8911results about "Sensing by electromagnetic radiation" patented technology

Implementations relate to processing an image of a machine-read-able identifier (e.g., a QR code or other 2D barcode) to extract information that is encoded in the machine-readable identifier, and using the extracted information in automatically populating input fields of a fillable form that is being rendered at an application (e.g., a web browser application) of a computing device. Some implementations convert certain information, extracted from a machine-readable identifier, to a converted format and cause the converted format information to be populated in a corresponding input field in lieu of the certain information in its raw format that is extracted from the machine-readable identifier.

The invention discloses a pig breeding intelligent management and control system based on multi-modal data monitoring, and belongs to the technical field of pig breeding management, and the system comprises a data collection and individual recognition module which comprises an RFID ear tag, an inspection robot, an environment sensor and an intelligent feeder, and is used for determining the identity information of a pig individual based on the data collected by the RFID ear tag and the inspection robot, associating the collected multi-modal data of the live pigs in the pig house, and uploading the multi-modal data to edge computing equipment through an MQTT protocol for preprocessing; the feature extraction module extracts physiological and behavior features of live pigs by using a multi-modal deep learning fusion model; the key breeding index analysis module constructs a live pig health index and an environment quality index; the abnormity early warning module adopts a CUSUM control chart to accumulate index deviation and respond to abnormity; the management regulation and control model constructs a Markov decision process by minimizing energy consumption and maximizing health indexes, intelligently adjusts the rotating speed of a fan and a feeding strategy, and realizes precise environmental control and feeding optimization.

The invention provides an assembly line electronic tag management system based on multi-frequency fusion, and relates to the technical field of the Internet of Things, and the system comprises a dual-band module which is used for integrating a high-frequency and ultrahigh-frequency dual-band radio frequency electronic tag on the surface of a target object, and forming a tag dual-mode function; and the signal processing module is used for synchronously acquiring the high-frequency positioning signal and the ultrahigh-frequency identification signal through the multi-band reader-writer array on the basis of a tag bimodal function so as to obtain a preprocessed signal flow with aligned time domains. According to the invention, the efficiency of label identification, data transmission and production management is improved in a complex scene, errors and cost are reduced, and efficiency and quality are improved.

Systems and methods are provided for providing package delivery assistance. The systems and methods detect, by a wearable device, an identifier associated with a package and retrieve package delivery information from a package delivery device using the identifier of the package. The systems and methods display, by the wearable device, a portion of the package delivery information and generate, by the wearable device, visual navigational assistance to guide a courier to a delivery location associated with the package.

A reconfigurable intelligent surface (RIS) includes one or more radio frequency identification (RFID) tags. The one or more RFID tags may perform functions of a controller of the RIS. The one or more RFID tags receive a reference signal from a wireless communications device. The RIS may process the received reference signal and the one or more RFID tags backscatter a response signal to the wireless communications device. The wireless communications device may also perform processing of the backscattered response. Processing includes measuring channels from the wireless communication to the RFID tags. Processing also includes estimating channels from the wireless communication to elements of the RIS. Based on the estimated channels, a beam matrix corresponding to optimized weights of the RIS elements is determined and transmitted to the RIS.

The invention discloses an intelligent traceable hazardous waste management system based on RFID, particularly relates to the technical field of hazardous waste intelligent supervision, and is used for solving the problems of unreliable data acquisition, misreading and misreading and state updating delay caused by signal interference of an existing RFID system in a high-density hazardous waste storage scene. The method comprises the following steps: dynamically dividing warehouse sub-regions, distributing a unique grouping identification code, and combining a directional antenna array partition scanning technology to avoid signal crosstalk; by analyzing the multi-path phase fluctuation rate and the polarization direction offset, a main interference frequency band is dynamically identified by using a covariance decomposition algorithm, and the communication frequency is switched, so that the tag identification rate in a complex electromagnetic environment is improved; scheduling a target sub-region scanning process based on a warehouse-in and warehouse-out instruction, synchronously verifying a label state and an actual position, generating an operation link space-time atlas, actively tracing cross-region time logic contradictions and triggering full-disk scanning; and full-process accurate tracing of the hazardous waste container and complete data management and control in a high-density scene are realized.

