Water dispenser advertisement playing method, system and equipment based on cloud linkage and medium

Abstract

The invention relates to a water dispenser advertisement playing method, system and device based on cloud linkage and a medium, and relates to the field of advertisement putting and device linkage control, and the method comprises the steps that the playing behavior of a customized advertisement is adjusted based on a preset triggering rule or a cloud instruction, and the playing behavior comprises an autonomous playing event and a user triggering event; recording the playing behavior and the equipment state change in real time, and reporting the playing behavior and the equipment state change to a cloud according to a preset reporting strategy; and receiving an analysis report generated by the cloud based on the reported advertisement playing behavior and the equipment state change, and optimizing the advertisement putting rule according to the analysis report. According to the invention, remote centralized management, real-time pushing, accurate putting and playing state monitoring of the advertisement content can be realized, so that the efficiency and flexibility of advertisement release are improved.

Description

Technical Field

[0001] This application relates to the field of advertising placement and equipment linkage control, and in particular to a method, system, equipment and medium for playing advertisements on a water dispenser based on cloud linkage. Background Technology

[0002] Smart home appliance technology has developed rapidly in recent years, greatly improving people's quality of life. With the continuous advancement of the Internet of Things (IoT) and cloud computing technologies, the functions of smart home appliances are becoming increasingly diverse, and their application scenarios are constantly expanding. Smart home appliances can not only achieve basic device control functions, but also realize more value-added services through network connectivity. As one of the common smart home appliances, the market demand for smart water dispensers is gradually increasing, and their usage frequency is high in both public and home settings. However, the current functional development of smart water dispensers still has certain limitations, failing to fully realize their potential value.

[0003] In the traditional smart water dispenser market, most control panels only display basic status information such as water temperature and volume, lacking interactive and value-added service capabilities. Existing smart water dispensers with screens typically rely on local storage to save advertising materials, requiring manual updates. This means that every update necessitates manual intervention, making it cumbersome and inefficient. Even some dispensers that can update advertising content use a simple, fixed pattern, unable to flexibly adjust to changing circumstances.

[0004] However, these existing technologies have significant drawbacks. Local storage and manual updates of advertising content prevent water dispensers from achieving large-scale, unified, and real-time management and content delivery. This results in poor timeliness of advertising content, failing to meet the demands of modern precision marketing and dynamic information dissemination. Furthermore, the advertising display value of the water dispenser's control panel is not fully utilized, leading to a waste of resources. Summary of the Invention

[0005] The purpose of this application is to provide a cloud-based advertising method for water dispensers, which enables remote centralized management, real-time push, precise delivery, and playback status monitoring of advertising content, thereby improving the efficiency and flexibility of advertising.

[0006] Firstly, this application provides a cloud-based advertising method for water dispensers, employing the following technical solution: A method for playing advertisements on a water dispenser based on cloud-based linkage, comprising: The playback behavior of customized advertisements is adjusted based on preset trigger rules or cloud instructions. The playback behavior includes autonomous playback events and user-triggered events. The playback behavior and device status changes are recorded in real time and reported to the cloud according to a preset reporting strategy; Receive analysis reports generated from the cloud based on reported ad playback behavior and device status changes, and optimize ad delivery rules based on the analysis reports.

[0007] By adopting the above technical solutions, the idle value of smart water dispenser screens can be fully utilized to create new advertising revenue channels. By monitoring the status and linking playback, the advertising effect can be improved, and precise advertisements can be delivered to users in real time. Targeted and real-time advertising effect data can be provided to help advertisers make decisions, thereby improving the efficiency, timeliness and flexibility of advertising. It can also realize remote centralized management of precise advertising delivery and scenario-based marketing for each water dispenser to improve the efficiency and flexibility of advertising.

[0008] In a preferred embodiment, this application can be further configured as follows: the step of adjusting the playback behavior of customized advertisements based on preset trigger rules or cloud instructions, wherein the playback behavior includes autonomous playback events and user-triggered events, includes: Set preset trigger rules, which include changes in the water dispenser's status and user operations; When a change in the water dispenser's status is detected, if there is no user interaction, the playback behavior is switched to an autonomous playback event, whereby the autonomous playback event plays a customized advertisement related to the current status. When a user action is detected, the playback behavior is switched to a user-triggered event, wherein the user-triggered event is to play a customized advertisement related to the current action.

