A store management method, device, medium and product

Abstract

A store management method, device, medium, and product relate to the field of data processing. In this method, upon receiving a service request from an interactive terminal in a target private room, a service scheduling session is initiated. Within the service scheduling session, the current playlist of the target private room is acquired and parsed, and the timeline sequence of songs to be played within a preset time period is identified. Based on the preset song attributes of each song to be played, multiple service windows are marked on the timeline sequence, and the service complexity and service divisibility corresponding to the service item identifier in the service request are queried. Based on the service complexity, service divisibility, and the duration of the multiple service windows, a delivery node is determined, and service personnel are guided to complete the delivery of the service request based on the delivery node. Implementing the technical solution provided in this application improves the user experience.

Description

Technical Field

[0001] This application relates to the field of data processing, specifically to a store management method, device, medium, and product. Background Technology

[0002] With the development of the social economy and the upgrading of consumption patterns, competition in the offline entertainment service industry, represented by KTV, is becoming increasingly fierce. Customers' demands for the consumption experience are no longer limited to hardware facilities, but rather they are pursuing a higher quality, more personalized, and immersive entertainment process. In this context, any interference with customers' core entertainment activities (such as singing) will directly affect their satisfaction and loyalty. Therefore, how to provide an undisturbed experience during the service process has become the key for stores to improve service quality and core competitiveness.

[0003] Currently, while mainstream KTV management systems have achieved informatization of back-end operations, a significant technical bottleneck remains when handling immediate service requests from customers. When a customer presses the call service button, the system can only send a general request signal to the service personnel. Service personnel cannot anticipate the specific situation inside the private room, and their entry into the room is entirely random and unpredictable. This service response mode easily leads to service personnel entering the room during the climax of a song or when the customer is engrossed in singing, thus interrupting the customer's entertainment rhythm and severely damaging their immersive experience. This conflict between service delivery timing and customer experience caused by the inability to perceive the customer's entertainment rhythm is a major technical problem that existing technologies urgently need to solve in improving the quality of immediate service. Summary of the Invention

[0004] This application provides a store management method, device, medium, and product that improves the user experience.

[0005] A first aspect of this application provides a store management method, comprising: upon receiving a service request sent by an interactive terminal in a target private room, initiating a service scheduling session; in the service scheduling session, acquiring and parsing the current playlist of the target private room, and identifying a timeline sequence of songs to be played within a preset time period; marking multiple service windows on the timeline sequence according to preset song attributes of each song to be played, each service window having a corresponding service duration, the preset song attributes including interlude information or outro information for defining non-core vocal segments within the song; calling a preset service attribute library to query the service complexity and service divisibility corresponding to the service item identifier in the service request; wherein, the service complexity is used to characterize the time resources required to complete the service, and the service divisibility is used to characterize whether the service can be split; determining a delivery node based on the service complexity, the service divisibility, and the duration of the multiple service windows, and guiding service personnel to complete the delivery of the service request based on the delivery node.

[0006] By adopting the above technical solutions, a service scheduling session is initiated to achieve unified management and tracking of service requests, ensuring that each service request has an independent processing flow. The current song list of the target private room is obtained and parsed, identifying the timeline sequence of songs to be played within a preset time period, enabling accurate prediction of entertainment activities in the private room over a future period. Multiple service windows are marked on the timeline sequence based on the preset song attributes of the songs to be played, accurately locating non-core singing segments using interlude and outro information, providing time periods for service execution that do not affect the customer's singing experience. A preset service attribute library is called to query service complexity and service divisibility, enabling differentiated processing for different service types. Service complexity ensures sufficient execution time is allocated to the service, while service divisibility supports flexible service arrangement strategies. Delivery nodes are determined based on service complexity, service divisibility, and the duration of multiple service windows, enabling intelligent selection of service timing, ensuring that the service is completed smoothly without interfering with the customer's entertainment. Based on the delivery nodes, service personnel are guided to complete the delivery of service requests, achieving precise scheduling of service execution, improving service efficiency and customer satisfaction.

[0007] Optionally, the step of marking multiple service windows on the timeline sequence according to the preset song attributes of each song to be played specifically includes: performing audio feature analysis on each song to be played, identifying the spectral features of the audio signal through Fourier transform, and determining the start and end times of the interlude and the outro in the song structure of the song to be played based on the spectral features; obtaining multiple available service periods and the net duration of each available service period based on the start and end times of the interlude and the outro, and selecting available service periods with a net duration greater than the preset service interference threshold as candidate service windows according to a preset service interference threshold; performing weight evaluation on each candidate service window, and determining multiple service windows based on the weight evaluation results, wherein the weight evaluation includes time interval index evaluation, position distribution index evaluation, and continuity index evaluation.

[0008] By employing the above technical solution, audio feature analysis is performed on each song to be played. Fourier transform is used to identify the spectral characteristics of the audio signal, enabling a scientific analysis of the song's internal structure and accurately locating the start and end times of interludes and outro segments, avoiding subjective errors and workload associated with manual annotation. Based on the start and end times of the interludes and outro segments, multiple available service periods and net durations are obtained, achieving precise quantification of service availability. Candidate service windows are filtered according to a preset service interference threshold, ensuring that the selected service windows have sufficient time to complete the service and avoiding haste and interruptions during service execution. Each candidate service window undergoes a weighted evaluation including time interval indicators, location distribution indicators, and continuity indicators, achieving a multi-dimensional evaluation of service window quality. Time interval indicators ensure timely service response, location distribution indicators guarantee the rationality of service timing, and continuity indicators maintain the integrity of service execution.

[0009] Optionally, determining the delivery node based on the service complexity, the service divisibility, and the duration of the multiple service windows specifically includes: if the service divisibility is determined to be indivisible, then matching and selecting the optimal service window that satisfies the service complexity from the multiple service windows as the delivery node; if the service request is a divisible service, then decomposing the service request into a preparation phase and a delivery phase; triggering the preparation phase, and selecting the optimal service window that satisfies the service complexity from the multiple service windows as the delivery node.

