86 results about "Internet appliance" patented technology

The invention discloses a big data-based internet equipment fault prediction method, which comprises the following steps of: acquiring operation data, environment data and historical fault records of internet equipment, and performing data cleaning, normalization processing and feature fusion processing on the operation data, the environment data and the historical fault records to generate a training data set; substituting the training data set into an Internet equipment fault prediction model constructed based on an integrated learning algorithm for learning training; dynamic feature extraction is carried out on real-time data flow of the Internet equipment through a sliding window mechanism, fault prediction model parameters are updated in an incremental learning mode, and a fault risk prediction result about the Internet equipment is output online; and generating a graded early warning signal according to a prediction result, and linking the automatic operation and maintenance system to execute a predefined maintenance strategy. According to the method, through multi-source data fusion and efficient model training, sliding window incremental learning and an automatic operation and maintenance strategy are combined, and the dynamism, accuracy and reliability of Internet equipment fault prediction are achieved.

The invention discloses an Internet of Things equipment fault prediction system based on big data analysis, and relates to the technical field of industrial Internet of Things equipment fault prediction, and the system comprises a multi-field collaborative perception dynamic data capture module which is used for constructing an operation mode-stress state mapping matrix based on Internet equipment historical data and a physical failure knowledge base, monitoring the working condition of the equipment in real time, dynamically identifying and entering a high-risk working condition window through a lightweight time sequence clustering algorithm, and when the high-risk window is identified; by constructing the operation mode-stress state mapping matrix and combining the lightweight time sequence clustering algorithm, the method can dynamically and accurately identify that the equipment enters the high-risk working condition window, can sense the possible risk of the equipment in advance, provides a powerful early-stage guarantee for subsequent fault prediction, and at the same time, improves the efficiency of fault prediction. And the high-dimensional original data set with the space-time alignment tag is output, so that the quality and availability of the data are ensured, and a rich and reliable data basis is provided for subsequent feature extraction and analysis.

The invention discloses an equipment state prediction method and device, equipment and a readable storage medium, and is applied to the technical field of internet equipment management, and the method comprises the steps: determining a feature vector corresponding to each type of equipment data based on a data modal characteristic and business demand coupling principle, and carrying out the alignment of each feature vector, and obtaining an equipment state feature vector; uploading the equipment state feature vector to a server, so that the server updates an equipment state prediction model by utilizing cross-equipment group knowledge on the premise of not sharing equipment data; predicting by utilizing a latest equipment state prediction model based on the equipment state feature vector, and determining an equipment abnormal state; the latest equipment state prediction model is a model for global updating and local incremental updating of the edge node based on the server. According to the method, the information of each mode is deeply associated, global updating and local incremental updating are carried out on the model based on the server, the latest model is used for prediction, and the accuracy of state prediction is remarkably improved.

Systems and techniques are provided for wireless communications. A process can include receiving first configuration information associated with transmission of carrier wave (CW) signals to an ambient Internet of Things (AIoT) device, wherein the first configuration information is indicative of a plurality of candidate frequencies. The process can include determining, based on second configuration information, that the network entity is a valid source for a current CW transmission occasion. The process can include transmitting, to the AIoT device, a first CW signal using a selected frequency of the plurality of candidate frequencies, wherein a transmission power for the first CW signal is based on the second configuration information.

Method, apparatus, and device for communicating with an extended range. The apparatus is a network apparatus communicating with an ambient internet of things device having an energy storage and capability to transmitting data by backscattering a radio transmission. The apparatus detects that the device has failed to transfer data by backscattering and responsively sends to the device a first radio transmission having instructions to decrease a radio reflection coefficient to increase wireless energy harvesting. The device decreases the radio reflection coefficient accordingly. The device detects sufficient wireless charging of its energy storage with the decreased radio reflection coefficient and increases the radio reflection coefficient accordingly.