[0009] By adopting the above technical solution, preset trigger rules are set that include changes in the water dispenser's status and user operations. When a change in the water dispenser's status is detected and there is no user operation, the playback behavior is switched to an autonomous playback event related to the current water dispenser status. When a user operation is detected, the playback behavior is switched to a user-triggered event that plays a customized advertisement related to the current operation. This achieves contextualized ad playback, improves ad relevance and user experience, and thus increases ad conversion rates.

[0010] In a preferred embodiment, this application can be further configured as follows: before the step of adjusting the playback behavior of customized advertisements based on preset trigger rules or cloud instructions, wherein the playback behavior includes autonomous playback events and user-triggered events, the application further includes: Receive an ad playback task instruction package from the cloud, the instruction package including the ID or URL of the customized ad, the playback plan and the target device identifier; Determine if the ID or URL of the customized advertisement exists in the local advertising material library. If it does not exist, download the customized advertisement from the cloud to the advertising material library. If it exists, call the customized advertisement in the advertising material library.

[0011] By adopting the above technical solution, the system receives the ad playback task instruction package from the cloud to obtain the specific arrangement of ad playback and determines the playback order of ads in each scenario; it also determines whether the customized ad exists in the local material library. If it does not exist, it is downloaded; if it exists, it is called, thus realizing material caching, reducing network traffic consumption, adapting to different network environments, and providing a basic preparation for adjusting ad playback behavior based on preset trigger rules or cloud instructions.

[0012] In a preferred embodiment, this application can be further configured as follows: the step of recording the playback behavior and device state changes in real time, and reporting them to the cloud according to a preset reporting strategy, includes: Records autonomous playback events in real time and monitors user-triggered events and device status information; The preset reporting strategy includes reporting timed logs. If the current playback behavior is an autonomous playback event, a timed log is generated based on the content of the autonomous playback event, and the timed log is uploaded to the cloud. The preset reporting strategy also includes reporting event logs. If the current playback behavior is a user-triggered event, an event log is generated based on the content of the user-triggered event, and the event log is uploaded to the cloud.

[0013] By adopting the above technical solutions, autonomous playback events are recorded in real time, user-triggered events and device status information are monitored, and timed logs or event logs are generated and reported to the cloud based on playback behavior. This provides objective and real-time advertising performance data, offering data support for advertisers' decision-making.

[0014] In a preferred embodiment, this application can be further configured as follows: the step of receiving an analysis report generated from the cloud based on reported advertising playback behavior and device status changes, and optimizing advertising delivery rules according to the analysis report, includes: If a timed log is reported, the advertising delivery rules will be optimized based on the first analysis report generated from the cloud based on the timed log. The first analysis report includes the exposure and playback duration of each advertising material on the current device, as well as playback data, online rate, and success rate of several device regions. If an event log is reported, the advertising rules are optimized based on a second analysis report generated from the cloud based on the reported event log, wherein the second analysis report includes the current user interaction rate of the device.

[0015] By adopting the above technical solutions, corresponding analysis reports can be generated based on different types of logs. Based on multi-dimensional data such as exposure, playback duration, playback data by region, online rate, success rate, and user interaction rate, precise targeting and scenario-based marketing can be achieved. The reports can also be used to optimize advertising rules and provide objective and real-time advertising performance data to help advertisers make decisions and improve advertising conversion rates.

[0016] In a preferred embodiment, this application can be further configured as follows: the step of adjusting the playback behavior of customized advertisements based on preset trigger rules or cloud instructions, wherein the playback behavior includes autonomous playback events and user-triggered events, includes: Based on preset trigger rules or cloud commands, control the playback / switching / stopping of advertisements in a specified area of ​​the screen.

[0017] By adopting the above technical solutions, it is possible to control the playback, switching, or stopping of advertisements in designated areas of the screen, reducing interference with the user's core operations.

[0018] In a preferred embodiment, this application can be further configured as follows: the step of receiving an advertisement playback task instruction package from the cloud, wherein the instruction package includes the advertisement's ID or URL, playback plan, and target device identifier, includes: Receive instruction packets generated by the cloud based on target devices / groups and delivery time, wherein the target devices / groups include the device ID, geographical location and location type for targeted delivery.

[0019] By adopting the above technical solution, the system receives instruction packets generated based on target devices / groups and delivery time. The target devices / groups include the device ID, geographical location, and venue type for targeted delivery. This enables the delivery of advertisements at specific times for different devices, regions, and venue types. It also allows for unified, remote, and automated management of large-scale devices, improving the efficiency, timeliness, and flexibility of advertising delivery.

