Cloud collaborative intelligent shopping system

Abstract

The invention relates to the technical field of electronic commerce, in particular to an intelligent shopping system based on cloud collaboration. According to the system, a multi-mode interaction technology is adopted, various interaction modes such as voice, touch and gesture recognition are supported, and the user operation convenience is improved; absolute security of user information and transaction data in a transmission process is guaranteed by using a quantum security communication technology; a block chain technology is integrated, so that the non-tampering and traceability of commodity information and transaction records are ensured, and the transparency and credibility of the system are enhanced; rapid processing and response of data are realized through edge calculation, delay is reduced, and user experience is optimized; a machine learning algorithm is used for analyzing user behaviors and preferences, and accurate personalized recommendation services are provided. In addition, the system is especially suitable for a family environment, supports unmanned delivery of an unmanned aerial vehicle or a robot and unmanned signing of an intelligent door lock system, and creates brand new family shopping experience. The invention aims to provide a shopping system which is more intelligent, safer and more convenient, and has wide application prospect and market value.

Description

Technical Field

[0001] This invention belongs to the field of intelligent shopping systems, specifically cloud-based collaborative intelligent shopping systems. Background Technology

[0002] With the rapid development of the internet and mobile technology, smart shopping systems have been widely used in e-commerce, offline retail, and other fields. However, current smart shopping systems still have limitations in several aspects and urgently need improvement and refinement.

[0003] 1. Limitations of existing smart shopping systems

[0004] In terms of user interaction, although technologies such as voice recognition and gesture control have been applied to some extent, most systems still have limitations when handling complex interactive tasks. For example, the accuracy of voice recognition decreases in noisy environments, and the error rate of gesture recognition is relatively high, affecting the user experience. In addition, existing AR display technologies still need improvement in spatial positioning accuracy and the integration of real objects with virtual information, failing to provide users with a fully immersive shopping experience.

[0005] In terms of personalized recommendations, traditional recommendation algorithms often rely solely on users' historical purchase behavior or browsing history, lacking consideration for real-time environmental data and the user's current state, resulting in insufficient accuracy and timeliness of recommendations. For example, when a user's shopping environment changes (such as weather or indoor temperature), existing recommendation systems cannot adjust their recommendation strategies in a timely manner, causing the recommended results to mismatch with the user's actual needs.

[0006] Regarding payment security, while existing encryption technologies offer some protection for transactions, they remain in a passive defensive posture in the face of increasingly complex network environments and attack methods. Traditional encryption algorithms may not be effective against the potential threats of emerging technologies such as quantum computing, posing risks of user information leakage and transaction tampering.

[0007] 2. Current Status of Related Technology Development

[0008] In recent years, significant progress has been made in technologies such as the Internet of Things, artificial intelligence, blockchain, and quantum computing, providing new opportunities for the optimization and upgrading of smart shopping systems.

[0009] The development of IoT technology enables various devices to interconnect and collect and transmit massive amounts of data in real time. By connecting smart home terminals, environmental sensors, and other devices with smart shopping systems, rich user behavior and environmental data can be obtained, providing strong support for personalized recommendations and precision marketing. For example, smart bracelets can record users' exercise data, and smart air conditioners can monitor indoor temperature; this data can all be used as the basis for personalized recommendations.

[0010] Breakthroughs in artificial intelligence technology have brought more intelligent and personalized service capabilities to smart shopping systems. The development of deep learning and machine learning algorithms has significantly improved the accuracy and efficiency of technologies such as speech recognition, image recognition, and natural language processing. For example, deep learning-based speech recognition models can achieve high-precision speech recognition in various noise environments, while image recognition-based gesture control technology can achieve more precise operations. At the same time, the combination of reinforcement learning and recommendation algorithms can provide users with more accurate and real-time personalized recommendations, improving user satisfaction.

[0011] Blockchain technology, with its decentralized, immutable, transparent, and secure characteristics, offers a new solution for transaction security in smart shopping systems. Through smart contracts, automated transaction processes and rule execution are achieved, ensuring transparency and fairness in transactions. For example, in product traceability, blockchain technology can record the entire process of a product's production, distribution, and sales. Consumers can use the blockchain to query the product's authentic information, increasing their confidence in purchasing.

[0012] The emergence of quantum computing technology has brought new challenges and opportunities to the fields of data security and communication. Although the application of quantum computing is still in its early stages, the principles of quantum encryption algorithms demonstrate its enormous potential in ensuring information security. For example, quantum key distribution technology can achieve absolutely secure key distribution, resisting both traditional computational attacks and quantum attacks, providing a higher level of protection for payment security and user privacy in smart shopping systems.

[0013] 3. Technical opportunity of the present invention

[0014] While existing smart shopping systems have made progress in various technological fields, none have yet fully integrated multiple cutting-edge technologies such as the Internet of Things (IoT), artificial intelligence (AI), blockchain, and quantum security to provide a highly intelligent, personalized, secure, and seamless shopping experience. This invention aims to address the limitations of existing smart shopping systems by fully leveraging the technological advantages of IoT, AI, blockchain, and quantum security to innovatively construct a cloud-based collaborative smart shopping system. This system will provide more intelligent, convenient, secure, and personalized shopping services to meet the growing needs of users.

[0015] With the development of the Internet and mobile technology, smart shopping systems have been widely used, but there are still shortcomings in user interaction, personalized recommendations, payment security and system collaboration, such as limited interaction methods, inaccurate recommendations, payment security risks and poor collaboration among various links. Summary of the Invention

[0016] To address the aforementioned technical problems, this invention provides a metering device for metering residual fluid in analgesic pumps, thereby resolving shortcomings in existing shopping systems regarding user interaction, personalized recommendations, payment security, and system collaboration. These shortcomings include limited interaction methods, inaccurate recommendations, payment security risks, and poor collaboration among various stages.

[0017] This invention is based on a cloud-based collaborative architecture, integrating multiple cutting-edge technologies such as the Internet of Things, artificial intelligence, blockchain, and quantum security. Through close collaboration between its layers, it achieves comprehensive support and service optimization for the user's shopping process. The system mainly includes a perception layer, an edge layer, a cloud layer, and an application layer, all working collaboratively to provide efficient shopping services.

[0018] Perception layer

[0019] The perception layer collects user voice, gestures, and environmental data through multimodal interaction devices (such as microphone arrays and smart cameras) and environmental sensors (such as temperature, humidity, and light sensors) to provide a foundation for subsequent processing.

[0020] Multimodal Interaction Device Integration: This integrates multiple interaction devices, including but not limited to high-precision microphone arrays, intelligent gesture recognition modules, and advanced environmental sensors (such as temperature, humidity, and motion sensors). These devices work together to achieve real-time perception and data collection of user voice commands, gestures, and the surrounding environment. For example, users can use natural and fluent voice commands to query product information and initiate purchase requests, or use gestures to operate on products and view details in AR displays. Simultaneously, sensor data can be used to analyze the user's shopping environment and behavioral state.

[0021] Real-time data transmission and preprocessing: Data collected by the perception layer is transmitted in real time to the edge computing nodes via efficient and stable wireless communication protocols (such as Wi-Fi 6 and Bluetooth Low Energy). During transmission, preliminary preprocessing, such as data cleaning and format conversion, is performed to ensure data accuracy and consistency, preparing it for subsequent processing and analysis.

[0022] The collected data needs to be preprocessed and analyzed at the edge layer to achieve real-time response and preliminary data processing.

[0023] Edge computing nodes in the edge layer preprocess and analyze the data transmitted from the perception layer, including speech recognition, gesture recognition, and environmental data analysis, to generate real-time status information and interaction commands for users, and ensure data transmission security through quantum encryption technology.

[0024] Edge computing node processing: Edge computing nodes are equipped with high-performance computing chips (such as NVIDIA Jetson AGX Orin) and dedicated processing software, responsible for real-time and efficient processing and analysis of data transmitted from the perception layer. For example, real-time SLAM algorithms (such as ORB-SLAM) are used to perform real-time synchronous localization and mapping of environmental sensor data, constructing an accurate 3D spatial model of the home to support AR displays; deep learning algorithms are used to perform real-time recognition and parsing of voice and gesture data, enabling natural interaction with users.

