Store management methods, systems and related equipment based on the Internet of Things and AI

Abstract

The present invention provides a store management method, system and related equipment based on the Internet of Things and AI, the method includes deploying Internet of Things hardware in stores that need to be managed, the Internet of Things hardware includes cameras and data acquisition sensors; establishing data transmission between the Internet of Things hardware and a cloud server; obtaining camera data and sensor data collected by the Internet of Things hardware; performing store SOP standard inspection and business data analysis on the camera data and the sensor data based on the AI ​​model preset in the cloud server to obtain a store report; obtaining a store adjustment strategy based on the store report, and rectifying the store through the store adjustment strategy. The technical solution of the present invention realizes automated store inspection analysis of stores with the help of the Internet of Things and AI technology, without the need for human participation, thereby improving store management efficiency.

Description

Technical Field

[0001] The present invention relates to the field of data analysis technology, and in particular to a store management method, system and related equipment based on the Internet of Things and AI. Background Art

[0002] With the rapid development of IoT hardware devices and big data, store management scenarios have been widely used in the digitalization process of enterprises, and the standardization and intelligence of store management have become the key to improving service quality and operational efficiency, which can help brand chain stores improve customer experience, optimize store operations, and reduce operating and management costs. The improvement of operational efficiency driven by digitalization is crucial to improving quality and efficiency, improving profitability, and building competitive barriers. Although the store management methods of existing technologies have realized data collection with the help of IoT hardware, most of the store data collected by IoT hardware still remain in the stage of manual judgment and analysis, which leads to low data processing efficiency and the inability to fully utilize the data.

[0003] Therefore, the prior art still needs to be improved and developed. Summary of the invention

[0004] The present invention provides a store management method, system and related equipment based on the Internet of Things and AI. The main purpose of the present invention is to solve the technical problems mentioned in the background technology of the prior art.

[0005] A first aspect of the present invention provides a store management method based on the Internet of Things and AI, comprising:

[0006] Deploy IoT hardware in stores that need to be managed, including cameras and data collection sensors;

[0007] Establishing data transmission between the IoT hardware and the cloud server;

[0008] Obtaining camera data and sensor data collected by the IoT hardware;

[0009] Performing a store SOP standard check and operating data analysis on the camera data and the sensor data based on the AI ​​model preset in the cloud server to obtain a store report;

[0010] A store adjustment strategy is obtained based on the store report, and the store is rectified using the store adjustment strategy.

[0011] In an optional implementation manner of the first aspect of the present invention, performing a store SOP standard inspection and an operation data analysis on the camera data and the sensor data based on the AI ​​model preset in the cloud server to obtain a store report includes:

[0012] Read each inspection item in the store SOP standard in turn;

[0013] For each of the inspection items, the camera data and the sensor data are analyzed and identified by the AI ​​model to obtain dependency data of each of the inspection items;

[0014] Determining whether each of the dependent data meets its corresponding inspection standard;

[0015] Collect the inspection results of each inspection item and obtain the store SOP inspection records;

[0016] Analyze and identify the camera data and the sensor data through the AI ​​model to obtain store operation related data;

[0017] Calculate key business indicators based on the store operation related data to obtain calculated values ​​of each key business indicator;

[0018] Collecting the store operation related data and the calculated values ​​of each of the key business indicators to obtain store operation status records;

[0019] The store report is generated based on the store SOP inspection record and the store operation status record.

[0020] In an optional implementation manner of the first aspect of the present invention, for each of the inspection items, analyzing and identifying the camera data and the sensor data by the AI ​​model to obtain the dependency data of each of the inspection items includes:

[0021] For each of the inspection items, determining whether the inspection item involves scene detection;

[0022] If the inspection item involves scene detection, obtaining the scene detection type corresponding to the inspection item;

[0023] Based on the scene detection type, a target scene detection algorithm is loaded from a preset scene algorithm library;

[0024] The camera data is subjected to scene detection through the AI ​​model and based on the target scene detection algorithm to obtain the dependency data of the inspection item.

[0025] In an optional implementation of the first aspect of the present invention, the scene detection includes employee clothing detection, employee behavior detection, store environmental hygiene detection, commodity display detection, customer flow detection and emergency detection.