Methods and apparatus are described for automatically discriminating authentic wireless Internet-of-Things (IoT) devices using a trained machine-learning module. In a training phase, the machine-learning module is trained to identify authentic IoT devices based on data in frame headers of wireless data emitted by the IoT devices. The trained machine-learning module may identify authentic IoT devices without analysing data from the payload of the frames to which the frames headers belong, and thus the privacy of data in the payload of the frame is not compromised and encryption of the payload data does not adversely affect performance of the trained machine-learning module in a subsequent production phase. Each training data sample may consist of header data from a sequence of successive frames of wireless data from authentic wireless IoT devices and, to enhance accuracy, may exclude address data.

The invention provides an intelligent analysis and processing method and system for industrial internet equipment data and a medium, and belongs to the technical field of equipment data analysis and processing.The method comprises the steps that a general data interface is defined to integrate a mainstream industrial communication protocol, and equipment data types are automatically matched based on an equipment template library and are matched with an optimal communication protocol for collection; constructing an industrial equipment knowledge graph and converting the extracted heterogeneous data into uniform features; cleaning and preprocessing the collected data to generate optimal processing parameters; analyzing the optimal processing parameters by using a meta-learning-based rapid adaptive large model, predicting the service life of the equipment, and performing equipment health assessment and equipment energy consumption analysis; and displaying the analysis result of the industrial equipment data by using a visual component. According to the invention, by integrating a general data interface, a data processing algorithm, a deep analysis model and a visual display component, efficient acquisition, accurate preprocessing, deep analysis and visual display of industrial equipment data are realized.

The invention addresses the problem of activator-to-tag interference, or AT interference, when reading signals from ambient Internet-of-Things (IoT) devices, also known as ambient tags. A reader receives a reference signal from an activator and derives therefrom an activator-reader channel response (ACR). The ACR is used in determining a "combiner". Upon receipt of an activation signal from the activator, the tag sends a reply signal to the reader. However, when the reply signal is received at the reader, it suffers direct interference from the activation signal. The reader uses the combiner to isolate the transmitted tag signal from the activation signal interference. In an embodiment the reader is a multi-antenna reader and zero forcing is applied to find a combiner which orthogonalizes the activation and reply signals. In a preferred embodiment the reply signal is received at a later time than the reference signal, but the reader is nevertheless able to estimate the ACR at the time the reply signal is received, using a measured estimated Doppler shift.

The invention discloses a data center demand response method, system and equipment considering electric power-computing power-thermal power cooperation, and relates to the field of data center demand response. The method comprises the following steps: constructing an objective function and a constraint condition of a data center demand response considering electric power-computing power-thermal power collaboration, and forming a data center demand response model together; the target function takes the minimum total electricity price of the internet equipment and the cooling equipment in the scheduling period as a target; solving the demand response model of the data center according to the operation data of the scheduling period, and obtaining an electric power-computing power-heating power collaborative scheduling result of the scheduling period; the electric power-computing power-heating power collaborative scheduling result comprises the optimal load scheduling of each server in each scheduling time period, and the optimal on-off decision and the power demand of each server in each scheduling time period. According to the invention, collaborative optimization of the data center in the aspects of electric power, computing power and thermal power can be realized, the energy utilization efficiency of the data center is improved, and the operation cost is reduced.

Techniques for detecting anomalous behavior of an Internet-of-Things (IoT) device in an IoT network. IoT events of an IoT device are captured and analyzed to identify periodic activities of the IoT device. The periodic activities of the IoT device are tracked over time, and variations in the periodic activities are analyzed to assess potential threats to the IoT network.

An AI-assisted document organization system includes an internet equipment, an identification equipment, a processing unit which is matched and connected to the internet equipment and the identification equipment. The processing unit includes a central processor, an artificial intelligence software and a document organization software. The document organization software includes document organization goals which include automatic document classification and identification, artificial intelligent data extraction, automatic data verification, automatic approval verification, compliance and regulatory compliance, document tracking and control, automatic reporting, and notification. The central processor drives the artificial intelligence software. The processing unit acquires document data through the identification equipment. The artificial intelligence software reads the document data and, based on the document organization goals set by the document organization software, to search relevant information via the internet equipment and intelligently calculate the best organization solution for the obtained document data. The database stores the classified and organized document data.

Certain aspects of the present disclosure provide techniques for utilizing configured grant (CG) for ambient internet of things (IoT) devices. An example method, performed at a wireless device, generally includes receiving, from a network entity, configuration information indicating at least one configured resource for periodic reporting, and transmitting at least one report including device originated (DO) data using the configured resource.