The invention relates to the technical field of medical equipment, and discloses a multi-head transfusion intelligent switching control system, which comprises the following modules interconnected with a control bus through a data bus: a multi-source information binding module; a multi-modal sensing data fusion module; an intelligent safety control module; an edge-cloud collaborative decision module; a human factor engineering interaction module; a system full life cycle management module; and an infusion pipeline switching execution mechanism. Through the multi-mode sensing fusion and real-time data processing technology, the whole-course automatic monitoring of the infusion progress, the flow speed and the remaining medicine amount is achieved. The nurse station central billboard and the mobile terminal synchronously display infusion states of all beds, sound-light alarm is triggered in time when abnormal conditions occur, manual patrol video frequency is remarkably reduced, an edge computing node is applied to carry out localized data analysis, and it is ensured that alarm response delay is lower than a clinical safety threshold value. And the problem of low efficiency caused by manual regular patrol traditionally is effectively solved.

The invention provides a tracing processing method and system for a disinfection supply center. The method comprises the following steps: recording acquired operator input data, sterilization equipment attribute information, sterilization equipment operation data and identification data of articles to be sterilized; the traceability system carries out proofreading and data summarization on all the collected data according to timestamps to form a unified data set; the traceability system compares records in the data set with preset sterilization parameter data item by item, and generates corresponding comparison identifiers; the traceability system executes inventory information updating according to the consumable warehousing record and the packaging or issuing data, and records an inventory state; and establishing a data association index for the classified and stored record data according to the timestamps and the sequence of each subdivision process. According to the technical scheme adopted by the embodiment of the invention, a multi-level mathematical model is constructed to realize decision making, calculate the safety inventory in real time and trigger graded early warning, information tracing and sharing of the whole process are realized, a complete autonomous chain of data acquisition, anomaly detection, balance evaluation and parameter optimization is formed, and the safety of the system is improved. And a systematic solution is provided for fine management of medical supplies.

The invention discloses a code reader distorted image correcting and decoding method and system based on machine vision. The method comprises the following steps: acquiring an original image containing a bar code through image acquisition equipment, preprocessing the original image, and extracting feature parameters; image distortion types including radial distortion and perspective distortion are judged according to the extracted features, and distortion correction is carried out by adopting a corresponding correction model; performing quality evaluation on the corrected image, and when a quality threshold value is met, repositioning a bar code area and performing decoding processing; the method can effectively solve the problem of image distortion caused by inherent defects of an optical system and a shooting angle in the bar code reading process, remarkably improves the accuracy and success rate of bar code recognition, and is suitable for bar code recognition application in the fields of industrial automation, logistics management and the like.

The invention discloses a fresh cold chain quality early warning regulation and control method based on the Internet of Things, and belongs to the technical field of detection and analysis of fresh goods, and the method comprises the steps: obtaining the original quality state of goods, and obtaining the initial data of the goods; acquiring temperature, humidity, gas concentration and vibration intensity in the cold chain environment, and generating multi-source environmental parameters; based on the commodity initial data and the multi-source environment parameters, calculating to obtain a corruption activity index; generating a graded early warning signal according to the decay activity index; in response to the graded early warning signal, generating an equipment cooperation instruction; the device cooperation instruction is sent to the cold chain device cluster to execute regulation and control; and acquiring environment feedback parameters after the cold chain equipment cluster executes regulation and control, and updating the corruption activity index based on the environment feedback parameters. According to the method, the fresh food quality degradation risk can be accurately predicted, the targeting and effectiveness of regulation and control are improved, and the goods damage in the cold chain transportation process is remarkably reduced.

