Service recommendation system based on user behavior and environment

Abstract

The invention discloses a service recommendation system based on user behaviors and environment, and the system comprises a data collection module which is used for collecting user behaviors and environment data; the edge calculation module is used for analyzing the people flow density and the business peak period and calculating the business handling priority; the service recommendation module is used for generating and pushing priority prompts; the service execution module is used for adjusting the service process according to the priority prompt; according to the invention, by analyzing the people flow density and the business peak in real time, service resources can be reasonably allocated, the condition of service congestion in the business peak is avoided, and the overall service efficiency is improved; the method can adapt to different service scenes, can realize service optimization recommendation by adjusting own parameters and algorithms for government affair services, financial services, commercial services and the like, and has very high universality; the whole system is high in automation degree, the requirement for manual intervention is reduced, and the labor cost is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent service recommendation, and in particular to a service recommendation system based on user behavior and environment. Background Art

[0002] In many service scenarios, such as government services, financial services, and commercial services (shopping malls, supermarkets, etc.), traditional service delivery methods are often passive, requiring users to independently understand the available services and follow established procedures to obtain them. With the diversification of service needs and the increasing complexity of service content, this traditional service delivery approach has some obvious shortcomings.

[0003] On the one hand, many users, faced with complex service options, find it difficult to quickly determine the service that best suits them, resulting in a poor service experience and wasted time. For example, in government service halls, users may not be clear about the procedures and priority levels for different services, and need to spend a considerable amount of time consulting staff. On the other hand, during peak business hours, service resources may not be allocated properly, resulting in long wait times for some users and affecting overall service efficiency. For example, at financial branches, high traffic during certain hours can lead to congestion in business processing, and traditional approaches lack intelligent response mechanisms for such situations. While there are currently some attempts at service recommendations based on fixed rules, they lack the ability to dynamically adjust based on actual user behavior and real-time environment, and cannot truly meet user needs or optimize service delivery.

[0004] In addition, with the development of the Internet of Things and smart devices, sensors have been able to collect various types of environmental data on a large scale. However, how to combine this environmental data (such as crowd density) with real-time analysis technology to achieve accurate recommendations for user services remains a problem that needs further resolution. Summary of the Invention

[0005] The purpose of the present invention is to provide a service recommendation system based on user behavior and environment in order to solve all or one of the above problems in the prior art.

[0006] In order to solve the above technical problems, the specific technical solutions of the present invention are as follows: The present invention provides a service recommendation system based on user behavior and environment, comprising: Data collection module, edge computing module, service recommendation module and service execution module; The data collection module is used to collect user behavior and environmental data; The edge computing module is used to analyze traffic density and business peak hours and calculate business processing priorities; The service recommendation module is used to generate and push priority prompts; The service execution module is used to adjust the service process according to the priority prompt.

[0007] Furthermore, the data acquisition submodule in the data acquisition module includes at least one of a camera, an infrared sensor and an infrared thermal imaging sensor.

[0008] Furthermore, the edge computing module is also provided with a data processing unit, which is also used to identify user behavior patterns by analyzing visual information and determine business peak periods based on time series data and preset rules.

[0009] Furthermore, the edge computing module is also provided with a priority calculation unit, which is also used to calculate the business processing priority based on the crowd density, user behavior and business peak period.

[0010] Furthermore, the service recommendation module is further provided with a prompt generation unit, which is further used to generate a service handling priority prompt in the form of text, voice or visual guidance.

[0011] Furthermore, the service recommendation module is also provided with a push unit, which is further used to accurately push priority prompts to relevant users through multiple methods, including mobile phone APP, self-service terminal and broadcast system.

[0012] Furthermore, the service execution module is also used to process services for users according to priority in government service scenarios, and to adjust the service strategies of staff in commercial service scenarios to adapt to different user traffic.

[0013] Furthermore, the data acquisition module, the edge computing module, the service recommendation module and the service execution module communicate with each other through a high-speed and stable data transmission link.

[0014] Furthermore, the service recommendation system based on user behavior and environment is also used to adjust the parameters and algorithms of each module according to actual application scenarios and service requirements.

[0015] Furthermore, the service recommendation system based on user behavior and environment is also used for application in government services, financial services and commercial services.

[0016] The beneficial effects of the technical solution of the present invention are: The service recommendation system based on user behavior and environment described in the present invention can reasonably allocate service resources by real-time analysis of crowd density and business peak hours, avoid service congestion during business peak hours, and improve overall service efficiency; for example, in government service halls, it can reduce user waiting time and improve government service satisfaction; secondly, based on user behavior and priority prompts, it provides users with more personalized service guidance, such as optimizing customers' shopping routes in commercial service places, so that customers can find the goods or services they need more quickly, improving user service experience; thirdly, the system can adapt to different service scenarios, whether it is government services, financial services or commercial services, etc., it can achieve optimized service recommendations by adjusting its own parameters and algorithms, and has strong versatility; in addition, the entire system has a high degree of automation, which reduces the need for manual intervention and reduces labor costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0018] Figure 1 Schematic diagram of the architecture of the service recommendation system based on user behavior and environment according to an embodiment of the present invention. DETAILED DESCRIPTION

[0019] The preferred embodiments of the present invention are described in detail below with reference to the accompanying drawings so that the advantages and features of the present invention can be more easily understood by those skilled in the art, thereby making a clearer and more precise definition of the protection scope of the present invention.