[0010] By adopting the above technical solutions, service requests are classified and processed based on service divisibility, providing customized scheduling strategies for different types of services. When a service is indivisible, the optimal service window that meets the service complexity is selected from multiple service windows as the delivery node, ensuring that the entire service is completed within a complete time window, guaranteeing service continuity and integrity. When a service is divisible, the service request is decomposed into a preparation phase and a delivery phase, achieving optimized decomposition of the service process. The preparation phase can be completed ahead of schedule without affecting customers, improving service efficiency. After the preparation phase is triggered, the optimal service window that meets the service complexity is selected from multiple service windows as the delivery node, achieving time decoupling between preparation and delivery. The early completion of the preparation phase ensures the rapid execution of the delivery phase, reducing service time in private rooms and minimizing customer disruption. Through flexible service decomposition and scheduling, the overall efficiency and quality of the service are improved.

[0011] Optionally, the step of matching and selecting the optimal service window that satisfies the service complexity among multiple service windows as the delivery node specifically includes: obtaining the window duration of each service window and obtaining the minimum required service duration corresponding to the service complexity; for each service window, determining whether the window duration is greater than or equal to the minimum required service duration to obtain an available window set; determining the comprehensive matching score of each service window in the available window set, wherein the comprehensive matching score is obtained by weighted calculation based on target parameters, the target parameters including time interval indicators, location distribution indicators, and continuity indicators; selecting the service window with the highest comprehensive matching score as the optimal service window, and marking the start time of the optimal service window as the delivery node.

[0012] By adopting the above technical solution, the minimum required service time corresponding to the window duration and service complexity of each service window is obtained, achieving precise matching between service demand and available resources. Determining whether the window duration meets the minimum required service time yields a set of available windows, ensuring that all selected service windows possess the basic conditions to complete the service and avoiding service interruptions or failures. The comprehensive matching score of each service window in the available window set is determined, and a comprehensive evaluation of service window quality is achieved through weighted calculations of time interval indicators, location distribution indicators, and continuity indicators. The time interval indicator ensures the timeliness of service, avoiding excessive customer waiting; the location distribution indicator ensures the rationality of service timing selection, avoiding disturbance to customers during critical entertainment times; and the continuity indicator maintains the smoothness of service execution, preventing service interruptions. The service window with the highest comprehensive matching score is selected as the optimal service window, achieving optimal service timing. The start time of the optimal service window is marked as the delivery node, providing precise time guidance for service execution and ensuring that the service is completed at the best time.

[0013] Optionally, after decomposing the service request into a preparation phase and a delivery phase, the method further includes: extracting the preparation duration corresponding to the preparation phase and the delivery duration corresponding to the delivery phase from the preset service attribute library according to the service item identifier; selecting a first service window whose window duration meets the preparation duration in chronological order from among the multiple service windows, and marking the first service window as a preparation node; selecting a second service window whose window duration meets the delivery duration from the remaining service windows after the first service window, and marking the second service window as the delivery node; sending a preparation instruction to the service personnel terminal when the preparation node is triggered, and sending a delivery instruction to the service personnel terminal when the delivery node is triggered.

[0014] By employing the above technical solution, preparation and delivery times are extracted from a pre-set service attribute database, enabling precise acquisition of time requirements for each stage of a divisible service and providing accurate time parameters for phased scheduling. The first service window meeting the required preparation time is selected as the preparation node according to the timeline sequence, ensuring that preparation work can begin at an early and appropriate time, allowing sufficient time for subsequent delivery. The second service window meeting the required delivery time is selected as the delivery node after the first service window, achieving a sequential arrangement of preparation and delivery to ensure timely delivery after preparation is completed. When the preparation node is triggered, a preparation instruction is sent to the service personnel's terminal, ensuring that service personnel begin preparation work in advance and avoiding delays caused by last-minute preparations. When the delivery node is triggered, a delivery instruction is sent, achieving precise control of service delivery, and service personnel enter the private room on time to complete the service according to the instructions. By separating the scheduling of preparation and delivery, the time service personnel spend in the private room is reduced, improving service efficiency while minimizing the impact on customers' entertainment.

[0015] Optionally, guiding service personnel to complete the delivery of the service request based on the delivery node specifically includes: obtaining the playback progress information of the current song in the target private room, comparing the playback progress information with the timeline sequence to obtain the countdown status of the delivery node on the timeline sequence; when the countdown status reaches a preset advance notification duration, pushing a service execution notification containing the room identifier of the target private room, the service item identifier, and the estimated arrival time to the service personnel's mobile terminal; when the service window corresponding to the delivery node is open, sending a status prompt indicating that the service is in progress to the user in the target private room through the interactive terminal; after the service request is delivered, receiving a completion confirmation signal from the service personnel's mobile terminal, and closing the service scheduling session according to the completion confirmation signal.

[0016] By employing the aforementioned technical solution, the playback progress information of the current song in the target private room is obtained and compared with the timeline sequence to obtain the countdown status of the delivery node, enabling dynamic tracking and precise control of service timing. When the countdown reaches the preset advance notification duration, a service execution notification is pushed to ensure that service personnel have sufficient preparation and movement time. The notification includes the room identifier, service item identifier, and estimated arrival time, providing service personnel with complete task information. When the service window corresponding to the delivery node opens, a status prompt is sent through the interactive terminal, allowing users in the private room to understand the service status, reducing accidents and inconveniences caused by service personnel entering, and improving the user experience. The completion confirmation signal from the service personnel's mobile terminal is received to achieve real-time confirmation of the service completion status, ensuring the traceability of service quality. Based on the completion confirmation signal, the service scheduling session is closed, achieving timely release of resources and complete archiving of service records. The entire guidance process achieves full control from service preparation, execution to completion, ensuring timely, accurate, and efficient service completion.

[0017] Optionally, after determining the delivery node based on the service complexity, the service divisibility, and the duration of the multiple service windows, the method further includes: monitoring whether the playlist of the target private room has undergone a change event, the change event including adding songs, deleting songs, or adjusting the song playback order; if the change event is detected, re-identifying the updated timeline sequence within the preset time period based on the changed playlist; marking the updated multiple service windows according to the preset song attributes of each song to be played in the updated timeline sequence; determining whether the determined delivery node is within the updated multiple service windows; if the determined delivery node is not within the updated multiple service windows, re-determining a new delivery node based on the service complexity, the service divisibility, and the duration of the updated multiple service windows, and pushing a delivery node change notification to the service personnel's mobile terminal.

