11results about How to "Reduce bandwidth pressure" patented technology

This invention discloses a power distribution IoT communication and equipment management system based on dynamic optimization algorithms. It adopts a four-layer architecture: a perception layer, an edge layer, a platform layer, and an application layer. The end devices in the perception layer are used to collect power distribution data and execute control commands. The edge devices in the edge layer, and their managed sub-devices, are used for protocol conversion, data preprocessing, and executing dynamic optimization algorithms. The platform layer is used for message parsing, algorithm optimization, device management, and data storage. The application layer provides a visual user interface. Through dynamic optimization algorithms and a full lifecycle device management scheme, the system significantly improves the reliability of power distribution IoT data transmission, optimizes network resource utilization, enhances equipment operating efficiency, ensures the real-time performance of critical services, and features strong compatibility, security, and concurrent processing capabilities.

The present application relates to the technical field of Internet of Things, in particular to a city intelligent guardrail real-time monitoring method based on Internet of Things, comprising the following steps: collecting original vibration signals of the guardrail through an Internet of Things sensing terminal deployed on a city guardrail node, projecting and reducing dimension of the original vibration signals by using a preset compressive sensing observation matrix to obtain a compressed measurement value data packet; in the present application, time-frequency feature extraction is performed on the reconstructed time-domain vibration waveform, the impact event type is identified according to the characteristic data, and the rapid response and processing of traffic accidents are ensured; in the case that no impact occurs and the waveform presents a free decay trend, the decay tail wave data segment is intercepted, the guardrail structure fastening integrity evaluation index is calculated, and comparison with the safety benchmark threshold value is performed, so that the loosening state of the connecting piece can be quantitatively determined, and external impact monitoring and internal structure health condition diagnosis can be simultaneously realized by using a single vibration source without additional deployment of stress sensors.

This invention relates to the field of byte processing technology, providing a method and apparatus for accelerating byte encryption and decryption. The invention adds operation bits to bitwise operation instructions; uses corresponding operation bits to perform byte selection, endianness conversion, single-input multiple shift processing, and / or efficient table lookup operations. Specifically, byte selection avoids invalid bit calculations, improving instruction utilization. Endianness conversion ensures correct data order, minimizing duplicate data requests due to order errors, thus reducing the need for bitwise operations and improving GPU bandwidth utilization. Single-input multiple shift processing reduces the number of shift instructions, increasing throughput and avoiding repeated loading of the same data; efficient table lookup operations improve bitwise computation throughput, significantly reducing bandwidth pressure. This invention optimizes the granularity of bitwise operations, enabling encryption and decryption algorithms to efficiently utilize computing resources on the GPU while minimizing bandwidth consumption.

This application relates to a method and apparatus for substation equipment condition monitoring based on edge computing. The method includes: deploying edge computing nodes at the substation side, which aggregate real-time condition data collected by monitoring equipment; preprocessing and extracting features from the real-time condition data at the edge computing nodes to obtain equipment feature vectors representing the health status of the equipment; dynamically determining high-risk monitoring areas within the substation based on historical operation and maintenance data and real-time power grid operation requirements, and deploying corresponding lightweight intelligent diagnostic models at the edge computing nodes according to these high-risk monitoring areas; using the lightweight intelligent diagnostic models to perform real-time analysis of the equipment feature vectors to obtain equipment condition diagnostic results including fault types and fault probabilities; and executing tiered early warning or rapid control operations at the edge side based on the equipment condition diagnostic results. This method can improve the diagnostic results of substation equipment condition monitoring.

This invention belongs to the field of mine safety monitoring technology, specifically involving an intelligent management system based on miners' positioning data processing. The system includes a wearable precision inertial measurement device, a multi-source data fusion gateway, an underground wireless transmission network, a biomechanical feature extraction server, a behavioral quality evaluation management platform, and a multi-dimensional early warning terminal. The wearable device collects high-frequency motion vector data of miners in real time, performs preliminary noise reduction using the gateway, and the server establishes a gait cycle segmentation model to accurately extract gait feature parameters such as stride length, ground contact time interval, and body center of gravity oscillation frequency. This invention realizes a shift from simple spatial location monitoring to in-depth monitoring of biological signals and behavioral quality, filling the monitoring blind spots caused by passive displacement and improving the proactiveness of mine risk early warning and the accuracy of safety supervision.

The application relates to the technical field of fault diagnosis, in particular to a distributed industrial fault diagnosis system and method, which comprises edge terminals and edge servers arranged in various industrial components. The edge terminal is provided with a rapid diagnosis module, a high-level diagnosis module and a dual-mode trigger communication module. The dual-mode trigger communication module independently and in parallel controls uploading of deep feature data according to event triggering and periodic triggering conditions. The edge server is provided with a synchronous sampling module, a feature fusion module and a global diagnosis module, which are used for aligning and fusing multi-source heterogeneous data on a unified time axis, and performing system-level fault diagnosis. The application guarantees real-time response to sudden faults and continuous monitoring of system states through dual-mode triggering, realizes efficient resource utilization and accurate identification of cross-component implicit faults through a hierarchical collaborative architecture, and significantly improves the comprehensive performance of fault diagnosis of complex industrial systems.

