508 results about "Product identification" patented technology

The invention relates to the technical field of block chains, and discloses a supply chain tracing method and system based on a block chain, and the method comprises the steps: carrying out the collection and feature learning of the product identification information and transaction records of a supply chain node, and obtaining a supply chain transaction feature vector; based on the supply chain transaction feature vector, executing intelligent contract verification strategy confirmation and weighted voting verification on a transaction group to obtain a consensus confirmation block; extracting transaction data from the consensus confirmation block, constructing a double-Hash Merkle tree structure and generating supply chain traceability features; and executing a commodity tracing contract, a quality verification contract and a responsibility judgment contract according to the supply chain tracing characteristics, and generating an execution log and a visual tracing report, thereby reducing the number of verification nodes and network communication overhead while ensuring the block verification reliability, improving the consensus efficiency, and improving the objectivity and efficiency of the tracing process.

A computing device for generating on-demand products based upon real-time geolocation data is configured to receive and store at least one product definition associated with a respective product. Each product definition defines an availability of the product and includes a product availability location. The computing device is also configured to receive real-time location data from a user computing device, and periodically query a memory device with the real-time location data. The computing device detects that the user computing device has entered a first location by retrieving, in response to a successful query of the memory device, a first product definition associated with a first product having a product availability location including the first location. The computing device is also configured to generate a product identification message including at least a portion of the first product definition, and transmit the product identification message to the user computing device.

The invention provides a manufacturing abnormality diagnosis method and system based on a production data stream, and relates to the technical field of artificial intelligence, and the method comprises the steps: collecting an initial multi-source heterogeneous data stream of a production site, and implanting virtual data anchor points corresponding to key production equipment, process nodes and quality monitoring links in the initial multi-source heterogeneous data stream; performing spatial point set construction and tetrahedron inclusion detection based on the virtual data anchor points to perform data relevance quantitative evaluation and pruning on the initial multi-source heterogeneous data stream to generate an optimized multi-source heterogeneous data stream; and based on a pre-established unified semantic metadata dictionary, performing semantic analysis and normalization processing on the optimized multi-source heterogeneous data stream, and generating a standardized production event stream with unified semantics and time sequence and product identification. According to the invention, accurate diagnosis and root cause positioning of manufacturing abnormality can be realized.

The invention discloses an automobile production data tracing method, system and device based on a block chain and a medium, and the method comprises the steps: obtaining a product identifier of a production process, original production data and key metadata, storing the original production data to a distributed file system, and generating a unique hash value; packaging the unique hash value and the key metadata to generate a data block, generating block index information according to the unique hash value and the product identifier, and uploading the data block and the block index information to a block chain; obtaining a target hash value and a target data block through indexing on the block chain according to the target product identifier, and determining target metadata according to the target data block; and searching in the distributed file system according to the target hash value to obtain target production data, and generating a target tracing record according to the target production data and the target metadata. The automobile production data tracing efficiency and the accuracy, real-time performance and safety of the automobile production data are improved, and the automobile production data tracing method can be applied to the technical field of automobile production.

The invention discloses a tortoise-shell glue transparency detection method and system based on multispectrum, and the method comprises the steps: S1, obtaining a multispectral image sequence of a tortoise-shell glue sample, carrying out the wave band correction, constructing a multispectral image data cube, and carrying out the spatial registration; s2, generating a spectral angle mapping graph according to the registered multispectral image data cube; s3, extracting a tortoise-shell glue region through spectral angle mapping and a region growing algorithm, and constructing a spectral feature matrix; s4, based on the spectral feature matrix and a cross validation method, obtaining an optimal tortoise-shell glue transparency qualified product identification model, and performing qualification judgment on the transparency of the tortoise-shell glue sample to be detected; and S5, constructing a transparency quality evaluation model, and carrying out quality grade division on the transparency of the tortoise-shell glue. And carrying out quality grading on the transparency of the tortoise-shell glue. According to the method, objective and comprehensive evaluation of the transparency quality of the tortoise-shell glue can be realized by acquiring the image information of the tortoise-shell glue sample in a plurality of spectral bands and combining an intelligent analysis algorithm.