[0025] Local Data Caching and Security Protection: In addition to data processing, the edge layer also features local data caching. For temporary or infrequently updated data, such as recent user shopping preferences or real-time data collected by environmental sensors, caching can be performed at edge nodes to reduce data transmission latency and bandwidth consumption, thereby improving system response speed. Simultaneously, deploying quantum security gateways and post-quantum cryptography acceleration cards allows for the generation of shared keys through quantum key distribution (such as the BB84 protocol). This, combined with the CRYSTALS-Kyber algorithm, encrypts sensitive data, ensuring security during local transmission and storage and preventing data leakage and attacks.

[0026] The data processed at the edge layer will be uploaded to the cloud layer for further in-depth analysis and processing to achieve more powerful functions.

[0027] The cloud layer comprises a distributed database and a cloud application server. The distributed database stores and manages product information, user data, and transaction records; the cloud application server performs user profiling, personalized recommendations, and transaction services, and uses blockchain technology to authenticate transaction records.

[0028] Distributed Data Storage and Management: The cloud layer employs a distributed database architecture to achieve large-scale data storage, management, and rapid retrieval. Massive amounts of product information, user data (including shopping history, preference tags, etc.), and transaction records are stored in a distributed manner to ensure data reliability and scalability. For example, based on Elasticsearch, it enables fast search and retrieval, supporting product information queries for tens of millions of SKUs, providing users with an efficient shopping search experience.

[0029] Intelligent Recommendation and Decision Engine: Combining data uploaded from the edge layer, the cloud layer uses complex machine learning models (such as the LightGBM model) to perform real-time data analysis, constructing accurate user profiles, and providing personalized product recommendations based on real-time user data (such as current environment, shopping preferences, etc.) and historical behavioral data. Furthermore, blockchain-based smart contract technology runs in the cloud, automatically executing transaction rules and processes to ensure transparency, immutability, and traceability of transactions, thus guaranteeing transaction security.

[0030] Blockchain-based Evidence Preservation and Security: The cloud layer leverages blockchain platforms (such as Ethereum and Hyperledger Fabric 2.4) to establish a secure and reliable evidence preservation system. Each transaction record is packaged into an immutable block on the blockchain, allowing all participants to view and verify the authenticity and integrity of the transaction information in real time. Simultaneously, the decentralized nature of blockchain enhances the data and system's resistance to attacks and reliability, effectively preventing data tampering and single points of failure.

[0031] With the support of the cloud layer, the application layer provides users with an intuitive and convenient interactive interface and personalized services.

[0032] The application layer provides users with a shopping interface and recommendation services through multimodal interaction APIs and recommendation service APIs, receives user commands, and calls cloud layer services to respond to user needs.

[0033] Multimodal Interaction API: The application layer provides a rich variety of multimodal interaction API interfaces, supporting users to interact with the system through various natural methods such as voice and gestures. Users can use voice commands to complete operations such as product search, querying details, and placing orders, and can also use gestures to control product display and switch perspectives. These API interfaces ensure an efficient and smooth interactive experience between the system and the user.

[0034] Recommendation Service API: The Recommendation Service API provides users with personalized product recommendations based on cloud-based intelligent recommendation algorithms. The system can adjust recommendations in real-time based on users' real-time and historical behavioral data, presenting users with products that best meet their needs. For example, when a user uses AR to view a product in a store, the system's Recommendation Service API will immediately recommend related or other potentially interesting products based on the user's current environment and preferences.

[0035] Payment Service API: The Payment Service API is responsible for processing user payment requests. It uses quantum-safe algorithms (such as CRYSTALS-Kyber) to encrypt transaction information, ensuring the confidentiality and integrity of data during the transaction process. Simultaneously, it securely communicates with various financial institutions and payment platforms to complete the payment transaction process and safeguard user payment security.

[0036] Compared with the prior art, the present invention has the following beneficial effects:

[0037] By combining multimodal interaction technology with local edge computing, a real-time, natural, and convenient user interaction experience is achieved, improving the efficiency and accuracy of interaction between users and the system.

[0038] By leveraging cloud-based intelligent recommendation and decision-making engines, combined with rich data collected from the Internet of Things and the transparent evidence storage mechanism of blockchain, we provide users with highly personalized and accurate shopping recommendation services to meet their diverse shopping needs.

[0039] The synergistic application of quantum security technology and blockchain provides end-to-end security protection for users' transaction data, ensuring the security and immutability of data during transmission, storage and processing, and effectively preventing various security risks.

[0040] The system can automatically provide relevant product recommendations and services based on the user's real-time environment and behavior, without requiring much active user intervention, thus achieving a seamless shopping experience and improving user satisfaction and loyalty.

[0041] By leveraging AR display technology and multimodal interaction, an immersive shopping environment is created for users, allowing them to more intuitively experience the features and advantages of products, thus enhancing the fun and appeal of shopping.

[0042] Through real-time data processing and analysis, businesses can gain a more accurate understanding of consumer needs and behaviors, optimize product display, inventory management, and marketing strategies, and improve operational efficiency and economic benefits.

[0043] The intelligent shopping system of this invention has good scalability and versatility, and can be widely applied in many fields such as homes, commercial environments, exhibition centers, medical environments, and elderly communities, providing personalized shopping services for users in different scenarios and expanding the market application space. Attached Figure Description

[0044] Figure 1 This is a diagram showing the overall architecture of the intelligent shopping system of the present invention;

[0045] Figure 2 This is a schematic diagram of the scenario-based multimodal interaction system of the present invention;

[0046] Figure 3 This is a flowchart of the quantum-secure payment system of the present invention;

[0047] Figure 4 This is a schematic diagram illustrating the working principle of the service combination optimization engine of this invention.

[0048] Figure 5 This is a schematic diagram illustrating the application of the present invention in a home environment;

[0049] Figure 6 This is a flowchart of the product recommendation function of the present invention. Detailed Implementation

[0050] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0051] Example 1: Home Shopping

[0052] Case Background

[0053] Ms. Wang is a busy working professional who wants to easily complete her shopping tasks after get off work, especially her needs for home furnishings. She hopes to enjoy a convenient and personalized shopping experience at home through a smart shopping system.

[0054] Technical details

[0055] Environmental perception and modeling

[0056] SLAM technology: The system utilizes OpenCV and ORB-SLAM algorithms to capture and analyze home environment information in real time through cameras and IMU devices within the home. The system can then construct an accurate 3D home map for subsequent product recommendations and interactions.

[0057] Environmental feature extraction: The system analyzes features such as lighting, area, and existing furniture in a home to provide environmental basis for product recommendations.

[0058] Multimodal interaction

[0059] Voice recognition: Ms. Wang can issue voice commands through the smart speaker, such as "Buy a coffee table suitable for the living room." The system utilizes the Google Cloud Speech-to-Text API for voice recognition to ensure accurate understanding of the user's intent.

[0060] AR Display: The system displays a virtual model of the coffee table through AR glasses and adjusts the placement and angle of the model according to the home environment information, so that Ms. Wang can intuitively see the effect of the coffee table in the living room.

[0061] Gesture control: Ms. Wang can use gestures (such as pointing, grabbing, rotating) to select and adjust the display effect of the coffee table.

[0062] Quantum-secure payment

[0063] Key distribution: The system generates a shared key through the BB84 protocol to ensure the security of communication during key transmission.

[0064] Information encryption: The CRYSTALS-Kyber algorithm is used to encrypt transaction information to ensure the confidentiality of sensitive information such as transaction amount and user payment account.

[0065] Blockchain-based evidence storage: Transaction information is recorded on the blockchain to ensure the immutability and traceability of transactions.