[0018] By employing the above technical solutions, changes to the playlist in the target private rooms are monitored, including song additions, deletions, and playback order adjustments. This enables real-time awareness of changes in the service environment, ensuring that service scheduling is always based on the latest room status. Upon detecting a change, the timeline sequence is re-identified based on the updated playlist, dynamically updating the service schedule and ensuring consistency between the timeline sequence and the actual playback plan. The updated service window is labeled according to the preset song attributes of each song to be played in the updated timeline sequence, ensuring the real-time accuracy of the service window information. It is determined whether the identified delivery node is still within a valid service window, intelligently verifying the validity of the original service plan. When a delivery node fails, a new delivery node is re-determined based on service complexity, service divisibility, and the updated service window, ensuring the service can be successfully completed under the new schedule. Delivery node change notifications are pushed to service personnel's mobile terminals, ensuring they are promptly informed of plan adjustments and avoiding the execution of services according to outdated plans. This dynamic adjustment mechanism ensures the flexibility and adaptability of service scheduling, guaranteeing smooth service delivery even when the private room entertainment plan changes.

[0019] In a second aspect, embodiments of this application provide a store management device, which includes: one or more processors and a memory; the memory is coupled to the one or more processors, and the memory is used to store computer program code, which includes computer instructions, and the one or more processors call the computer instructions to cause the store management device to perform the method described in the first aspect and any possible implementation thereof.

[0020] Thirdly, embodiments of this application provide a computer-readable storage medium including instructions that, when executed on a store management device, cause the store management device to perform the method described in the first aspect and any possible implementation thereof.

[0021] Fourthly, embodiments of this application provide a computer program product containing instructions that, when the computer program product is run on a store management device, cause the store management device to perform the method described in the first aspect and any possible implementation thereof.

[0022] In summary, one or more technical solutions provided in this application have at least the following technical effects or advantages: 1. Improved service response efficiency and accuracy: By analyzing the song list of the target private room, identifying the interludes and outros of songs on the timeline, dynamically marking the service window, and effectively utilizing the gaps in non-core performance segments for service scheduling, the service's interference with the user experience is reduced, thereby improving the timeliness and accuracy of service response.

[0023] 2. Improved flexibility in service resource allocation and scheduling: Based on the complexity and divisibility of service requests, the optimal service window can be flexibly selected as the delivery node, or the service task can be decomposed into a preparation phase and a delivery phase for step-by-step execution, ensuring efficient utilization of service resources. At the same time, through mechanisms such as weight evaluation, the accurate matching of complex services can be achieved, further improving the intelligence level of service scheduling.

[0024] 3. Enhanced dynamic adaptability and user experience assurance: When changes occur to the playlist, the system can monitor and update the timeline sequence and service window in real time, dynamically adjust delivery nodes, and ensure that the service plan is synchronized with actual needs. At the same time, through advance notification and status prompt functions, the system optimizes the interaction experience between service personnel and users, ensuring the smooth completion of service requests and improving user satisfaction. Attached Figure Description

[0025] Figure 1 This is a flowchart illustrating a store management method disclosed in an embodiment of this application; Figure 2 This is another schematic diagram of a store management method disclosed in an embodiment of this application; Figure 3 This is a schematic diagram of the structure of a store management device provided in an embodiment of this application.

[0026] Explanation of reference numerals in the attached drawings: 301, Central Processing Unit; 302, Read-Only Memory; 303, Random Access Memory; 304, Bus; 305, Input / Output Interface; 306, Input Section; 307, Output Section; 308, Storage Section; 309, Communication Section; 310, Driver; 311, Removable Media. Detailed Implementation

[0027] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0028] In the description of the embodiments of this application, the words "for example" or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design that is described as "for example" or "for instance" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design options. Rather, the use of the words "for example" or "for instance" is intended to present the relevant concepts in a specific manner.

[0029] In the description of the embodiments of this application, the term "multiple" means two or more. For example, multiple system devices refer to two or more system devices, and multiple screen terminals refer to two or more screen terminals. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the indicated technical features. Thus, a feature defined with "first" or "second" may explicitly or implicitly include one or more of that feature. The terms "comprising," "including," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0030] This application provides a store management method, referring to... Figure 1 , Figure 1 This is a flowchart illustrating a store management method provided in an embodiment of this application. The method is applied to a server, which can execute a store management program. The method includes steps S101 to S105, as follows: Step S101: When a service request is received from an interactive terminal in the target private room, a service scheduling session is started.

[0031] In step S101, a service request refers to various service requests submitted by customers in the private room through an interactive terminal, and a service scheduling session represents a complete task processing flow created by the server to handle the service request.

[0032] Specifically, the server continuously monitors the network connection status of interactive terminals in each private room. When it detects a service request data packet sent by an interactive terminal in the target private room, the server immediately parses the basic information in the data packet, such as the request type, request time, and private room number. The server then creates a unique session identifier and allocates dedicated memory space to store all data generated during this service scheduling process. Simultaneously, the server records the timestamp of the received service request and adds it to the pending queue to ensure the orderly execution of subsequent processing.

[0033] Step S102: In the service scheduling session, obtain and parse the current playlist of the target room, and identify the timeline sequence of songs to be played within the preset time period.

[0034] In step S102, the selected playlist represents all the songs in the target private room that have been selected by the customer and added to the playlist, and the timeline sequence is used to represent the arrangement structure of these songs in the time dimension according to the playback order.

[0035] Specifically, the server retrieves the current playlist data for the target room from the database by calling the song management interface, including the name, duration, and current playback status of each song. Based on the remaining duration of the currently playing song and the complete duration of subsequent songs, the server calculates the start and end times of all songs to be played within a preset time period. The server then arranges these time points in chronological order, forming a continuous timeline sequence, with each time point labeled with corresponding song information and playback status.

[0036] Step S103: Based on the preset song attributes of each song to be played, mark multiple service windows on the timeline sequence. Each service window has a corresponding service duration. The preset song attributes include interlude information or outro information used to define non-core singing segments within the song.

[0037] In step S103, the preset song attributes refer to the data set stored in the system in advance to describe the structural characteristics of the song, the interlude information refers to the pure music segment in the middle of the song without vocals, the outro information refers to the pure music segment at the end of the song, and the service window refers to the time period on the timeline during which services can be performed without affecting the customer's listening experience.

[0038] Specifically, the server reads the preset song attributes of each song to be played in the timeline sequence one by one, extracting the start and end times of the interlude and the start and end times of the outro from the attribute data. The server calculates the duration of each interlude and outro segment and evaluates whether these durations meet the minimum time requirements for service execution. The server marks the time segments that meet the conditions on the timeline sequence, forming multiple independent service windows. The server records the start and end times and available service duration for each service window, and assigns different priority weights based on the window's position in the song.