[0020] In the description of the present invention, it should be noted that the embodiments described in the present invention are only part of the embodiments of the present invention, rather than all of the embodiments; based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative work are within the scope of protection of the present invention.

[0021] The terms "first," "second," and the like in the specification and claims herein and in the accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a particular order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate so that the embodiments of the present invention described herein can be implemented in orders other than those illustrated or described herein. In addition, the terms "including" and "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, apparatus, product, or device comprising a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such process, method, product, or device.

[0022] Embodiment, this embodiment provides a service recommendation system based on user behavior and environment, such as Figure 1 As shown, including: Data collection module, edge computing module, service recommendation module and service execution module; The data collection module is used to collect user behavior and environmental data; The edge computing module is used to analyze traffic density and business peak hours and calculate business processing priorities; The service recommendation module is used to generate and push priority prompts; The service execution module is used to adjust the service process according to the priority prompt.

[0023] Furthermore, the data acquisition submodule in the data acquisition module includes at least one of a camera, an infrared sensor and an infrared thermal imaging sensor.

[0024] Furthermore, the edge computing module is also provided with a data processing unit, which is also used to identify user behavior patterns by analyzing visual information and determine business peak periods based on time series data and preset rules.

[0025] Furthermore, the edge computing module is also provided with a priority calculation unit, which is also used to calculate the business processing priority based on the crowd density, user behavior and business peak period.

[0026] Furthermore, the service recommendation module is further provided with a prompt generation unit, which is further used to generate a service handling priority prompt in the form of text, voice or visual guidance.

[0027] Furthermore, the service recommendation module is also provided with a push unit, which is further used to accurately push priority prompts to relevant users through multiple methods, including mobile phone APP, self-service terminal and broadcast system.

[0028] Furthermore, the service execution module is also used to process services for users according to priority in government service scenarios, and to adjust the service strategies of staff in commercial service scenarios to adapt to different user traffic.

[0029] Furthermore, the data acquisition module, the edge computing module, the service recommendation module and the service execution module communicate with each other through a high-speed and stable data transmission link.

[0030] Furthermore, the service recommendation system based on user behavior and environment is also used to adjust the parameters and algorithms of each module according to actual application scenarios and service requirements.

[0031] Furthermore, the service recommendation system based on user behavior and environment is also used for application in government services, financial services and commercial services.

[0032] It should also be understood that in the embodiments herein, the term "and / or" merely describes an association between associated objects, indicating that three possible relationships exist. For example, "A and / or B" could represent: A alone, A and B simultaneously, or B alone. Furthermore, the character " / " in this document generally indicates an "or" relationship between the associated objects.

[0033] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the above description has generally described the composition and steps of each example according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this document.

[0034] In the several embodiments provided herein, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices, or units, or can be an electrical, mechanical, or other form of connection.

[0035] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiments herein.

[0036] In addition, the functional units in the various embodiments herein may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0037] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this article is essentially or the part that contributes to the existing technology, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of this article. The aforementioned storage medium includes: various media that can store program code, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0038] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention's description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A service recommendation system based on user behavior and environment, characterized by: include: Data collection module, edge computing module, service recommendation module and service execution module; The data collection module is used to collect user behavior and environmental data; The edge computing module is used to analyze traffic density and business peak hours and calculate business processing priorities; The service recommendation module is used to generate and push priority prompts; The service execution module is used to adjust the service process according to the priority prompt.

2. The service recommendation system based on user behavior and environment according to claim 1, characterized in that: The data acquisition submodule in the data acquisition module includes at least one of a camera, an infrared sensor and an infrared thermal imaging sensor.

3. The service recommendation system based on user behavior and environment according to claim 1, characterized in that: The edge computing module is also provided with a data processing unit, which is also used to identify user behavior patterns by analyzing visual information and determine business peak periods based on time series data and preset rules.

4. The service recommendation system based on user behavior and environment according to claim 1, characterized in that: The edge computing module is also provided with a priority calculation unit, which is also used to calculate the business processing priority based on traffic density, user behavior and business peak period.

5. The service recommendation system based on user behavior and environment according to claim 1, characterized in that: The service recommendation module is further provided with a prompt generation unit, which is further used to generate a service handling priority prompt in the form of text, voice or visual guidance.

6. The service recommendation system based on user behavior and environment according to claim 1, characterized in that: The service recommendation module is also provided with a push unit, which is further used to accurately push priority prompts to relevant users through multiple methods, including mobile phone APP, self-service terminal and broadcast system.

7. The service recommendation system based on user behavior and environment according to claim 1, characterized in that: The service execution module is also used to process services for users according to priority in government service scenarios, and to adjust the service strategies of staff in commercial service scenarios to adapt to different user traffic.

8. The service recommendation system based on user behavior and environment according to claim 1, characterized in that: The data acquisition module, the edge computing module, the service recommendation module and the service execution module communicate with each other through a high-speed and stable data transmission link.

9. The service recommendation system based on user behavior and environment according to claim 1, characterized in that: The service recommendation system based on user behavior and environment is also used to adjust the parameters and algorithms of each module according to actual application scenarios and service requirements.

10. The service recommendation system based on user behavior and environment according to claim 1, characterized in that: The service recommendation system based on user behavior and environment is also used in government services, financial services and commercial services.

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