[0066] Service Combinations and Delivery

[0067] Service demand analysis: Based on Ms. Wang's shopping decision, the system automatically completes the combination and scheduling of services such as delivery and installation.

[0068] Smart contract verification: Verify the service package through smart contracts to ensure the legality and compliance of the services.

[0069] Contactless delivery: The system automatically deploys drones for delivery and uses smart locks to ensure unmanned signing for the package, guaranteeing safe delivery.

[0070] The safety and convenience of the process.

[0071] User Interaction Process

[0072] Needs expressed: After returning home from get off work, Ms. Wang expressed her shopping needs through a smart speaker: "Buy a coffee table suitable for the living room."

[0073] Product Display: After the system recognizes the command, it displays virtual models of multiple coffee tables through AR glasses and adjusts the display effect according to the home environment information.

[0074] Selection and Confirmation: Ms. Wang selected a coffee table using gestures and confirmed her purchase.

[0075] Payment and Delivery: The system completes transactions via quantum-secure payment and automatically calls upon drones for delivery. Upon delivery, the smart lock automatically unlocks to receive the goods.

[0076] Satisfaction rating: After receiving the product, Ms. Wang used a smart speaker to rate her shopping experience.

[0077] This detailed application scenario description demonstrates that the intelligent shopping system of this invention provides a convenient, safe, and personalized shopping experience for home use. The system, implemented using advanced technology, meets users' needs for efficient shopping and a high-quality life.

[0078] Example 2: A highly detailed implementation plan in the fields of industrial production, customer service, and public security services.

[0079] Project Initiation and Requirements Analysis

[0080] Project team formation: Establish a cross-departmental project team, including technical experts, industry consultants, project managers, etc.

[0081] Needs assessment: Conduct in-depth research at the front lines of industrial production, customer service, and government and legal services to collect specific needs and compile a requirements document. Technical feasibility analysis: Assess the maturity of the required technologies, integration difficulty, and implementation risks.

[0082] System Design and Architecture Planning: System architecture design:

[0083] Industrial production: Adopting an IoT edge computing architecture to achieve real-time monitoring and scheduling of materials.

[0084] Customer service: Build a cloud-based service platform that integrates modules such as natural language processing and knowledge graphs.

[0085] Legal and political services: Blockchain technology is used to ensure data security, combined with artificial intelligence reasoning to assist decision-making.

[0086] Technology Selection: Industrial Production: High-precision sensors, edge computing servers, AR / VR devices, etc. Customer Service: Advanced natural language processing engines, multimodal interaction devices, etc.

[0087] Legal and political services: Utilize mature blockchain platforms and artificial intelligence inference engines.

[0088] Interface design and data specifications: Establish unified data interface specifications to ensure seamless integration between systems.

[0089] Technology implementation and system integration in industrial production:

[0090] IoT device deployment: Install sensors on the production line to enable real-time monitoring of materials.

[0091] Edge computing implementation: Deploy edge servers to quickly process material data and achieve efficient scheduling. AR / VR technology application: Develop AR / VR-assisted operation programs to improve worker assembly efficiency.

[0092] Blockchain Integration: Establish a blockchain platform to record the source of materials and the production process, ensuring traceability. Customer Service Area:

[0093] Natural Language Processing Engine Integration: Integrates with advanced NLP engines to achieve intelligent dialogue and question answering. Knowledge Graph Construction: Organizes industry knowledge, constructs a knowledge graph, and provides accurate information retrieval.

[0094] Sentiment Analysis Module Development: Develop sentiment analysis algorithms to identify customer emotions and provide personalized services.

[0095] Deployment of multimodal interactive devices: Install devices that support multiple interaction methods such as voice, text, and images. Legal and political service sector:

[0096] Blockchain Platform Construction: Establish a dedicated blockchain platform for law enforcement to ensure the security and traceability of case data. AI Reasoning Engine Integration: Integrate with an AI reasoning engine to assist judges in case analysis.

[0097] Online litigation system development: Develop an online litigation platform to provide convenient litigation services.

[0098] Multimodal interaction support: Ensures that the system supports multiple interaction methods to facilitate use by different users.

[0099] Testing and Optimization

[0100] Unit testing: Perform independent testing on each module to ensure that it functions correctly.

[0101] Integration testing: After integrating each module, conduct tests to ensure seamless integration between systems.

[0102] Performance testing: Simulate the actual operating environment to test system performance and ensure that requirements are met.

[0103] Optimization and Adjustment: Based on the test results, optimization and adjustment will be carried out to improve system stability and performance.

[0104] Deployment and Training

[0105] System Deployment: Deploy the system at industrial production, customer service, and law enforcement service sites to ensure normal operation. User Training: Provide system training to operators to ensure they are proficient in its use.

[0106] Operations and maintenance support: Establish an operations and maintenance team to provide 24 / 7 technical support.

[0107] Operation and maintenance

[0108] Routine monitoring: Monitor the system's operating status in real time to ensure stable operation.

[0109] Regular maintenance: Regularly maintain and upgrade the system to improve performance and security. Feedback collection: Collect user feedback to continuously optimize system functions.

[0110] Technical details supplement

[0111] Data Encryption and Security: Advanced encryption technologies are employed to ensure secure data transmission and storage. Disaster Recovery and Backup: A disaster recovery and backup mechanism is established to ensure rapid system recovery in case of unforeseen circumstances. Scalability Design: A modular design approach is adopted to ensure easy system expansion and upgrades. Compliance Considerations: The system ensures compliance with relevant laws and regulations, such as data protection laws.

[0112] Example 3: Implementation Plan for Shopping in a Large Shopping Mall

[0113] This project aims to leverage cloud-based collaborative technology to create an efficient, intelligent, and secure shopping environment for large shopping malls. By integrating advanced technologies such as cloud computing, big data, the Internet of Things, and artificial intelligence, it optimizes the allocation of internal mall resources, enhances the customer shopping experience, and strengthens the mall's operational management capabilities.

[0114] IaaS layer: It uses public or private cloud infrastructure to provide computing, storage, networking and other resources.

[0115] PaaS layer: Builds an application development platform to support rapid development and deployment of mall applications.

[0116] SaaS Layer: Provides software services such as mall management software and customer service applications. Big Data Processing Center

[0117] Data Collection: Collect various types of data within the mall (such as customer behavior, product information, environmental data, etc.) through IoT devices. Data Storage: Employ a distributed storage system to ensure data security and scalability.

[0118] Data analytics: Utilizing big data analytics technology to uncover the value of data and support business decision-making.

[0119] Internet of Things (IoT) sensing network

[0120] Sensor Deployment: Deploy various sensors within the shopping mall to achieve functions such as environmental monitoring and product tracking. Edge Computing: Perform data preprocessing at edge nodes to reduce the burden on the cloud and improve response speed.

[0121] Artificial Intelligence Engine

[0122] Machine learning: Training models for product recommendations, customer behavior prediction, etc.

[0123] Natural Language Processing: Enables functions such as intelligent customer service and voice-guided shopping.

[0124] Computer vision: used in scenarios such as facial recognition and product recognition.

[0125] Security protection system

[0126] Data encryption: Encryption technology is used to protect the security of data transmission and storage.

[0127] Identity authentication: Implement multi-factor authentication to ensure user identity security.

[0128] Network security: Deploy firewalls, intrusion detection systems, etc., to prevent network attacks.

[0129] Implementation Plan

[0130] Cloud-based collaborative platform construction

[0131] Choose a suitable cloud service provider and build a cloud computing platform.

[0132] Deploy a big data processing center to achieve data collection, storage, and analysis.

[0133] Integrating an IoT sensing network enables interconnectivity among devices within the shopping mall. The smart shopping system develops a multimodal interactive interface, supporting various interaction methods such as touch, voice, and gestures.

[0134] Implement product recommendation functionality, providing personalized recommendations based on customer historical data and real-time behavior. Integrate an intelligent shopping guide robot to offer services such as navigation and consultation.

