4359 results about "Data control" patented technology

A system for monitoring and optimizing the performance of an e-commerce platform, which includes the following: a) a data collection and integration module configured to retrieve real-time data from e-commerce platforms, marketing channels, inventory systems and user interactions using APIs, tracking scripts and server-to-server communication; b) a data preprocessing and filtering module for cleaning and structuring the collected data by removing inconsistencies, normalizing formats and detecting outliers; c) a machine learning and predictive analytics machine that uses deep learning, regression models and clustering algorithms to analyze historical and real-time data to predict sales trends, customer behavior and demand fluctuations; d) a performance monitoring dashboard configured to visualize key performance indicators, sales trends and marketing effectiveness, and to provide custom reports and real-time alerts; e) an automated module for optimizing marketing campaigns, which dynamically adjusts advertising strategies, budget allocations, target audience approach and creative elements based on real-time data insights; f) an automated decision and control system configured to execute AI-driven optimization strategies, including bid adjustments, price changes and inventory reallocations without manual intervention; (g) a fraud detection and compliance monitoring module that uses anomaly detection algorithms to identify fraudulent transactions, fake reviews and advertising fraud while ensuring compliance with legal regulations; the system continuously monitoring, analyzing and optimizing the performance of the e-commerce platform through automated data-driven decision-making.

The invention discloses an adaptive protocol stack reconstruction and transaction-level data control method for 5G communication, and aims to solve the technical problems of fixed protocol stack structure, coarse transmission control granularity and the like of an existing communication module. The method comprises the following steps: firstly, analyzing an application layer communication session initialization instruction, generating a communication task label, acquiring 5G network environment state data in real time, and constructing a network state feature vector; then, the communication task label and the network state feature vector are input into a protocol mapping decision map, a protocol reconstruction instruction is generated, loading and unloading of a protocol module in a protocol stack resource pool are controlled, a dynamically-adaptive protocol path is constructed, and a transaction identifier is allocated to the protocol path; and establishing a transaction-level data buffer area based on the transaction identifier, performing priority marking on the data packet, and executing differentiated dynamic flow control operation according to the network state feature vector and the priority label, thereby realizing high-reliability and low-delay 5G communication data management.

The invention discloses a database management method and management system, and relates to the technical field of general database management, and the system comprises a user information management module, a work management module, a salary settlement module, an evaluation feedback module, an analysis prediction module, a multi-terminal integration module and a safety guarantee module. In the invention, a role-based access control permission model is constructed in a permission control layer and a module definition, and a field-level data control mechanism is implemented for three roles of a platform administrator, a customer enterprise and an employee, for example, the employee can only check a specific public field in a salary list, and sensitive fields such as a salary calculation formula are dynamically shielded; through a permission inheritance mechanism, the system automatically adds a filtering condition that employee ID = current user ID for a query request of an employee role, data isolation is ensured, a multi-dimensional data relation graph of employee-post-customer-contract is constructed, and a dynamic association path between entities is mapped in real time through a visual view.

Systems, methods, and apparatus for detecting UAVs in an RF environment are disclosed. An apparatus is constructed and configured for network communication with at least one camera. The at least one camera captures images of the RF environment and transmits video data to the apparatus. The apparatus receives RF data and generates FFT data based on the RF data, identifies at least one signal based on a first derivative and a second derivative of the FFT data, measures a direction from which the at least one signal is transmitted, analyzes the video data. The apparatus then identifies at least one UAV to which the at least one signal is related based on the analyzed video data, the RF data, and the direction from which the at least one signal is transmitted, and controls the at least one camera based on the analyzed video data.

Procedures, methods, architectures, apparatuses, systems, devices, and computer program products for decentralized data control and access management. For example, a data owner may perform a subscription procedure to obtain verification credentials and an index (e.g., address, identifier) to public data control and access information. The data owner may perform a registration procedure to register ownership of data using the public data control and access information. The public data control and access information may include a public key. The public key is paired with a private trapdoor key to form a key pair. The data owner and a data consumer may perform an access procedure to grant access to registered data. For example, the registration procedure may verify collisions between a token hash, a data hash, and a data owner hash based on use of the key pair.