Disclosed are systems and methods for determining whether an unknown product matches a scanned barcode during checkout. The system includes a checkout lane having a flatbed scanning area with scanning devices and a point of sale (POS) terminal that scans a product identifier of an unknown product, identifies a product associated with the scanned product identifier, and transmits, to a computing system, product information. An overhead camera idnentifies, based on detecting an optical signal from the POS terminal, that a scanning event occurred, captures image data of the unknown product, and transmits, to the computing system, the image data. The computing system generates machine learning product identification models for identifying unknown products, identifies candidate product identifications for the unknown product based on applying the models to the image data, and determines, based on the candidate product identifications and the information about the product, whether the unknown product matches the product.

The invention relates to the technical field of intelligent production and food safety traceability, in particular to an agricultural product identification method and system and a storage medium, and the method comprises the steps: collecting holographic images, multispectral images, weight and environment data, and adding a high-precision timestamp to form a global original data packet; after the edge processing module carries out noise reduction, correction and time-space alignment on the data, a pre-trained holographic vision Transform, a special spectrum convolutional network and a full-connection network are adopted to extract modal features respectively, deep fusion is realized by using a hypergraph neural network, and digital twin data and digital fingerprint data are constructed; the multi-modal identification network compares the fused data with standard data, outputs the category, quality evaluation and state judgment of the agricultural products, and the identification result is subjected to digital signature and then is chained to realize tamper-resistant evidence storage; and realizing self-adaptive updating of the global model through federal learning. According to the method, the accuracy, robustness and safety of agricultural product identification are remarkably improved, and the requirements of modern agriculture for food safety and traceability tracking are met.

The invention provides a printer control method, electronic equipment and a printer control system. The printer control method can be applied to systems of mobile terminals and printers such as mobile phones and tablet personal computers. And the terminal equipment can obtain the product identifier of the printer in the process of finding the printer. On the basis of the product identifier, the terminal equipment can determine the protocol type of the printer so as to obtain a protocol packet matched with the protocol type of the printer, configuration information of the current local area network is sent to the printer through the protocol packet, and the printer is controlled to access the network. And then, the terminal equipment can control the printer to execute a printing task by printing a standard mopria protocol packet or a protocol packet provided by a printer manufacturer. Wherein when the mopria protocol packet is not provided by the printer manufacturer, the terminal equipment can control the printer to execute the printing task through the mopria protocol packet.

The invention relates to the technical field of Internet of Things, and discloses an FPC production information tracing method and system based on a product identification code, and the method comprises the steps: determining a tracing demand of an FPC product, defining a coding rule of the FPC product, coding the FPC product through the coding rule, and obtaining an FPC product code; a production detection device of the FPC product is defined, a tracing integrity coefficient of the production detection device to the FPC product is calculated, and a tracing block chain network of the production detection device is constructed; associating the production flow data with the FPC product codes to obtain a flow data-code set, and establishing a product tracing library of the FPC products; obtaining tracing information of a target FPC product corresponding to the tracing instruction, and analyzing a tracing abnormal state of the target FPC product by using a trained tracing abnormal analysis model; and positioning an abnormal node of the target FPC product, analyzing a production optimization parameter of the abnormal node, and executing information tracing optimization of the FPC product based on the production optimization parameter. According to the invention, the tracing effect of the FPC production information can be improved.

The invention is suitable for the field of data processing, and discloses a visual guidance method and device for a storage location, terminal equipment and a storage medium. The visual guidance method for the storage location comprises the following steps: when an access instruction is detected, positioning a target storage location according to a product identification code carried by the access instruction; according to the target storage location, unique indicator light control parameters are generated, and the indicator light control parameters comprise color parameters, brightness parameters and / or flicker frequency; according to the indicator light control parameters, control operation of the LED lamp is executed, and visual guidance is provided for the target position where the target storage location is located. By generating a unique indicator lamp control parameter (including a color parameter, a brightness parameter and / or a flicker frequency) for each access instruction, each operator can clearly identify an LED lamp that guides himself / herself. The detection of the access instruction, the positioning of the target storage location and the generation of the indicator light control parameters make the storage process more efficient.

In accordance with at least one aspect of this disclosure, a product identification and tracking interface system includes an interface unit. The interface unit includes an input / output configured and adapted to be coupled to at least one of a tracking system or an identification system, a memory configured to store instructions, and a processor disposed in communication with said memory. The processor upon execution of the instructions is configured to receive a trigger command from a tracking system, send a read command to an identification system, receive a respective identifier from the identification system, package the respective identifier into a packaged identifier in a format readable by the tracking system, and send the packaged identifier to the tracking system.