[0135] Deployment of quantum-secure payment system

[0136] The introduction of quantum key distribution technology ensures the security and uncrackability of the payment process.

[0137] It integrates multiple payment methods, such as mobile payment and facial recognition payment, to improve payment convenience.

[0138] Service optimization engine implementation

[0139] Machine learning algorithms are applied to achieve dynamic optimization of service composition.

[0140] Introducing a multi-objective optimization strategy to balance service efficiency, cost, and customer satisfaction. Home environment application integration.

[0141] Deploy a home environment sensor network to collect environmental data. Implement edge computing technology to improve data processing efficiency.

[0142] Develop a home shopping application that seamlessly integrates with the mall's system. System testing and optimization.

[0143] Conduct system functional testing, performance testing, and security testing. Optimize and adjust the system based on the test results.

[0144] Training and Promotion

[0145] Provide system operation training to mall employees.

[0146] Develop a marketing and promotion plan to attract customers to use the new system.

[0147] Technical details cloud computing platform

[0148] By adopting a microservice architecture, the system can be flexibly expanded and efficiently maintained.

[0149] Use container technologies (such as Docker and Kubernetes) for application deployment and management. Big Data Processing Center

[0150] Use big data processing frameworks such as Hadoop or Spark.

[0151] Implement a data lake strategy to store both raw and processed data. (IoT sensing network)

[0152] Sensor data transmission is performed using Low-Power Wide-Area Network (LPWAN) technology. Edge computing nodes are deployed to enable real-time data processing and analysis.

[0153] Artificial Intelligence Engine

[0154] Model training is performed using deep learning frameworks such as TensorFlow or PyTorch. Model compression and optimization techniques are implemented to improve the model's efficiency on edge devices.

[0155] Security protection system

[0156] Data encryption is performed using algorithms such as RSA and AES. Authentication and authorization mechanisms such as OAuth2.0 and JWT are implemented.

[0157] Deploy WAF (Web Application Firewall) and IDS / IPS (Intrusion Detection and Prevention System).

[0158] Implementation Plan

[0159] Preliminary Preparations (Months 1-3)

[0160] Conduct needs analysis, market research, and technology selection. Develop project implementation plans and budgets.

[0161] Platform setup and development (months 4-12)

[0162] Build a cloud computing platform and a big data processing center.

[0163] Develop an intelligent shopping system, a quantum-secure payment system, and a service optimization engine. System integration and testing (months 13-18)

[0164] Integrate the various subsystems to form a complete shopping solution. Conduct system testing and optimization.

[0165] Pilot operation and promotion (months 19-24)

[0166] A pilot program was conducted in select shopping malls to gather feedback. The system was then adjusted and optimized based on this feedback.

[0167] Develop a promotion plan and gradually expand the application scope. Continuously upgrade and maintain (from month 25 onwards).

[0168] Continuously monitor the system's operational status to ensure stability and security. Perform regular system upgrades and feature expansions.

[0169] Provide technical support and maintenance services.

[0170] Budget and resource requirements

[0171] Hardware equipment procurement costs: including servers, sensors, edge computing devices, etc.

[0172] Software development and system integration costs: including development costs for cloud computing platforms, big data processing centers, smart shopping systems, etc.

[0173] Personnel training and operation and maintenance costs: This includes expenses for employee training, system maintenance, and technical support. Total budget: A detailed budget will be prepared based on specific needs.

[0174] Risk Management and Response Measures: Technological Risks

[0175] Countermeasures: Establish a technology risk assessment mechanism and conduct technology verification and testing in advance.

[0176] Market risk

[0177] Countermeasures: Continuously monitor market dynamics and flexibly adjust marketing strategies. Security Risks

[0178] Countermeasures: Strengthen security measures and conduct regular security audits. Operational Risks

[0179] Countermeasures: Establish a sound operation and management system to ensure stable system operation.

[0180] Expected results and benefits: Enhance the shopping experience

[0181] Through intelligent shopping systems and multimodal interaction, we provide more convenient and personalized shopping services.

[0182] Improve operational efficiency

[0183] By optimizing its service portfolio and implementing a quantum-secure payment system, the company aims to reduce operating costs, improve transaction efficiency, and enhance market competitiveness.

[0184] By applying advanced technologies, we can enhance the shopping mall's brand image and market competitiveness. Data value mining.

[0185] By leveraging big data analytics, we can uncover the value of customer behavior data and provide support for shopping mall decision-making.

[0186] in conclusion

[0187] This implementation plan aims to comprehensively enhance the shopping experience and operational efficiency of large shopping malls through cloud-based collaborative technology. Through scientific planning, rational implementation, and effective management, it is expected to achieve the project's intended goals and bring significant economic and social benefits to the mall.

[0188] Example 4: Home Shopping Scenario

[0189] Scene description:

[0190] User Alice uses the smart shopping system of this invention to shop at home via a smart speaker.

[0191] Operating steps:

[0192] Voice recognition challenge: Alice says to the smart speaker, "I want to buy some fruit." The smart speaker uses a deep neural network model for voice recognition, overcoming interference from background noise and regional accents.

[0193] Edge computing processing: The speech recognition results are processed through edge computing nodes within the home. These nodes employ efficient real-time data processing algorithms to ensure low-latency response times.

[0194] Quantum-secure communication: Edge computing nodes send encrypted requests to the cloud layer through a quantum-secure gateway, using quantum key distribution technology to ensure the security and unbreakability of data transmission.

[0195] Intelligent Recommendation Engine: The cloud-based intelligent recommendation engine combines Alice's historical purchase records, real-time inventory data, and machine learning algorithms to provide personalized fruit combination recommendations.

[0196] Order generation and blockchain notarization: After Alice confirms the purchase, the system automatically generates an order and uses blockchain technology to notarize the transaction, ensuring the immutability and traceability of the order information.

[0197] Drone delivery: After receiving an order, the distribution center uses drones for delivery. The drones are equipped with advanced GPS and visual navigation systems, enabling precise positioning and obstacle avoidance during flight.

[0198] Smart lock integration: Upon arrival, the drone, authorized by the smart lock system, places the fruit in a designated secure location. The smart lock integrates biometric and encryption technologies to ensure delivery security.

[0199] Implementation results:

[0200] Alice can complete her shopping without having to go to a store in person, enjoying a convenient, fast, and secure shopping experience through simple voice interaction. At the same time, the system overcomes several technical challenges, including voice recognition, data security, personalized recommendations, and drone delivery.

[0201] Example 5: Online Retail Scenarios

[0202] Scene description:

[0203] Bob, a user, uses the smart shopping system of this invention to purchase electronic products online via his smartphone.

[0204] Operating steps:

[0205] 1. Multimodal Interaction Challenge: Bob initiates a shopping request through a smartphone app that supports multiple interaction methods, including voice, touch, and gestures, providing a flexible user experience.

[0206] 2. Big Data Analytics: The system uses a cloud-based big data analytics platform to analyze Bob's shopping behavior, product reviews, and social media activities to provide accurate product recommendations.

[0207] 3. Real-time inventory management: The system interfaces with retailers' real-time inventory management systems, ensuring the accuracy of product inventory and the rapid processing of orders.

[0208] 4. Intelligent delivery scheduling: The system adopts advanced logistics optimization algorithms, taking into account traffic conditions, delivery costs, and users' expected delivery time, to achieve intelligent delivery scheduling.

[0209] 5. Unmanned delivery vehicles: The distribution center uses unmanned delivery vehicles for delivery. The vehicles are equipped with autonomous driving technology and intelligent sensors, enabling autonomous navigation and obstacle avoidance.

[0210] 6. Secure Payment: Bob chose online payment, and the system uses multi-factor authentication and encrypted payment technology to ensure the security and fraud prevention capabilities of the payment process.

[0211] Implementation results:

[0212] Bob's online shopping experience is seamless, with the entire process—from product recommendations to payment and delivery—being efficient and secure. The system successfully addressed multiple technical challenges, including multimodal interaction, big data analytics, real-time inventory management, intelligent delivery scheduling, and secure payment.