The application belongs to the technical field of Internet, and particularly relates to an industrial Internet cross-domain metadata trusted fusion method and system, comprising the following steps: collecting structured metadata, time series metadata and relationship metadata of each industrial domain node, and constructing an intra-domain metadata graph based on field attributes and call relationships; performing semantic coding and time series coding on the intra-domain metadata graph, obtaining corresponding semantic representations and time series representations, and calculating inter-field consistency; identifying stable field clusters, drift field clusters and abnormal nodes according to the inter-field consistency in each industrial domain node; and performing segmented aggregation on the stable field clusters and the drift field clusters by each industrial domain node to generate anchor field summaries and drift trajectory summaries. The application combines metadata graph coding, field clustering and federal dynamic weighting, and realizes industrial cross-domain metadata private trusted fusion through abnormal compensation correction.

The application discloses a transformer state monitoring and data transmission method, system, device and medium based on cloud edge cooperation, belongs to the technical field of power equipment monitoring, and comprises the following steps: collecting transformer data through an edge layer; judging whether matched fault physical characteristics exist in a fault characteristic library; triggering a diagnostic rule engine to obtain a first diagnostic result when the matched fault physical characteristics exist; calling a lightweight diagnostic model to obtain a second diagnostic result; calculating the final probability of various faults according to the first diagnostic result and the second diagnostic result; determining a health state according to the final probability; determining a data transmission level according to the health state; determining data to be transmitted according to the data transmission level; predicting available bandwidth and determining a transmission mode; and transmitting the data to be transmitted from the edge layer to a cloud layer. Through the cloud edge cooperation architecture and the data hierarchical transmission mechanism, the application meets the real-time requirement of data transmission and maintains the fault diagnosis capability when communication is interrupted.

This application discloses a privacy-preserving feature extraction method and system applicable to data base generation, relating to the field of IoT privacy protection technology. The method includes: operating in a first power consumption mode and with a first computational precision to acquire environmental perception data and obtain a complexity level; if the complexity level exceeds a first preset threshold, waking up a second feature extraction unit to extract first structured feature data and uploading it to a cloud data base; if the confidence score of the first structured feature data is lower than a second preset threshold, extracting local area data and uploading it to the cloud data base; performing refined identification on the local area data to generate second structured feature data and storing it in the cloud data base. This solves the technical problems of insufficient feature extraction accuracy, excessive power consumption, and high bandwidth pressure in existing vehicle-side applications due to edge computing power limitations.

The present invention relates to the technical field of automated maintenance operations in power systems. Specifically, it relates to a complete set of operation systems and methods for power verification and grounding wire hanging and removal based on an unmanned aerial vehicle (UAV). The method includes: determining whether the transmission wire is charged, and generating a permission signal after confirming that there is no electricity; under the trigger of the permission signal, controlling the UAV to perform the operation of hanging or removing the grounding wire, and identifying and discriminating the state of the grounding wire device during the operation; monitoring the operation process in the steps of hanging and removing the grounding wire in real time, and transmitting the operation status and associated operation site images to the ground terminal. Through the present invention, a systematic process integrating power verification, state identification, and operation monitoring is achieved, realizing full-process automation and intelligence from power verification to hanging and removing operations and then to process monitoring, improving operation safety and efficiency.

This invention relates to a handheld integrated multimodal diabetic foot screening terminal and a cloud-edge-device collaborative screening system. It uses Time-of-Flight (ToF) and Induction Memory (IMU) fusion to estimate the relative pose and motion state of the terminal and the foot in real time, constructing a joint stability criterion based on distance, angle, and jitter. A three-dimensional mesh model of the foot is reconstructed based on the ToF depth map, mapping multispectral and thermal textures onto the three-dimensional surface and unfolding it onto a standard two-dimensional plane. Combined with distance-squared compensation, incident angle compensation, and low-confidence region masking, surface effects and uneven illumination are suppressed. The terminal uses a neural network acceleration unit to run a lightweight artificial intelligence model, outputting risk level, suspected lesion location, and model uncertainty. When uncertainty or quality control rules are triggered, only anonymized and encrypted difficult data packets are selectively uploaded to the cloud for human-in-the-loop annotation and retraining. This invention significantly improves the consistency and accuracy of screening under handheld imaging, and is suitable for mobile scenarios such as bedside, primary healthcare, and home follow-up.