An intelligent system for interactive processes and experiences in the store, consisting of: a network of IoT sensors, including RFID readers, computer vision cameras, LiDAR sensors and environmental sensors, configured to capture real-time data on customer movements, product interactions and store conditions; an AI-powered analytics engine configured to process real-time and historical sensor data using machine learning models, customer behavior analysis, and forecasting techniques to generate dynamic insights into customer preferences, purchasing patterns, and inventory optimization; a real-time advertising module that is operationally connected to the AI-supported analysis engine, whereby the module dynamically generates and delivers personalized advertising content via digital signage, mobile applications, interactive kiosks or AI-supported smart carts based on individual customer profiles, customer traffic analyses and product demand trends; a subsystem for inventory management that includes RFID-based tracking, computerized shelf monitoring and predictive analytics, and is configured to automate inventory level detection, trigger replenishment alerts and optimize product placement in the store; an AI-driven workforce management module configured to dynamically allocate store staff based on real-time customer density, service demand, and predicted workload distribution, with staff assignments adaptively updated using AI-driven planning techniques; an interactive checkout subsystem that includes RFID-based automatic product identification, mobile payment integration, and AI-powered fraud detection; a cloud-integrated data processing server that communicates with the IoT sensor network and the AI-powered analytics engine, with the server performing distributed computing tasks to refine machine learning models, store historical data, and synchronize operational parameters across multiple retail locations; and a user interface system consisting of mobile applications, AR-enabled shopping assistants and voice-interactive kiosks, configured to provide customers with guided navigation, product recommendations and virtual try-on features based on real-time store interactions and AI-driven engagement models.

The invention discloses a system burning method of embedded equipment and electronic equipment, in a recovery mode, to-be-burnt equipment can receive an external instruction to carry out firmware updating, target specification types of multiple to-be-burnt equipment are determined according to a product identification code, and the to-be-burnt equipment is stored in the product identification code. And obtaining the flash script, the root file system and a differentiated configuration file corresponding to the target specification type. As the multiple to-be-burnt devices in the current batch have the same hardware specification, the target specification types of the multiple to-be-burnt devices are determined through the read product identification codes, so that the differentiated configuration files corresponding to the target specification types are obtained. Since the flash script and the root file system both support devices of various specifications and types, embedded devices of different specifications and types can be processed, and only specific differentiated configuration files need to be provided for the embedded devices of different specifications, so that the number of repeated mirror images is greatly reduced, and the resource reuse rate between embedded device modules is improved.

The invention discloses a self-service cashier method and system based on multi-modal interaction and a storage medium, and belongs to the technical field of data processing, and the method comprises the steps: shooting an initial image of a predetermined region, splitting the initial image into a plurality of commodity images, and recognizing each commodity image to obtain commodity information and first confidence in the commodity image; generating a first commodity list based on the commodity information of which the first confidence is greater than a first threshold value, and performing joint reasoning based on all commodity images and weight information to obtain commodity information of unidentified commodities and second confidence; if the second confidence coefficient is smaller than the first threshold value, the commodity information is verified based on the picking and placing information of the selling shelf; and if the verification is successful, adding the commodity information of the unidentified commodities into the first commodity list to obtain a second commodity list, generating amount information based on the second commodity list, and displaying a collection interface. According to the invention, the to-be-settled commodity information is obtained in combination with multiple methods, so that the commodity identification accuracy is greatly improved.

The invention relates to a dangerous goods identification and detection system based on an intelligent AI algorithm. The system comprises an environment required for deploying YOLOv8s development training; the attention of the EMA is added to a check layer of a YOLOv8s algorithm; a deformable convolution DCNv2 is added to the backbone part of the YOLOv8s, and the deformable convolution DCNv2 is added to the backbone part of the YOLOv8s; an improved pigeon inspired algorithm is introduced to automatically update and adjust the learning rate, and finally the final detection precision of the improved model is improved on the hyper-parameter optimization level; carrying out an experiment on the improved YOLOv8s model, and carrying out comparative analysis on the improved YOLOv8s model and an experiment result obtained by an original YOLOv8s algorithm; an improved YOLOv8s model is deployed on a PyQt5 platform, a visual interface is constructed, and early warning can be achieved while prohibited goods are detected. The system can automatically give an alarm to remind security inspectors while detecting contraband goods, and can assist the security inspectors in daily work, so that the detection precision of the security inspectors on dangerous goods is improved, the false detection rate is reduced, the working efficiency of the security inspectors is improved, and the waiting time of passengers is greatly shortened.