The present invention discloses a multi-scenario adaptation method and system for industrial Internet of Things device interface resources. The method includes: detecting the status of the inserted board in the card slot through the ID bus and obtaining the parameter information of the inserted board. The type of the inserted board in the industrial Internet of Things device and the number of different types of boards in the current scenario are determined based on the devices connected to the industrial Internet of Things device in the current scenario; obtaining the driver program file of the inserted board based on the parameter information of the inserted board and performing driver configuration on the inserted board. The present invention effectively solves the problems of increased costs and wasted hardware resources caused by the mismatch of the hardware port type or quantity of industrial Internet of Things devices in different application scenarios in the prior art.

The utility model discloses an industrial internet large screen structure, and relates to the technical field of industrial internet equipment. The device comprises a bottom plate, the top of the bottom plate is fixedly connected with a supporting column, the top of the supporting column is fixedly connected with a rotating mechanism, the top of the rotating mechanism is fixedly connected with a mounting frame, the rear end of the top of the mounting frame is provided with an adjusting assembly, and one side of the adjusting assembly is fixedly connected with a display screen. The direction of the display screen can be adjusted through the rotating mechanism, after the motor is started, the output end of the motor drives the first gear to rotate, and the first gear is tightly meshed with the fluted disc fixed in the inner cavity of the rotating sleeve, so that the rotating sleeve is driven to stably rotate around the supporting column, and the mounting frame and the display screen are driven to rotate at multiple angles; by means of the design, the large screen can easily meet different watching requirements in a complex industrial environment, and the screen can be rapidly rotated to the optimal display direction in different operation areas of a large production workshop.

A storage product manufactured as a standalone computer component and installed in a computing system to implement an internet application. The storage product includes a network interface, a host interface, computing circuits, and a local storage device having a storage capacity accessible via the network interface. A data generator is connected to the network interface. A local host system is connected to the host interface to control access, made via the network interface. The data generator can send bulk data to the network interface. The computing circuits can generate derived data from the bulk data and store the derived data and / or the bulk data in the local storage device. A central server and / or a user device can connect over internet via to the network interface of the storage product to access the derived data and / or the bulk data.

A method performed by a network node is provided. The method includes transmitting (408), to a first, ambient Internet of Things (loT), device, a first beam; and receiving (410) a first measurement of the first device on the first beam. The method further includes determining (412) whether the first device is trusted based on whether the first measurement is from a dominant beam based on whether at least a second device sent a second measurement by the second device of a same type as the first measurement that is within a specified range of the first measurement. The method further includes, when the first device is trusted, generating (414) a virtual networking stack for the first device hosted in the network node that emulates at least one of a physical device address and an IP address for the first device. Related methods and apparatus are also provided.

Method, apparatus, and device for communicating with an extended range. The apparatus is a network apparatus communicating an ambient internet of things device having an energy storage and capability to transmitting data by backscattering a radio transmission. The apparatus detects that the device has failed to transfer data by the backscattering and responsively sends to the device a first radio transmission having instructions to decrease a radio reflection coefficient to increase wireless energy harvesting. The device decreases the radio reflection coefficient accordingly. The apparatus further sends to the device a second radio transmission having instructions to increase the radio reflection coefficient to decrease wireless energy harvesting. The device increases the radio reflection coefficient accordingly. The apparatus attempts to detect that the device has succeeded to transfer data by the backscattering.

The application is suitable for the technical field of internet equipment, and provides an industrial internet equipment intelligent interconnection control method and system based on edge computing, acquires industrial internet equipment control basic information, and establishes an equipment basic information table through the basic information; collects own operation state parameters through the basic information table and sends the operation state parameters to an edge computing node to comprehensively judge the operation state of the internet equipment; if it is judged that the collaborative control requirement is met, the edge computing node selects a collaborative control strategy according to the judgment result, compares the equipment load with a load threshold value; when an equipment exception is detected, the control state and execution result during the exception period are synchronized to a cloud end management node, the control instruction transmission time delay and the occurrence probability of multi-equipment collaborative control conflict are effectively reduced, and the control real-time performance, stability and reliability of the industrial internet equipment in a complex operation environment are improved.