[0026] In an optional implementation manner of the first aspect of the present invention, generating the store report based on the store SOP inspection record and the store operation status record includes:

[0027] Upload the store SOP inspection record and the store operation status record to a pre-built centralized cloud service platform;

[0028] Generate, store and manage the store report according to preset report specifications through the centralized cloud service platform;

[0029] An open API interface is provided through the centralized cloud service platform so that different types of clients can access the centralized cloud service platform and access and obtain the store report after logging into the management account.

[0030] In an optional implementation manner of the first aspect of the present invention, obtaining a store adjustment strategy based on the store report and rectifying the store by using the store adjustment strategy includes:

[0031] The camera data and the sensor data of the store after rectification are collected through the IoT hardware;

[0032] Based on the AI ​​model preset in the cloud server, the camera data and the sensor data of the store after rectification are subjected to store SOP standard inspection and business data analysis to obtain a new store report;

[0033] The new store report is compared with the store report before rectification to obtain the rectification effect of the store.

[0034] In an optional implementation manner of the first aspect of the present invention, obtaining a store adjustment strategy based on the store report, and rectifying the store by using the store adjustment strategy includes:

[0035] Obtain each problem item in the store report;

[0036] Match each of the problem items with the strategy library to obtain the target strategy for each of the problem items;

[0037] Collect and organize the target strategies for each of the above issues to obtain store adjustment strategies;

[0038] Sending the store adjustment strategy to a preset task management module, creating rectification tasks for each of the problems through the task management module, and automatically matching a responsible person and a rectification deadline for each rectification task;

[0039] Allocate each rectification task to the corresponding responsible person.

[0040] A second aspect of the present invention provides a store management system based on the Internet of Things and AI, and the store management system based on the Internet of Things and AI includes:

[0041] A hardware deployment module, used to deploy IoT hardware in stores that need to be managed, wherein the IoT hardware includes cameras and data acquisition sensors;

[0042] A transmission establishment module, used to establish data transmission between the IoT hardware and the cloud server;

[0043] A data acquisition module, used to acquire camera data and sensor data collected by the IoT hardware;

[0044] A data analysis module, used to perform a store SOP standard check and business data analysis on the camera data and the sensor data based on the AI ​​model preset in the cloud server to obtain a store report;

[0045] The store rectification module is used to obtain a store adjustment strategy based on the store report and rectify the store according to the store adjustment strategy.

[0046] A third aspect of the present invention provides a store management device based on the Internet of Things and AI, the store management device based on the Internet of Things and AI comprising: a memory and at least one processor, the memory storing instructions, the memory and the at least one processor being interconnected via a line;

[0047] The at least one processor calls the instructions in the memory so that the store management device based on the Internet of Things and AI executes the store management method based on the Internet of Things and AI as described in any one of the first aspects above.

[0048] A fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the store management method based on the Internet of Things and AI as described in any one of the first aspects above is implemented.

[0049] Beneficial effects: The present invention provides a store management method, system and related equipment based on the Internet of Things and AI, the method comprising deploying Internet of Things hardware in stores that need to be managed, the Internet of Things hardware comprising cameras and data acquisition sensors; establishing data transmission between the Internet of Things hardware and a cloud server; obtaining camera data and sensor data collected by the Internet of Things hardware; performing store SOP standard inspection and business data analysis on the camera data and the sensor data based on the AI ​​model preset in the cloud server to obtain a store report; obtaining a store adjustment strategy based on the store report, and rectifying the store through the store adjustment strategy. The technical solution of the present invention, with the help of the Internet of Things and AI technology, realizes automated store inspection and analysis without manual participation, thereby improving store management efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 This is a schematic diagram of an embodiment of a store management method based on the Internet of Things and AI of the present invention;

[0051] Figure 2 This is a brief schematic diagram of the overall process of a store management method based on the Internet of Things and AI in the present invention;

[0052] Figure 3 This is a schematic diagram of the business framework of a store management method based on the Internet of Things and AI at the system level of the present invention;

[0053] Figure 4 This is a schematic diagram of an embodiment of a store management system based on the Internet of Things and AI of the present invention;

