206 results about "IMT Advanced" patented technology

The present disclosure describes systems and methods for detecting and preventing data misconfigurations within a security-focused data fabric platform. The system integrates an advanced script migration engine designed to streamline the translation of security rules and scripts across different scripting languages while ensuring alignment with the fabric's unified schema. The method involves receiving inputs from data sources, mapping these inputs to entities of a target schema, monitoring real-time data changes, and simulating impacts on operational dependencies to detect misconfigurations proactively. Leveraging AI-driven mechanisms, including Large Language Models (LLMs), the system dynamically identifies breaking changes in third-party data streams, issues alerts, and provides suggested fixes. The script migration engine further enhances the platform's functionality by automating cross-platform script translations and enabling faster onboarding of security tools. Together, these innovations ensure scalable, accurate, and resilient integration and management of security data across heterogeneous sources, strengthening operational integrity and minimizing security risks.

The invention discloses an equipment real-time monitoring and intelligent scheduling system based on IoT and AI fusion, which comprises a sensing layer, a transmission layer, an edge computing layer, a cloud intelligent center layer and an application interaction layer, and is characterized in that the sensing layer maps heterogeneous data collected by a sensor to a unified space-time coordinate system by adopting a space-time encoder technology; the transmission layer is responsible for transmitting the data collected by the sensing layer to the edge computing layer and the cloud; the edge calculation layer calculates a three-dimensional risk field in real time based on the current operation state data of the equipment; the cloud intelligent center layer constructs digital twinborn bodies, and synchronizes the running state of equipment in real time; the application interaction layer presents equipment operation risk distribution through the risk field thermodynamic diagram; by constructing a multi-layer and multi-module collaborative architecture and fully applying advanced IoT and AI technologies, all-around real-time monitoring, accurate fault prediction and intelligent scheduling decision making of industrial equipment are realized, an intelligent, efficient and reliable operation environment is created for enterprises, and industrial production is promoted to be transformed into intelligentization and digitization.

Cybercriminals are using advanced techniques to access information not only inside a company network but outside of a company network in the ecosystem of company communications with customers, suppliers, partners, and professional advisors. There are many ways cybercriminals gain access to this information, often by compromising email accounts, archives, and document management systems outside of a company's own control and / or outside of their control to manage security of those external accounts. This invention provides an apparatus that will proactively detect when a cybercriminal has accessed or is attempting to access a document attached to an email, a document stored in a repository, a link to an e-signature transaction, a link to a file download (“Files”), and pre-emptively auto-lock the attempted-to-be-eavesdropped on Files and alert the File owner of a high risk information breach in progress, even if that breach is outside their network or information perimeter.

The invention relates to the technical field of server management and cloud computing, in particular to a dynamic load-oriented intelligent identification heterogeneous server resource expansion method. The method aims at optimizing the resource management efficiency, the hardware expansion flexibility and the overall operation stability of the system in a data center and a cloud computing environment by integrating an advanced intelligent identification technology, a real-time data analysis capability and a self-adaptive resource scheduling mechanism. The method is particularly suitable for modern data center scenes requiring high concurrent processing capability, dynamic load adaptability and high reliability, such as a large-scale cloud computing service platform, an enterprise-level distributed storage system and an artificial intelligence computing cluster.

Along with continuous development of technologies such as deep learning and natural language processing, the AI model shows powerful capabilities in the aspects of understanding user intentions, processing complex information, realizing accurate matching and the like. The large star model is a large AI model which is developed by China Telecom and is based on an advanced Transform architecture. The Transformer architecture obtains significant results in the fields of natural language processing, image recognition and the like due to good expandability and strong performance of the Transformer architecture. When the method is applied to a customer service scene, the large star model can deeply understand the appeal of the user. Through natural language processing and semantic understanding technologies, the model can accurately identify and analyze questions of a user and quickly give corresponding answers or suggestions. In addition, the large star model also has strong copywriting generation ability and knowledge question-answering ability, can provide personalized exchange recommendation and shopping preferential information for the user, and further improves the user experience.