The invention relates to the technical field of data sharing, and discloses a multi-department data sharing method and device, equipment and a storage medium. The method comprises the following steps: carrying out acquisition and standardized preprocessing on multi-department data required by enterprise project application to generate an intermediate data packet; establishing an event trigger distributed data control mechanism based on the intermediate data packet, calculating a dynamic trigger threshold, monitoring data change, and generating a target control data stream; performing template-free adaptive learning to generate an optimal data processing flow definition file; executing data classification, self-adaptive compression and increment processing at the edge computing node to generate an optimized data packet and metadata thereof; and inputting the optimized data packet and the metadata thereof into a SaaS cloud server central data warehouse to generate a project declaration data packet, thereby realizing consistency coordination and conflict automatic resolution of data of multiple departments, and realizing unified access and standardized processing of heterogeneous data sources.

The invention discloses a CNNLSTM-based energy storage equipment temperature control method and system, and the method comprises the steps: collecting the load temperature of energy storage equipment through a temperature sensor, inputting the load temperature into a trained CNNLSTM model for temperature prediction, and taking an error between the predicted temperature and the target temperature of the energy storage equipment as feedforward input data of a PID control unit, and the PID control unit controls the input data to a temperature control system of the energy storage equipment according to the error feedback so as to adjust the load temperature. According to the CNNLSTM model, the CNNLSTM model combines the CNN and the LSTM to process and predict the load temperature of the energy storage equipment, has strong capabilities of processing time sequence data, extracting features and capturing a long-term dependency relationship, and shows remarkable advantages in the fields of energy storage equipment load temperature prediction, equipment state monitoring and the like.

The present invention relates to the technical field of warehousing control. In particular disclosed are an automatic cargo loading and unloading warehousing control system and a cargo loading and unloading device therefor, the system being provided with a compartment parking information acquisition and processing module, an intelligent cargo conveyance control module, a warehousing management information comprehensive determination module, and a data control library. First, compartment parking information acquisition and preprocessing is performed, and it is determined whether a cargo loading and unloading AGV can be started, and next, a first channel is screened out to convey a goods in a compartment. Hence, a control anomaly value of warehousing management information of an intelligent warehousing control platform is comprehensively calculated, and the warehouse management information is subjected to autonomous early warning control and indication, thus facilitating rapid operations of cargo loading and unloading, and greatly improving the efficiency of warehousing intelligentization. Meanwhile, the labor costs of warehousing operations can be reduced, and the quality and accuracy of cargo processing can also be improved.

The invention relates to the technical field of automatic manufacturing, and discloses a metal pipe part welding path intelligent planning and monitoring system which comprises a path planning module used for generating an optimal welding path according to the geometrical shape of a metal pipe part, welding process requirements and sensor feedback information; the sensor module monitors key parameters in the welding process in real time through a visual sensor, a thermal imaging sensor and a force sensor; the data processing and analyzing module is used for processing and analyzing the real-time data acquired by the sensor; the welding control module is used for controlling operation of welding equipment according to path planning and sensor feedback data; and the quality monitoring and feedback module is used for monitoring the quality in the welding process in real time. According to the system, the welding path is generated through the intelligent path planning module, and the path is dynamically optimized in combination with real-time sensor data, so that the accuracy of the welding process is improved, the system can adapt to changes in a complex welding environment, and the welding efficiency and quality are improved.

The invention discloses a server link fault positioning system and method, electronic equipment and a storage medium, and relates to the technical field of server link tests.Physical layer data and protocol layer data of a data collection point are collected through a collection assembly, a test assembly is controlled to conduct server link testing, the test assembly comprises a control module and an analysis module, and the control module is connected with the analysis module. The test instruction is issued to the server link through the control module, when the server link fault is monitored, the analysis module acquires the physical layer data and the protocol layer data of each data acquisition point from the acquisition assembly, and determines the fault position and / or the fault type of the server link according to the acquired data, so that the automatic link quality evaluation is realized, and the efficiency is improved. And the fault position and the fault type can be determined, so that the problems of difficulty in accurately positioning the fault position and distinguishing the hardware link fault and the software error through a single pressure test and low troubleshooting efficiency caused by manual fault positioning in the prior art are solved, and the technical effect of improving the troubleshooting efficiency is achieved.