[0039] In one possible implementation, multiple service windows are marked on the timeline sequence according to the preset song attributes of each song to be played. Specifically, this includes: performing audio feature analysis on each song to be played, identifying the spectral characteristics of the audio signal through Fourier transform, and determining the start and end times of the interlude and the outro in the song structure based on the spectral characteristics; obtaining multiple available service periods and the net duration of each available service period based on the start and end times of the interlude and the outro, and selecting available service periods with a net duration greater than the preset service interference threshold as candidate service windows according to a preset service interference threshold; performing weight evaluation on each candidate service window, and determining multiple service windows based on the weight evaluation results. The weight evaluation includes time interval index evaluation, position distribution index evaluation, and continuity index evaluation.

[0040] Specifically, for each song to be played in the timeline sequence, the server first retrieves the corresponding audio file data from the audio database. The server samples the audio file, converting the continuous audio signal into a discrete digital signal sequence. The server then performs a Fast Fourier Transform algorithm on the digital signal sequence, transforming the time-domain signal into the frequency domain, obtaining spectral distribution data for different time periods. The server analyzes the changing patterns of the spectral characteristics. When it detects a significant decrease in the energy of the vocal frequency range (typically 85Hz to 255Hz) within a certain time period, while the energy of the instrumental frequency range remains stable or increases, it determines that the time period is an interlude or outro. The server records the precise start and end times of these segments, forming time-stamped data for the song's structure.

[0041] The server calculates the duration of each segment based on the identified start and end times of the interlude and outro segments. Adjacent interlude or outro segments within the same song are merged to create longer available service periods. The server calculates the net duration of each available service period, which is the actual available time after deducting necessary transition times from the total segment duration. The server reads a preset service interference threshold, typically set at 15 seconds, representing the minimum time required to perform the service. Available service periods with a net duration less than the preset service interference threshold are removed, and periods with a net duration greater than or equal to the threshold are retained as candidate service windows.

[0042] The server performs a multi-dimensional weight evaluation on each selected candidate service window. In the time interval evaluation, the server calculates the time distance between the candidate service window and the preceding and following core performance segments; the larger the time interval, the smaller the potential impact on the performance experience, and the higher the corresponding weight value. In the positional distribution evaluation, the server analyzes the relative position of the candidate service window within the entire song; windows located in the middle of the song generally have higher service suitability than those at the beginning or end, and are therefore assigned higher weights. In the continuity evaluation, the server checks whether the candidate service window is a complete and continuous time period or a combination of multiple short segments; windows with better continuity receive higher weights. The server combines the evaluation results from these three dimensions to calculate the total weight score for each candidate service window, and selects the window with the highest weight score as the final service window.

[0043] For example, when processing a popular song with a duration of 4 minutes and 30 seconds, the server uses Fourier transform analysis to find a 30-second interlude from 2 minutes 15 seconds to 2 minutes 45 seconds and a 25-second outro from 4 minutes 05 seconds to 4 minutes 30 seconds. The server calculates the net duration of the interlude to be 28 seconds and the net duration of the outro to be 23 seconds, both exceeding the preset service interference threshold of 15 seconds. Therefore, both are listed as candidate service windows. After weight evaluation, the interlude receives a higher weight score because it is located in the middle of the song and has sufficient vocal content before and after it. The outro, although long enough, receives a relatively lower weight score because it is at the end of the song and may affect the transition to the next song. Ultimately, the server determines the interlude as the higher-priority service window.

[0044] Step S104: Call the preset service attribute library to query the service complexity and service divisibility corresponding to the service item identifier in the service request; whereby service complexity is used to characterize the time resources required to complete the service, and service divisibility is used to characterize whether the service can be split.

[0045] In step S104, the preset service attribute library refers to a database that stores detailed information on various service items, and the service item identifier represents a code used to uniquely identify different service types.

[0046] Specifically, the server parses the service item identifier carried in the service request and uses this identifier as a search keyword to look up the corresponding service record in a pre-defined service attribute database. The server extracts the service complexity value of the service item from the query results; this value, expressed in seconds, represents the standard time required to complete the entire service. The server also extracts a service divisibility flag, a Boolean value indicating whether the service can be broken down into multiple independently executable subtasks. The server stores the retrieved service complexity and divisibility data in the temporary storage area of ​​the service scheduling session for use in subsequent scheduling decisions.

[0047] Step S105: Based on service complexity, service divisibility, and the duration of multiple service windows, determine the delivery node, and guide service personnel to complete the delivery of service requests based on the delivery node.

[0048] In step S105, the delivery node represents the specific time point or time period for the final determined execution of the service.

[0049] Specifically, the server first determines the value of the service divisibility flag. If the service is not divisible, the server iterates through all service windows and calculates whether the service duration of each window is greater than or equal to the time required by the service complexity. From the windows that meet the duration requirement, the server selects the window closest to the current time and with the least impact on the customer experience as the delivery node. If the service is divisible, the server decomposes the service into a preparation phase and a delivery phase, immediately initiating the preparation phase and simultaneously selecting a window from the service windows that can accommodate the time required for the delivery phase as the delivery node. The server generates detailed instructions containing the delivery node time, service content, and execution steps, and pushes them to the designated service personnel via mobile terminals, guiding them to complete the service delivery according to the predetermined time and process.

[0050] For example, a customer in a KTV private room orders a fruit platter via an interactive terminal during their performance. Upon receiving this request, the server immediately initiates a service scheduling session, retrieves the room's current playlist, and finds five songs waiting to be played. Analyzing the structure of these songs, the server identifies a 30-second interlude for the second song, a 25-second outro for the third song, and a 40-second interlude for the fifth song. Checking the fruit platter's attributes, the server determines that it requires 20 seconds to complete and is an indivisible service. After calculation and comparison, the server selects the 30-second interlude of the second song as the delivery point and notifies the staff to prepare the fruit platter five minutes in advance, ensuring it arrives on time when the second song's interlude begins, thus completing the service without disrupting the customer's singing experience.

[0051] In one possible implementation, the delivery node is determined based on service complexity, service divisibility, and the duration of multiple service windows. Specifically, this includes: if the service is determined to be indivisible, then matching and selecting the optimal service window that satisfies the service complexity from multiple service windows as the delivery node; if the service request is a divisible service, then decomposing the service request into a preparation phase and a delivery phase; triggering the preparation phase, and selecting the optimal service window that satisfies the service complexity from multiple service windows as the delivery node.