The method comprises the following steps that two-dimensional image data and three-dimensional point cloud data of a to-be-detected product are synchronously collected through a multi-mode sensor, and the multi-mode sensor comprises a high-resolution line scanning camera, a TOF sensor and a tunable annular light source; and matching a multi-brand knowledge base based on the product identifier or the appearance feature, and calling a feature template and a defect judgment standard of a corresponding brand. According to the visual detection method and system capable of self-adapting to the multiple brands, through the transfer learning framework and the multi-brand knowledge base, new brand products can be automatically identified, the pre-training model can be loaded, high initial detection accuracy can be achieved without extra annotation data, and by combining the self-supervised generative adversarial network and the federal learning mechanism, the detection accuracy is improved. And when the defect sample size is small, the relatively high defect detection rate can still be realized, and the false alarm rate is relatively low.

The invention discloses a digital authentication method and system based on industrial production data, and the method comprises the steps: obtaining original industrial production data, generating a unique fingerprint of equipment, binding the unique fingerprint with the original data, and generating an equipment-data binding hash value through employing a national cipher SM3 algorithm; the alliance block chain node dynamically selects a consensus protocol according to the timeliness of the original industrial production data, constructs a Merkle tree structure and stores a root hash value; verifying whether the device-data binding hash value is included by the Merkle tree corresponding to the specific root hash value through a zero-knowledge proof protocol; in the authentication stage, the verified hash value and index information are called, and encryption quality parameters stored under the chain are positioned and decrypted; and generating a three-dimensional credible identifier and a dynamic authentication description text based on the original quality parameter, the hash value, the product identifier information and the block chain transaction information, and performing signature verification through a quantum security electronic signature. According to the invention, the security and reliability of industrial data authentication are improved, and data tampering and counterfeiting are effectively prevented.

The invention relates to the field of product authentication and traceability, and discloses a block chain-based product authentication and traceability method and system, and the method comprises the steps: obtaining the authentication information of a product, carrying out the encryption processing of data through a Hash algorithm, and uploading the processed authentication information to a block chain system; based on the product identification code, calling an intelligent contract deployed in a block chain network, and performing automatic verification on the traceability information uploaded by each participation node in the product circulation link; collecting traceability information corresponding to the product identification code, and uploading the traceability information to a block chain system in sequence; based on the tracing information, dividing information bound with the product identification code into common information and sensitive information, performing encryption processing on the sensitive information according to an authority strategy, and generating a hierarchical access data representation structure; and based on the encrypted data representation structure, generating a visual traceability path diagram of the product in combination with each time node and the product circulation path. The method has the advantage of improving the traceability of the authentication information.

To provide a cooked product identification support device capable of easily identifying cooked products.SOLUTION: A cooked product identification support device of the present disclosure includes an image obtaining unit and a cooked product identification unit. The image obtaining unit obtains a cooked product image in which a cooked product is captured. The cooked product identification unit obtains container feature information of a container in which the cooked product is contained based on the cooked product image, and identifies a type of the cooked product based on the container feature information.SELECTED DRAWING: Figure 1

The invention discloses a category price-based hot competitive product mining method for AI intelligent marketing, and relates to the technical field of marketing, and the method comprises the following steps: building a unified time base line, extracting a continuous sales volume curve of commodities under a target category, calculating the instantaneous slope of sales volume change in the sales volume curve, and calculating the instantaneous slope of the sales volume change; based on the sudden change interval of the instantaneous slope, determining a candidate region of short-period sales volume increase; and constructing a causal factor set in the candidate region, and mapping the channel expansion track and the promotion track to a sales volume curve point by point. According to the method, through the joint constraint of the causal residual and the user behavior density tensor, the sales volume anomaly weight index is generated and written back to the competitive product portrait, false sales volume signals are effectively filtered, and the accuracy of competitive product identification and marketing decision is improved. And meanwhile, short-time Fourier transform is introduced to decompose a sales volume curve, high-frequency abnormity is dynamically weakened by using a spectral domain attenuation coefficient, and a hot sell weight is ensured to truly reflect a long-term and periodic trend, so that the reliability and the analysis precision of a competitive product portrait are enhanced.