[0020] Secondly, this application provides a cloud-based advertising playback system for water dispensers, employing the following technical solution: A cloud-based advertising display system for water dispensers includes: Ad triggering module: used to adjust the playback behavior of customized ads based on preset triggering rules or cloud instructions, the playback behavior including autonomous playback events and user-triggered events; Log upload module: used to record the playback behavior and device status changes in real time, and report them to the cloud according to the preset reporting strategy; The ad delivery optimization module is used to receive analysis reports generated from the cloud based on reported ad playback behavior and device status changes, and to optimize ad delivery rules according to the analysis reports.

[0021] Thirdly, this application provides an electronic device that adopts the following technical solution: An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described cloud-based water dispenser advertising playback method.

[0022] Fourthly, this application provides a computer storage medium, as follows: A computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the above-described cloud-based water dispenser advertising playback method.

[0023] In summary, this application has the following beneficial technical effects: This application leverages the idle value of smart water dispenser screens by using user interaction with the dispenser and linking playback to specific statuses. This enables precise ad targeting and contextualized marketing, creating new revenue streams for operators and improving the efficiency, timeliness, and flexibility of ad delivery. Furthermore, by targeting ads and adjusting playback positions, it reduces interference with core user operations and provides objective, real-time ad performance data to support advertisers' decision-making. Attached Figure Description

[0024] Figure 1 This is a flowchart of a cloud-based advertising playback method for water dispensers, as described in one embodiment of this application.

[0025] Figure 2 This is a sub-step of step S1 in one embodiment of this application. Figure 1 .

[0026] Figure 3 This is a flowchart of the steps added before step S1 in one embodiment of this application.

[0027] Figure 4 This is a flowchart of a sub-step of step S2 in one embodiment of this application.

[0028] Figure 5 This is a flowchart of a sub-step of step S3 in one embodiment of this application.

[0029] Figure 6 This is a sub-step of step S1 in one embodiment of this application. Figure 2 .

[0030] Figure 7 This is a flowchart of a sub-step of step S13 in one embodiment of this application.

[0031] Figure 8 This is a schematic diagram of the structure of a cloud-based advertising playback system for water dispensers, according to one embodiment of this application.

[0032] Figure 9 This is a schematic block diagram of an electronic device in one embodiment of this application.

[0033] Attached labels: 1. Ad triggering module; 2. Log upload module; 3. Targeting optimization module. Detailed Implementation

[0034] The following is in conjunction with the appendix Figure 1-9 This application will be described in further detail.

[0035] It should be noted that all actions involving the acquisition of data or information in this application are carried out in accordance with the relevant data protection laws and policies of the country where the application is located, and with the authorization of the relevant users.

[0036] refer to Figure 1 A method for playing advertisements on water dispensers based on cloud-based linkage, specifically including: S1. Adjust the playback behavior of customized advertisements based on preset trigger rules or cloud instructions. Playback behavior includes autonomous playback events and user-triggered events.

[0037] Specifically, for water dispenser scenarios, a rule-parsing advertising strategy engine is deployed on the smart water dispenser. This engine receives and executes dynamic instructions from the cloud, such as inserting customized advertisements according to a playback schedule. Alternatively, it can play scenario-appropriate advertisements based on preset trigger rules, such as playing related advertisements when the user selects the "hot water" function, or automatically starting a preset advertisement carousel if the device is idle for a set period of time. By using preset user operations and device states as core trigger conditions, intelligent linkage and dynamic adjustment of advertising playback behavior are achieved.

[0038] In this embodiment, by leveraging the timeliness and contextual relevance of water dispenser screen advertisements, the problems of cumbersome updates and inability to flexibly display advertisements based on real-time conditions in traditional advertising are solved. This fully utilizes the advertising value of the water dispenser interactive screen, making advertising push more natural and effective.

[0039] S2. Record playback behavior and device status changes in real time, and report them to the cloud according to the preset reporting strategy.

[0040] Specifically, it captures and temporarily stores key event data locally in real time, including ad playback behavior and device status changes. Following protocols supported by the communication gateway, such as MQTT, it compresses and transmits the reported logs to the cloud using a preset reporting strategy. This ensures real-time cloud monitoring of ad playback status and device health across massive numbers of devices, enabling unified, remote, and automated management of large-scale devices. It provides comprehensive, low-redundancy data for accurate analysis, solving the problem of remote tracking limitations caused by local storage.