[0054] Figure 5 This is a schematic diagram of an embodiment of a store management device based on the Internet of Things and AI of the present invention. DETAILED DESCRIPTION

[0055] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including" or "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0056] With the rapid development of IoT hardware devices, big data, AI and other technologies, store management scenarios have been widely used in the process of enterprise digitalization, and the standardization and intelligence of store management have become the key to improving service quality and operational efficiency, which can help brand chain stores improve customer experience, optimize store operations, and reduce operating and management costs. Improving operational efficiency driven by digitalization is crucial to improving quality and efficiency, improving profitability, and building competitive barriers. Most of the current technical limitations are mainly manifested in: store standard detection mainly relies on manual inspections, which are inefficient and prone to errors. Traditional monitoring systems can only provide video records, and cannot achieve automated standard detection and real-time feedback; it is impossible to conduct effective data analysis and extract useful information from videos.

[0057] In order to solve the above problems existing in the prior art, refer to Figure 1 The first aspect of the present invention provides a store management method based on the Internet of Things and AI, comprising:

[0058] S100, deploy IoT hardware in stores that need to be managed, the IoT hardware includes cameras and data acquisition sensors; in step S100 of the present invention, deployment and configuration of IoT devices, where the installation of cameras mainly involves installing high-definition cameras at key locations of the store (such as entrances, shelf areas, cashier areas, etc.) to capture video data. Data acquisition sensors include IoT devices such as audio sensors, temperature and humidity sensors, and customer flow counters, which are used to collect environmental and behavioral data.

[0059] S200, establishing data transmission between the IoT hardware and the cloud server; in the present invention, after the cameras and data acquisition sensors are deployed, it is necessary to ensure that all IoT devices can be connected to the Internet so that data can be transmitted to the cloud server or the local server.

[0060] S300, obtaining the camera data and sensor data collected by the IoT hardware; in the present invention, the camera data is mainly video data, and the camera captures the video stream in real time, including employee behavior, customer flow and product display, etc.; the sensor data includes audio sensors collecting audio data in the store, which may be used to analyze environmental noise or specific audio events, temperature and humidity sensors collecting store environment data, etc., to ensure that the storage conditions of the products meet the requirements, and customer flow counters counting the number of customers entering and leaving the store, analyzing customer flow and customer behavior.

[0061] In step S200 of the present invention, video compression can use video compression technology such as H.265 to reduce the storage and transmission requirements of video data. Data processing can format the various types of collected data for further processing and analysis. Data storage needs to ensure real-time synchronization of data for real-time monitoring and analysis, and store structured data (such as passenger flow statistics) in a database for easy query and analysis. Data transmission can transmit data to the cloud or local server via a wired or wireless network.

[0062] S400, based on the AI ​​model preset in the cloud server, the camera data and the sensor data are subjected to a store SOP standard inspection and an operation data analysis to obtain a store report; in the present invention, after the IoT hardware collects the data, the data is mainly analyzed through a preset AI model, and the intelligent store patrol system through the AI ​​model can bring a more efficient and intelligent operation and management mode to the chain stores, thereby improving the overall business performance and market competitiveness.

[0063] In an optional implementation of the first aspect of the present invention, performing a store SOP standard inspection and an operation data analysis on the camera data and the sensor data based on the AI ​​model preset in the cloud server to obtain a store report includes:

[0064] Read each inspection item in the store SOP standard in sequence; the store SOP standard is a standardized operation process made by the store to make the store operation more standardized.

[0065] For each of the inspection items, the camera data and the sensor data are analyzed and identified by the AI ​​model to obtain the dependency data of each of the inspection items; in an optional implementation of this step, for each of the inspection items, the camera data and the sensor data are analyzed and identified by the AI ​​model to obtain the dependency data of each of the inspection items, including: for each of the inspection items, determining whether the inspection item involves scene detection, the scene detection includes employee dress detection, employee behavior detection, store environmental sanitation detection, commodity display detection, customer flow detection and emergency detection; if the inspection item involves scene detection, obtaining the scene detection type corresponding to the inspection item; based on the scene detection type, loading a target scene detection algorithm from a preset scene algorithm library; performing scene detection on the camera data by the AI ​​model and based on the target scene detection algorithm to obtain the dependency data of the inspection item.