The invention discloses an agricultural product distribution automatic identification system and a distribution method thereof, and relates to the technical field of agricultural product identification and distribution, and the system comprises a basic information module which is used for obtaining basic identification features of agricultural products; the information screening module is used for obtaining visual data, spectral data and texture data; the visual identification module is used for performing first identification on the agricultural products according to the difference quantity to obtain a first identification result; the spectrum identification module is used for carrying out second identification on the agricultural product according to the internal quality and the maturity to obtain a second identification result; the texture recognition module is used for performing third recognition on the agricultural products according to the product texture data and the packaging texture data to obtain a third recognition result; and the general management distribution module is used for distributing the agricultural products according to the final identification result. The method has the effects of improving the accuracy in the automatic identification process of the agricultural products and reducing the adverse effects caused by conditions such as time, stains and damage.

The invention discloses a data processing method and device based on user new media APP interaction operation, and the method comprises the steps: responding to an interaction instruction of a user for a comment box of a target object, and inputting the content into the comment box in real time; the target object is a work browsed by the user in the new media APP, and the work is used for describing the target product; identifying whether semantic clusters related to the content of the real-time input comment box exist in semantic clusters corresponding to all themes in a preset dynamic theme library or not; if yes, obtaining a target theme to which a semantic cluster related to the content input into the comment box in real time belongs, intercepting a regional screenshot of the comment box, and extracting all user comment texts; according to a preset quantization parameter and the user comment text, determining a demand label of the user for the target product; and storing a ternary mapping relationship among the product identifier of the target product, the target theme and the demand label. Therefore, by adopting the method and the device, high accuracy of the acquired data can be ensured, and real demands and behavior modes of the user can be comprehensively reflected.

An information processing system according to an embodiment includes: a first receiving means for receiving, from a merchant terminal which is a terminal of a merchant related to the manufacture or transfer of physical goods, product information indicating the attributes of the physical goods and a registration instruction to register the physical goods in a marketplace; a writing means for writing, in a distributed ledger network having a smart contract related to the e-commerce of the physical goods in response to the registration instruction, a) product identification information for individually identifying the physical goods, and b) storage location information indicating the product information or the storage location of the product information; a second receiving means for receiving, from a seller terminal which is a terminal of a seller selling the physical goods, a posting instruction to post information related to the physical goods on a page for product sales; a starting means for starting the smart contract when a predetermined operation is performed on the product identification information of the physical goods on the page, from a buyer terminal which is a terminal of a buyer who intends to purchase the physical goods; and an output means for outputting data for causing information related to the delivery of the physical goods to the buyer to be displayed on the buyer terminal, according to the processing of the smart contract.

The utility model discloses a key hand feeling detection machine, and belongs to the technical field of detection equipment, and the key hand feeling detection machine comprises a rack, a feeding device, a scanning mechanism, a sliding table mechanism, a detection mechanism and a discharging device. The rack is provided with a bottom plate; the feeding device comprises a feeding mechanism and a feeding carrying mechanism, and the feeding carrying mechanism is located above the feeding mechanism and used for carrying products at the tail end of the feeding mechanism. The scanning mechanism is located above the tail end of the feeding mechanism and used for scanning product marks. The sliding table mechanism comprises a sliding table assembly and a clamp assembly, the sliding table assembly is located below the feeding carrying mechanism, and the clamp assembly is connected with the driving end of the sliding table assembly. The discharging device comprises a discharging carrying mechanism and a discharging mechanism, and the discharging carrying mechanism is located above the sliding table assembly and used for carrying products at the tail end of the sliding table assembly. According to the automatic key detection device, automatic detection of product keys is achieved, and the quality of the detection result, the detection efficiency and the product delivery yield are improved.