The invention belongs to the technical field of logistics conveying, particularly relates to an automatic material conveying system for a door and window processing workshop, and aims to solve the problem of low efficiency caused by insufficient automation, flexibility and intelligence of an existing system. The system comprises a data acquisition and perception module, a digital twinning module, a task management and scheduling module, an intelligent path planning and obstacle avoidance module, a multi-agent cooperative control module, an execution and feedback module, a man-machine interaction and visualization module and the like. And multi-mode collaborative operation, real-time path optimization and dynamic task allocation of the material conveying equipment are realized. The production efficiency, the flexibility and the intelligent level of a door and window processing workshop are remarkably improved.

The system develops a set of complete traceability management system based on the block chain technology according to the quality safety and traceability management requirements in the production, processing and circulation processes of traditional Chinese medicinal materials, guarantees the traceability of the whole process from planting to consumption, improves the transparency of a supply chain, guarantees the rights and interests of consumers, and provides precise data support for supervision departments. The system adopts a front and back end separation architecture, a back end is developed based on SpringBoot and interacts with a Fabric block chain network, tamper-proof and verifiable storage of traceability data is realized, and data storage, quality examination and authority management are automatically executed through an intelligent contract; the front end is developed based on a Vue.js framework, smooth user experience is provided, and consumers can inquire complete traceability information of the traditional Chinese medicinal materials by scanning codes. System functions cover full life cycle traceability, block chain evidence storage, intelligent contract management, authority hierarchical control and data visualization, a supervision mechanism is supported to utilize big data analysis to accurately supervise quality problems, and market supervision efficiency is improved. The system guarantees the data security and transparency through the block chain, optimizes the supply chain management, improves the brand value, and assists the digital and standardized development of the traditional Chinese medicinal material industry.

The invention relates to the technical field of intelligent spectrum tuning, in particular to an intelligent spectrum tuning code scanning auxiliary lighting method, system and device and a medium. The method comprises the following steps: firstly, monitoring environment illumination intensity, color temperature and a light incident angle in real time through an illumination sensor, and meanwhile, detecting a spatial position relationship between a two-dimensional code and equipment by utilizing a distance sensor; the system performs intelligent analysis according to the real-time parameters, determines an optimal light supplementing strategy, and controls the RGBW LED array to output a corresponding spectrum combination; the system continuously monitors the scanning effect after light supplementation, and dynamically adjusts light supplementation parameters by evaluating the definition and contrast of the two-dimensional code until the optimal scanning state is reached; the environment illumination parameters and the spatial position parameters are combined for comprehensive analysis, and the RGBW LED array is adopted to realize adjustable spectrum output, so that the influence of the outdoor complex illumination environment on two-dimensional code scanning can be effectively overcome, and the payment efficiency is remarkably improved.

The invention discloses an external parameter calibration method for a laser radar and camera system, and the method specifically comprises the steps: synchronously collecting the laser radar point cloud and camera image data of a circular plane calibration plate through employing the circular plane calibration plate with a two-dimensional coding pattern printed at the center; segmenting laser radar point cloud subsets belonging to the calibration plate from the laser radar point cloud through a plane extraction algorithm, and calculating centroid coordinates of the point cloud subsets as three-dimensional feature points; detecting angular points of the two-dimensional coding pattern in the camera image, and calculating geometric centers of the angular points as two-dimensional feature points; multiple groups of three-dimensional-two-dimensional feature point corresponding relations are established through multiple times of scanning, and initial external parameters are solved by using a PnP algorithm; and minimizing a re-projection error through a nonlinear optimization algorithm to obtain a final external parameter. The method provided by the invention is suitable for application scenes such as robots, automatic driving or three-dimensional reconstruction, and accurate, efficient and automatic external parameter calibration can be realized.