The invention discloses an intelligent agricultural big data system, and belongs to the field of agricultural big data, and the system comprises an environment monitoring module, a sensing layer deploys a sensor to collect original data, and a transmission layer is provided with an edge gateway which is connected with the sensor and carries out the transmission of the original data; the equipment layer is used for regulating and controlling irrigation, ventilation and light supplement schemes, and the control layer is used for optimizing MQTT message middleware to control the agricultural Internet of Things system; according to the data management module, a data collection layer obtains original data, a data processing layer processes the original data according to a three-layer data cleaning mechanism, and a data storage layer stores the processed data; according to the system management module, the data application layer constructs an interface covering Web, a mobile terminal and AR equipment, the data display layer generates a soil moisture thermodynamic diagram, a crop growth distribution diagram and an equipment operation state diagram, and intelligent management of agricultural production is ensured. The advanced Internet of Things technology is adopted, and the accuracy and the real-time performance of data acquisition are improved.

Quantum teleportation is essential for many quantum information technologies, including long-distance quantum networks. Using fiber-coupled devices, including state-of-the-art low-noise superconducting nanowire single-photon detectors and off-the-shelf optics, we achieve conditional quantum teleportation of time-bin qubits at the telecommunication wavelength of 1536.5 nm. We measure teleportation fidelities of ≥90% that are consistent with an analytical model of our system, which includes realistic imperfections. To demonstrate the compatibility of our setup with deployed quantum networks, we teleport qubits over 22 km of single-mode fiber while transmitting qubits over an additional 22 km of fiber. Our systems, which are compatible with emerging solid-state quantum devices, provide a realistic foundation for a high-fidelity quantum Internet with practical devices.

Disclosed is a system and method for controlling and optimizing a fleet of semiconductor process systems using advanced digital twin technology. Each process system has a specific digital twin constructed from various subsystem digital twins and calibrated with real-time sensor data. An AI machine leverages these digital twins to create a fleet-level system digital twin. The AI machine continuously trains a policy neural network to autonomously generate and adjust process recipes. Both individual and fleet digital twins, incorporating statistical models, determine if a specific process system falls within the statistical distributions of the fleet, ensuring consistent and optimal performance.

In large domes and stadiums, this system integrates advanced information systems, user interfaces, and real-time data to ensure that visitors are properly guided to their destinations (seats, restaurants, shops, etc.), can understand congestion levels, receive information on products and events tailored to their individual needs, and, in the face of the increasing adoption of unmanned stores, enable efficient inventory management and payment processing. [Solution] A system including a digital display device and means for the user to input a desired destination; a central control unit and means for receiving destination information from the digital display device and calculating the optimal route; means for providing the user with optimal route guidance using a geographic information system including real-time congestion information; and means for communication with the central control unit.

The invention discloses a mobile-fixed charging station cooperative scheduling system and method based on reinforcement learning, and the system employs an advanced machine learning algorithm to predict the load of a fixed charging station, and achieves the dynamic scheduling of a mobile charging station in combination with a reinforcement learning framework. According to the system, the position of the mobile charging station can be adaptively adjusted, so that the mobile charging station efficiently serves a high-demand area, the charging waiting time is remarkably shortened, the resource utilization rate is increased, and the flexibility and the intelligent level of the whole electric vehicle charging infrastructure are enhanced.

This invention provides an adaptive network management system for mesh networks, utilizing advanced wake-up mechanisms that include AI-driven predictive algorithms, adaptive transmission protocols, multi-layer verification processes, and device-specific wake-up profiles. The system is designed to improve network efficiency, reduce latency, and enhance energy management by selectively waking up devices based on real-time conditions, predefined schedules, or a combination of both. This system is applicable to a variety of fields, including military communications, industrial automation, and smart grids, where reliable and efficient network management is critical.