[0213] Example 6: Smart Home Environment Application

[0214] Scene description:

[0215] User Charlie uses the smart shopping system of this invention to purchase home furnishings at home through a smart home system.

[0216] Operating steps:

[0217] 1. Environmental perception and data fusion: The smart home system collects current home environment data through environmental sensors, including temperature, humidity and user behavior patterns, and uses data fusion technology to provide more comprehensive shopping suggestions.

[0218] 2. Edge Intelligent Decision Making: Edge computing nodes analyze the collected data and use machine learning algorithms to predict Charlie's shopping needs, thus realizing edge intelligent decision making.

[0219] 3. Quantum encrypted communication: The system sends requests to the cloud layer through a quantum secure gateway, employing quantum encrypted communication technology to ensure absolute security of data transmission.

[0220] 4. Personalized Recommendations: The cloud-based intelligent recommendation engine combines environmental data and analysis results to provide Charlie with personalized recommendations for home furnishings.

[0221] 5. Unmanned Delivery and Smart Storage: After Charlie confirms the purchase, the system automatically generates an order and arranges for unmanned delivery. Upon delivery, the smart home system's smart storage solution automatically returns the product to its designated location.

[0222] 6. User experience optimization: The entire shopping process is seamlessly integrated into the smart home environment, providing an exceptional user experience.

[0223] Implementation results:

[0224] Charlie enjoyed a seamless shopping experience in his smart home environment. The system provided accurate recommendations based on environmental data, and the unmanned delivery service enhanced shopping convenience. Simultaneously, the system successfully addressed multiple technical challenges, including environmental perception, data fusion, edge intelligent decision-making, quantum-encrypted communication, and user experience optimization.

[0225] Implementation Plan

[0226] 1. Technical Implementation

[0227] 1.1 System Architecture Setup

[0228] 1.1.1 Perception Layer:

[0229] Choose a high-performance multimodal terminal device and integrate the Google Cloud Speech-to-Text API for speech recognition, supporting a recognition accuracy of 98.7%.

[0230] Equipped with MediaPipe for gesture recognition, with a response time of ≤50ms.

[0231] AR displays can be performed using AR glasses (such as Microsoft HoloLens 2) to achieve high-precision spatial positioning of ±2cm.

[0232] Deploy temperature, humidity, and motion sensors, with a data acquisition frequency of 1Hz.

[0233] 1.1.2 Edge Layer:

[0234] Deploy an NVIDIA Jetson AGX Orin node, configured with an ARM Cortex-A78 @ 2.4GHz CPU, an NVIDIA AdaLovelace GPU, and 32GB of LPDDR5 memory.

[0235] Configure a quantum-secure gateway (IDQuantiqueQKDBox) and a post-quantum cryptography accelerator card (supporting the CRYSTALS-Kyber algorithm).

[0236] 1.1.3 Cloud Layer:

[0237] Build a distributed product database based on Elasticsearch to support fast retrieval of tens of millions of SKUs.

[0238] Based on the Ethereum platform and Hyperledger Fabric 2.4, it enables automatic execution of smart contracts and storage of transaction records.

[0239] 1.1.4 Application Layer:

[0240] Develop a multimodal interaction API that supports voice recognition, gesture control, and AR display.

[0241] Develop a recommendation service API that combines user profiles and environmental data, using the LightGBM model for product recommendations. Develop a payment service API that utilizes the BB84 protocol and the CRYSTALS-Kyber algorithm to ensure payment security.

[0242] 1.2 Core Technology Integration: Real-time SLAM

[0243] Image processing is performed using OpenCV, combined with the ORB-SLAM algorithm for real-time synchronous localization and mapping. Accurate 3D models of home or exhibition environments are constructed with an accuracy controlled within ±2cm.

[0244] Personalized recommendations:

[0245] By combining users' historical shopping data, real-time environmental data, and user profiles, the LightGBM model is used for accurate recommendations.

[0246] Employing the Transformer-XL model to achieve cross-session context awareness improves recommendation accuracy. Quantum-secure payments:

[0247] A shared key is generated using the BB84 protocol, and the handshake time is shortened by combining it with the CRT key derivation method.

[0248] The CRYSTALS-Kyber algorithm is used to encrypt transaction information to ensure the security and immutability of transactions.

[0249] 2. System Construction

[0250] 2.1 Procurement of hardware deployment equipment:

[0251] Based on application scenario requirements, procure hardware equipment such as multimodal terminals, environmental sensors, and edge computing nodes. Select products that meet safety standards to ensure the reliability and security of the equipment.

[0252] Network configuration:

[0253] Ensure stable network connectivity, supporting high-speed data transmission and low-latency communication. Deploy firewalls and intrusion detection systems to protect the network from attacks.

[0254] 2.2 Software Deployment and System Integration:

[0255] Integrate software components at each layer to ensure that all parts of the system work together.

[0256] Use microservice architectures (such as Spring Cloud) and service meshes (such as Istio) for management and scaling. Testing and verification:

[0257] Perform unit testing, integration testing, and performance testing to verify the correctness and performance of each functional module. Develop test plans and test cases to ensure the comprehensiveness and effectiveness of the testing.

[0258] 3. Daily Operation

[0259] 3.1 User Management, Registration, and Login:

[0260] Provides user registration and login functionality, supporting multiple authentication methods (such as username / password, OAuth2.0). Implements multi-factor authentication (MFA) to improve account security.

[0261] Access control:

[0262] Control user access to and operations on the system based on user roles and permissions.

[0263] A strategy combining RBAC (role-based access control) and ABAC (attribute-based access control) is used.

[0264] 3.2 Real-time data processing:

[0265] Real-time data processing is performed using edge computing nodes to reduce the load on the cloud.

[0266] Real-time data processing and analysis using stream processing frameworks such as Apache Flink. Data Analysis:

[0267] Regularly analyze user behavior data to optimize recommendation algorithms and system performance.

[0268] Use machine learning models (such as TensorFlow and PyTorch) for deep data analysis.

[0269] 3.3 System Maintenance and Updates:

[0270] Regularly inspect and maintain hardware and software systems to ensure stable system operation.

[0271] Use monitoring tools (such as Prometheus and Grafana) to monitor system performance and health in real time. Feature update:

[0272] Continuously optimize and update system functions based on user feedback and market changes. Develop version control strategies to ensure system maintainability and scalability.

[0273] 4. Security Guarantee 4.1 Encrypted Data Transmission:

[0274] The TLS 1.3 protocol is used to ensure the security of data transmission.

[0275] Authentication is performed using certificates issued by a Certificate Authority (CA). Storage encryption:

[0276] Use the AES-256 encryption algorithm to protect the confidentiality of stored data. Rotate the encryption key regularly to enhance security.

[0277] 4.2 Privacy-Preserving Federated Learning:

[0278] Employing a federated learning framework (such as FATE) ensures the privacy of user data.

[0279] Model training is performed on local devices or edge nodes, sharing only model parameters. Trusted execution environment:

[0280] Deploying Intel SGX chips in edge computing nodes and cloud services ensures the security of sensitive operations. Utilizing TEE technology protects sensitive data and operations.

[0281] 4.3 Security Audit Log Recording:

[0282] Record system operation logs, including user operations, system events, and security events.

[0283] Use ELKStack (Elasticsearch, Logstash, Kibana) for log management and analysis. Incident Response:

[0284] Develop emergency response plans to respond quickly to safety incidents. Conduct regular safety drills to improve emergency response capabilities.

[0285] 5. Legal protection

[0286] 5.1 Data Compliance and Data Protection Regulations:

[0287] Comply with local data protection regulations such as GDPR and CCPA to ensure the security and legal use of user data. Conduct regular compliance reviews to ensure system compliance.

[0288] Privacy Policy:

[0289] Develop a clear privacy policy that informs users how their data is used and how it is protected. Provide a link to the privacy policy during user registration to ensure users are informed and give their consent.