The invention relates to the technical field of data control, in particular to a digital visual control method and system for a grease production line. The method comprises the following steps: acquiring full-process physical data; performing noise filtering on the whole-process physical data to obtain whole-process noise filtering data; abnormal data detection is carried out on the whole-process noise filtering data, and abnormal data are removed to obtain a whole-process data set of the grease production line; therefore, by constructing a feature driving mechanism of physical-data fusion of the grease production line, the problems of low data utilization rate, insufficient prediction precision and control optimization lag in a traditional grease production line are solved, and the operation efficiency and decision intelligent level of the grease production line under complex working conditions are improved.

The invention is suitable for the field of data management, and provides a front-end AI dialogue data management system and method, and the system comprises an asynchronous data flow management module; a state management module; a streaming data control module; a Markdown rendering engine is adopted; the beneficial effects of the invention are that the asynchronous data flow management module realizes high-efficiency synchronization of front-end and rear-end data, significantly reduces the data processing delay, and the state management module ensures the consistency of a user interface and rear-end data, optimizes the user experience, and improves the user experience. The built-in advanced Markdown rendering engine supports various self-defined grammars, so that the output content of the AI can be flexibly subjected to personalized rendering, modular design is adopted, customization and expansion can be performed according to service requirements, and the method is suitable for different application scenes.

The embodiment of the invention discloses an abnormity monitoring system applied to a plasma etching machine. The abnormity monitoring system comprises constant current source equipment, a coil, a coil detection circuit and a controller, and the constant current source equipment is configured to output driving current according to preset etching process parameters; the coil is configured to generate a magnetic field in the etching cavity in response to the input of the driving current to guide the plasma to move towards the direction of the substrate so as to etch the substrate; the coil detection circuit is configured to detect coil state data of the coil; the controller is configured to generate device service information based on the coil state data. According to the embodiment of the invention, the working state of the coil is monitored through the coil state data, and the actual condition of the coil is reflected through the equipment maintenance information, so that a user can quickly know whether the coil is in an abnormal state, the user is helped to quickly position the maintenance direction, the user is prevented from detaching and maintaining the coil from the etching cavity, and the user experience is improved. And various resource investments wasted due to the fact that the coil is abnormal do not exist.

An AI-powered system (100) for multimodal data processing, dynamic authentication and secure FinTech and IoT transactions, which includes the following: a multimodal data processing module configured to process structured, semi-structured and unstructured data, including financial transactions, IoT sensor data, voice input and image-based data; an AI-powered dynamic authentication module configured to provide behavioral biometrics, context analysis, and multi-factor authentication (MFA) for continuous user and device verification; an anomaly detection module integrated with machine learning models and configured to provide real-time fraud detection by analyzing transaction patterns, user behavior, and device interactions; a secure encryption module configured to use homomorphic encryption and secure multi-party computations to protect sensitive financial and IoT data; and a blockchain-based transaction validation module configured to create an immutable, tamper-proof ledger to ensure data integrity and transaction transparency.

A work vehicle includes a sensor to sense an area of the work vehicle and output sensor data, a controller to control self-driving of the work vehicle based on the sensor data, and a link to attach an implement to the work vehicle. When the work vehicle performs the self-driving with the implement linked to the work vehicle, the controller is configured or programmed to detect and classify an object based on the sensor data, determine a first influence degree indicating a magnitude of influence when the object contacts the work vehicle and a second influence degree indicating a magnitude of influence when the object contacts the implement in accordance with a result of the classification of the object, and execute in accordance with at least one of the first and second influence degrees at least one of avoiding contact with the object or continuing the self-driving without executing avoiding.

The invention relates to equipment and a method for water-guided laser collaborative forcible entry of a reinforced concrete pile head based on artificial intelligence recognition, and belongs to the technical field of forcible entry equipment. Comprising a mobile chassis; the rack is mounted on the movable chassis; the water jet system is mounted on the rack and is provided with a first working part; the mechanical drill bit system is mounted on the rack and is provided with a second working part; the identifying and positioning module is used for collecting real-time data of a three-dimensional structure, steel bar distribution and a forcible entry area of the pile head; and the control unit is in communication connection with the identifying and positioning module, the water jet system and the mechanical drill bit system, and the control unit receives data of the identifying and positioning module to generate a forcible entry strategy and a mechanical drill bit path plan so as to guide the first working part and the second working part to cooperatively work. The technical problems that in the prior art, impact force of water jet forcible entry is limited, and the forcible entry efficiency of a hard core layer and a complex forcible entry environment is not high are solved.