Systems and methods for facilitating computer-vision-based detection and identification of consumer products comprise a support surface for supporting thereon one or more consumer products to be detected and a plurality of digital cameras each arranged at a different height relative to the support surface and positioned such that a field of view of each of the digital cameras includes the consumer product(s) located on the support surface. Movement of the support surface and / or the digital cameras permits the digital cameras to capture images of the consumer product from different angles of view and up to a full 360 degree of rotation around the at least one consumer product. A computing device uses at least the image data from such images to train a computer vision consumer product identification model to generate a reference image data model to be used for recognition of the at least one consumer product.

The invention discloses a method for identifying freshness of different parts of pork and application. The method comprises the following steps: firstly, constructing a PCA-LDA model for identifying fresh pork and frozen-thawed pork, wherein the PCA-LDA model comprises the following steps: respectively obtaining mass spectrum fingerprint data of the fresh pork and the frozen-thawed pork; and based on a principal component analysis method and a linear discriminant analysis method, constructing a PCA-LDA model by using the mass spectrum fingerprint data of the fresh pork and the mass spectrum fingerprint data of the frozen and thawed pork. Secondly, a pork sample to be detected is identified on the basis of the PCA-LDA model, the result shows that the identification accuracy reaches 99% or above, the identification efficiency is high, the single-time determination identification speed is 6 seconds per sample, fresh pork and frozen-thawed pork at different parts can be rapidly and accurately distinguished, and the method has an extremely good application prospect in pork product identification.

The invention provides a product traceability method and system based on a space-time code, a terminal and a storage medium, and belongs to the technical field of product traceability, and the method comprises the steps: generating a commodity code of a raw material; for each subsequent product processing link, all the commodity codes of the previous upstream link are scanned and analyzed, production subject identification information associated with each commodity code is acquired, and the validity of the production subject identification information is verified; when the production subject identification information is valid, analyzing a space-time code from each commodity code of a previous upstream link as a parent space-time code of a product of a current link; generating a commodity code of the current link product in combination with the space-time code of the current link product and the product identification information; and obtaining a traceability result. According to the invention, the product is identified by using the corresponding space-time code and the product identifier in each production link, and when the commodity code of the final product is scanned, the traceability can be carried out without manual intervention, so that the product traceability efficiency is effectively improved.

The invention discloses a product anti-counterfeiting verification system based on biological information. The product anti-counterfeiting verification system comprises an information acquisition unit, a key generation unit, a quantum coding unit, a block chain storage unit and a verification judgment unit, the information acquisition unit acquires user biological characteristics and product identification information; the key generation unit adopts a topological entropy fusion algorithm to generate a biological key and realize time evolution; the quantum coding unit converts a key into a quantum dot physical identifier which is difficult to copy and has a tamper-proof function; the block chain storage unit ensures safe storage of data through multi-stage salinization processing; the verification judgment unit adopts a similarity function to provide adaptive authenticity judgment; the problems that a traditional anti-counterfeiting technology is easy to copy and lacks dynamic nature and verification potential safety hazards are solved, higher anti-counterfeiting level and adaptability are achieved, all-around anti-counterfeiting guarantee is provided for high-value products, and meanwhile safety and user experience are balanced.

The present invention relates to a TV platform comprising: an output unit including a display unit and a sound output unit; a communication unit that performs a communication connection with an NFT market server and a broadcasting station server; a scene analysis unit that detects a feature point from a broadcast scene of broadcast content received from the broadcasting station server and output through the output unit; and a control unit that receives digital product-related data including identification information of a digital product and an access information of an NFT purchase page of the digital product, generates a database according to the digital product-related data, displays a graphic object indicating that there is a digital product related to the broadcast scene on the basis of a result of matching the feature point detected from the broadcast scene and pieces of digital product identification information included in the database, and performs an access to an NFT purchase page of a specific digital product on the basis of selection of a user regarding the graphic object.

This disclosure relates generally to a method and system for identifying alternative products from competitor products having closer similarity to a retailer product. State-of-the-art methods for alternative product identification based on collaborative filtering often yield inappropriate matches as they do not consider context relevance. Moreover, due to the large size of dataset, such methods require more computation time. While making a comparison of retailer product with the competitor product, a context aware comparison as well as achieving sizable dataset is not yet achieved. The present disclosure addresses these problems through a method of processing metadata of the retailer product and the competitor products to derive feature importance score. The processing results in a filtered data set comprising unique retailer-competitor product pairs. The filtered data is then processed by a machine learning algorithm to identify alternative products based on closest similarity with the retailer product and accordingly ranked.