[0290] 5.2 Intellectual Property Patent Applications:

[0291] File a patent application to protect the intellectual property rights of your invention.

[0292] Patent rights will be protected when necessary to safeguard legitimate interests. Contract terms:

[0293] Clearly define intellectual property ownership and usage rights in cooperation agreements with partners and suppliers. Use standard contract templates to ensure the legality and validity of contracts.

[0294] 5.3 Legal Compliance Review:

[0295] Conduct regular legal compliance reviews to ensure that the system's operation complies with relevant laws and regulations.

[0296] Legal compliance requirements should be considered during the system design and implementation phases. Legal consultation:

[0297] Seek professional legal advice when necessary to ensure the legal operation of the system. Maintain communication with legal counsel to stay informed about legal developments and guidance.

[0298] Application effects, advantages, problems and future expansion

[0299] 1. Ease of application:

[0300] Multimodal interaction: Speech recognition is achieved through integration with the Google Cloud Speech-to-Text API, supporting multiple languages ​​and dialects with a recognition accuracy of up to 98.7%. The gesture control module, based on MediaPipe, can recognize more than 20 common gestures with a response time of less than 50 milliseconds. The AR glasses combine Unity3D and OpenXRSDK to achieve high-precision spatial positioning of ±2 cm, providing an immersive shopping experience.

[0301] Real-time performance: Edge computing nodes are equipped with high-performance CPUs and GPUs, enabling them to process user requests in real time, reducing latency and improving response speed. Security:

[0302] Quantum-secure payments: A shared key is generated using the BB84 protocol to ensure the security of key transmission. The CRYSTALS-Kyber algorithm is used to encrypt transaction information, ensuring the confidentiality and integrity of transaction data.

[0303] Blockchain technology: Through the Ethereum platform and Hyperledger Fabric 2.4, smart contracts are used to ensure the immutability and transparency of transaction records.

[0304] Personalization:

[0305] Data-driven: The system collects indoor temperature, humidity, and light data through environmental sensors, combines this data with users' historical shopping records and behavioral data, and uses the LightGBM model to make real-time product recommendations.

[0306] Context awareness: By combining the Transformer-XL model, the system can achieve cross-session context awareness and provide more accurate personalized recommendations.

[0307] Efficiency improvement:

[0308] Edge computing: Deploy NVIDIA Jetson AGX Orin nodes at the edge layer to achieve rapid data processing and security, and reduce data transmission latency.

[0309] Distributed storage: Adopting a distributed database architecture, it supports large-scale data storage and fast querying, improving data processing efficiency.

[0310] 2. Advantageous Technological Innovation:

[0311] Multimodal interaction: Combining voice recognition, gesture control, and AR display, it provides a natural and convenient user interaction experience.

[0312] Quantum-secure communication: ensures the security of data transmission and storage, providing theoretically unbreakable communication guarantees.

[0313] Blockchain technology: Through smart contracts, transaction records are made immutable and traceable, enhancing the transparency and credibility of the system.

[0314] User experience:

[0315] Accessibility design: Provides multiple language support and high-contrast display to ensure the system is user-friendly for visually and hearing impaired users.

[0316] Secure payment: Employs a quantum-secure payment system to ensure the security and immutability of transactions.

[0317] 3. Potential problems and solutions

[0318] 3.1 Technical Complexity

[0319] Problem: The implementation of the system involves multiple advanced technologies, which may require a high level of technical expertise and specialized personnel. Solution:

[0320] Standardized modules: The system is broken down into multiple standardized modules, each focusing on a specific function, which facilitates development and maintenance.

[0321] Technical Training: We offer comprehensive technical training courses to help businesses and users quickly master system operation and maintenance skills. Remote Support: We have established a remote technical support platform to provide real-time technical guidance and troubleshooting services.

[0322] 3.2 Privacy Protection

[0323] Problem: Despite the adoption of privacy protection technologies, protecting user data privacy still faces challenges in the big data environment. Solution:

[0324] Differential privacy: Introducing differential privacy technology during data processing ensures that users' personal information is not leaked even when a single record is added to or removed from the dataset.

[0325] Data anonymization: Sensitive information is anonymized during data storage and transmission to reduce the risk of data leakage. Regular audits: Regular audits of data security and privacy protection are conducted to ensure compliance and promptly identify potential risks.

[0326] 3.3 Cost Input

[0327] Problem: System deployment and maintenance require certain hardware and software investments, which may increase the company's operating costs. Solution:

[0328] Cloud Service Model: Provides a cloud-based service model, reducing hardware investment for enterprises, offering pay-as-you-go pricing, and lowering initial costs. Modular Deployment: Employs a modular design, allowing enterprises to gradually deploy system functions according to actual needs, spreading costs. Cost-Benefit Analysis: Provides detailed cost-benefit analysis reports to help enterprises assess the long-term return on investment of the system.

[0329] 4. Technical training on solutions:

[0330] Professional guidance: We provide technical training and guidance to help businesses lower technical barriers and improve the efficiency of technology implementation. Remote support: We offer remote technical support services to reduce the need for on-site maintenance.

[0331] Legal compliance:

[0332] Regulatory Compliance: Strengthen compliance with data protection regulations to ensure the legal use and protection of user data. Regular Audits: Conduct regular audits of data security and privacy protection to ensure compliance.

[0333] Cost optimization:

[0334] Large-scale deployment: Reduce system deployment and maintenance costs through large-scale deployment and optimized resource allocation. Modular design: Employ a modular design to facilitate system expansion and maintenance.

[0335] 5. Future Expansion

[0336] 5.1 Technological Progress

[0337] Artificial Intelligence and Machine Learning: With the continuous development of AI technology, the system will further integrate more advanced machine learning algorithms to improve the accuracy and real-time performance of personalized recommendations. For example, deep learning models will be used for more complex behavior prediction and sentiment analysis.

[0338] Augmented Reality (AR) and Virtual Reality (VR): The system will explore the integration of AR and VR technologies to provide users with a more immersive shopping experience. Through VR headsets, users can freely browse and select products in a virtual store.

[0339] Edge computing and the Internet of Things (IoT): With the proliferation of IoT devices, the system will integrate with more smart devices, enabling comprehensive intelligence in home and business environments. Edge computing nodes process data from various sensors in real time, providing more precise services.

[0340] 5.2 Application Area Expansion

[0341] Industry and Manufacturing: The system will expand into the industrial and manufacturing sectors, providing supply chain management and inventory optimization services. Through real-time data analysis, it helps businesses improve production efficiency and reduce costs.

[0342] Education and Training: In the field of education and training, the system will be used to provide personalized learning resources and course recommendations to meet the learning needs of different students.

[0343] Public services: The system will be applied to public service sectors, such as smart city management and public facility maintenance, to improve the efficiency of urban management and the quality of life for residents.

[0344] 5.3 Market Demand and Business Model

[0345] Global Markets: As globalization accelerates, the system will expand into international markets, providing multilingual support and localized services to meet the needs of global users.

[0346] Comparison of Examples

[0347] 1. Comparison with traditional smart shopping systems

[0348] Compared with traditional smart shopping systems, the smart shopping system of this invention

[0349] The current interaction methods are mainly voice or unimodal, which lack naturalness and flexibility. By adopting multimodal interaction technology, integrating voice, gestures, and environmental awareness, a more natural and fluid interactive experience can be provided.

[0350] Personalized recommendations are based on a user's historical purchase records, lacking analysis of real-time environment and dynamic needs, resulting in limited accuracy. By leveraging edge computing and artificial intelligence technologies, and combining multi-source data such as real-time environmental data, historical behavioral data, and health information, we can perform in-depth analysis and provide more accurate recommendations.

[0351] Traditional encryption algorithms for data security are vulnerable to security threats from emerging technologies such as quantum computing; insufficient privacy protection measures also leave user data at risk of leakage. By introducing quantum security technology and blockchain encryption mechanisms, we can provide strong security for shopping transactions and user data, while simultaneously applying privacy-preserving computing technology to ensure user privacy.

