14results about How to "Reduce data transfer costs" patented technology

The invention discloses a data real-time analysis and decision-making system based on an edge intelligent Internet of Things, belongs to the technical field of Internet of Things, and aims to solve the technical problems of insufficient real-time performance, high delay, large bandwidth occupation and high dependence on a central server in data processing of Internet of Things equipment. Comprising an edge device layer, an edge computing node layer, a cloud edge collaboration module and a central server layer, each edge computing node is used for taking data after local analysis processing as input, performing prediction analysis through a local model, making a decision through a decision generation mechanism based on an analysis result, and performing cloud edge collaboration. Generating decision optimization through an adaptive decision optimization algorithm, and performing data exchange with the central server layer through a cloud edge collaboration module; and the central server layer is used for carrying out model updating based on the real situation and the analysis result corresponding to the analyzed and processed data uploaded by each edge computing node, and returning the updated model parameters to the edge computing node layer.

The invention relates to the technical field of data processing, and discloses an esophageal cancer patient nursing remote monitoring system and method capable of improving the nursing level, and the system comprises a data collection module, a personalized data transmission module, a remote monitoring center and a remote service module. The personalized data transmission module is used for predicting potential key data of a patient by using a collaborative recommendation algorithm, distributing corresponding personalized transmission parameters to the potential key data and non-potential key data in the monitoring data, and transmitting the monitoring data to the patient based on a 5G communication technology and the corresponding personalized transmission parameters; the potential key data and the non-potential key data are transmitted to a remote monitoring center; and the remote monitoring center is used for receiving the monitoring data and performing remote monitoring analysis on the nursing condition according to the monitoring data. According to the method, the doctor seeing burden of the patient can be relieved, medical staff can obtain key data in the first time, a more appropriate treatment scheme is formulated for the patient, and therefore the overall medical care level is improved.

The invention discloses a multi-sensor edge system and method based on cross-modal dynamic attention. The method comprises the following steps: S1, acquiring environment data based on multiple sensors and multi-modal input data based on an interaction module; s2, preprocessing the acquired environment data and the multi-modal input data, and performing feature extraction to obtain multi-modal feature data after feature extraction; s3, carrying out space-time dimension enhancement on the multi-modal feature data; s4, dynamically optimizing the configuration of each modal resource based on the enhanced multi-modal characteristic data obtained in the step S3; and S5, inputting the dynamically optimized modal resource information into the generative model to generate an output result. According to the method provided by the invention, the data processing flow is optimized, the data transmission delay is reduced, efficient integration and utilization of information are realized through a cross-modal dynamic attention mechanism, and the accuracy and robustness of decision making are enhanced.

The invention relates to the technical field of virtual simulation, and mainly relates to a virtual simulation model based on thermal power plant pneumatic ash conveying. A high-precision, high-performance and autonomous learning processing simulation model library is constructed, and the operation state and the optimization process of ash conveying of the thermal power plant are comprehensively simulated, so that powerful support is provided for operation of the intelligent power plant. According to the method, key technologies such as a simulation technology, a mathematical modeling technology, a three-dimensional modeling technology, a physical engine technology, a big data analysis technology and a neural network technology are mainly used. Firstly, according to relevant parameters and requirements, model construction is achieved through simulation software. And real-time data acquisition is realized through a plurality of communication protocols. The model is constructed through simulation software according to relevant parameters and requirements in combination with the actual situation of on-site physical equipment. And finally, powerful support is provided for operation of the intelligent power plant by comprehensively simulating the operation state and the optimization process of ash conveying of the thermal power plant.

The embodiment of the invention provides an industrial data collection method and device, equipment, a storage medium and a program product. The method comprises the steps of obtaining a scene configuration file of an industrial scene, determining a data set needing to be collected, further determining description information with an incidence relation in the data set, and obtaining a de-reconfiguration file corresponding to the description information with the incidence relation, and controlling an edge computing unit to collect equipment data in the industrial scene based on the de-reconfiguration file. In this way, the edge computing unit can dynamically filter redundant data in the data needing to be collected, so that the redundant data does not need to occupy the bandwidth and the storage space of the edge computing unit, the collection efficiency of industrial data can be improved, and the data transmission cost and the edge storage cost can be reduced.

The invention relates to the technical field of packaging testing, in particular to a semiconductor packaging testing optimization method and system, and the system comprises an equipment node generation module which is used for collecting packaging testing equipment data, obtaining the processing capability and connection parameters of the testing equipment data, and generating a packaging testing module; and compiling the processing capability and the connection parameters into a structured data entry representing a single device to generate a device node set. According to the invention, equipment functions and resources are integrated through equipment identification and performance evaluation, and the efficiency and accuracy of the packaging test are optimized. Through the accurate extraction of the device identifier and the measurement of the connection parameter, the coordination and resource allocation among the nodes are more reasonable, and the working efficiency of the nodes is improved. In the aspect of data flow path customization, a data transmission path is optimized according to equipment performance and requirements, and resource waste and transmission delay are reduced. Task dependence is defined, a data flow path is optimized, and data exchange between devices is accelerated.

The application discloses a power distribution network communication management method and equipment based on a 5G RedCap industrial-grade communication terminal, which receives an equipment access request through an edge terminal to match a network slice identifier, and establishes a session request with a network center; based on the session request, two-way identity authentication of the edge terminal is performed, and after the authentication, an encrypted transmission channel between the edge terminal and the network center is constructed, and multiple encryption transmission processing is performed on the data of the edge terminal; the communication link state in the data encryption transmission process is monitored in real time, when the communication link state reaches the preset network switching condition, the current communication network is switched over for hot standby switching processing; when the optimal communication link is restored, the edge terminal transmits data through double communication links in parallel within a preset transition time window, and when the preset switching condition is reached, the current communication network is switched to the optimal communication link. The method realizes the effects of reducing data transmission cost, reducing network switching delay and packet loss probability, and reliable data transmission.