A high-security pet and child confinement gate designed to prevent unauthorized access. The gate incorporates advanced control mechanisms, such as a sensory circuit with a camera, capable of wireless communication with smart devices. The camera can be integrated or removable, providing image data to smart devices. The gate may include a free-spinning mechanism to deter climbing attempts, equipped with sensors and audio devices to produce deterring sounds. Additionally, the gate may include a pressure sensor and an audio device that emits ultrasonic sounds upon detecting crossing attempts. The communication module is adaptive, allowing interaction with cellular networks, Wi-Fi, or Bluetooth, and can receive commands from smart devices to enhance security measures, including sound playback, vibrations, and increased spinning speed.

The invention discloses an agricultural crop growth parameter collecting, monitoring and tracing all-in-one machine which comprises an all-in-one machine body, and a multi-parameter sensor module, a data collector, a wireless communication module and a power management module are arranged outside the all-in-one machine body. The system comprises an advanced multi-parameter sensor module, a high-efficiency data acquisition and processing system, a reliable wireless communication module, a data processing platform, an intelligent decision support system and a block chain data tracing platform, and is characterized in that the advanced multi-parameter sensor module, the high-efficiency data acquisition and processing system, the reliable wireless communication module and the intelligent decision support system are integrated; key growth parameters such as soil humidity, illumination intensity, air temperature and humidity and carbon dioxide concentration can be monitored in real time, and accurate irrigation and fertilization suggestions can be provided through data analysis. Besides, the system adopts a data tracing platform constructed by a block chain technology, the authenticity and non-tampering property of all monitoring data are ensured, and the transparency and credibility of the whole agricultural production process are enhanced, so that the quality and yield of agricultural products are effectively improved.

The invention relates to the technical field of power equipment monitoring, and discloses a power distribution cabinet internal environment monitoring method, which comprises the following steps: selecting a low-power-consumption, high-precision and wireless temperature and humidity sensor, a gas sensor, a partial discharge sensor and a laser dust sensor, installing the sensors on a power distribution cabinet, reasonably deploying a plurality of data acquisition nodes in the power distribution cabinet, the data acquisition nodes acquire data of peripheral sensors and transmit the acquired data to the main data receiving device. According to the method for monitoring the internal environment of the power distribution cabinet, the temperature, the humidity, the gas concentration, the dust content, the electrical parameters and the multi-dimensional parameters of partial discharge in the power distribution cabinet are comprehensively monitored, and advanced sensors and data acquisition and transmission technologies are adopted, so that the limitation of traditional monitoring is avoided, and the accuracy of monitoring data is improved; through real-time data analysis and historical data modeling, operation and maintenance personnel can know abnormal changes of the internal environment of the power distribution cabinet in time and take measures in advance to prevent faults.

The invention discloses a receiving system for fusion of multiple meteorological satellites. The receiving system comprises a data receiving subsystem, a data processing and fusion subsystem, a data storage and management subsystem, a data presentation subsystem, a communication and interface subsystem and a satellite signal monitoring and calibration subsystem, the data receiving subsystem comprises an antenna unit, a satellite signal tracking module, a satellite signal demodulation module and a satellite signal decoding module. By integrating a plurality of advanced subsystems, efficient receiving, fusion processing, storage management, presentation display and communication sharing of the multi-source meteorological satellite data are realized, and the requirements of simultaneous receiving and efficient processing of the multi-source heterogeneous meteorological satellite data are met; the problems of poor compatibility and limited fusion processing capability in the prior art are effectively solved, more powerful and comprehensive technical support is provided for development of meteorological services, and the method has remarkable innovativeness and practical value.

According to the large-scale MIMO channel estimation method fusing the double attention mechanism and the TCN-BiLSTM network, the TCN and the BiLSTM network are combined, and the double attention mechanism is introduced to further enhance the feature extraction and focusing capability of the model. Compared with other advanced deep learning models, the method has the advantages that prediction errors can be greatly reduced in various channel environments; the method shows excellent performance and stability in a non-line-of-sight scene with a multipath effect and serious interference; by providing more accurate CSI, according to the method, a large-scale MIMO base station can generate more accurate beams, signal energy is more effectively transmitted to a target user, meanwhile, interference to other users is reduced to the minimum, a higher single-user data rate is brought, a system is allowed to serve more users in the same spectrum resource at the same time, and the user experience is improved. Therefore, the throughput and the spectrum utilization efficiency of the whole network are remarkably improved.