[0352] The system suffers from poor inter-system collaboration, with data processing concentrated in the cloud, resulting in significant response latency. Adopting an edge computing and cloud-based collaborative architecture enables distributed data processing and collaborative workflow, improving system response speed and operational efficiency.

[0353] 2. Comparison with existing seamless shopping solutions

[0354] Compared with existing contactless shopping solutions, the present invention provides an intelligent shopping system.

[0355] Environmental perception capabilities are limited to a few environmental parameters, resulting in weak analysis and understanding of user behavior. Equipped with a rich array of environmental sensors and advanced data analysis algorithms, this system can comprehensively perceive the user's shopping environment and behavioral state, enabling more accurate personalized recommendations.

[0356] The system's adaptability and scalability are poor across different scenarios, requiring customized development for specific situations. Adopting a modular design and universal interfaces, it possesses excellent scalability and adaptability, enabling rapid deployment and application to various different scenarios.

[0357] User experience consistency is crucial because user experiences vary across different scenarios, making it impossible to provide a uniform shopping service. By using unified cloud services and standardized application-layer interfaces, a consistent, efficient, and convenient shopping experience can be provided to users in different scenarios.

[0358] The data security mechanism is not robust enough, posing a risk of data leakage and tampering. By integrating multiple security technologies, a comprehensive security protection system has been built to ensure the security of user data and the reliability of transactions.

[0359] Application areas

[0360] 1. Retail and Commercial Sector

[0361] Traditional retail stores: Deploy smart shopping systems in various supermarkets, convenience stores, department stores and other traditional retail locations to provide customers with personalized product recommendations, virtual fitting mirrors, AR product displays and other services, thereby enhancing the customer shopping experience and increasing sales.

[0362] E-commerce platforms: Collaborating with major e-commerce platforms to integrate intelligent shopping systems, providing users with smarter and more convenient shopping services. For example, recommending nearby merchants and promotional activities based on the user's real-time location and preferences; and using AR technology to allow users to experience realistic product displays while shopping online.

[0363] Unmanned retail stores: Applied to unmanned retail stores, this technology automates product identification, checkout, and inventory management. Customers can interact with the system via voice or gestures to complete the shopping process without human intervention, improving operational efficiency and reducing labor costs.

[0364] 2. Family Life

[0365] Smart Home Shopping Assistant: Integrating with smart home systems, it becomes a smart shopping assistant for family life. Users can control it via voice or gestures to check household item inventory, purchase daily necessities, and schedule delivery services. The system can also provide personalized product recommendations and consumption suggestions based on the home environment and user habits.

[0366] Senior-Friendly Shopping Service: This service is specifically designed for seniors, taking into account their physical characteristics and operating habits. It offers features such as voice interaction, large font display, and a simple user interface. The system can recommend relevant health products and medicines based on the senior's health data and medication needs, and provides home delivery service.

[0367] 3. Healthcare sector

[0368] Smart Drug Purchase System for Hospital Pharmacies: Deploying a smart shopping system in hospital pharmacies allows patients to query drug information, obtain medication guidance, and complete the purchase process via voice or gestures. The system can also connect to patients' electronic medical records and health files, providing personalized medication advice and recommendations based on the patient's condition and medication history.

[0369] Nutritional Supplement Recommendation System for Rehabilitation Centers: This system provides nutritional supplement recommendations to patients in rehabilitation centers, suggesting suitable supplements based on their rehabilitation needs, physical condition, and dietary preferences. The system can monitor patients' health data in real time, such as blood sugar and blood pressure, and dynamically adjust the recommended treatment plan to help patients recover better.

[0370] 4. Education and Training Sector

[0371] Campus Smart Shopping Platform: This involves establishing a smart shopping platform within schools or educational institutions to provide convenient shopping services for students and faculty. For example, students can purchase school supplies, textbooks, and uniforms through the system; faculty can purchase office supplies and teaching equipment. The system can also provide personalized product recommendations and purchasing suggestions based on the user's role and needs.

[0372] Online education course recommendation system: Based on users' online learning behavior and interests, this system recommends suitable online courses and learning resources. By analyzing data such as users' learning progress, exam scores, and course evaluations, it provides personalized learning paths and course recommendations to improve learning outcomes.

[0373] 5. Industrial and manufacturing sector

[0374] Industrial supply chain management: Applied to the supply chain management of industrial enterprises, it enables intelligent management of raw material procurement, inventory management, and logistics distribution. By monitoring production data and inventory status in real time, the system can automatically predict raw material demand, optimize procurement plans, reduce inventory costs, and improve production efficiency.

[0375] Product Demonstration and Sales: In the demonstration and sales of industrial products, AR technology and intelligent shopping systems are used to provide customers with more intuitive and detailed product displays and introductions. Customers can use gestures to view the product's internal structure, working principles, and usage methods, enhancing their understanding and trust in the product and boosting sales.

[0376] 6. Public service sector

[0377] Smart City Applications: In the construction of smart cities, smart shopping systems can serve as part of public services, providing convenient living services for citizens. For example, by setting up smart shopping terminals in public facilities such as parks, libraries, and subway stations, citizens can use the system to check nearby business information, purchase tickets, and pay fees.

[0378] Community Service Center: A smart shopping system will be deployed in the community service center to provide residents with one-stop shopping and daily necessities services. Residents can use the system to search for information on businesses within the community, book housekeeping services, and purchase daily necessities, improving the convenience and efficiency of community services.

[0379] 7. Tourism and Culture

[0380] Smart Navigation and Shopping in Tourist Attractions: Smart shopping systems are installed in tourist attractions to provide visitors with services such as intelligent navigation, attraction information, and product recommendations. Visitors can interact with the system via voice or gestures to obtain relevant information about the attraction and recommended products, enhancing their travel experience.

[0381] Souvenir sales at cultural venues: Smart shopping terminals are installed in cultural venues such as museums, art galleries, and libraries to provide visitors with souvenir recommendations and sales services. The system can recommend relevant souvenirs based on visitors' interests and cultural background, thereby increasing cultural consumption.

[0382] 8. Logistics and Distribution Sector

[0383] Intelligent warehouse management: This involves applying intelligent shopping systems to logistics warehouses to automate the management and sorting of goods. Through sensors and robotics, the system can monitor inventory and location information in real time, automatically completing inbound, outbound, and sorting operations, thus improving warehousing efficiency and accuracy.

[0384] Delivery route optimization: By combining user order information and geographic location data, the system can plan the optimal delivery route in real time, improving delivery efficiency and reducing delivery costs. Simultaneously, the system can communicate in real time with logistics vehicles and delivery personnel, providing navigation and task allocation functions.

[0385] 1. Summary of System Implementation and Application

[0386] This intelligent shopping system integrates advanced technologies such as multimodal interaction, quantum-secure communication, blockchain, edge computing, and machine learning to provide a convenient, secure, and personalized shopping experience. The system adopts a four-layer architecture, including a perception layer, edge layer, cloud layer, and application layer. These layers work closely together to achieve a seamless shopping experience.

[0387] 1.1 Technical Implementation

[0388] Multimodal interaction: By integrating voice recognition, gesture control, and AR displays, the system provides a natural and convenient user interaction experience. Combined with environmental sensors and user profiles, it enables accurate personalized recommendations.

[0389] Quantum-secure payment: A shared key is generated using the BB84 protocol, and transaction information is encrypted using the CRYSTALS-Kyber algorithm to ensure the security and immutability of the payment process.

[0390] Edge computing: Deploying computing nodes at the edge layer enables rapid data processing and security, reduces data transmission latency, and improves system response speed.

[0391] Blockchain technology: By using a blockchain platform, transaction records are made immutable and traceable, ensuring the transparency and security of transactions.

[0392] Machine learning: Combining user behavior data and real-time environmental data, models such as LightGBM and Transformer-XL are used to provide accurate recommendations and personalized services.