There is provided a method for monitoring and assessing compliance of a computing system. The method may include receiving documents containing rules. Each document may be converted to a tree structure having nodes. A mapping object may be generated to map a tree structure to another tree structure. A second mapping object may be generated to relate a tree structure to compliance controls. A third mapping object may be generated to relate compliance controls to a set of compliance control evidence. A compliance score may be determined based on the controls, the evidence, and the mappings.

The invention discloses a vehicle-mounted ground penetrating radar attitude compensation device and a control method, and belongs to the technical field of ground penetrating radar detection. The attitude compensation device comprises a control mechanism and a monitoring system, the control mechanism comprises a radar supporting part and a vehicle-mounted supporting part, the radar supporting part is connected with the vehicle-mounted supporting part through a buffer compensation part, the buffer compensation part comprises a mechanical telescopic structure, and the two ends of the mechanical telescopic structure are connected with the radar supporting part and the vehicle-mounted supporting part respectively; the monitoring system is arranged on the radar supporting part and comprises an IMU sensor, a laser range finder and a data processor. The IMU sensor, the laser range finder, the data processor and the like of the monitoring system are utilized, pose information is fed back in time through information monitoring, and the compensation device is controlled to carry out pose compensation by analyzing motion data, so that the platform is always located at a horizontal position with a certain distance from the ground; the detection precision and the anti-interference capability of the ground penetrating radar system are obviously improved, and different road conditions are flexibly coped with.

The invention relates to the field of factory intelligent cooling, and discloses an MPC-based large factory intelligent cooling system and a cooling control method, the system comprises a data acquisition module, an AI control module, a cooling tower control module, a cooling water pump control module and a cooling-water machine control module; the data acquisition module acquires outdoor environment temperature and humidity, cooling tower outlet water temperature, cooling water pump inlet and outlet water temperature difference and flow and water chiller operation state data in real time. The AI control module constructs a system model through real-time data, predicts and optimizes by using an MPC algorithm, and calculates optimal values of the running frequency of a cooling tower fan, the running frequency of a cooling water pump and the power of a cooling-water machine compressor by adopting sequential quadratic programming, so as to realize cooperative dynamic control of equipment in the system; the overall operation efficiency of the cooling system under the outdoor temperature and humidity change condition is effectively improved, and the overall energy consumption of the system is minimized in real time.

The invention relates to the technical field of control systems, and particularly discloses an electric vehicle and renewable energy source integrated energy management measurement and control system and method, and the system comprises an acquisition module, an optimization control module, a control execution module, a constraint module, and a fault tolerance module. The acquisition module acquires photovoltaic, wind power and electric vehicle load data through a distributed sensor network, and the control execution module issues an instruction through a multi-priority message queue and performs closed-loop feedback; the constraint module decouples space-time constraints through causal derivation, and updates strategy network parameters in combination with federated learning; and the fault-tolerant module performs dynamic fault tolerance based on the Bayesian network and the generative adversarial network. The method covers multi-source data processing, hierarchical optimization instruction generation, closed-loop verification and anti-interference training processes, solves the problem of optimization path deviation caused by difficult solution of high-dimensional mixed integer programming and time-space correlation interference, and realizes dynamic balance of energy supply and demand and low-carbon operation.

A hybrid neural network architecture is disclosed that integrates matrix multiplication-free (MatMul-free) transformation layers with spiking neural network (SNN) layers for efficient, low-power computation. The system includes an interface module configured to convert intermediate continuous-valued data from MatMul-free layers into a spike-compatible format using encoding techniques such as rate coding, phase coding, or threshold-based conversion. The SNN layers process the spike-encoded data in an event-driven manner, enabling sparse, temporal inference. Training is supported by a hybrid optimization strategy combining backpropagation in MatMul-free components with surrogate gradient descent or spike-timing-dependent plasticity (STDP) in SNN layers. The architecture reduces computational complexity, supports real-time adaptability, and enables deployment in energy-constrained environments such as edge devices and neuromorphic platforms. The system may be implemented in hardware, software, or a co-designed pipeline optimized for dynamic sensor data, control signals, or continuous inference tasks.