[0052] Specifically, the server first reads the service divisibility flag value obtained from a preset service attribute database. When the server determines that a service is indivisible, it means that the service must be completed continuously within a complete time period and cannot be interrupted or executed in segments. The server iterates through all marked service windows, extracts the duration data of each service window, and compares it with the time required by the service complexity. The server selects service windows with a duration greater than or equal to the service complexity as the feasible window set.

[0053] The server comprehensively scores each service window in the feasible window set. It calculates the time slack for each service window, which is the remaining time after subtracting service complexity from the window duration. A larger slack indicates more time to execute the service, resulting in a higher score. The server assesses the time urgency of each service window by calculating the time difference between the current time and the current window. A smaller time difference indicates a more timely service response, but the feasibility of service preparation must also be considered. The server analyzes the impact of each service window on the customer experience, including factors such as the popularity of the song in the window and whether there are climactic scenes before or after the window. Based on the scores from these multiple dimensions, the server calculates the comprehensive score for each feasible window using a weighted summation method, selects the service window with the highest score as the optimal service window, and designates this window as the delivery node.

[0054] When the server determines that a service is divisible, it invokes the service decomposition rule base to split the service request into two independent parts: a preparation phase and a delivery phase, based on the service type. The preparation phase includes tasks that can be performed in advance and do not need to be completed within the private room, such as item preparation, equipment debugging, and route planning. The delivery phase, on the other hand, is the service process that must be completed within the private room in front of the customer. The server immediately generates execution instructions for the preparation phase and sends these instructions to the relevant service personnel or the back-end preparation area, initiating the execution process for the preparation work.

[0055] The server simultaneously records the estimated completion time of the preparation phase and uses this as a constraint to re-evaluate service windows. The server eliminates service windows that have already ended before the preparation work is complete, ensuring that the selected windows are time-feasible. From the remaining service windows, the server selects the most suitable service window for executing the delivery phase, following a similar evaluation method to that for indivisible services. During the selection process, the server pays particular attention to whether the time required for the delivery phase can be fully accommodated within the window, and whether executing delivery within that window will cause minimal disruption to the customer's entertainment experience. The server designates the selected service window as the delivery node and generates a complete service execution plan that includes the start time of the preparation phase and the delivery node time.

[0056] For example, a server processes a food service request and finds that the service complexity is 180 seconds and the service is divisible. The server breaks down the service into a 120-second preparation phase (including food preparation and plating) and a 60-second delivery phase (delivery and placement). The server immediately triggers the kitchen to begin preparation while simultaneously searching for a suitable delivery opportunity from multiple identified service windows. Considering the 120-second preparation time, the server excludes service windows within the next 2 minutes and ultimately selects a 75-second interlude window during the fourth song as the delivery node, ensuring that the food can be delivered promptly after preparation and that there is sufficient time to complete the delivery service.

[0057] In one possible implementation, among multiple service windows, the optimal service window that meets the service complexity is matched and selected as the delivery node. Specifically, this includes: obtaining the window duration of each service window and obtaining the minimum required service duration corresponding to the service complexity; for each service window, determining whether the window duration is greater than or equal to the minimum required service duration to obtain a set of available windows; determining the comprehensive matching score of each service window in the set of available windows, the comprehensive matching score being obtained by weighted calculation based on target parameters, including time interval indicators, location distribution indicators, and continuity indicators; selecting the service window with the highest comprehensive matching score as the optimal service window, and marking the start time of the optimal service window as the delivery node.

[0058] Specifically, the server reads the start and end times of each service window from the service window dataset one by one, and calculates the window duration for each service window by the difference between the two times. The server directly uses the service complexity value as the minimum required service duration, which represents the minimum time necessary to complete the service. The server creates an empty set of available windows to store service windows that meet the duration requirements.

[0059] The server performs a duration check on each service window, comparing its duration with the minimum required service duration. If the window duration is greater than or equal to the minimum required service duration, the server adds the service window to the set of available windows. If the window duration is less than the minimum required service duration, the server marks the window as unavailable and excludes it from further evaluation. Through this filtering process, the server obtains a set of available windows containing all service windows with the required duration.

[0060] The server performs a multi-dimensional evaluation of each service window in the available window set to calculate a comprehensive matching score. When calculating the time interval metric, the server measures the time elapsed since the current moment for each service window. A shorter time interval indicates a faster service response, but excessively short intervals may lead to insufficient preparation. Therefore, the server uses a piecewise function to assign different metric values ​​to different time intervals. When calculating the position distribution metric, the server analyzes the relative position of the service window within the entire timeline sequence, considering whether there are important performance segments before or after the window, and whether the execution of the service would disrupt the customer's emotional flow. When calculating the continuity metric, the server checks for breakpoints or discontinuities within the service window; completely continuous windows receive the highest continuity metric value.

[0061] The server assigns preset weight coefficients to the three target parameters: the weight coefficient for the time interval indicator is set to 0.3, the weight coefficient for the location distribution indicator is set to 0.4, and the weight coefficient for the continuity indicator is set to 0.3. The server multiplies the three indicator values ​​of each service window by their corresponding weight coefficients and then sums them to obtain the window's overall matching score. The server sorts the overall matching scores of all available windows and selects the service window with the highest score as the optimal service window.

[0062] The server reads the detailed information of the optimal service window and extracts its start time. The server sets this start time as the delivery node, indicating that service personnel should begin performing the service at this precise time. The server generates a delivery instruction, which includes the specific time of the delivery node, a description of the service content, and the estimated completion time, ensuring that service personnel can accurately grasp the timing of the service.

[0063] For example, when processing a beverage service that requires 45 seconds to complete, the server selects three available windows from five service windows, each with a duration exceeding 45 seconds. The first window is 60 seconds long, 3 minutes from the current time, and is located during a song's interlude; the second window is 50 seconds long, 5 minutes from the current time, and is located during a song's outro; the third window is 70 seconds long, 8 minutes from the current time, and is located during the transition between two songs. After comprehensive matching score calculation, the first window receives the highest score of 0.82 due to its timely response and suitable location, the second window scores 0.68, and the third window scores 0.55. The server ultimately selects the first window as the optimal service window and marks its start time 3 minutes later as the delivery node.

