5results about How to "Data Security" patented technology

This invention discloses a six-degree-of-freedom underwater robot, comprising a frame, a propulsion system, a sensor monitoring system, and a controller. The propulsion system includes four horizontal vector thrusters and two vertical thrusters. The controller is communicatively connected to the propulsion system and the sensor monitoring system, and achieves independent, decoupled control of the propulsion system's six degrees of freedom based on multi-dimensional sensor data collected by the sensor monitoring system. This invention also discloses a corresponding six-degree-of-freedom underwater robot control system, including a host computer layer, a ROS core layer, a control layer, a drive layer, and a hardware terminal layer, all connected by communication. This solution optimizes the hardware layout, achieves independent, decoupled control of the six degrees of freedom, and improves underwater motion and hovering stability. This design features deep hardware and software synergy, improving underwater operational stability, shortening the development cycle, and enhancing operational safety, making it suitable for various scenarios such as underwater exploration, detection, and scientific research.

This invention discloses a method and system for integrated collaborative management and control of multiple public warehouses. The method includes steps S1: unified modeling of multiple warehouses and standardization of data across the entire domain; step S2: dynamic permission isolation control for multiple tenants and multiple warehouses; step S3: a differentiated rule engine driving business flow across multiple warehouses; step S4: cross-warehouse collaborative scheduling and real-time synchronization of status across the entire domain; and step S5: adaptation to the domestic IT innovation environment and end-to-end data security assurance. The purpose of this invention is to solve the problems of data fragmentation, inefficient collaboration, insufficient supervision, and incompatibility with domestic IT innovation in existing multi-warehouse systems. It provides a method and system for integrated collaborative management and control of multiple public warehouses, achieving integrated management and control with multi-warehouse parallelism, business isolation, data interoperability, process collaboration, security controllability, and full-stack domestic IT innovation compatibility.

The application discloses a business card digital certificate authentication method, a terminal, a system and equipment, and after a terminal of a doer completes company registration, a doer business card digital certificate is generated and activated, and business card information is verified and publicized through a cloud publicizing platform, and the doer business card information is safe and reliable and cannot be tampered with; an executor terminal applies for an executor business card digital certificate according to an invitation link of the executor business card authentication digital certificate generated by the doer terminal, and after authorization and activation, the business card information is verified and publicized through the cloud publicizing platform; and a business card receiver obtains the business card information according to a two-dimensional code. The doer cannot tamper with the staff information, and therefore cannot pretend to be the doer to cheat the business card receiver, so that the problem of lack of safety and reliability of the business card information is solved, and the rights and interests of the real business card owner, the company or the interests of the business card receiver are prevented from being infringed.

The invention discloses a low-power-consumption high-precision positioning method based on an intranet RTK technology. The method comprises the steps that S1, a base station network and a service platform are deployed, and a terminal collects, formats, compresses and uploads Beidou original observation data; s2, the platform collects data of the terminal and the base station, constructs a differential processing model, generates high-precision differential correction information in real time, and issues the high-precision differential correction information to the terminal through an internal network; s3, differential data are received and analyzed, data preprocessing, Kalman filtering, ambiguity fixing and fixed solution verification algorithm processes are sequentially executed in combination with self observation values, and centimeter-level accurate position coordinates are finally solved; s4, low-power-consumption operation is realized through a dynamic power management strategy and a time-triggered sleep wake-up mechanism, and the stability, precision and update frequency of positioning are maintained in a high-speed and high-interference dynamic scene by using adaptive Kalman filtering and a fast convergence algorithm; the method has the advantages of high positioning precision, low use power consumption, wide application range and safe and reliable data.

The application provides a big data fast processing and abnormality identification system and method. The system comprises a data acquisition and access module, which can acquire data from heterogeneous data sources in multi-thread parallel mode and standardize the data; a distributed buffering and storage module, which adopts Kafka and HDFS to realize high-throughput buffering and reliable storage; a streaming processing calculation module, which can aggregate features based on a dynamic sliding window and can also calculate trend features; an abnormality identification engine, which is internally provided with an adaptive threshold algorithm model, the tolerance coefficient of which can be dynamically adjusted, and has a cold start strategy for new data streams; an alarm and action execution module, which can trigger multi-level alarms and automatic actions; and a system management and visualization module, which provides configuration, display and other functions. The method covers the whole process from data acquisition to model iteration. The application can efficiently process data, intelligently identify abnormalities, and continuously improve the model performance and abnormality identification accuracy.