[0066] Determine whether each of the dependent data meets its corresponding inspection standards; in this step, for example, if the data collected by the camera is recognized by the AI ​​model that there are employees in the video frame, then further determine whether the employees are wearing prescribed work clothes. For another example, determine whether employees comply with service specifications through continuous video frames, guide customers to consume, etc.

[0067] The inspection results of each inspection item are collected to obtain the store SOP inspection record; in the present invention, each inspection item and its inspection result will be associated and bound in the store SOP inspection record, and the unqualified items will be highlighted by color in the store SOP inspection record to facilitate subsequent rectification.

[0068] The camera data and the sensor data are analyzed and identified by the AI ​​model to obtain store operation related data; in the present invention, the store operation related data includes customer flow, details of commodity sales and store operating costs, etc.

[0069] Key business indicators are calculated based on the store operation-related data to obtain calculated values ​​of each key business indicator; the key business indicators include the proportion of customers entering the store, the proportion of customers spending in the store, the average spending amount of customers entering the store, the store profit margin, the ranking of store best-selling products, etc.

[0070] The store operation related data and the calculated values ​​of each of the key business indicators are collected to obtain a store operation status record; in the present invention, the store operation related data for calculating the key business indicators will be summarized into the store operation status record together with the calculated values ​​of each of the key business indicators, so that the store operation data and the key business indicators obtained based on the store operation data can be clearly seen, thereby facilitating store managers to make decisions.

[0071] The store report is generated based on the store SOP inspection record and the store operation status record. In the present invention, the generation of the store report based on the store SOP inspection record and the store operation status record includes: uploading the store SOP inspection record and the store operation status record to a pre-built centralized cloud service platform; generating, storing and managing the store report according to preset report specifications through the centralized cloud service platform; providing an open API interface through the centralized cloud service platform so that different types of clients can access the centralized cloud service platform and access and obtain the store report after logging into the management account.

[0072] In this embodiment of the present invention, the centralized cloud service platform is responsible for the life cycle management of the report, and is responsible for the generation, storage and management of the report. Through the open API interface, different clients (mobile terminal, PC terminal, WeChat, office platform, etc.) are allowed to access and obtain reports. The centralized cloud service platform can adapt to data synchronization on multiple terminals: develop applications adapted to different clients or use responsive design to ensure that reports can be displayed correctly on different devices and platforms. Utilize data synchronization technology, such as mPaaS mobile synchronization service (MSS), to achieve incremental push and merge push of report data, reduce network transmission costs, and improve the timeliness of data synchronization. In addition, report document integration and distribution can integrate the reporting system into third-party platforms such as WeChat and DingTalk, and use the message push function of these platforms to promptly notify users to view reports. At the same time, use the CDN network to distribute the report content throughout the network to ensure that users in different regions can quickly access the report.

[0073] S500, based on the store report, obtain the store adjustment strategy, and rectify the store through the store adjustment strategy. In the present invention, the store adjustment strategy is obtained based on the store report, and the store is rectified through the store adjustment strategy, including: obtaining each problem item in the store report; matching each problem item with the strategy library to obtain the target strategy of each problem; collecting and collating the target strategy of each problem to obtain the store adjustment strategy; sending the store adjustment strategy to the preset task management module, creating rectification tasks for each problem through the task management module, and automatically matching the responsible person and the rectification deadline for each rectification task; assigning each rectification task to the corresponding responsible person. In the present invention, the AI ​​intelligent management system automatically identifies the problem and generates the rectification task; the task is automatically assigned to the corresponding responsible person through the system, and the rectification deadline is set; after the rectification is completed, the rectification result is fed back through the system, and finally verified and evaluated by the system or manually. The task management module is responsible for the functions of task creation, assignment, tracking and reminder; each task is associated with a specific store and employee to ensure that the responsibility is assigned to the person; set reminder and urging mechanism to ensure that the task is completed on time.

