33 results about "Smart products" patented technology

The invention discloses an intelligent product quality safety risk multi-dimensional information fusion evaluation method, which comprises the following steps: calculating raw material production data aggregation degree and deviation degree, carrying out abnormity identification to obtain an abnormity result, calculating a potential hardware risk coefficient, calculating a first influence degree and correcting the potential hardware risk coefficient to obtain a hardware risk coefficient, and carrying out evaluation. According to a matching abnormal result fed back by a user, feature enhancement is carried out to obtain risk features, data quality evaluation and cross enhancement are carried out to obtain a software integration risk coefficient, and a risk association propagation network and an intelligent product quality safety risk evaluation model are constructed; and inputting the multi-dimensional information of the intelligent product to be evaluated into the intelligent product quality safety risk evaluation model to obtain an intelligent product quality safety risk evaluation result. The method not only can improve the comprehensiveness, dynamism and accuracy of intelligent product risk evaluation, but also has important significance for improving the reliability of the intelligent product and the industry risk management and control level.

The invention relates to the technical field of artificial intelligence, and discloses an intelligent product life cycle management system and method based on a large model, a data layer is used for receiving multi-modal heterogeneous data input of different stages of a product full life cycle and is connected with a domain knowledge base; the model layer comprises a basic model and a task model, wherein the basic model is formed by fusing a large language model subjected to efficient parameter fine adjustment with a visual Transform hybrid architecture, and the task model is supported and driven by the basic model to run, and the model layer outputs a result based on the data layer; the data analysis module is used for analyzing heterogeneous data, constructing a knowledge graph for cross-source data intelligent retrieval and reasoning, and performing user demand analysis, semantic intelligent material classification, BOM full-life-cycle management, demand-driven optimization product design, supply chain risk prediction, dynamic process response and quality control and knowledge precipitation; and the application layer outputs a result based on the task model, and carries out real-time collaboration and key information visualization. According to the invention, automatic, intelligent and collaborative management of product life cycles of research, development and manufacturing enterprises is realized.

The invention relates to the technical field of intelligent product recommendation, in particular to an intelligent product recommendation method based on a large model, which comprises the following steps of: firstly, receiving a user dominant demand text and real-time behavior data, analyzing the behavior data through a dynamic window self-adaptive mechanism, identifying a time sequence correction logic chain for adding, comparing clicking and canceling adding, and finally recommending the user dominant demand text to the real-time behavior data. Combining attribute-level focus capture and visual thermodynamic diagram feedback positioning core attributes, quantifying a behavior weight offset effect, generating a composite label fusing explicit and implicit demands, adopting time-space density clustering statistics attributes to compare effective click frequencies, combining an attribute dependency relationship network to rearrange attribute priorities, and obtaining a real-time feature; according to the method, dynamic attribute weight distribution is formed by differentially distributing weights through a weight rebalance tree model, finally, three types of information are integrated through a large model, the weights are calibrated through antagonism verification, a product recommendation list conforming to real preferences of users is generated, and recommendation accuracy and individuation degree are improved.

An information handling system receives a query for a product recommendation, translates the query to a first cue for a large language model, and generates a second cue to direct the large language model to mark a task for searching assistance data in accordance with the query. The system provides the first cue and the second cue to the large language model to generate and mark the task for searching the auxiliary data, executes the task to obtain the auxiliary data, and provide a third prompt to the large language model to generate an aggregate of the assistance data based on the assistance data in response to the third prompt. The system receives the product recommendation from the large language model based on the candidate product included in the summary in response to providing a fourth cue with the candidate product to the large language model.

The utility model relates to the technical field of display screens, and discloses a plastic and metal integrated frame, a backlight module, a display screen and electronic equipment. Wherein a plurality of connecting bridges protruding outwards are arranged on the periphery of the metal frame; the plastic frame is integrally formed on the metal frame in an injection molding mode and fixedly connected with the metal frame through the connecting bridge. According to the plastic and metal integrated frame, the backlight module, the display screen and the electronic equipment, the connecting bridges protruding outwards are arranged on the periphery of the metal frame, the plastic frame is designed to be integrally formed on the metal frame in an injection molding mode, and the plastic frame is fixedly connected with the metal frame through the connecting bridges; therefore, the bonding strength between the plastic frame and the metal frame is greatly improved, the use performance of the backlight module can be effectively improved, the product quality is improved, and the ever-increasing quality requirement of consumers for intelligent products is met.