The invention discloses an RFID electronic tag anti-collision processing system, which relates to the technical field of radio frequency identification and comprises an encryption module, a signal processing module and a real-time processing module. The encryption module is used for realizing label identity verification based on a hash function; the signal processing module adopts a mixed anti-collision mechanism combining a time slot ALOHA protocol and a binary tree search algorithm; the real-time processing module comprises a multi-channel parallel processing unit, and each channel is configured with an independent local frequency. According to the RFID electronic tag anti-collision system, the encryption module, the signal processing module and the real-time processing module are combined, the problem of multi-tag collision of the RFID technology in a high-density and dynamic application scene is effectively solved, the encryption module adopts a hash function and an elliptic curve encryption algorithm, safe and efficient verification of tag identities is achieved, and the security and reliability of the RFID electronic tag are improved. The innovative hybrid anti-collision mechanism of the signal processing module is the combination of a slot ALOHA protocol and a binary tree search algorithm.

The invention discloses a warehouse in-out rechecking management system based on automatic visual scanning, which relates to the technical field of warehouse rechecking management, and comprises a pose acquisition unit, a visual calibration unit, a cargo reading unit, a record management unit, a warehouse-in rechecking unit and a warehouse-out rechecking unit, the pose acquisition unit is used for acquiring a color image and a depth image of a target cargo in a to-be-identified area so as to obtain pose information of the cargo, and the visual calibration unit is used for obtaining a relation matrix of a camera coordinate system and a mechanical arm coordinate system by calculating a rotation matrix and a translation matrix. And space coordinates in an image collected by the camera are converted into a mechanical arm coordinate system. The automatic visual scanning and mechanical arm technology are combined, the intelligent level in the warehouse management process can be greatly improved, the method is more suitable for actual complex warehouse scenes, the cargo warehouse-in and warehouse-out speed can be increased, and the cargo checking accuracy can also be improved.

The invention relates to the technical field of book position retrieval, in particular to an intelligent library book retrieval method based on the Internet of Things, which comprises the following steps of: deploying an RFID (Radio Frequency Identification Device) dense read-write array on a bookshelf layer, arranging a UWB (Ultra Wideband) positioning base station in a library area channel, and embedding a composite label integrated with various sensors into a book cover; a dynamic position discrimination algorithm is introduced to identify the moving state of the book, an extended Kalman filter is utilized to fuse data to establish a motion trail prediction model, a hierarchical position display mechanism is adopted to provide detailed position information, and for temporarily placed books and overtime non-return books, the accuracy of positioning and tracking of the books is improved. And special processing and alarm prompting are respectively carried out, so that the problems of dynamic position updating lagging and inaccurate retrieval result in traditional library book retrieval are effectively solved, and the book retrieval efficiency of readers is remarkably improved.

The invention relates to the technical field of computers, and discloses a chip mounter material tracing management method and system based on a knowledge graph. The method comprises the following steps: constructing a dynamic knowledge graph covering the whole process of a patch; injecting multi-source data in real time to drive dynamic updating of the atlas; when the materials are abnormal, reverse tracing and forward influence double-path reasoning are started; isolation, rework and reset instructions are automatically generated and pushed to a manufacturing execution system; and synchronously updating the atlas state to form an auditable record. The system comprises a dynamic knowledge graph construction module, a real-time data injection module, a bidirectional inference engine module, an automatic processing instruction generation module and a graph state synchronization module. According to the scheme, millisecond-level error positioning and closed-loop processing are realized, and the tracing efficiency and the quality guarantee capability are improved.

The invention relates to the technical field of RFID tag signal optimization, and discloses an RFID tag signal optimization method and system based on deep learning. According to the method, feature extraction is carried out on a backscattering signal, core features of a multipath channel are quantized from a frequency domain and a time domain respectively, numerical representation of a channel state is further obtained, then obtained data information is used as input of a deep learning network, training and forward calculation are carried out, original emission parameters are adjusted, and a multi-path channel is obtained. Therefore, the conversion from blind extensive control to precise control of the transmitting end is realized, so that the problem of mismatching of parameter control and channel state caused by information splitting of the transmitting end and the receiving end in the prior art is solved; according to the signal optimization method for realizing joint adjustment of transmitting and receiving parameters through an end-to-end deep learning architecture, the optimization effect of an RFID tag signal in a complex environment is remarkably improved.