[0041] S3. Receive analysis reports generated from the cloud based on reported ad playback behavior and device status changes, and optimize ad delivery rules based on the analysis reports.

[0042] Specifically, the cloud-based data analysis and reporting module processes device-reported data to generate multi-dimensional reports. The advertising strategy engine dynamically optimizes the rule base based on these reports, adjusting delivery strategies, updating trigger conditions, and redefining target groups for each smart water dispenser's status changes. The optimized rules are then distributed to target devices in real-time via a task scheduler, forming a closed loop of "data feedback - strategy iteration - precise targeting." This maximizes the advertising value of water dispenser screens, solves the strategy lag problem caused by traditional manual updates, and continuously improves ROI.

[0043] refer to Figure 2 Furthermore, in one embodiment, step S1 is refined into the following sub-steps: S10. Set preset trigger rules, which include changes in the water dispenser's status and user operations.

[0044] Specifically, the cloud-based advertising strategy engine pre-sets two types of trigger rules: one is the water dispenser status change rule, such as the device being idle for more than a set time, the filter life falling below a threshold, or the network connection being interrupted; the other is the user operation rule, such as selecting the "hot water" function, triggering the "start dispensing water" button, or clicking on the screen interaction area. These rules are configured through the cloud-based management console and then distributed to the advertising playback engine on the smart water dispenser terminal for storage and execution. This achieves a deep binding between advertising rules and the water dispenser's usage scenarios, providing accurate judgment criteria for subsequent dynamic playback. This solves the problem of traditional advertising being unable to respond to the real-time status of the device, and improves the flexibility and scenario adaptability of rule configuration.

[0045] In this embodiment, when setting the trigger rules, a regional device activity rule is set. The rule is dynamically distributed through the management console by configuring the regional range, activity threshold, and associated advertising content. Specifically, the device management module of the smart water dispenser counts the number of online water dispensers and their usage frequency within a specified geofence in real time, such as the proportion of devices simultaneously using water in an office building in a business district between 8 and 10 a.m. When the number of active devices exceeds the threshold, relevant advertisements, such as breakfast delivery or coffee promotions, are automatically pushed to the devices in that area, while the original rules are retained.

[0046] S11. When a change in the water dispenser's status is detected, if there is no user operation, the playback behavior will be switched to an autonomous playback event, where the autonomous playback event plays a customized advertisement related to the current status.

[0047] Specifically, when the device status monitoring module detects a change in the water dispenser's status and there is no user interaction, the advertising playback engine immediately triggers an autonomous playback event. It matches advertising materials associated with the current status from the local cache, such as playing brand image ads when the device is in standby mode, pushing replacement service ads when the filter life is low, and automatically playing them in designated areas of the screen. It also simultaneously recommends repair service contact information when a fault warning is issued. By leveraging the device's idle state to uncover advertising exposure opportunities, the advertising content becomes strongly correlated with the device's status, solving the problem of wasted screen resources and improving the conversion rate of contextualized advertising value.

[0048] S12. When a user operation is detected, the playback behavior is switched to a user-triggered event, where the user-triggered event is to play a customized advertisement related to the current operation.

[0049] Specifically, when the device-side status monitoring module detects a user operation, the advertising playback engine immediately interrupts the current content and switches to user-triggered event mode. In this embodiment, the event mode includes: Basic response: Based on preset rules, load ads directly related to the user's actions and prioritize their playback in high-attention areas. By responding to user actions in real time, it achieves precise, contextualized targeting and improves ad conversion rates. Deeply correlate and synchronously analyze the historical usage rate of each function. After big data analysis in the cloud, send relevant instruction packages to the corresponding water dispenser devices and dynamically push derivative advertisements with strong function tags to realize the mining of derivative needs based on function usage rate and extend the user consumption chain. The device health feature is expanded so that when the device management module detects that the number of repairs exceeds a threshold or indicates a risk of aging due to prolonged continuous operation, it accurately pushes advertisements for new models with similar user preferences to users who frequently use the function. For example, if a user frequently uses the "coffee" water temperature button or clicks on related ad slots, the event log is reported to the cloud. After big data analysis, the cloud sends relevant instruction packages to the corresponding water dispenser devices, displaying recommendations for water dispensers with "intelligent coffee extraction" upgrades on the dispenser screen. By converting device health status into replacement marketing opportunities, a closed-loop linkage between fault warnings and product upgrades is achieved.