The invention discloses a novel multi-agent adaptive hybrid parallel training method for a power system, and the method comprises the steps: obtaining a topological structure and network parameters of the system through building a physical simulation model of the power system; establishing tuples of a Markov decision process according to the topological structure and the network parameters to obtain a plurality of tuples; establishing a target function according to the tuples; and distributing the agents with high coupling degree to the same sub-node server or adjacent sub-node servers for training to obtain a multi-agent training result. According to the multi-agent self-adaptive hybrid parallel training method of the novel power system, the agents with high coupling degree are distributed to the same or adjacent sub-node servers for training, so that the memory and the calculation pressure of a single calculation node can be reduced; the problem that it is difficult to carry out training under the condition of adapting to a universal server cluster so as to relieve the memory and calculation pressure of a single calculation node and improve the training speed of an intelligent agent can be solved.

This invention discloses an intelligent weather phenomenon recognition method based on AI recognition algorithms, belonging to the fields of image processing and meteorological monitoring technology. The method includes: acquiring weather image data through edge devices; separating the foreground and background of the weather image data to obtain the target area; determining whether the target area triggers a weather rule based on a preset weather rule scenario; when a weather rule is triggered, inputting the target area into a pre-trained AI recognition model for recognition and analysis to obtain the weather recognition result. This invention can achieve accurate recognition of various weather phenomena such as snowfall and frost, improving the accuracy and consistency of weather phenomenon recognition, and overcoming the problems of strong subjectivity and inconsistent judgment standards in manual observation methods.

The invention relates to a data transmission method of a configuration system and related equipment thereof, and relates to the technical field of computers. A specific embodiment of the method comprises the steps of obtaining operation technology data generated by a data producer accessing the configuration system, determining a data priority corresponding to the operation technology data, and determining a target data transmission channel corresponding to the operation technology data according to the data priority; determining the data volume of the operation technology data so as to adjust the data pushing frequency of the target transmission channel according to the data volume and the transmission priority and the transmission capability corresponding to the target data transmission channel; and pushing the operation technology data to the target data transmission channel according to the data pushing frequency, and performing data transmission on the operation technology data through the target data transmission channel. According to the embodiment, the data transmission stability of the configuration system in a high data load scene is guaranteed, the data transmission cost is reduced, and the application scene of the data transmission method is expanded.

The invention relates to the technical field of image processing, in particular to a large-volume image automatic cutting method and device based on a range line, a boundary range is obtained by traversing nodes of a given polygon area, and the area occupied by the given polygon is split according to the given image size S to obtain a plurality of small areas; and then solving a public area of the given polygonal area and the preliminarily segmented small areas to obtain optimized sub-areas so as to realize accurate segmentation of the image data. According to the method, the problems of relatively high computing resource consumption and relatively low efficiency during large-volume image data processing in the prior art are effectively solved, and rapid access and analysis of the large-volume image data are realized within the storage capability and processing capability range of a computer. According to the invention, the data transmission and storage cost of the large-size image is reduced, and under the condition that the network bandwidth and the storage space are limited, the rapid transmission and storage of the large-size image data are realized, and the data transmission and storage space is reduced.

The embodiment of the invention relates to the technical field of vehicles, and discloses a data processing method and device, a vehicle and a computer readable storage medium, and the method comprises the steps: obtaining first CAN data corresponding to at least one CAN channel, processing the at least one piece of first CAN data according to a pre-obtained configuration file, obtaining a target file, and storing the target file in a server; the configuration file records an identifier of at least one to-be-collected CAN and a compression mode of data corresponding to the at least one to-be-collected CAN, and then the target file is uploaded to the cloud. By applying the technical scheme of the invention, the size of the network data packet can be reduced, the data transmission flow is saved, and the data transmission cost is reduced.

The invention discloses a target detection method, an electronic device and a computer readable storage medium, the method is applied to an edge device in a target detection system, the target detection system comprises the edge device and a plurality of front-end devices, and the method comprises the following steps: obtaining structured information matched with a target in a target scene sent by the front-end devices; based on the to-be-detected structured information of the to-be-detected target, obtaining a reference target meeting a preset distance condition with the to-be-detected target, obtaining reference structured information of the reference target, and constructing a feature map by using the to-be-detected structured information and the reference structured information; obtaining a target feature vector of a to-be-detected target and a reference feature vector of a reference target in the feature map; and determining target detection positions of the to-be-detected target and the reference target in the global coordinate system based on the target feature vector and the reference feature vector. According to the scheme, the detection cost of target detection can be reduced, and the precision of target detection can be improved.

The present application relates to the technical field of charging piles, and discloses a charging pile energy management method, device, equipment and storage medium. The method includes: performing swarm-style data collection on the charging pile network to obtain a distributed data set; adaptively compressing the distributed data set based on a hybrid compression algorithm of wavelet transform and autoencoder to obtain a compressed data set; reconstructing the compressed data set through a graph neural network to obtain an optimized data set; performing multimodal fusion prediction analysis on the optimized data set to obtain a charging demand prediction result; dynamically dividing the charging pile network into microgrids and coordinating the scheduling according to the charging demand prediction result to obtain a target energy allocation plan. The present application improves the accuracy of charging pile energy allocation.