1. The name of the design product: data collector. 2. The use of the design product: the design product is used for collecting and updating intelligent product data information. 3. The design points of the design product: the overall shape of the product. 4. The picture or photo that best indicates the design points: perspective view 1.

The invention relates to the technical field of product design, in particular to an intelligent product design system based on deep learning, and the system comprises an information analysis module which comprises a collection unit for collecting product design information and an analysis unit which is connected with the collection unit and is used for analyzing the product design information to obtain design element features; the product design module comprises a conversion unit for converting a design target input by a user into a constraint condition; the generation judgment module is used for judging whether the generation accuracy of the product design scheme meets the requirement or not according to the constraint condition satisfaction rate; the sampling judgment module is used for judging whether the sampling temperature of the deep learning model meets the requirement or not according to the verification failure rate of the product design scheme; and the training adjustment module is used for determining the confrontation disturbance intensity in the model training process according to the minimum characteristic disturbance amplitude judged by the boundary condition. The generation accuracy of the product design scheme is improved.

The invention relates to an intelligent product promotion system based on AI, and belongs to the technical field of big data processing and analysis. The system firstly determines the basic weight of each promotion mode according to the proportion of users who purchase promoted products under each promotion mode in historical promotion data, then analyzes the interaction behaviors of the users who purchase the products and the promotion, and determines the reflection weight of each interaction behavior to purchase intentions. And in combination with the reflection weight of each interaction behavior, the specific interaction behavior and the purchase time of the user due to promotion, determining the acceptance speed of the customer for each promotion mode so as to correct the basic weight, and obtaining the optimal relative promotion weight of each promotion mode at present. According to the method, the result dimension and the process dimension are integrated, and the popularization result and the popularization accepting speed are quantitatively considered at the same time, so that the finally obtained relative popularization weight is more accurate in popularization effect characterization of each popularization mode, and the popularization efficiency for the current user platform can be remarkably improved.

The invention relates to the field of intelligent products, discloses an NFC label anti-counterfeiting authentication method applied to an intelligent household appliance, and solves the problems that an existing NFC label anti-counterfeiting authentication scheme is tedious in implementation process and high in development difficulty. According to the method, the non-repeated KEYs are generated at the cloud in batches and written into the PC end test software, the PC end test software packs the read UID of the NFC label and the selected KEYs into common data and writes the common data into the NFC label, in a user use scene, the mobile terminal supporting the NFC function touches the NFC label to read the UID and the packed data, and the user experience is improved. The method comprises the steps of reading a UID, performing preliminary verification based on the read UID and a UID analyzed from packet data, and uploading an analyzed key KEY to a cloud for re-verification after the preliminary verification is passed, so that the key generation and write-in process is simplified without an encryption algorithm, the UID cannot be duplicated, the cloud key management is utilized, and the encryption algorithm is not needed, and the key generation and write-in process is simplified, so that the key generation and write-in process is simplified, and the key generation and write-in process is simplified. Precise identification of the copy paste and the pirate paste of the NFC label is realized, and NFC label anti-counterfeiting authentication with low development difficulty and high anti-counterfeiting reliability is achieved.

An intelligent product catalog system provides for electronic creation, management and viewing of product information using a multimedia display system. A central database repository stores the product information and provides for an unlimited number of product attributes and dynamic reconfiguration of the product information. The central database repository comprises a metadata system, a scheme system and an object model system. A plurality of applications access the central database repository, the applications being automatically adaptive to the dynamic reconfiguration of the product information. A user interface provides display, sorting and filtering of the product information including the unlimited number of product attributes.

1. Name of the product in this design: Wireless charging dock (GSA0023). 2. Purpose of this design: for charging smart products. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D view 1.

The invention discloses an intelligent product recommendation method and device based on a graph thought and electronic equipment, and the method comprises the steps: obtaining a directed weighted graph corresponding to a to-be-recommended target user, the directed weighted graph representing a graph constructed with the user as a starting point, an interactive product as an end point and user features as nodes; based on the weight parameter of each node in the directed weighted graph, the importance parameter of each node is determined, and the weight parameter representation of each node is determined based on the relationship between the starting point and the node and the relationship between the node and the end point in the directed weighted graph; determining target user features based on the importance parameter of each node; and determining a to-be-recommended target interactive product corresponding to the target user based on the target user feature and the product feature of each interactive product. According to the method, the user features are screened based on the directed weighted graph, and the screened user features are used as supplementary features of the interactive product, so that the problem of inaccurate recommendation due to few product features can be solved.