Disclosed herein is a Voice-Enabled AI Chat Agent, optimized for use within web browsers. This advanced AI system facilitates natural, voice-driven interactions, allowing users to engage in conversations through speech instead of traditional text input. It features a sophisticated voice recognition module, a dynamic natural language processing engine, and a versatile role adaptation mechanism, enabling it to assume various user-defined roles such as a tutor, doctor, or counsellor. Designed with an emphasis on accessibility and user-friendliness, this AI chat agent represents a significant advancement in human-computer interaction, making digital communication more intuitive and accessible for a wide range of users.

The utility model is applicable to the technical field of IO (input / output) boxes, and provides an externally-hung IO control box which comprises a box body and a machine table, the box body is hung on the side wall of the machine table, a communication module, an IO expansion module and an electromagnetic valve group module are sequentially arranged in the box body from top to bottom, a rectangular groove is formed in the side wall of the box body, an IO point end is arranged on the bottom surface of the electromagnetic valve group module, and the IO point end is connected with the machine table. The IO point end penetrates through the bottom surface of the box body and extends to the outside; preferably, the rectangular groove is located in the box body and connected with a non-setting adhesive sponge strip. Preferably, a vacuum breaking valve is arranged above the electromagnetic valve group module; preferably, a wiring channel is arranged between the communication module and the IO expansion module. By adopting the high-speed data transmission interface, the data transmission delay is reduced; an advanced data processing chip is integrated, so that the data processing speed is increased; a modular structure is designed, so that maintenance and upgrading are facilitated; multi-task parallel processing is realized, and the overall performance of the system is improved.

The invention provides an end-to-end multi-modal three-dimensional target detection method based on SPAD-RGB data, and the method comprises the steps: S1, synchronously obtaining multi-modal original data, and carrying out the preprocessing of the multi-modal original data; s2, inputting the processed multi-modal original data into a neural network model for feature extraction and deep fusion, and outputting multi-module fusion features; and S3, connecting the multi-modal fusion features with a 3D target detection head, and dynamically adjusting a threshold value of non-maximum suppression by the 3D target detection head based on an overall scene uncertainty factor in the multi-modal fusion features to complete three-dimensional target detection. According to the method, physical information such as photon-level noise distribution and multi-reflection is directly learned and reserved from original SPAD data, RGB semantics are combined, and compared with the most advanced point cloud fusion method, the 3D average precision is improved by more than 15% on data sets such as KITTI and nuScenes, especially on severe weather and long-distance small target subsets. And the detection recall rate of the transparent object is obviously improved.

The invention discloses a converter station intelligent voltage control method, product and equipment, and relates to the technical field of power system automation and intelligent control, and the detection method comprises the steps: obtaining the historical operation data and state parameters of a converter station; constructing a deep reinforcement learning control model by utilizing a deep deterministic strategy gradient algorithm, and designing a multi-target reward function to coordinate voltage stability and equipment action by adopting an Actor-Critic network structure; multiple typical training scenes are set, and normal, fault and new energy fluctuation conditions are covered; through combination of off-line training and on-line application, self-adaptive closed-loop voltage control less than 100 milliseconds is realized. According to the method, a state-action-reward mechanism is constructed, a deep neural network approximation optimal control strategy is combined, self-adaptive optimization control over the voltage of the converter station is achieved, a training scene is further designed, control requirements under different operation conditions are simulated, voltage stability is accurately maintained, an advanced voltage control means is provided for a smart power grid, and the method is suitable for large-scale popularization and application. And the construction of a novel power system is facilitated.