The invention relates to the technical field of computers, and discloses a data control method and system, electronic equipment and a storage medium, and the method comprises the steps: receiving a data control strategy defined by a data owner, and the data control strategy is constructed based on a quintuple framework and comprises a subject, an object, an environment condition, an operation behavior and an effect; compiling the data control strategy into an intelligent contract code, and generating a source code based on an intelligent contract template; deploying the smart contract code to a block chain network to form a decentralized strategy decision point; intercepting the data access request, triggering the smart contract to verify the access request, and generating an access credential when the verification is passed; and allowing data access based on the access credential, and monitoring a data use behavior to ensure consistency with the data control strategy. According to the method, the fine granularity and the whole-process coverage of data control can be improved, the auditing credibility can be improved, the automation level and the efficiency of a control system can be improved, and the end-to-end safety guarantee capability is enhanced.

The invention discloses a nonlinear multi-agent system sampling consistency control method and system and a medium, and the method comprises the following steps: S101, obtaining system model parameters, including a nonlinear function # imgabs0 #, a pulse gain # imgabs1 #, a sampling period # imgabs2 #, a communication topological graph # imgabs3 # and a leader-follower kinetic equation; s102, verifying an assumed condition; s103, constructing a Lyapunov function # imgabs4 #, and analyzing the stability of an error system in combination with pulse disturbance; s104, deriving a consistency condition through a Lyapunov method and a pulse theory, calculating key parameters, and determining a pulse gain and a sampling period constraint; s105, selecting parameters meeting conditions; s106, constructing a sampling controller containing pulse disturbance; and S107, implementing the controller and performing numerical simulation. According to the invention, the anti-pulse disturbance capability is strong: through the design of the pulse gain # imgabs5 #, the instantaneous interference of an input channel is effectively counteracted, and the robustness of the system is improved; a sampling data control strategy is adopted, a control signal is updated only at a discrete sampling moment, and the communication burden is reduced.

The invention discloses a secure data transmission method in a cloud platform salary management system, which belongs to the technical field of cloud platform data transmission, and comprises the following steps: acquiring user post attributes and authority levels to generate a post authority matrix, and generating a segmentation encryption rule to dynamically segment salary data to generate an encrypted data segment group; generating an environment security score based on the characteristics of the current network transmission path, and verifying the environment security score with the encrypted data segment group; after data transmission is completed, implanting a two-dimensional verification watermark into the encrypted data segment group to generate a controlled data packet; and generating a protection intensity grade and a gradient response instruction based on the current operation step and the environmental safety score, and executing a dynamic data protection operation. According to the method, the security classified storage, the dynamic encryption transmission and the accurate tracing control of the salary data can be realized by adopting the intelligent verification mechanism based on the dynamic segmentation encryption of the post permission matrix and the environmental security score and the multi-level data control technology of the two-dimensional verification watermark.

Display assemblies utilizing air characteristic data to verify internal operating conditions and related systems and methods are disclosed. The display assembly includes a side assembly, including an electronic display, is connected to a structural framework. Sensor(s) are provided, at least one of which is located at, or fluidly connected to, a closed airflow pathway. A controller receives data from the sensor(s) and determines whether an initial indication of an operating condition exists. If so, a testing routine is initiated, additional data is received from the sensor(s) during and / or thereafter. The controller confirms whether the operating condition exists based on the additional data.

The present application discloses a virtual object control method and apparatus, a storage medium, and an electronic device. The method comprises: displaying a target virtual scene; acquiring environment perception data corresponding to a first virtual object in the target virtual scene, the first virtual object representing an object controlled by a system, and a portion of data associated with a target virtual object in the environment perception data being determined by whether the target virtual object is visible to the first virtual object; determining action packet data on the basis of the environment perception data, and controlling the first virtual object to execute a target action according to the action packet data, the action packet data comprising different types of sub-actions predicted on the basis of the environment perception data, and the target action being determined by combining different types of sub-actions. The present application solves the technical problem of the accuracy of control of a virtual object being low due to the presentation of the virtual object being singular. The embodiments of the present application can be applied to various scenarios, such as cloud technology, artificial intelligence and smart traffic.