The invention relates to the technical field of intelligent products, discloses an intelligent equipment parameter information writing device and method, and solves the problems that an existing intelligent equipment production test system is single in function, and NFC label data and distribution network information cannot be written at the same station. According to the invention, in a production detection scene of the intelligent equipment carrying the NFC tag, two functions of NFC tag data writing and intelligent equipment distribution network information writing are integrated in the same test station through function extension and system architecture optimization of existing upper computer test software; the method comprises the following steps: establishing serial communication with an NFC data read-write device through upper computer test software, packaging NDEF data based on an intelligent equipment MAC tag, and writing the NDEF data into an NFC tag; meanwhile, in combination with two configuration files in the upper computer test software, public key information and equipment private key information corresponding to the type are extracted respectively and packaged into one-machine one-password distribution network information, and the distribution network information is written into the intelligent equipment through a UDP protocol.

Various embodiments of a system and associated method for a smart handoff integrated platform for handoff of items to customers in the retail space are disclosed herein.

This invention discloses a method for intelligent product retrieval and recommendation based on an industry database. The invention relates to the field of data processing technology. It obtains user-inputted search content through an interactive interface, extracts product keywords, and performs a fuzzy search in an industry database to generate a candidate product set. Further, it extracts the click-through rate, viewing time, and conversion rate of candidate products from search logs, constructs a search matching model to calculate a search matching index, and generates a search product sequence to be displayed to the user. Simultaneously, it extracts priority products from the search product sequence and, based on the priority product's sequence number, extracts recommended products from a product association table to generate a recommended product sequence, which is displayed to the user synchronously with the search product sequence to achieve accurate product recommendations.

1. Name of the product in this design: Intelligent Control Box. 2. Purpose of this design: For controlling and operating intelligent products. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D view 1.

An information handling system receives a query for a product recommendation, converts the query into a first prompt for a large language model, and generates a second prompt to guide the large language model in marking a task for searching auxiliary data according to the query. The system provides the first prompt and the second prompt to the large language model to generate and mark the task for the searching of the auxiliary data, executes the task to obtain the auxiliary data, and provides a third prompt to the large language model to generate a summary of the auxiliary data in response to the third prompt based on the auxiliary data. The system receives the product recommendation from the large language model based on candidate products included in the summary in response to providing a fourth prompt with the candidate products to the large language model.

A system and method are including a computer and a processor and memory. The computer receives a product class representing a product in a supply chain network including one or more supply chain entities and generates one or more new products for the product class using one or more automatically generated templates including a graphical representation of an exemplary product using a first smart product attribute value, the first smart product attribute value defined by a quantifiable measurement of a product attribute. The computer further causes items to be transported among the one or more supply chain entities to restock the inventory of the one or more items of the product class according to the current state of items in the supply chain network and the one or more new products.

1. Name of the product in this design: Controller. 2. Purpose of this design: To control smart wearable devices and smart products with functions such as massage, electric heating, and vibration. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: a 3D model.

The application relates to the technical field of device control, and provides a device management method and system, which comprises the following steps: determining first device state information of a device storage cabinet when a cabinet door is opened, and second device state information when the cabinet door is closed; the device storage cabinet is used for storing devices, the device storage cabinet is connected with a device signal, and is used for acquiring device state information of the devices; and the ownership information of the devices is managed according to the first device state information and the second device state information. According to the device management method, the devices are stored in the device storage cabinet, the state information of the devices is monitored in real time by the device storage cabinet, information interaction is carried out with a cloud end, the cloud end analyzes and determines the ownership information of the devices according to the state information of the devices, the devices can be efficiently managed, and the registration error of the devices is avoided, so that the test on intelligent products is not affected.

1. Name of the product in this design: AI Speaker. 2. Purpose of this design: This design is a device for audio output, which obtains audio output by interacting with the smart product. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D view 1.