[0064] In one possible implementation, after decomposing the service request into a preparation phase and a delivery phase, the method further includes: extracting the preparation duration corresponding to the preparation phase and the delivery duration corresponding to the delivery phase from a preset service attribute library based on the service item identifier; selecting a first service window whose window duration meets the preparation duration in chronological order from multiple service windows, and marking the first service window as a preparation node; selecting a second service window whose window duration meets the delivery duration from the remaining service windows after the first service window, and marking the second service window as a delivery node; sending a preparation instruction to the service personnel terminal when the preparation node is triggered, and sending a delivery instruction to the service personnel terminal when the delivery node is triggered.

[0065] Specifically, after decomposing the service request into a preparation phase and a delivery phase, the server uses the service item identifier as an index key to access the preset service attribute database again. The server reads the phase duration configuration information for that service item from the detailed records in the service attribute database, extracting the preparation duration value for the preparation phase and the delivery duration value for the delivery phase. The preparation duration represents the standard time required to complete all preparation work, and the delivery duration represents the standard time required to complete service delivery within the service room. The server stores these two duration values ​​in a temporary variable of the service scheduling session.

[0066] The server iterates through all marked service windows in chronological order along the timeline. Starting with the earliest service window, the server checks the window duration of each service window to see if it is greater than or equal to the preparation duration. When the server finds the first service window that meets the preparation duration requirement, it immediately stops iterating and designates that service window as the first service window. The server extracts the time information of the first service window, including the start and end times, and marks the entire time period of the first service window as a preparation node.

[0067] The server records the position index of the first service window in the timeline sequence and continues traversing from the next service window after that position. The server searches for a service window with a duration greater than or equal to the delivery duration among the remaining service windows. The server evaluates the time interval between each candidate window and the preparation node to ensure that preparation work can be completed before delivery begins. The server selects the service window that is most suitable in terms of time and whose window duration meets the requirements as the second service window, and marks the time period of the second service window as the delivery node.

[0068] The server establishes a timed trigger mechanism to continuously monitor the relationship between the current time and the start time of the preparation node. When the system time reaches the start time of the preparation node, the server automatically generates a preparation instruction. The preparation instruction includes the specific details of the service item, a list of items to be prepared, the standard procedure for preparation, and the estimated completion time. The server pushes the preparation instruction to the terminal device of the designated service personnel via a wireless network. Upon receiving the instruction, the service personnel's terminal will emit a prompt tone and display detailed information.

[0069] The server continues to monitor the time progress. When the system time reaches the start time of the delivery node, the server generates a delivery instruction. The delivery instruction includes the target room number, specific service content, delivery precautions, and any special requirements from the customer. The server also sends the delivery instruction to the service personnel's terminal to ensure that the service personnel can arrive at the room on time to complete the service delivery. After sending both instructions, the server records the sending time and receipt confirmation information, forming a complete service execution log.

[0070] For example, a server processes a birthday cake service request. A query of the preset service attribute database reveals a preparation time of 180 seconds and a delivery time of 90 seconds. The server finds a 200-second interlude window for the second song on the timeline, meeting the preparation time requirement, and thus marks it as a preparation node. The server continues searching and finds a 120-second interlude window for the fourth song, meeting the delivery time requirement and having sufficient time interval to be placed before the preparation node, so it marks it as a delivery node. When the interlude for the second song begins, the server sends a preparation instruction to the service staff, reminding them to prepare the cake, light the candles, etc. When the interlude for the fourth song begins, the server sends a delivery instruction, and the service staff brings the prepared birthday cake into the private room, completing the surprise service without interfering with the customer's singing.

[0071] In one possible implementation, guiding service personnel to complete the delivery of service requests based on delivery nodes specifically includes: obtaining the playback progress information of the current song in the target private room, comparing the playback progress information with the timeline sequence to obtain the countdown status of the delivery node on the timeline sequence; when the countdown status reaches the preset advance notification duration, pushing a service execution notification containing the room identifier of the target private room, the service item identifier, and the estimated arrival time to the service personnel's mobile terminal; when the service window corresponding to the delivery node is open, sending a status prompt indicating that the service is in progress to the user in the target private room through the interactive terminal; after the service request is delivered, receiving a completion confirmation signal from the service personnel's mobile terminal, and closing the service scheduling session based on the completion confirmation signal.

[0072] Specifically, the server continuously acquires the playback progress information of the current song in the target private room through a real-time data interface with the KTV song selection system. This playback progress information includes the name of the currently playing song, the elapsed playback time, the remaining playback time, and a playback status indicator. The server precisely compares the time data in the acquired playback progress information with the timeline sequence to calculate the current position on the timeline. Based on the difference between the current position and the delivery node's position, the server calculates the remaining time to reach the delivery node in real time, creating a dynamically updated countdown.

[0073] The server is set to a preset advance notification duration of 120 seconds to ensure service personnel have sufficient preparation and movement time. The server continuously monitors the countdown timer; when the countdown equals the preset advance notification duration, the server triggers the notification sending process. The server constructs a data structure for the service execution notification, including the target room's room identifier, the service item identifier, the estimated arrival time, and service precautions. The server pushes the service execution notification to the designated service personnel's mobile devices via mobile network. Upon receiving the notification, the mobile device alerts the service personnel through vibration, sound, and screen display, ensuring they are promptly informed of the service task.

[0074] The server continues to track the time progress. When the system time reaches the start time of the service window corresponding to the delivery node, the server determines that the service window has officially opened. The server generates a status message indicating that the service is in progress. This message is presented in a way that does not affect music playback, usually as scrolling text or a semi-transparent overlay at the edge of the screen. The server sends the status message to the interactive terminal in the target private room. The interactive terminal displays a friendly message such as "Service personnel are serving you" on the screen, allowing users in the private room to understand the current service status and avoiding any inconvenience or misunderstanding caused by service personnel entering the room.

[0075] The server maintains a communication connection with the service personnel's mobile terminal during the service window. After the service personnel complete service delivery, they click the "Complete" button through a dedicated application interface on their mobile terminal. The mobile terminal generates a completion confirmation signal containing a completion timestamp, the service personnel's employee ID, and the actual service duration. Upon receiving the completion confirmation signal, the server first verifies its integrity and validity to confirm that the service has indeed been completed. The server updates the service request status to "Completed," records the actual execution details of the service, including the actual start time, actual end time, and executor information. The server then performs session cleanup operations, releasing the memory resources allocated to this service scheduling session, archiving relevant data to the historical record database, and officially closing the service scheduling session.