[0050] In addition, refer to Figure 3 Furthermore, in one embodiment, steps S13 and S14 are added before step S1: S13. Receive the advertisement playback task instruction package from the cloud. The instruction package includes the ID or URL of the customized advertisement, the playback plan, and the target device identifier.

[0051] Specifically, the system receives ad playback task instruction packages from the cloud task scheduler via the communication network. These packages contain ad creative IDs / URLs, playback plan parameters such as time periods / carousel order, and target device identifiers. The ad playback engine parses the instruction packages and extracts key parameters. After verifying the matching of device identifiers, the system enters the execution process, thereby achieving standardized and structured transmission of ad tasks from the cloud to a massive number of devices. This ensures the parseability and device targeting of instructions, solves the problem of instruction confusion caused by traditional broadcast push, and lays the foundation for precise targeting.

[0052] S14. Determine if the ID or URL of the customized advertisement exists in the local advertising material library. If it does not exist, download the customized advertisement from the cloud to the advertising material library. If it exists, call the customized advertisement in the advertising material library.

[0053] Specifically, the ad playback engine queries the locally stored ad creative library based on the ad ID / URL in the instruction package: If the content is missing, it will be downloaded from the cloud ad content library and cached locally via network communication, and then added to the playback queue after download. If the material already exists, the local cached material will be used directly to execute the playback plan, while the MD5 value of the material version will be verified to avoid playing expired content.

[0054] The dynamic caching mechanism ensures the timeliness and integrity of advertising content, reduces duplicate transmission of traffic, improves playback reliability in weak network environments, resolves the contradiction between limited local storage space and content freshness, and provides a foundation for adjusting advertising playback behavior based on preset trigger rules or cloud instructions.

[0055] In addition, refer to Figure 4 Furthermore, in one embodiment, step S2 is refined into the following sub-steps: S20: Records autonomous playback events in real time, and monitors user-triggered events and device status information.

[0056] Specifically, it captures key data in real time, enabling synchronized monitoring of the entire ad playback process and device health status. This provides a complete, noise-free raw data source for accurate analysis, resolving the issues of missing or mixed event records in traditional solutions. All data is temporarily stored in a local log queue after removing duplicate and invalid records. Key data includes: Autonomous playback events, such as the start / end time of carousel ads on the standby screen and the ID of the playback material; User-triggered events, such as clicking on an ad slot or selecting water temperature; Device status information, such as network latency, filter life, and error codes.

[0057] S21. The preset reporting strategy includes reporting timed logs. If the current playback behavior is an autonomous playback event, a timed log is generated based on the content of the autonomous playback event, and the timed log is uploaded to the cloud.

[0058] Specifically, for the autonomous playback events of carousel ads within fixed time periods, logs are uploaded to the cloud according to a scheduled logging strategy. In this embodiment, when an autonomous playback event is executed, all autonomous playback records during the period are packaged in batches at low frequency, and then the data is compressed and uploaded to the cloud via a communication gateway (MQTT / HTTPS). Batch processing avoids peak device operation periods to reduce resource consumption, thereby reducing network traffic and device power consumption caused by frequent reporting, while ensuring the integrity of continuous advertising behavior data, adapting to large-scale device deployment scenarios.

[0059] S22. The preset reporting strategy also includes reporting event logs. If the current playback behavior is a user-triggered event, an event log is generated based on the content of the user-triggered event and uploaded to the cloud.

[0060] Specifically, for user-triggered events, an event log is uploaded to the cloud in real time. In this embodiment, a lightweight log containing key fields is generated immediately when an event occurs, including event type, timestamp, and associated ad ID. This log is then uploaded to the cloud in real time, prioritizing network bandwidth usage. If the network is interrupted, the log is temporarily stored in a local retry queue. This ensures the timeliness of high-value user interaction data, supports real-time adjustments to the ad delivery strategy, and improves the agility of ad optimization.

[0061] In addition, refer to Figure 5 Furthermore, in one embodiment, step S3 is refined into the following sub-steps: S30. If a timed log is reported, the advertising placement rules will be optimized based on the first analysis report generated from the cloud based on the timed log. The first analysis report includes the exposure and playback duration of each advertising material on the current device, as well as playback data, online rate, and success rate of several device regions.