The invention relates to the technical field of Internet data processing, in particular to an industrial Internet equipment data extraction method and system, and the method comprises the steps: S1, analyzing multi-source equipment data through a full-protocol compatible layer, and outputting a standardized data stream through protocol analysis middleware and a data fusion mechanism; when the system is used, by seamlessly integrating industrial internet equipment with more than three hundreds of protocols, plug-and-play is realized, the cost of docking industrial data islands and systems is reduced, and by standardizing a data output uniform format, format fragmentation, semantic conflicts and time sequence chaos of original data are avoided, and a data circulation barrier between equipment is broken; a weak data mode is introduced through the edge computing terminal, data preprocessing, caching and mode optimization are completed, real-time screening, rapid positioning and target data extraction of high-throughput data are achieved, the rear-end computing pressure and the data integration cost are synchronously reduced, and the flexibility and efficiency of industrial data full-link processing are improved.

Embodiments of the present disclosure relate to method and apparatus for charging ambient internet of things devices. A first communication device may: determine whether to charge by receiving a signal from a second communication device; and in response to determining to charge, charge for a duration based on the received signal.

Systems and methods are for identifying online advertisements to display to a user based on historical user data collected across the user's use of a plurality of Internet devices. One method includes receiving, over a network, a request for an advertisement to display at a first device of the user, the request including a unique identifier stored on the user's first device; accessing, in a database, a demographic or browsing history information generated from the user's use of a second device, the demographic or browsing history information being stored in the database in relation to the unique identifier; and identifying, based on the demographic or browsing history information, an advertisement to display at the user's first device. The demographic or browsing history information is synchronized based on the unique identifier being stored on the user's first device and the user's second device.

Methods, a system, and apparatus for managing the separation and distribution of digital controls wherein the digital content in a network system includes receiving a request from any one of control devices, host server response to control device request (and output devices), host server may either non-discriminatively or discriminatively broadcast to any of the control devices, and control device handling responses throughout home network system. The methods, system, and computer readable medium include user experience optimized application types for (optimally) separating and distributing the associated control and associated status information elements during active sessions from the host server to the control devices and output devices within a network system. Configuring a control session comprises receiving a request to execute an input / output application from a control application executing on a mobile control device Configuring the control session also includes aggregating a plurality of real-world connectable processing nodes into an application session set of processing nodes by allocating at least one function required by the input / output application for execution on each processing node in the set of processing nodes, wherein the set of processing nodes is determined based on processing requirements of the input / output application.

The embodiment of the application relates to the technical field of industrial internet equipment management, and discloses an industrial equipment operation state monitoring system, method, device and storage medium, the system comprises an industrial gateway, a Kafka subsystem, a storage unit and a big data analysis modeling platform, wherein the industrial gateway obtains original operation data of industrial equipment, carries out data cleaning, obtains first operation data, and transmits the first operation data to a first message node of the Kafka subsystem; the first message node transmits the first operation data to the storage unit; the big data analysis modeling platform obtains the first operation data from the first message node to execute a data monitoring task, if the first operation data is abnormal, marks the first operation data to obtain second operation data and transmits the second operation data to a second message node of the Kafka subsystem; and the second message node transmits the second operation data to the storage unit. Through the above mode, the embodiment of the application realizes real-time monitoring of the operation state of the industrial equipment.

This invention discloses an internet asset management method, relating to the fields of device operation and maintenance and asset management. The method includes: acquiring policy information of each internet device and configuring topology nodes according to the policy information of each internet device; wherein, the topology nodes include device nodes that perform address port translation operations and asset nodes that provide external services; configuring topology edges according to the policy information of the device nodes; wherein, the topology edges include translation edges describing address port mapping relationships and attribution edges describing the subordinate relationships between device nodes and asset nodes; and generating an asset link topology through a graph database based on the device nodes, asset nodes, translation edges, and attribution edges. The technical solution of this invention not only realizes automated operation and maintenance of internet assets, improving the security and operational efficiency of internet assets, but also optimizes the network resource management process, ensuring the timeliness of internet asset management.