The present invention relates to the technical field of DM code recognition, and provides a DM code positioning and recognition method based on a combination of deep learning and pixel-level detection. The method comprises: firstly, using a coarse positioning model to extract a roughly positioned DM code image from an original image to be detected; then performing extraction on the roughly positioned DM code image respectively by means of a pixel-wise traversal method and a semantic segmentation method to obtain a plurality of candidate corner point combinations; and finally sequentially traversing all the obtained candidate corner point combinations, and performing pixel-wise parsing on the roughly positioned DM code image, so as to complete positioning and recognition. According to the method, by means of a combination of a pixel-wise traversal method and a deep learning method, candidate corner point combinations are respectively extracted, and the two methods are complementary, thereby ensuring the recognition speed while improving the accuracy and success rate of DM code positioning and recognition, and achieving a good recognition effect.

A multi-view (MV) system with multiple MV displays utilizes state information to assign personalized versions of content to display to viewers, thereby providing a coordinated MV display experience. These systems may include a sensing system for detecting viewers and other environmental conditions, and a controller to manage the content assignments for the MV displays. The controller can manage the viewer states, viewer state transitions, and content assignment changes based on changes of those viewers and conditions. The systems can be utilized to simultaneously present coordinated and personalized content to multiple viewers of multiple MV displays.

The invention discloses an intelligent logistics transportation operation system and a method thereof, and relates to the technical field of logistics transportation intelligent management. The whole logistics transportation process is comprehensively optimized through an intelligent means, in the aspect of Internet of Things equipment monitoring, equipment state data are collected in real time, the health condition is evaluated through machine learning, stable data transmission is ensured through a standby channel or local cache, an unmanned vehicle positioning module is combined with a multi-source fusion algorithm, the positioning precision in a complex environment is remarkably improved, and the positioning accuracy is improved. The distribution path is optimized, a multi-band RFID scanning technology and a deep learning algorithm are adopted, goods classification and storage layout are optimized, the storage efficiency is improved, the comprehensive optimization module globally adjusts a transportation route, a distribution task and a storage strategy through a multi-target optimization algorithm, optimal resource configuration is achieved, and the storage efficiency is improved. The problems of unstable dynamic data, large positioning error, low storage efficiency and the like are effectively solved, and the intelligent level and the overall operation efficiency of a logistics system are remarkably improved.

The invention discloses a method for assisting in identifying telecommunication fraud through artificial intelligence, and relates to the technical field of artificial intelligence risk control, and the method comprises the steps: automatically identifying voice or text content through artificial intelligence, and extracting account and identity information; performing online verification on the account and the identity information, and under the condition that the identity cannot be verified, performing behavior monitoring and evaluating whether the user has a transfer intention or not; when the transfer intention exists, performing communication verification between the artificial intelligence and the cloud server, and if the communication fails or the verification is abnormal, terminating the transaction request; if the communication is normal and the user insists in payment, further judging whether the identity of the payee is credible or not, and if not, automatically transferring to the credible payee account to which the payee belongs; synchronously calling a block chain technology to record transaction information, generating a block chain smart contract, and locking funds to a contract account after user confirmation; and releasing the fund to the collection account after the smart contract condition is fulfilled, otherwise, returning the fund to the user account along the original path.

An intelligent parcel locker and methods for forming a package container in the parcel locker are provided. The parcel locker includes multiple front plates connected by multiple actuatable linking pins, a first single vane rotary actuator to dispense linked first side plates, a second single vane rotary actuator to dispense linked second side plates, a third single vane rotary actuator to dispense linked top plates, and a fourth single vane rotary actuator to dispense linked bottom plates. The parcel locker further includes a computing device connected to the multiple rotary actuators and the actuatable linking pins, receives a request to form the package container of a size to hold a package, generates command signals to actuate the rotary actuators to form the package container, and actuates the actuatable linking pins to form a front door of the package container.