[0062] Specifically, the cloud platform analyzes and processes the batch logs periodically reported by the smart water dispensers to generate a first analysis report. This report includes statistics on the exposure of ad creatives on individual devices, average playback duration, and aggregated regional data, such as a 98% online rate for devices in office buildings within a certain business district and an 82% completion rate for breakfast ads. Based on this data, the advertising strategy engine optimizes the delivery rules, such as lowering the priority of low-exposure creatives and increasing the frequency of popular ads in high-online-rate areas. This enables refined scheduling of advertising resources based on group playback behavior data, solving the problem of single-strategy ad delivery in specific regions and improving ad penetration and resource utilization in high-value areas.

[0063] S31. If an event log is reported, the advertising rules are optimized based on the second analysis report generated from the cloud based on the reported event log, where the second analysis report includes the current user interaction rate of the device.

[0064] Specifically, the cloud-based real-time stream processing engine parses event logs generated by user-triggered events to produce a second analysis report. This second analysis report focuses on single-device user interaction rates, such as the click-through rate of coffee ads being 15% on office devices compared to 5% on home devices, analyzing preference differences based on function operation types. Furthermore, the advertising strategy engine dynamically adjusts rules, such as pushing similar ad derivative content to high-interaction-rate device groups and replacing ad creatives in low-interaction scenarios. This transforms real-time user interaction data into a basis for optimizing ad delivery strategies, enabling rapid matching of ad content with audience preferences, resolving response lag issues, and improving ad conversion rates and user engagement.

[0065] In addition, refer to Figure 6 Furthermore, in one embodiment, step S1 is refined into the following sub-steps: S15. Based on preset trigger rules or cloud commands, control the playback / switching / stopping of advertisements in a specified area of ​​the screen.

[0066] Specifically, the ad playback engine dynamically controls the playback of ads in screen partitions based on preset trigger rules or real-time instructions issued from the cloud, based on time periods and device status. This includes loading matching ad creatives in designated areas, such as full-screen standby screens and banners at the bottom of water-filling waiting screens.

[0067] Furthermore, the ad playback engine can switch playback logic based on rule priority or user operation, such as interrupting the carousel content when a fault warning is issued, or switching to the details page after a user clicks on an ad.

[0068] Furthermore, the device will automatically stop playing ads when it goes into sleep mode, or stop playing ads on the smart water dispenser when it receives an emergency stop command from the cloud, such as when ads are removed.

[0069] By dynamically controlling the playback of advertisements in different screen zones, the advertisements are integrated with the water dispenser's functional interface, minimizing the obstruction of the water dispenser's original core information, such as water temperature and volume. At the same time, the contextualized zoning increases the advertisement's visibility and solves the problem of traditional full-screen advertisements interfering with the user experience.

[0070] In addition, refer to Figure 7 Furthermore, in one embodiment, step S13 is refined into the following sub-steps: S130: Receive instruction packets generated by the cloud based on target devices / groups and delivery time. Target devices / groups include the device ID, geographical location, and location type for targeted delivery.

[0071] Specifically, the communication gateway receives targeted instruction packets from the cloud-based task scheduler. These packets are generated based on rules from the advertising strategy engine and include device ID whitelists, geofences, and location type tags. Simultaneously, the instruction packets carry delivery time parameters. After verifying that the local device identifier matches the spatiotemporal conditions, the advertising playback engine executes the playback task, thereby achieving precise spatiotemporal reach of advertisements to the target device group. This solves the problem of traditional push notifications being unable to distinguish between location scenarios, reduces the invalid delivery rate, and increases the value per unit exposure.

[0072] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0073] This application also provides a cloud-based water dispenser advertising playback system, which corresponds one-to-one with the cloud-based water dispenser advertising playback method in the embodiments.

[0074] refer to Figure 8 A cloud-based advertising system for water dispensers includes: an ad triggering module 1, a log upload module 2, and a campaign optimization module 3. Detailed descriptions of each functional module are as follows: Ad Trigger Module 1: Used to adjust the playback behavior of customized ads based on preset trigger rules or cloud instructions. Playback behavior includes autonomous playback events and user-triggered events.

[0075] Log upload module 2: Used to record playback behavior and device status changes in real time, and report them to the cloud according to the preset reporting strategy.