[0393] 1.2 Application Effect

[0394] Home environment: Users can easily complete shopping operations through voice and gestures, enjoy a convenient shopping experience, reduce the number of times they need to go out shopping, and improve life efficiency.

[0395] Business environment: Customers can browse and purchase goods through smart terminals within the mall, reducing waiting time and improving customer satisfaction.

[0396] Showroom: Through AR displays and smart contracts, it provides an immersive and transparent shopping experience, enhancing product presentation and increasing sales conversion rates.

[0397] Medical environment: Providing patients with personalized nutritional supplement recommendations, ensuring the security and privacy of patient data, and improving recovery outcomes and quality of life.

[0398] Senior communities: By using barrier-free design and secure payment technology, they provide a convenient shopping experience, reduce the inconvenience of going out shopping, and improve the quality of life.

[0399] 1.3 Innovative Features

[0400] This system, by combining multimodal interaction, quantum-secure communication, and blockchain technology, demonstrates its comprehensiveness and advanced nature in terms of technological innovation and application prospects. The system not only provides a convenient shopping experience but also ensures data security and privacy, meeting the needs of diverse user groups.

[0401] Appendix Figure 1 :

[0402] This diagram illustrates the overall architecture of an intelligent shopping system, including the cloud layer, edge layer, application layer, and terminal layer. The diagram details the main functions and components of each layer, such as the quantum-secure communication module, multimodal interaction interface, blockchain payment system, and interaction methods with users and the shopping environment. Data flow and inter-layer communication are clearly indicated by arrows.

[0403] Appendix Figure 2 Schematic diagram of a scenario-based multimodal interaction system

[0404] This diagram illustrates the working principle of a scenario-based multimodal interaction system, including various interaction methods such as voice recognition, touchscreen input, and gesture control. The diagram shows how these interaction methods are integrated with environmental sensors and the user interface, and how they exchange data with the cloud and edge computing layers through the central processing unit.

[0405] Appendix Figure 3 Schematic diagram of quantum-safe communication module

[0406] This diagram details the process of a quantum-secure payment system, including steps such as quantum key distribution, encryption of transaction data, decryption verification, and payment confirmation. The diagram illustrates the interactions between users, payment gateways, quantum key servers, and banks, as well as the secure transmission of data between these components.

[0407] Appendix Figure 4 Service Composition Optimization Engine Working Principle Diagram

[0408] This diagram illustrates the working principle of the service composition optimization engine, including data input, preprocessing, optimization algorithm application, and result output. The diagram labels the data collection module, analysis module, optimization algorithm module, and output module, as well as the data flow and process sequence between these modules.

[0409] Appendix Figure 5 : Schematic diagram of home environment application

[0410] This diagram illustrates the application of a smart shopping system in a home environment, showcasing how smart devices such as smart speakers, smart refrigerators, and wearable devices are integrated into the home. The diagram shows the data flow between these devices and the smart shopping system, and how features such as voice commands, inventory management, and personalized recommendations enhance the user experience.

[0411] Appendix Figure 6 Product recommendation function flowchart

[0412] This diagram details the process of a product recommendation function, including steps such as user data collection, user profile construction, application of machine learning algorithms, and personalized recommendation output. The diagram includes components such as user data, a product database, a recommendation engine, and a user interface, as well as the information flow and sequence of steps from data input to the final recommendation.

[0413] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0414] The accompanying drawings of the embodiments disclosed in this invention only involve structures relevant to the embodiments disclosed in this invention. Other structures can be referred to with common designs. Unless otherwise specified, the same embodiment and different embodiments of this invention can be combined with each other.

[0415] Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. Independent claim 1: A cloud-based collaborative intelligent shopping system, characterized in that, include: The perception layer includes a multimodal interaction device and environmental sensors, used to collect user voice, gestures, and environmental data; the multimodal interaction device is connected to an edge computing node, and the environmental sensors are also connected to the edge computing node. The edge layer includes at least one edge computing node for preprocessing and analyzing data transmitted from the perception layer to generate real-time status information and interaction commands for the user; the edge computing node is communicatively connected to the perception layer and the cloud layer. The cloud layer includes a distributed database and a cloud application server. The distributed database is used to store and manage product information, user data, and transaction records. The cloud application server is used to further analyze and process the data uploaded by edge computing nodes, build user profiles, execute personalized recommendations and transaction services, and use blockchain technology to store transaction records. The application layer, including multimodal interaction APIs and recommendation service APIs, is used to provide users with shopping interaction interfaces and recommendation services, receive user commands, and call cloud layer services to respond to user needs.

2. Independent claim 2: The cloud-based collaborative intelligent shopping system according to claim 1, characterized in that, The multimodal interaction device includes a high-precision microphone array, a smart camera, and a gesture recognition module, used to realize voice interaction, gesture interaction, and environmental information collection; the environmental sensors include a temperature sensor, a humidity sensor, and a light sensor.

3. Independent claim 3: The cloud-based collaborative intelligent shopping system according to claim 1, characterized in that, The edge computing node includes a deep learning algorithm module, an image processing module, and a data processing module, which are used for speech recognition, gesture recognition, environmental data analysis, and the generation of real-time status information, respectively, and use quantum encryption technology to encrypt and transmit sensitive data.

4. Independent claim 4: The cloud-based collaborative intelligent shopping system according to claim 1, characterized in that, The cloud application server includes: The user data management module is used to collect, organize, and analyze users' historical shopping data and real-time interaction data; The personalized recommendation module provides users with a personalized list of product recommendations based on deep learning algorithms and user profiles; the personalized recommendation module is connected to a distributed database. The transaction service module is used to process user purchase requests, including generating orders and completing payment settlements; the transaction service module is connected to a distributed database and a blockchain module. The blockchain module uses blockchain technology to store transaction records, ensuring the immutability and traceability of transaction data, and uses the CRYSTALS-Kyber algorithm to encrypt transaction information.

5. Independent claim 5: The cloud-based collaborative intelligent shopping system according to claim 1, characterized in that, The multimodal interaction API of the application layer includes a voice interaction interface and a gesture interaction interface, which are used to receive user commands and transmit the commands to the cloud application server; the recommendation service API is used to recommend suitable products to users based on their historical data and real-time needs, and return the recommendation results to the interactive interface of the application layer for display to the user.

6. Dependent claim 6: The cloud-based collaborative intelligent shopping system according to claim 3, characterized in that, The speech recognition in the deep learning algorithm module uses the Google Cloud Speech-to-Text API and combines it with a custom deep learning model based on convolutional neural networks (CNN) or long short-term memory networks (LSTM) to pre-train the speech, thereby improving the accuracy of speech recognition.

7. Dependent claim 7: The cloud-based collaborative intelligent shopping system according to claim 3, characterized in that, The gesture recognition in the image processing module uses the MediaPipe gesture recognition framework combined with a gesture recognition model based on a convolutional neural network (CNN) to perform gesture recognition and analysis on the image data captured by the camera.

8. Dependent claim 8: The cloud-based collaborative intelligent shopping system according to claim 4, characterized in that, The user profile construction in the personalized recommendation module uses an automatic feature extraction algorithm based on an autoencoder and a time series analysis algorithm based on a recurrent neural network (RNN) to deeply mine and analyze user data.

9. Dependent claim 9: The cloud-based collaborative intelligent shopping system according to claim 4, characterized in that, The data transmission between the cloud application server and the edge computing node uses HTTP or WebSocket communication protocols to ensure low latency and high-efficiency data transmission.

10. Dependent claim 10: The cloud-based collaborative intelligent shopping system according to claim 1, characterized in that, The system also includes third-party devices or platforms that interact with the smart shopping system, such as smart home systems, e-commerce platforms, and logistics and delivery systems, to enable collaborative work and data sharing between devices.

11. Dependent claim 11: The cloud-based collaborative intelligent shopping system according to claim 10, characterized in that, The system provides an open API interface for third-party developers to develop various applications and services, thereby enriching the functionality and content of the smart shopping system.

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