[0074] In an optional implementation of the first aspect of the present invention, the store adjustment strategy is obtained based on the store report, and after the store is rectified through the store adjustment strategy, it includes: collecting the camera data and the sensor data of the store after rectification through the IoT hardware; performing a store SOP standard inspection and business data analysis on the camera data and the sensor data of the store after rectification based on the AI ​​model preset in the cloud server to obtain a new store report; comparing the new store report with the store report before rectification to obtain the rectification effect of the store. In the present invention, big data analysis technology can also be used in the rectification process to compare and analyze the data before and after rectification, evaluate the rectification effect, adjust the rectification strategy according to the analysis results, and optimize the rectification process.

[0075] In order to better understand the technical solution of the present application, in simple terms, the process method of store management based on the Internet of Things and AI of the present invention can be as follows: Figure 2 As shown, the core applies image recognition technology, and the core working principle is as follows:

[0076] 1. Cameras, smart devices and platforms push monitoring streams through the RTMP protocol or use the GB / T28181 national standard protocol to pull monitoring streams. For the latter, you need to complete the registration process of the national standard device first.

[0077] 2. In the cloud, we record and store the surveillance stream and generate screenshots to create on-demand playback videos and screenshot files, so that users can check historical videos and screenshots at any time.

[0078] 3. Cloud storage services support the management of the life cycle of recorded videos and screenshots to ensure the validity and security of data.

[0079] 4. The monitoring stream is distributed across the entire network through the CDN network (content distribution network), ensuring that users in different regions can enjoy clear and smooth real-time monitoring streams and historical video playback experience.

[0080] 5. The system can easily connect to machine vision video intelligent analysis products to achieve structured analysis and processing of video content, and build business applications through big data products to improve the intelligence level of the monitoring system.

[0081] 6. Through the implementation of image recognition technology and AI-integrated business processes, the availability and convenience of monitoring data are improved, scene detection is refined, and AI intelligent analysis is realized, providing strong data support for business decision-making.

[0082] In the present invention, the entire business logic framework diagram on which the method depends can be shown as follows: Figure 3As shown in the figure, in the AI ​​scene fusion detection, dress code detection is used to identify whether employees are wearing prescribed work clothes, conduct real-time analysis of images captured by the camera, and detect whether employees' dress meets the standards; behavioral norms detection is used to analyze whether employees comply with service specifications and safe operating procedures, conduct real-time detection of negative behaviors (passive shopping guides, message idleness), and promptly notify management personnel; environmental sanitation detection is used to detect whether there are unsanitary conditions such as garbage and stagnant water in the store through image recognition technology, automatically trigger cleaning tasks, or notify cleaning staff to clean up; commodity display detection is used to monitor whether the placement of goods on the shelves meets the preset display standards, detect whether the shelves are out of stock or placed incorrectly, and promptly notify replenishment or adjustment; customer flow detection is used to detect and track algorithms to count customer flow and customer behavior patterns in the store, analyze customers' movement paths and stay time in the store, and provide data support for marketing activities; emergency detection is used to detect emergencies in the store, such as falls, fights, disputes, etc., and report them to the management system in real time. The method of the present invention can realize the implementation monitoring of store standards such as employee work clothes, takeaway placement, mask wearing, customer flow, shelves, etc., and real-time monitoring of customer flow through cameras and data collection boxes, thereby improving the standardization of chain brand stores and store sales conversion rates.

[0083] In store inspection management, data-driven decision support uses AI technology to intelligently analyze monitoring flows, extract key business indicators, and provide data support for operations management. Through real-time data analysis, problems in store operations can be quickly responded to, and decision-making efficiency and accuracy can be improved. Execution and monitoring of standardized processes The application side displays and executes standardized operating procedures to ensure the consistency and quality of store operations. The business service side monitors the execution of processes to ensure that employees comply with operating specifications and improve service quality. In remote management and task automation, the application side allows operations managers to remotely inspect stores, view store conditions in real time, and remotely assign and track tasks. The business service side automatically generates store inspection tasks and checklists based on AI analysis results to improve store inspection efficiency and systematization. Event response and continuous improvement: AI detects emergencies and immediately notifies operations managers to ensure rapid response and emergency handling. By continuously collecting feedback and AI analysis results, store operation processes are continuously optimized to form a closed loop of continuous improvement.