[0076] For example, the server schedules a beverage service for VIP room number 8, with the delivery point set 15 minutes later during a song interlude. The server monitors the playback progress in real time, and when the countdown shows 2 minutes remaining, it sends a notification to waiter Xiao Li's mobile phone: "Please deliver beverage service to VIP room number 8 in 2 minutes." Xiao Li receives the notification and begins preparing the beverage. When the interlude begins, the VIP room screen displays a "Service in progress" message, and Xiao Li enters the room to deliver the beverage. After completing the service, Xiao Li clicks the "complete" button on his phone. The server receives a confirmation signal, archives the service record, and ends the session. The entire service process is precise, efficient, and does not disrupt the customer's entertainment experience.

[0077] Please refer to Figure 2 In one possible implementation, after determining the delivery node based on service complexity, service divisibility, and the duration of multiple service windows, the method further includes steps S201-S205, as follows: Step S201: Monitor whether there are any changes to the song list in the target private room. Change events include adding songs, deleting songs, or adjusting the song playback order.

[0078] In step S201, a change event indicates any modification to the song list in the target private room. Adding a song means that the customer selects a new song and adds it to the playlist. Deleting a song means that the customer cancels the song selection. Adjusting the song playback order means that the customer changes the playback order of the songs.

[0079] Specifically, the server establishes a real-time monitoring mechanism for the song lists in the target private rooms, obtaining song list status information through a continuous connection with the song selection system database. The server maintains a version number and a hash value for the song list for each song list, reading the current song list data and calculating a new hash value at fixed time intervals. The server compares the newly calculated hash value with stored historical hash values; if they do not match, a change event is determined. The server further analyzes the specific changes to the song list, identifying whether songs have been added, deleted, or their playback order has been adjusted by comparing the song lists before and after the change, and records the specific change details.

[0080] Step S202: If a change event is detected, the updated timeline sequence within the preset time period is re-identified based on the changed playlist.

[0081] In step S202, the updated timeline sequence represents the song playback schedule recalculated based on the changed playlist.

[0082] Specifically, upon detecting a change event, the server immediately retrieves the updated complete playlist data from the karaoke system. The server recalculates the remaining duration of the currently playing songs and reconstructs the playback schedule within the preset time period based on the changed song order and the standard duration of each song. The server assigns new start and end times to each song in the updated playlist, forming an updated timeline sequence. The server pays special attention to handling time gaps caused by song deletions and time extensions caused by song additions, ensuring the continuity and accuracy of the timeline sequence.

[0083] Step S203: Based on the preset song attributes of each song to be played in the updated timeline sequence, mark the updated multiple service windows.

[0084] In step S202, the updated timeline sequence represents the song playback schedule recalculated based on the changed playlist.

[0085] Specifically, upon detecting a change event, the server immediately retrieves the updated complete playlist data from the karaoke system. The server recalculates the remaining duration of the currently playing songs and reconstructs the playback schedule within the preset time period based on the changed song order and the standard duration of each song. The server assigns new start and end times to each song in the updated playlist, forming an updated timeline sequence. The server pays special attention to handling time gaps caused by song deletions and time extensions caused by song additions, ensuring the continuity and accuracy of the timeline sequence.

[0086] Step S204: Determine whether the identified delivery node is in the updated multiple service windows.

[0087] In step S204, the determination operation is used to confirm whether the original service plan is still valid.

[0088] Specifically, the server extracts the time information of the identified delivery node, including its start time and the original service window identifier. The server searches through the updated list of multiple service windows to check if any service window exists whose time range includes the delivery node. The server uses the intersection of time intervals to determine if the delivery node is still within a valid service window. If the delivery node's time falls within the time range of any updated service window, the server determines that the delivery node is still valid; if the delivery node's time is not within the range of any service window, the server determines that the delivery node needs to be rescheduled.

[0089] Step S205: If the determined delivery node is not in the updated multiple service windows, then based on the service complexity, service divisibility and the duration of the updated multiple service windows, a new delivery node is determined, and a delivery node change notification is pushed to the service personnel's mobile terminal.

[0090] In step S205, the new delivery node represents the reselected service execution time point, and the delivery node change notification refers to the information informing service personnel of the service time adjustment.

[0091] Specifically, when the server determines that the original delivery node has failed, it re-executes the service window matching algorithm. Based on service complexity and service divisibility parameters, the server searches for a suitable replacement window among the updated service windows. The server prioritizes the service window that is closest in time to the original delivery node to reduce service latency. Once the server determines the new delivery node, it immediately generates a delivery node change notification, including the original service time, the adjusted service time, and an explanation of the reason for the change. The server sends the change notification to the service personnel's mobile devices via push notification, ensuring that service personnel are promptly informed of the plan change and can make corresponding adjustments.

[0092] For example, a private room was originally scheduled to receive drinks during the 30-second interlude of the third song, with the delivery point set 10 minutes later. However, the customer suddenly deleted the second song, causing the third song to start playing earlier, moving the original interlude window time forward by 4 minutes. After detecting the playlist change, the server recalculated the timeline and found that the original delivery point was no longer within any service window. The server then found the outro of the fourth song in the new service window, making it suitable for service, and adjusted the new delivery point to 12 minutes later. The server immediately notified the staff responsible for the service, informing them that the service time had been changed from 10 minutes to 12 minutes, allowing them ample time to adjust their preparation and ensure unaffected service quality.

[0093] The following describes a store management device according to an embodiment of the present invention from the perspective of hardware processing. Please refer to [link / reference needed]. Figure 3 This is a schematic diagram of the structure of a store management device in an embodiment of this application.

[0094] It should be noted that, Figure 3 The structure of the store management device shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0095] like Figure 3 As shown, a store management device includes a Central Processing Unit (CPU) 301, which can perform various appropriate actions and processes according to a program stored in a Read-Only Memory (ROM) 302 or a program loaded from a storage portion 308 into a Random Access Memory (RAM) 303, such as performing the methods described in the above embodiments. The RAM 303 also stores various programs and data required for device operation. The CPU 301, ROM 302, and RAM 303 are interconnected via a bus 304. An Input / Output (I / O) interface 305 is also connected to the bus 304.

