel room state reserved by the customer is obtained using the customer's history of reservations and accommodation records; The customer information management module is used to record customer preferences and historical consumption records, and provide customized welcome gifts and service arrangements based on customer preferences and historical consumption records.

2. The hotel online reservation service system based on Internet data intelligent service according to claim 1 is characterized in that: The reservation management module includes: A receiving unit, configured to receive hotel room reservation information from multiple channels and integrate the received hotel room reservation information from multiple channels; An allocation unit is used to synchronize the integrated hotel room reservation information in real time, extract customer preference factors, and automatically allocate the best hotel room based on hotel room status and customer preference factors; The confirmation unit is used to confirm the reservation success notification corresponding to the hotel room reservation order, and send the confirmed reservation success notification and the interior display picture of the hotel room to the customer in the form of email and text message.

3. The hotel online reservation service system based on Internet data intelligent service according to claim 2 is characterized in that: The distribution unit includes: Determine whether the hotel room reservation order is a quota room reservation order, wherein a quota room reservation order is used to request a quota room reservation, and a non-quota room reservation order can be used to request a quota room or a non-quota room reservation; If the hotel room reservation order is a quota room reservation order, a reservation success notification corresponding to the hotel room reservation order is generated; In the case where the hotel room reservation order is a non-quota room reservation order, the integrated hotel room reservation information is synchronized in real time to extract customer preference factors from the integrated hotel room reservation information; Preprocessing customer preference factors to obtain preprocessed data, and forming the preprocessed data into a data set; Construct a neural network, train and verify the neural network model based on the data set, and obtain a neural network model based on hotel room allocation; Re-extract customer preference factors, input the re-collected customer preference factors into the neural network model based on hotel room allocation, obtain the hotel room allocation results, and generate a successful booking notification corresponding to the hotel room reservation order.

4. The hotel online reservation service system based on Internet data intelligent service according to claim 1 is characterized in that: The guest room management module includes: An order acquisition unit is used to obtain the status of the hotel room reserved by the customer, determine a cleaning plan based on the status of the hotel room, and clean the hotel room according to the cleaning plan; The equipment management unit is used to obtain the usage of hotel room equipment, evaluate the operating status of equipment, formulate maintenance plans for faulty equipment, and conduct risk assessments on abnormal equipment that has not failed; Intelligent gateway unit, used to provide customers with encrypted networking plug-ins.

5. The hotel online reservation service system based on Internet data intelligent service according to claim 4 is characterized in that: The cleaning plan is determined according to the status of the hotel rooms, including: If the customer has no previous reservation or accommodation record, the room will be cleaned the day before the customer's arrival date. Comparing the state transition probability corresponding to the hotel room state reserved by the customer with a preset probability threshold; When the state transition probability corresponding to the hotel room state reserved by the customer exceeds a preset probability threshold, it is determined that the room will be cleaned on the date of the customer's arrival; When the state transition probability corresponding to the hotel room state reserved by the customer does not exceed a preset probability threshold, it is determined that the room will be cleaned one day before the customer's arrival date.

6. The hotel online reservation service system based on Internet data intelligent service according to claim 5 is characterized in that: The state transition probability corresponding to the hotel room state reserved by the customer is obtained by using the customer's historical reservation and accommodation records, including: Retrieve the customer's historical reservation and accommodation records; Equipment operating parameters from the customer during their stay at the house, wherein the equipment operating parameters include current waveform distortion, temperature drift, and humidity drift; Acquiring multimodal comprehensive data corresponding to each stay of the customer based on the equipment operating parameters of the customer during the stay; Retrieve the number of hotel room status changes that appear in the customer's historical reservation and accommodation records; Retrieving the time interval between the reservation time of the reserved hotel room status and the time when the hotel room status changes each time in the customer's historical reservation and accommodation records; Obtaining an average time interval by using the time interval between the reservation time of the hotel room status corresponding to each hotel room status change and the status change time of the hotel room status change; The state movement probability corresponding to the customer is obtained based on the average number of hotel room state changes and time intervals appearing in the customer's historical reservation and accommodation records and the multimodal comprehensive data corresponding to each accommodation of the customer.

7. The hotel online reservation service system based on Internet data intelligent service according to claim 4 is characterized in that: The intelligent gateway unit specifically includes: When the gateway is connected to the client terminal device, receiving the network deployment authorization of the client terminal device; According to the network deployment authorization, deploy the encrypted networking plug-in in the customer terminal device; The encrypted networking plug-in is configured with an encryption sub-plug-in, a network connection rotor plug-in, and a network switching sub-plug-in; The encryption sub-plug-in is used to encrypt the device information of the client terminal device and generate the corresponding encrypted network number; The rotor plug-in in the network connection is used to connect to the client terminal device through the encrypted network number, and establish a main network link with the client terminal device and a branch network link with the network switching sub-plug-in, the branch network link including a first branch network link and a second branch network link; The network switching sub-plug-in is used to detect the main network strength of the main network link of the client terminal device, and when the first branch network link is connected to the main network link, search for the gateway device through the second branch network link connection, and switch the branch network link when the network strength of the gateway device is greater than the main network strength.

8. The hotel online reservation service system based on Internet data intelligent service according to claim 4 is characterized in that: The device management unit specifically includes: The data acquisition unit is used to collect data from hotel room equipment and extract representations of the collected data after data processing and data fusion; An evaluation unit, configured to use the representation as a state characteristic quantity of the hotel room equipment, perform a state evaluation based on the state characteristic quantity of the hotel room equipment, determine the faulty equipment, and perform a risk evaluation on the abnormal equipment that has not failed; The maintenance unit is used to determine the fault type and cause of the faulty equipment and make fault repair decisions.

9. The hotel online reservation service system based on Internet data intelligent service according to claim 7 is characterized in that: The risk assessment for abnormal equipment that has not failed specifically includes: Obtaining operational data of abnormal equipment that has not experienced a failure and baseline operational data of abnormal equipment that has not experienced a failure; Combine the operating data of abnormal equipment with the baseline operating data to conduct a risk assessment on the abnormal equipment. If the assessment result is low risk, no maintenance decision is required. If the assessment result is high risk, fault prediction is performed for the hotel room equipment with high risk assessment result; Predict the future health status of hotel room equipment and make maintenance decisions based on the future health status of hotel room equipment; Obtain the maintenance category of the hotel room equipment, and make maintenance plans for different maintenance categories, maintenance restrictions, mutually exclusive maintenance restrictions, maintenance resources and power grid operations of the hotel room equipment to obtain a maintenance plan.

10. The hotel online reservation service intelligent terminal based on Internet data intelligent service is characterized by: The system comprises a memory and a processor, wherein the memory stores a computer program. When the computer program is executed by the processor, the processor executes the function of the hotel online reservation service system based on Internet data intelligent service according to any one of claims 1 to 9.

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