Embodiments of the present application provide a method and an apparatus for data processing based on Internet of Things, and the method includes that an Internet of Things platform: receives an authorization request message sent by an Internet of Things device, where the Internet of Things device is deployed with encrypted target content, and the authorization request message carries a device identification and an authentication code of the Internet of Things device; performs verification on the Internet of Things device according to the device identification and the authentication code, and generates a first authorization license for the Internet of Things device after the verification of the Internet of Things device is passed; sends the first authorization license to the Internet of Things device to enable the Internet of Things device to adopt the first authorization license to decrypt the encrypted target content and use decrypted target content.

The application discloses a domain name resolution method suitable for mobile target defense, and comprises the following steps: 1) a domain name system continuous updating device random address flow; 2) an identity authentication-oriented key negotiation flow; 3) a network device identity authentication flow; 4) a network device random address obtaining flow of a communication opposite end device; and 5) a network communication flow. The method can realize convenient authentication and security protection of internet devices, and help to improve the security of next-generation internet devices on the basis of guaranteeing the security of the internet.

The invention relates to the technical field of industrial Internet of Things and big data information processing, in particular to an industrial Internet equipment health fault monitoring system and method, which comprises a processing system and an acquisition subsystem, and is characterized in that the acquisition subsystem is arranged at industrial Internet equipment, the processing system is arranged in a remote monitoring room, and the processing system is connected with the processing system. The acquisition subsystem is in communication connection with the processing system; according to the method, the operation of the equipment is judged by detecting the workpiece, when it is judged that the workpiece is machined correctly, the processing system cannot analyze the collected equipment data, and only when it is detected that the workpiece machining does not meet the machining requirement, the processing system can analyze the collected corresponding equipment data; in the detection process, a large amount of collected equipment data does not need to be analyzed in real time, the problems of data redundancy and the like can be avoided, accurate and rapid analysis of the data is achieved, and the problems that a monitoring system is blocked and the analysis speed is affected due to analysis of a large amount of real-time data are solved.

An apparatus and mechanism to manage multi-modal real-time or quasi real-time sessions such as voice, video, instant messaging, or web-conferencing across multiple devices through a simple subscription to a session management service. A user can subscribe to the service from many devices (e.g. mobile device, desk phone, personal computer, internet appliance, internet TV, communication terminal, etc.) and through the service seamlessly move sessions back and forth between subscribed devices. In a preferred embodiment, a user utilizes a “virtual slider” in a simple “two touch” procedure to effectuate the movement of a communication session from one device to another device via the service.

The application relates to the technical field of device access authentication, and particularly discloses an internet device access authentication method for network security, which comprises the following steps: step S1: obtaining the type of a device to be accessed, associating historical access data of the device and historical traffic data of devices of the same type, and establishing a device behavior baseline; step S2: comparing the difference between the current access location and time of the device and a historical distribution map in combination with the geographical location of an enterprise, calculating an access location deviation value and an access time deviation value; based on the historical traffic fluctuation law of similar devices, the current traffic is evaluated for deviation from the expected value, and a traffic deviation value is generated; and step S3: comprehensively calculating a comprehensive risk value from the three deviation values, and matching an authentication strategy according to the risk level; the application balances safety and efficiency by quantifying behavior anomalies, and is suitable for massive device scenarios such as the Internet of Things.

The invention discloses an industrial internet equipment operation state assessment method and system, and particularly relates to the field of operation state risk assessment, and the method comprises the steps: collecting operation state parameters in industrial equipment, marking the operation state parameters as operation state main variables, and recording the source equipment, the measurement interface, the sampling mode and the updating period of each operation state main variable; and for each running state main variable, extracting an external input environment variable which the running state main variable depends on, performing structure registration by taking the external input environment variable as a state perception dependency item, and uniformly identifying each state perception dependency item as an environment reference variable. By constructing a structure binding relationship between a running state main variable and an environment reference variable and forming a state structure binding chain graph, an evaluation system can identify whether a reference structure is wrongly inherited, drifted or replaced, so that the hidden judgment distortion problem caused by staggered layers of a semantic coordinate system is captured; the core defect that a traditional method still generates systematic risks under the condition that numerical values are normal is overcome.