[0084] In summary, the technical advantages of the technical solution of this application are:

[0085] (1) Improve operational efficiency: Provide real-time video monitoring and data analysis application tools to enable managers to quickly respond to store situations and improve decision-making efficiency. Intelligent analysis algorithms process large amounts of data, reduce the need for manual store inspections, and reduce operating costs. Real-time collection of store audio and video data provides decision support for business service ends and improves monitoring efficiency.

[0086] (2) Enhance service quality and customer experience: Ensure service standardization and improve customer satisfaction by monitoring employee behavior and service quality. Analyze customer flow and customer behavior, optimize store layout and marketing strategies, and enhance customer experience. Collect environmental data through sensors to ensure that the store environment meets service standards and improve customer comfort.

[0087] (3) Optimize product management: Monitor the status of shelf products in real time, remind customers to restock in time, and reduce out-of-stock situations. Use AI to analyze product display and sales data, optimize inventory management, and reduce inventory backlogs. Use image recognition technology to detect product displays and ensure that product placement is in line with marketing strategies.

[0088] (4) Improve safety management: Monitor store safety in real time to promptly identify and address safety hazards. Improve safety management efficiency by identifying abnormal behaviors such as theft through AI analysis. Use sensors to monitor environmental anomalies such as fire and water leaks and issue early warnings.

[0089] (5) Data-driven decision-making: Provide a data visualization interface to help managers make more accurate decisions based on data. Integrate and analyze multi-source data to provide in-depth business insights and support strategic planning. Provide raw data support to provide a basis for data analysis on the business service side.

[0090] (6) Promote standardization and process optimization: Demonstrate standardized operating procedures, guide employees to perform daily tasks, and ensure service quality. The business service end monitors the execution of standardized processes to ensure the consistency and quality of store operations. The end-side devices perform standardized data collection and provide consistent data input for the business service end.

[0091] See also Figure 4 The second aspect of the present invention provides a store management system based on the Internet of Things and AI, and the store management system based on the Internet of Things and AI includes:

[0092] A hardware deployment module 10 is used to deploy IoT hardware in stores that need to be managed, wherein the IoT hardware includes cameras and data acquisition sensors;

[0093] The transmission establishment module 20 is used to establish data transmission between the IoT hardware and the cloud server;

[0094] A data acquisition module 30 is used to acquire camera data and sensor data collected by the IoT hardware;

[0095] A data analysis module 40, configured to perform a store SOP standard check and business data analysis on the camera data and the sensor data based on an AI model preset in the cloud server to obtain a store report;

[0096] The store rectification module 50 is used to obtain a store adjustment strategy based on the store report, and rectify the store according to the store adjustment strategy.

[0097] In an optional implementation of the second aspect of the present invention, the data analysis module includes:

[0098] An SOP reading unit, used to sequentially read each inspection item in the store SOP standard;

[0099] A dependency data acquisition unit, configured to analyze and identify the camera data and the sensor data through the AI ​​model for each of the inspection items, so as to obtain dependency data of each of the inspection items;

[0100] An inspection unit, used to determine whether each of the dependent data meets its corresponding inspection standard;

[0101] An SOP record acquisition unit, used to collect the inspection results of each inspection item and obtain the store SOP inspection record;

[0102] An operating data acquisition unit, configured to analyze and identify the camera data and the sensor data through the AI ​​model to obtain store operating related data;

[0103] A business indicator calculation unit, used to calculate key business indicators based on the store operation related data, and obtain the calculated value of each key business indicator;

[0104] An operation record acquisition unit, used to collect the store operation related data and the calculated values ​​of each of the key business indicators to obtain a store operation status record;

[0105] A report generating unit is used to generate the store report based on the store SOP inspection record and the store operation status record.

[0106] In an optional implementation of the second aspect of the present invention, the dependency data acquisition unit includes:

[0107] A scene detection judgment subunit, configured to judge, for each of the inspection items, whether the inspection item involves scene detection;

[0108] a scene detection type acquisition subunit, configured to acquire the scene detection type corresponding to the inspection item if the inspection item involves scene detection;

[0109] A detection algorithm acquisition subunit, used to load a target scene detection algorithm from a preset scene algorithm library based on the scene detection type;

[0110] A scene detection subunit is used to perform scene detection on the camera data through the AI ​​model and based on the target scene detection algorithm to obtain the dependency data of the inspection item.