A cyber security appliance for detecting the presence of a barcode is provided. The cyber security appliance is configured to: receive input data; obtain one or more images from the received input data; detect that a candidate barcode is present in the one or more images; and output an alert, wherein when the candidate barcode can be decoded, the alert indicates that a valid barcode is present in the received input data, and wherein when the candidate barcode cannot be decoded, the alert indicates a candidate barcode that cannot be decoded is present in the received input data. A corresponding method and non-transitory computer-readable medium are also provided.

A container arranged for containing a precursor material for use with a machine for preparing a beverage and / or foodstuff, the container including a machine-readable code storing preparation information for use with a preparation process performed by said machine, the code comprising a plurality of elements, wherein the elements of the code are arranged circumferentially to be read sequentially when the container is rotated about an axis of rotation relative a code reader, wherein the code is arranged as a plurality of directly adjoining discrete positions and an absence or presence of a primary element at a discrete position encodes the preparation information, wherein boundary elements are arranged at a boundary between two or more adjoining primary elements, and / or at a boundary between two or more adjoining absences of primary elements, and the boundary elements are of different reflective properties to a primary element or an absence of a primary element.

A method for distributing an interactive digital event program to a plurality of user devices comprising: receiving a request for an interactive digital event program from a first user device, the request received in response to scanning a first tag having a machine-readable code with the first user device; determining that the first tag belongs to a first group of tags to which a first version of the interactive digital event program is to be distributed; providing the first user device with the first version of the interactive digital event program, the first version of the interactive digital event program to include at least one dynamic content element that is capable of being updated while an event is in progress; and updating the at least one dynamic content element in the first version of the interactive digital event program in response to a predefined trigger.

The invention provides an RFID label positioning error correction method based on deep learning, and the method comprises the following steps: 1, deploying a multi-mode sensing network in a target region, synchronously collecting radio wave signals and environment auxiliary data of an RFID label, and constructing a space-time multi-dimensional feature data set; step 2, constructing a joint architecture hybrid model composed of a space-time Transform network and a generative adversarial network; according to the method, a space-time multi-dimensional feature data set is constructed by fusing RFID signals and environment auxiliary data through a multi-mode sensing network, adaptive parameters are dynamically generated in combination with a model-independent meta-learning algorithm so as to quickly respond to environment changes, multi-path signal correlation is captured by using a space-time Transform and generative adversarial network combined architecture, feature expression is optimized, and the robustness of the system is improved. The problems that a single signal feature is missing, model parameters cannot dynamically adapt to the environment and the anti-interference robustness of a traditional network is insufficient are effectively solved, and the effectiveness, the real-time performance and the precision of RFID label positioning in the complex environment are remarkably improved.

The invention relates to the technical field of multi-sensor fusion anomaly detection, in particular to a multi-sensor data fusion pig farm anomaly detection system which comprises the steps that data are continuously collected through sensors, a unique space-time anchor point is bound to an RFID tag, and a particle filter algorithm is utilized to predict the motion trail of a pig in different sensor view fields; local model training is carried out at each node according to own data, then local model parameters are uploaded to a central node for fusion through a gradient aggregation strategy, and a global anomaly detection model is generated; dividing a dynamic sensing network in the hog house, and evaluating the confusion degree and the abnormal possibility of data by calculating entropy values of grid units; a behavior fingerprint database is established for each pig, pig behavior data are monitored in real time, and matching degree calculation is carried out on the behavior fingerprint matching degree. And various types of sensors are widely deployed, so that multi-dimensional information of pigs can be comprehensively acquired, and the condition of the pig farm can be comprehensively sensed.

Systems and methods are disclosed herein for a user to use a mobile device with a camera and a terminal device with a camera to manage and use passwords via QR (Quick Response) codes. The terminal device may generate and display a QR code for a user account or data. The user running a password manager app on the mobile device may scan the QR code of the user account or the QR code of the data to generate, store, and retrieve a password, and to display a QR code for the password. The terminal device may scan the QR code of the password to receive and use the password in sign-up, sign-in, data encryption, and data decryption procedures.