The invention provides an industrial scene value-driven intelligent product full-life-cycle service method and system. The system comprises an industrial internet platform system, an evolution path subsystem and a sustainable operation value-added subsystem, the industrial internet platform system is a supporting environment subsystem for supporting the intelligent product full-life-cycle service system; the evolution path subsystem is a system of an evolution path from a product service system to an intelligent product service system and then to an intelligent product full life cycle service system; the sustainable operation value-added subsystem provides value services for each stage in the evolutionary path subsystem. According to the method, characteristics and factors such as an industrial transformation path and industrial value increment are comprehensively considered, an industrial internet platform mechanism and a sustainable operation theory are combined, reference is provided for enterprise manufacturing strategies and manufacturing paths, transformation and upgrading of enterprise manufacturing modes are promoted, system stability, customer stickiness and service efficiency are improved, service operation cost is reduced, and the method is suitable for popularization and application. Therefore, value increment of products and services is realized.

1. Name of the product in this design: Portable Bluetooth Handheld Speaker (HKJTL-Q6). 2. Purpose of this design: A device for audio output, which obtains audio output by interacting with the smart product. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D view 1.

A spherical display sound box relates to the field of intelligent products and comprises a base, a controller, a driver, a sound production module and an arc-shaped lamp panel module, the controller, the driver and the sound production module are all mounted on the base, and the controller is in communication connection with the driver and the sound production module at the same time; the driver is in transmission connection with the arc-shaped lamp panel module, and the driver is used for driving the arc-shaped lamp panel module to rotate relative to the base, so that the image of the arc-shaped lamp panel module is displayed in a spherical shape. According to the structural design of the sound box, the visual angle can be increased, the watching experience is improved, and the interactivity is higher.

The present invention belongs to the field of mobile health technology, and specifically relates to a product optimization method based on user review data, comprising: obtaining review data of wearable smart products, preprocessing the review data to obtain product data information; analyzing the product data information to obtain factors affecting product quality; using a Bayesian causal inference model to extract causal relationship features of the factors affecting product quality to obtain a posterior probability tracking graph; generating a causal relationship graph based on the posterior probability tracking graph, and calculating the causal effect; improving and optimizing the wearable smart product based on the causal effect; the present invention uses a Bayesian causal inference method to analyze the causal relationship between various factors of the product, determines whether the causal relationship is stable from the obtained posterior probability tracking graph, determines factors affecting user experience, and improves the product based on the results obtained by causal inference.

The invention relates to the technical field of intelligent product quality control, and discloses an intelligent product quality safety risk control and optimization method using machine learning, comprising: collecting multi-source data in the full life cycle of intelligent product production, and performing systematic preprocessing to form a structured training data set; training a machine learning model based on the structured training data set, realizing quality safety risk identification and prediction, and outputting risk probability, grade and root; real-time production data is input into the model for dynamic risk assessment, when an assessment result exceeds a threshold value, a particle swarm optimization algorithm is used for generating multiple schemes, risk elimination, cost and efficiency are integrated, an optimal strategy is selected, and production parameters are adjusted; meanwhile, the execution effect is monitored, feedback data is collected, the model weight and the strategy rule base are updated, and incremental training and dynamic iteration are achieved through online learning. The quality safety level and the operation efficiency of the intelligent product production process are improved.

The application relates to an AI-based intelligent product promotion system and belongs to the technical field of big data processing and analysis. The system first determines the basic weight of each promotion mode according to the proportion of users who purchase promoted products under each promotion mode in historical promotion data, then analyzes the interaction behavior of users who purchase products and promotion, determines the reflection weight of each interaction behavior on purchase willingness, combines the reflection weight of each interaction behavior, specific interaction behavior and the time used by users to purchase products due to promotion to determine the acceptance speed of customers to each promotion mode to correct the basic weight, and obtains the optimal relative promotion weight of each promotion mode at present. The application comprehensively considers the result dimension and the process dimension, simultaneously quantitatively considers the promotion result and the accepted speed of promotion, makes the relative promotion weight obtained finally more accurate in representing the promotion effect of each promotion mode, and therefore can significantly improve the promotion efficiency of the current user platform.

We provide the system. [Solution] A means for collecting individual datasets and preprocessing said datasets, A means for training a generative model using preprocessed data and generating individual generative intelligences, A means of providing individually generated generative intelligences on a sales platform and distributing profits based on their sales performance, A system that includes this.