The utility model discloses a standard data machine room module and a modularized data center, the scheme comprises two prefabricated module units, each prefabricated module unit is used for pre-assembling equipment, and the two prefabricated module units are detachably stacked along the vertical direction; any two of the server cabinet, the liquid cooling pipeline unit and the auxiliary unit are configured in one prefabricated module unit in a centralized manner, and the other one is configured in the other prefabricated module unit, so that the server cabinet, the liquid cooling pipeline unit and the auxiliary unit can be randomly distributed into two or three prefabricated module units in advance; by selecting the vertical stacking sequence of the prefabricated module units, exclusive customization can be carried out according to the specific functions of the required building database, the building flexibility of the standard data machine room module is improved, and the individual requirements of customers are fully met. A GB200 super chip processing unit can be adopted in the server cabinet, and the advanced GPU technology and the modular design concept are combined to meet the requirements of a modern data center for high-performance calculation and flexibility.

The application discloses a kind of dynamic response 5G communication differential protection data transmission method, so that the differential protection service based on 5G communication is widely applied in low-voltage distribution network field, promote the development of new technology of power grid relay protection, solve the protection terminal of traditional low-voltage power grid not dependent on channel cannot give consideration to speed and selectivity requirement, by using advanced 5G communication technology, with the high bandwidth of 5G communication network, low latency and high reliability wireless communication environment, realize the large-scale application of longitudinal differential protection in closed-loop operation low-voltage power grid, improve the protection level of power grid.The application applies dynamic response transmission mode in the communication process of distribution network transmission line differential protection based on 5G communication, meets the rapidity requirement of relay protection, reduces 5G communication transmission flow, saves communication resources and reduces communication cost.

The invention relates to a communication device based on Beidou positioning, which comprises a Beidou positioning module, a wireless communication module and a control module, and can acquire position information in real time and perform data transmission through cooperative work of the modules. The Beidou positioning module is responsible for receiving and processing positioning data of a Beidou satellite, and the positioning precision is improved through a differential positioning technology; the wireless communication module adopts an advanced communication protocol and technology to realize rapid transmission and encryption protection of data; the control module serves as a core and is responsible for coordination and management of overall functions, and intelligent decision making and adjustment are conducted according to real-time data and user requirements; the device has the advantages of being simple in structure, convenient to operate, high in positioning precision, stable and reliable in communication and the like; by integrating a Beidou satellite navigation system and a wireless communication technology, high-precision positioning and stable and reliable communication functions are realized.

The present invention introduces a system integrated into a mobile phone accessory, designed for the automated and highly customizable diffusion of perfumes and incenses. This advanced device leverages Internet of Things (IoT) technology to deliver an interactive and tailored user experience. It features a rotating disk outfitted with refillable cartridges that hold a variety of perfumes or perfume compounds. These can be selected based on the user's individual preferences. An electric actuator precisely activates these cartridges, dispensing the exact amount of perfume required into a mixing chamber for consistent scent distribution. Additionally, the system is equipped with a state-of-the-art incense burning mechanism that utilizes laser technology for precise, chemical-reaction-free ignition. This allows for superior control over the scent diffusion process. The device is engineered to be operated via a smartphone application, which communicates with an online server to dynamically adjust diffusion parameters in response to user interactions, ensuring a personalized ambiance tailored to the moment's needs.

The invention discloses an encryption method and system integrating anomaly detection and risk monitoring. The system comprises a key management module, a key storage module, a file encryption module and a dynamic security defense module. According to the invention, advanced hybrid encryption, blockchain, unsupervised machine learning algorithm, programming and other technologies are utilized to construct an open, credible, safe and efficient encryption and decryption system; secret key pairs are distributed for unit internal users by using hybrid encryption, public key data are coded and compressed and then registered to a block chain sharing smart contract, and private key data are segmented and encrypted and then registered to interstellar network nodes; public and efficient online encryption and decryption, digital signature and verification are provided for file circulation of internal users; machine learning anomaly detection and risk monitoring are fused, behavior-driven dynamic security defense and fine-grained permission control of an intelligent contract are implemented in real time, and system operation is safe and controllable.