[0076] Module 3 for ad delivery optimization: This module receives analysis reports from the cloud based on reported ad playback behavior and device status changes, and optimizes ad delivery rules based on these reports.

[0077] The ad triggering module 1 adjusts the playback behavior of customized ads based on preset triggering rules or cloud instructions, enabling precise ad targeting and contextualized marketing, improving ad relevance and user experience. It can also dynamically adjust ad content, timing, and format based on the water dispenser's status and user actions, fully utilizing the idle value of the smart water dispenser screen. The log upload module 2 records playback behavior and device status changes in real time and reports them to the cloud according to a preset reporting strategy, providing objective and real-time ad performance data to assist advertisers in decision-making and facilitate unified, remote, and automated management of large-scale devices. The ad delivery optimization module 3 receives analysis reports generated from the cloud based on the reported data and optimizes ad delivery rules accordingly, improving the efficiency, timeliness, and flexibility of ad delivery. Through the combined operation of these modules, a closed loop of "delivery -> playback -> monitoring -> analysis -> optimization" is achieved, increasing ad conversion rates and creating new advertising revenue channels for operators. Specific limitations regarding the cloud-based water dispenser advertising playback system can be found in the context of the limitations on the cloud-based water dispenser advertising playback method, and will not be repeated here. Each module in the aforementioned cloud-based water dispenser advertising playback system can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in the electronic device, or stored in the memory of the electronic device as software, so that the processor can call and execute the corresponding operations of each module. In one embodiment, an electronic device is provided, which is a user terminal. (Reference) Figure 9 The electronic device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database stores detection data tables. The network interface communicates with external terminals via a network connection. When the computer program is executed by the processor, it implements a cloud-based, interconnected method for playing advertisements on a water dispenser.

[0078] In one embodiment, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to perform the following steps: S1. Adjust the playback behavior of customized advertisements based on preset trigger rules or cloud instructions. Playback behavior includes autonomous playback events and user-triggered events.

[0079] S2. Record playback behavior and device status changes in real time, and report them to the cloud according to the preset reporting strategy.

[0080] S3. Receive analysis reports generated from the cloud based on reported ad playback behavior and device status changes, and optimize ad delivery rules based on the analysis reports.

[0081] In one embodiment, the sub-steps of step S1 refinement include: S10. Set preset trigger rules, which include changes in the water dispenser's status and user operations.

[0082] S11. When a change in the water dispenser's status is detected, if there is no user operation, the playback behavior will be switched to an autonomous playback event, where the autonomous playback event plays a customized advertisement related to the current status.

[0083] S12. When a user operation is detected, the playback behavior is switched to a user-triggered event, where the user-triggered event is to play a customized advertisement related to the current operation.

[0084] In one embodiment, the additional step before step S1 includes: S13. Receive the advertisement playback task instruction package from the cloud. The instruction package includes the ID or URL of the customized advertisement, the playback plan, and the target device identifier.

[0085] S14. Determine if the ID or URL of the customized advertisement exists in the local advertising material library. If it does not exist, download the customized advertisement from the cloud to the advertising material library. If it exists, call the customized advertisement in the advertising material library.

[0086] In one embodiment, the refined sub-steps of step S2 include: S20: Records autonomous playback events in real time, and monitors user-triggered events and device status information.

[0087] S21. The preset reporting strategy includes reporting timed logs. If the current playback behavior is an autonomous playback event, a timed log is generated based on the content of the autonomous playback event, and the timed log is uploaded to the cloud.

[0088] S22. The preset reporting strategy also includes reporting event logs. If the current playback behavior is a user-triggered event, an event log is generated based on the content of the user-triggered event and uploaded to the cloud.

[0089] In one embodiment, the refined sub-steps of step S3 include: S30. If a timed log is reported, the advertising placement rules will be optimized based on the first analysis report generated from the cloud based on the timed log. The first analysis report includes the exposure and playback duration of each advertising material on the current device, as well as playback data, online rate, and success rate of several device regions.

[0090] S31. If an event log is reported, the advertising rules are optimized based on the second analysis report generated from the cloud based on the reported event log, where the second analysis report includes the current user interaction rate of the device.

[0091] In one embodiment, the sub-steps of step S1 refinement include: S15. Based on preset trigger rules or cloud commands, control the playback / switching / stopping of advertisements in a specified area of ​​the screen.