The invention provides a quad-rotor unmanned aerial vehicle trajectory tracking control method and device, equipment and a storage medium, and belongs to the technical field of unmanned aerial vehicle control, and the method comprises the steps: determining a translation system state variable and an attitude system state variable of an unmanned aerial vehicle based on the real-time trajectory data of the quad-rotor unmanned aerial vehicle; calculating a translation disturbance estimated value based on the translation system state variable, the disturbance observer constant and the expected speed; thrust data is determined based on the translation system state variable, the translation disturbance estimated value, the expected speed, the expected position and outer ring controller parameters of the unmanned aerial vehicle; determining a desired attitude angle based on the thrust data and the desired yaw angle; calculating a control moment based on the expected attitude angle, the attitude system state variable and an inner ring controller parameter of the unmanned aerial vehicle; and based on the thrust data, the control torque and the physical parameters of the unmanned aerial vehicle, calculating to obtain a rotor expected rotating speed, and controlling the unmanned aerial vehicle based on the rotor expected rotating speed. The accuracy of flight control of the unmanned aerial vehicle can be improved.

The invention discloses an electric tractor with a power suspension and an endurance control system and method, and relates to the technical field of electric tractors, and the endurance control system comprises a data acquisition module used for acquiring target data; the control module is used for determining the distribution proportion of the driving torque of the tractor and the driving torque of the power trailer according to the driving torque required by the whole vehicle and the driving working condition of the whole vehicle when the ratio of the electric quantity of the power battery pack of the tractor to the electric quantity of the power battery pack of the power trailer is within a set proportion range; when the ratio is greater than the upper limit of the set proportion range, reducing the driving torque of the power trailer and increasing the driving torque of the tractor; when the ratio is smaller than the lower limit of the set proportion range, the driving torque of the power trailer is increased, and the driving torque of the tractor is reduced. The endurance mileage of the electric tractor is increased, and the power performance of the electric tractor is enhanced.

The invention relates to the technical field of automatic monitoring, in particular to a multi-sensor fusion automatic monitoring system and method based on Beidou positioning, and the system comprises an anti-interference and environment adaptation module which comprises a Beidou positioning module, a multi-sensor fusion unit and a data processing and communication unit, the Beidou positioning module is connected with the data processing and communication unit, and the multi-sensor fusion unit is connected with the anti-interference and environment adaptation module; the multi-sensor fusion unit is connected with the data processing and communication unit and used for collecting positioning signals, the multi-sensor fusion unit is connected with the data processing and communication unit and used for providing auxiliary monitoring data, and the control center analysis unit receives real-time data through the data processing and communication unit and is used for monitoring analysis and early warning. Therefore, the problems of easy signal shielding, precision fluctuation and data interruption of single Beidou positioning in a complex environment, insufficient three-dimensional monitoring precision and poor anti-interference and wide-temperature stability caused by lack of hard-soft cooperation in multi-sensor fusion, and high false and missing report rate caused by fixed early warning threshold are solved.

The invention provides a ship navigation situation sensing system and sensing method based on panoramic video construction, and belongs to the technical field of image processing, and a control module collects data through navigation equipment, environment measurement equipment and sensing equipment. The control module preprocesses the collected data. The control module performs feature extraction on the data and detects a static obstacle and a dynamic target. The control module performs association fusion on the static obstacle and the dynamic target through a multi-source data fusion algorithm; and the control module displays the static obstacle and the dynamic target through the display module. The control module evaluates the sailing risk of the ship according to the sailing state of the ship, the position of the static obstacle and the situation of the dynamic target; when the control module predicts danger, the control module gives an alarm through ship alarm equipment, provides adjustment suggestions and records dangerous events at the same time. According to the invention, comprehensive and accurate surrounding environment information is provided for a ship driver, and the safety of ship navigation is improved.