[0111] In an optional implementation of the second aspect of the present invention, the scene detection includes employee clothing detection, employee behavior detection, store environmental hygiene detection, commodity display detection, customer flow detection and emergency detection.

[0112] In an optional implementation of the second aspect of the present invention, the report generating unit includes:

[0113] A record uploading subunit, used to upload the store SOP inspection record and the store operation status record to a pre-built centralized cloud service platform;

[0114] A report service subunit, configured to generate, store and manage the store report according to preset report specifications through the centralized cloud service platform;

[0115] The open access subunit is used to provide an open API interface through the centralized cloud service platform so that different types of clients can access the centralized cloud service platform and access and obtain the store report after logging into the management account.

[0116] In an optional implementation of the second aspect of the present invention, the store management system based on the Internet of Things and AI further includes:

[0117] A data re-collection module, used to collect the camera data and the sensor data of the store after rectification through the IoT hardware;

[0118] A new report generation module, used to perform a store SOP standard inspection and business data analysis on the camera data and the sensor data of the store after rectification based on the AI ​​model preset in the cloud server to obtain a new store report;

[0119] The new and old report comparison module is used to compare the new store report with the store report before rectification to obtain the rectification effect of the store.

[0120] In an optional implementation of the second aspect of the present invention, the store rectification module includes:

[0121] A report parsing unit, used to obtain each problem item in the store report;

[0122] A strategy matching unit, used to match each of the problem items with a strategy library to obtain a target strategy for each of the problems;

[0123] A strategy collection unit, used to collect and organize the target strategies for each of the problems to obtain store adjustment strategies;

[0124] A task generation unit, used to send the store adjustment strategy to a preset task management module, create rectification tasks for each of the problems through the task management module, and automatically match a responsible person and a rectification deadline for each rectification task;

[0125] The task allocation unit is used to allocate each rectification task to the corresponding responsible person.

[0126] Figure 5 It is a structural diagram of a store management device based on the Internet of Things and AI provided by an embodiment of the present invention. The store management device based on the Internet of Things and AI may have relatively large differences due to different configurations or performances, and may include one or more processors 60 (central processing units, CPU) (for example, one or more processors) and a memory 70, and one or more storage media 80 for storing application programs or data (for example, one or more massive storage devices). Among them, the memory and the storage medium may be short-term storage or persistent storage. The program stored in the storage medium may include one or more modules (not shown in the figure), and each module may include a series of instruction operations in the store management device based on the Internet of Things and AI. Furthermore, the processor may be configured to communicate with the storage medium to execute a series of instruction operations in the storage medium on the store management device based on the Internet of Things and AI.

[0127] The store management device based on the Internet of Things and AI of the present invention may also include one or more power supplies 90, one or more wired or wireless network interfaces 100, one or more input and output interfaces 110, and / or one or more operating systems, such as Windows Serve, Mac OS X, Unix, Linux, FreeBSD, etc. It can be understood by those skilled in the art that Figure 5 The structure of the store management device based on the Internet of Things and AI shown does not constitute a limitation of the store management device based on the Internet of Things and AI, and may include more or fewer components than shown in the figure, or a combination of certain components, or a different arrangement of components.

[0128] The present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. Instructions are stored in the computer-readable storage medium. When the instructions are executed on a computer, the computer executes the steps of the store management method based on the Internet of Things and AI.

[0129] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the system or system or unit described above can refer to the corresponding process in the aforementioned method embodiment and will not be repeated here.

[0130] 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 the present invention is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program codes.

[0131] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A store management method based on the Internet of Things and AI, characterized in that: include: Deploy IoT hardware in stores that need to be managed, including cameras and data collection sensors; Establishing data transmission between the IoT hardware and the cloud server; Obtaining camera data and sensor data collected by the IoT hardware; Performing a store SOP standard check and operating data analysis on the camera data and the sensor data based on the AI ​​model preset in the cloud server to obtain a store report; A store adjustment strategy is obtained based on the store report, and the store is rectified using the store adjustment strategy.