[0092] In one embodiment, the sub-steps of step S13 include: S130: Receive instruction packets generated by the cloud based on target devices / groups and delivery time. Target devices / groups include the device ID, geographical location, and location type for targeted delivery.

[0093] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0094] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

Claims

1. A method for playing advertisements on a water dispenser based on cloud-based linkage, characterized in that, include: The playback behavior of customized advertisements is adjusted based on preset trigger rules or cloud instructions. The playback behavior includes autonomous playback events and user-triggered events. The playback behavior and device status changes are recorded in real time and reported to the cloud according to a preset reporting strategy; Receive analysis reports generated from the cloud based on reported ad playback behavior and device status changes, and optimize ad delivery rules based on the analysis reports.

2. The method according to claim 1, characterized in that, The steps of adjusting the playback behavior of customized advertisements based on preset trigger rules or cloud instructions, wherein the playback behavior includes autonomous playback events and user-triggered events, include: Set preset trigger rules, which include changes in the water dispenser's status and user operations; When a change in the water dispenser's status is detected, if there is no user interaction, the playback behavior is switched to an autonomous playback event, whereby the autonomous playback event plays a customized advertisement related to the current status. When a user action is detected, the playback behavior is switched to a user-triggered event, wherein the user-triggered event is to play a customized advertisement related to the current action.

3. The method according to claim 1, characterized in that, Before the step of adjusting the playback behavior of customized advertisements based on preset trigger rules or cloud instructions, the playback behavior includes both autonomous playback events and user-triggered events, the method further includes: Receive an ad playback task instruction package from the cloud, the instruction package including the ID or URL of the customized ad, the playback plan and the target device identifier; Determine if the ID or URL of the customized advertisement exists in the local advertising material library. If it does not exist, download the customized advertisement from the cloud to the advertising material library. If it exists, call the customized advertisement in the advertising material library.

4. The method according to claim 2, characterized in that, The step of recording the playback behavior and device status changes in real time and reporting them to the cloud according to a preset reporting strategy includes: Records autonomous playback events in real time and monitors user-triggered events and device status information; The preset reporting strategy includes reporting timed logs. If the current playback behavior is an autonomous playback event, a timed log is generated based on the content of the autonomous playback event, and the timed log is uploaded to the cloud. The preset reporting strategy also includes reporting event logs. If the current playback behavior is a user-triggered event, an event log is generated based on the content of the user-triggered event, and the event log is uploaded to the cloud.

5. The method according to claim 4, characterized in that, The step of receiving an analysis report generated from the cloud based on reported advertising playback behavior and device status changes, and optimizing advertising delivery rules according to the analysis report, includes: If a timed log is reported, the advertising delivery rules will be optimized based on the first analysis report generated from the cloud based on the timed log. The first analysis report includes the exposure and playback duration of each advertising material on the current device, as well as playback data, online rate, and success rate of several device regions. If an event log is reported, the advertising rules are optimized based on a second analysis report generated from the cloud based on the reported event log, wherein the second analysis report includes the current user interaction rate of the device.

6. The method according to claim 1, characterized in that, The steps of adjusting the playback behavior of customized advertisements based on preset trigger rules or cloud instructions, wherein the playback behavior includes autonomous playback events and user-triggered events, include: Based on preset trigger rules or cloud commands, control the playback / switching / stopping of advertisements in a specified area of ​​the screen.

7. The method according to claim 1, characterized in that, The step of receiving an advertisement playback task instruction package from the cloud, wherein the instruction package includes the advertisement's ID or URL, playback plan, and target device identifier, includes: Receive instruction packets generated by the cloud based on target devices / groups and delivery time, wherein the target devices / groups include the device ID, geographical location and location type for targeted delivery.

8. A cloud-based advertising playback system for water dispensers, characterized in that, include: Ad triggering module (1): used to adjust the playback behavior of customized ads based on preset triggering rules or cloud instructions, the playback behavior including autonomous playback events and user triggering events; Log upload module (2): used to record the playback behavior and device status changes in real time, and report them to the cloud according to the preset reporting strategy; The ad delivery optimization module (3) is used to receive an analysis report generated from the cloud based on the reported ad playback behavior and device status changes, and to optimize the ad delivery rules according to the analysis report.

9. An electronic device, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executed as any one of the cloud-based water dispenser advertising playback methods as described in claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer program is stored and can be loaded by a processor and executed as any one of the cloud-based water dispenser advertising playback methods as described in claims 1 to 7.

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