[0096] The following components are connected to I / O interface 305: input section 306 including audio input devices, push-button switches, etc.; output section 307 including a liquid crystal display (LCD) and audio output devices, indicator lights, etc.; storage section 308 including a hard disk, etc.; and communication section 309 including a network interface card such as a LAN (Local Area Network) card, modem, etc. Communication section 309 performs communication processing via a network such as the Internet. Drive 310 is also connected to I / O interface 305 as needed. Removable media 311, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 310 as needed so that computer programs read from them can be installed into storage section 308 as needed.

[0097] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing computer programs for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 309, and / or installed from removable medium 311. When the computer program is executed by central processing unit (CPU) 301, it performs the various functions defined in the present invention.

[0098] It should be noted that specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0099] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of the present invention. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those shown in the drawings.

[0100] Specifically, a store management device according to this embodiment includes a processor and a memory. The memory stores a computer program. When the computer program is executed by the processor, it implements a store management method provided in the above embodiment.

[0101] In another aspect, the present invention also provides a computer-readable storage medium, which may be included in a store management device described in the above embodiments; or it may exist independently and not assembled into the store management device. The storage medium carries one or more computer programs, which, when executed by a processor of the store management device, cause the store management device to implement the store management method based on IoT-based encrypted data transmission provided in the above embodiments.

Claims

1. A store management method, characterized in that, The method includes: When a service request is received from an interactive terminal in the target private room, a service scheduling session is initiated. In the service scheduling session, the current playlist of the target private room is obtained and parsed, and the timeline sequence of songs to be played within a preset time period is identified; Based on the preset song attributes of each song to be played, multiple service windows are marked on the timeline sequence. Each service window has a corresponding service duration. The preset song attributes include interlude information or outro information used to define non-core singing segments within the song. The system calls a preset service attribute library to query the service complexity and service divisibility corresponding to the service item identifier in the service request; wherein, the service complexity is used to characterize the time resources required to complete the service, and the service divisibility is used to characterize whether the service can be split. Based on the service complexity, the service divisibility, and the duration of multiple service windows, a delivery node is determined, and service personnel are guided to complete the delivery of the service request based on the delivery node.

2. The method according to claim 1, characterized in that, The step of marking multiple service windows on the timeline sequence according to the preset song attributes of each song to be played specifically includes: For each of the songs to be played, audio feature analysis is performed. The spectral features of the audio signal are identified by Fourier transform. Based on the spectral features, the start and end times of the interlude and the start and end times of the outro in the song structure of the song to be played are determined. Based on the start and end times of the interlude and the start and end times of the outro, multiple available service periods and the net duration of each available service period are obtained. Based on a preset service interference threshold, available service periods with a net duration greater than the preset service interference threshold are selected as candidate service windows. Each candidate service window is weighted and evaluated, and multiple service windows are determined based on the weight evaluation results. The weight evaluation includes time interval index evaluation, location distribution index evaluation, and continuity index evaluation.

3. The method according to claim 1, characterized in that, The determination of the delivery node based on the service complexity, the service divisibility, and the duration of multiple service windows specifically includes: If the service is determined to be indivisible, then among the multiple service windows, the optimal service window that satisfies the service complexity is matched and selected as the delivery node. If the service request is a divisible service, then the service request is decomposed into a preparation phase and a delivery phase; The preparation phase is triggered, and the optimal service window that meets the service complexity is selected from the plurality of service windows as the delivery node.

4. The method according to claim 3, characterized in that, The step of matching and selecting the optimal service window that satisfies the service complexity from among the multiple service windows as the delivery node specifically includes: Obtain the window duration of each service window, and obtain the minimum required service duration corresponding to the service complexity; For each service window, determine whether the window duration is greater than or equal to the minimum required service duration to obtain the set of available windows; The comprehensive matching score of each service window in the set of available windows is determined. The comprehensive matching score is obtained by weighted calculation based on target parameters, including time interval index, location distribution index, and continuity index. The service window with the highest comprehensive matching score is selected as the optimal service window, and the start time of the optimal service window is marked as the delivery node.

5. The method according to claim 3, characterized in that, After decomposing the service request into a preparation phase and a delivery phase, the method further includes: Based on the service item identifier, extract the preparation time corresponding to the preparation stage and the delivery time corresponding to the delivery stage from the preset service attribute library; Among the multiple service windows, the first service window whose window duration meets the preparation time is selected according to the timeline sequence, and the first service window is marked as the preparation node. In the remaining service windows following the first service window, select a second service window whose window duration meets the delivery duration, and mark the second service window as the delivery node; When the preparation node is triggered, a preparation instruction is sent to the service personnel terminal, and when the delivery node is triggered, a delivery instruction is sent to the service personnel terminal.

6. The method according to claim 1, characterized in that, The process of guiding service personnel to complete the delivery of the service request based on the delivery node specifically includes: Obtain the playback progress information of the current song in the target private room, and compare the playback progress information with the timeline sequence to obtain the countdown status of the delivery node on the timeline sequence; When the countdown reaches the preset advance notification duration, a service execution notification containing the room identifier of the target private room, the service item identifier, and the estimated arrival time is pushed to the service personnel's mobile terminal. When the service window corresponding to the delivery node is opened, a status notification indicating that the service is in progress is sent to the user in the target private room through the interactive terminal. After the service request is delivered, a completion confirmation signal is received from the mobile terminal of the service personnel, and the service scheduling session is closed based on the completion confirmation signal.

7. The method according to claim 1, characterized in that, After determining the delivery node based on the service complexity, the service divisibility, and the duration of multiple service windows, the method further includes: Monitor whether there are any changes to the song list in the target private room, including song additions, song deletions, or song playback order adjustments; If the change event is detected, the updated timeline sequence within the preset time period is re-identified based on the changed playlist. Based on the preset song attributes of each song to be played in the updated timeline sequence, multiple updated service windows are identified; Determine whether the identified delivery node is within the updated multiple service windows; If the identified delivery node is not within the updated multiple service windows, a new delivery node is re-identified based on the service complexity, the service divisibility, and the duration of the updated multiple service windows, and a delivery node change notification is pushed to the service personnel's mobile terminal.

8. A store management device, characterized in that, The store management device includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code including computer instructions, and the one or more processors call the computer instructions to cause the store management device to perform the method as described in any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, characterized in that, When the instruction is executed on the store management device, the store management device performs the method as described in any one of claims 1-7.

10. A computer program product, characterized in that, When the computer program product is run on the store management device, the store management device performs the method as described in any one of claims 1-7.

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