The invention relates to the cross technical field of a computer information technology and a college management information system, and provides a college institution service intelligent response system fusing self-service questions and answers and task work orders. The system comprises a user interaction module, a self-service question and answer engine, a work order generation and distribution module, a background processing and feedback module and a service statistics and optimization module. According to the invention, an advanced natural language processing technology, knowledge graph construction and intelligent work order management are fused, so that a college institution service intelligent response system integrating self-service question answering and task work orders is constructed. The system not only realizes seamless access and efficient intelligent interaction of multiple channels and multiple terminals, but also ensures that various problems are timely and accurately processed through automatic classification, responsibility distribution and closed-loop management.

The invention relates to the technical field of mining application, and discloses a 5G-MEC-based intelligent mine integrated control platform and a 5G communication system. The MEC core network is deployed in a mine core machine room, a switch is hung below the MEC core network, the MEC core network is in butt joint with an existing mine 10-gigabit industrial network, and data interaction between 5G and a mine industrial ring network is achieved; a mobile device data transmission and remote control system; an unattended system; cutting parameters and a tunneling path are optimized in a datamation mode, dynamic adjustment of equipment such as a coal mining machine in the operation process is achieved, and therefore the mining efficiency is guaranteed, meanwhile, energy consumption and abrasion of the equipment are effectively reduced, the service life of the equipment is prolonged, the maintenance cost is reduced, the overall economic benefit of mine mining is improved, and meanwhile the mining efficiency is improved. The advanced fault diagnosis technology is adopted, the identification accuracy of the inspection robot on equipment faults and normal states is improved, false alarms and missing alarms are reduced, the continuity and stability of mine production are guaranteed, and the safety risk is reduced.

Methods, systems, and computer storage media for providing a cross-domain secure authentication engine in an item listing system are described. The cross-domain secure authentication engine is an advanced, modular system designed to handle user authentication seamlessly across different service domains, while ensuring security features and an adaptive user experience. In an item listing system, the cross-domain secure authentication engine operates based on a security-focused framework that streamlines user authentication across multiple domains without sacrificing user experience. It integrates a modal containing an iframe-based sign-in interface associated with a separate authentication domain and employs a postMessage API for cross-origin communication. Key features include dynamic modal resizing—adjusting the sign-in window to different authentication steps (like email, password, or OTP)—and parameterized iframes that remove unnecessary UI elements for a cleaner user experience. The cross-domain secure authentication engine also supports security measures and supports incremental, multi-step authentication flows to reduce user friction.

The application relates to the technical field of cloud computing, in particular to an intelligent network self-recovery method and system applied to a smart traffic system, which comprises the following steps: data collection, abnormality detection, fault diagnosis, automatic repair and self-learning optimization; the beneficial effects are that the intelligent network self-recovery method and system applied to the smart traffic system can immediately identify abnormal behaviors in the network and respond quickly through real-time monitoring and a quick abnormality detection mechanism, and the time for fault detection and response is greatly reduced; advanced fault diagnosis algorithms, including deep learning and pattern recognition technology, are used, and the system can accurately diagnose various complex faults, including unknown or novel fault modes.

The invention discloses a capital construction feasibility investigation automation standard compliance verification method and system, relates to the technical field of data verification, and solves the problems that feasibility investigation in the prior art mainly depends on manual examination and is low in efficiency, high in subjectivity and easy to omit. According to the method, automatic checking of capital construction research and review automation standard compliance verification is realized through an intelligent algorithm, manual intervention is reduced, and the checking efficiency is improved; moreover, the advanced intelligent technology is utilized, so that the accuracy and the consistency of a verification result are improved; in addition, the standard library can be dynamically adjusted according to the updating of the capital construction feasibility research standard, so that the automatic standard compliance verification requirements of capital construction feasibility research examination in different regions and in different scales are met; moreover, the automatic standard compliance verification system for capital construction research and review can be upgraded and optimized according to actual requirements, so that the maintenance cost is reduced.