2. The store management method based on the Internet of Things and AI according to claim 1 is characterized in that: The store SOP standard inspection and business data analysis are performed on the camera data and the sensor data based on the AI ​​model preset in the cloud server to obtain a store report including: Read each inspection item in the store SOP standard in turn; For each of the inspection items, the camera data and the sensor data are analyzed and identified by the AI ​​model to obtain dependency data of each of the inspection items; Determining whether each of the dependent data meets its corresponding inspection standard; Collect the inspection results of each inspection item and obtain the store SOP inspection records; Analyze and identify the camera data and the sensor data through the AI ​​model to obtain store operation related data; Calculate key business indicators based on the store operation related data to obtain calculated values ​​of each key business indicator; Collecting the store operation related data and the calculated values ​​of each of the key business indicators to obtain store operation status records; The store report is generated based on the store SOP inspection record and the store operation status record.

3. The store management method based on the Internet of Things and AI according to claim 2 is characterized in that: For each of the inspection items, analyzing and identifying the camera data and the sensor data through the AI ​​model to obtain the dependent data of each of the inspection items includes: For each of the inspection items, determining whether the inspection item involves scene detection; If the inspection item involves scene detection, obtaining the scene detection type corresponding to the inspection item; Based on the scene detection type, a target scene detection algorithm is loaded from a preset scene algorithm library; The camera data is subjected to scene detection through the AI ​​model and based on the target scene detection algorithm to obtain the dependency data of the inspection item.

4. The store management method based on the Internet of Things and AI according to claim 3 is characterized in that: The scene detection includes employee clothing detection, employee behavior detection, store environment and sanitation detection, product display detection, customer flow detection and emergency detection.

5. The store management method based on the Internet of Things and AI according to claim 2 is characterized in that: The generating the store report based on the store SOP inspection record and the store operation status record comprises: Upload the store SOP inspection record and the store operation status record to a pre-built centralized cloud service platform; Generate, store and manage the store report according to preset report specifications through the centralized cloud service platform; An open API interface is provided through the centralized cloud service platform so that different types of clients can access the centralized cloud service platform and access and obtain the store report after logging into the management account.

6. The store management method based on the Internet of Things and AI according to claim 1, characterized in that: The obtaining of a store adjustment strategy based on the store report and rectifying the store by using the store adjustment strategy comprises: The camera data and the sensor data of the store after rectification are collected through the IoT hardware; Based on the AI ​​model preset in the cloud server, the camera data and the sensor data of the store after rectification are subjected to store SOP standard inspection and business data analysis to obtain a new store report; The new store report is compared with the store report before rectification to obtain the rectification effect of the store.

7. The store management method based on the Internet of Things and AI according to claim 1, characterized in that: The obtaining of a store adjustment strategy based on the store report and rectifying the store by using the store adjustment strategy comprises: Obtain each problem item in the store report; Match each of the problem items with the strategy library to obtain the target strategy for each of the problem items; Collect and organize the target strategies for each of the above issues to obtain store adjustment strategies; Sending the store adjustment strategy to a preset task management module, creating rectification tasks for each of the problems through the task management module, and automatically matching a responsible person and a rectification deadline for each rectification task; Allocate each rectification task to the corresponding responsible person.

8. A store management system based on the Internet of Things and AI, characterized in that: The store management system based on the Internet of Things and AI includes: A hardware deployment module, used to deploy IoT hardware in stores that need to be managed, wherein the IoT hardware includes cameras and data acquisition sensors; A transmission establishment module, used to establish data transmission between the IoT hardware and the cloud server; A data acquisition module, used to acquire camera data and sensor data collected by the IoT hardware; A data analysis module, used to perform a store SOP standard check and business data analysis on the camera data and the sensor data based on the AI ​​model preset in the cloud server to obtain a store report; The store rectification module is used to obtain a store adjustment strategy based on the store report and rectify the store according to the store adjustment strategy.

9. A store management device based on the Internet of Things and AI, characterized in that: The store management device based on the Internet of Things and AI includes: a memory and at least one processor, the memory stores instructions, and the memory and the at least one processor are interconnected through a line; The at least one processor calls the instructions in the memory so that the store management device based on the Internet of Things and AI executes the store management method based on the Internet of Things and AI as described in any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the store management method based on the Internet of Things and AI as described in any one of claims 1 to 7 is implemented.

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