264 results about "Aggregate data" patented technology

The invention discloses a material supply and resource recovery collaborative scheduling method and system, and belongs to the technical field of logistics scheduling, and the method comprises the steps: obtaining a material supply instruction and a garbage recovery instruction, carrying out the image recognition of a building garbage picture, obtaining the garbage attribute, and generating a demand instruction library; the method comprises the following steps: establishing a feature knowledge base, setting a spatial clustering method, carrying out spatial clustering and time window screening, carrying out geographic coordinate analysis and time sequence sorting on material demand points and recovery points, generating an initial task pool, setting a loading matching method, and generating a material supply and recovery loading schematic diagram according to building material and garbage attributes; a circulation path is planned, a path planning method is set, an ant colony algorithm is used for initial path planning, a monitoring feedback method is set, data are returned in real time, the running state of the vehicle is monitored, and an alarm is given out immediately once abnormity is found; and the sorted and regenerated aggregate data is synchronized to a building material database, a resource feedback method is set, a reverse transportation task is identified, and a material supply and resource recovery closed loop is formed.

A data intake and query system can ingest and index large amounts of data using one or more ingestors and indexers. The ingestors can ingest incoming data, use it to generate events, and communicate the generated events to a message bus. Indexers can monitor their capacity to process additional groups of events. Based on a determination that an indexer has capacity to process one or more groups of events, the indexer can request one or more messages from the message bus, and process the events associated with the one or more messages.

A network management system includes a memory and processing circuitry in communication with the memory. The processing circuitry is configured to obtain connection event data. The connection event data indicates a plurality of disconnection events. The processing circuitry is also configured to generate, from the connection event data, aggregate data according to a plurality of network scope levels and detect, based on the aggregate data, one or more network anomalies. Additionally, the processing circuit is configured to determine, based on the aggregate data, whether a root cause of the one or more network anomalies is associated with each network scope level of the plurality of network scope levels and output an indication of the determined network scope level associated with the root cause or performing a remedial action to address the root cause at the determined network scope level.

A system and method for combining data from disparate business intelligence systems and data sources. The method includes aggregating data in real-time across multiple, disparate data platforms of more than one third party, by mapping nonmatching data parameters used in the different platforms to a common data field. The business intelligence systems are queried to identify responsive data fields, which are then meshed in a translation and / or unification module into the common data field for display. The meshing of the data allows for efficient filtering according to user inputs. The system and method further include applications to allow users to create parameter mappings for the data meshing.

Evaluation system for obtaining and analyzing user interaction and physiological data to provide adaptive feedback, comprising: a portable multi-sensor device comprising: an electroencephalography sensor designed to measure the user's brainwave signals; and a galvanic skin response sensor designed to measure skin conductivity, which indicates the user's stress level; an interactive assembly device designed to recognize the user's assembly actions and generate corresponding assembly data; a computing device in communication with the wearable multi-sensor device and the interactive montage device, the computing device configured to receive and combine the brainwave signals, the skin conductance, and the montage data. Analyze the combined data in real time to create an estimate of the user's cognitive state and provide adaptive feedback to the user based on the cognitive state estimate via at least one output module. wherein the computing device is further configured to store the brainwave signals, the skin conductance, the compilation data, and the cognitive state estimate in a database for later retrieval and review.

The invention discloses an enterprise digital operation real-time data analysis method based on big data, and particularly relates to the field of data analys.The enterprise digital operation real-time data analysis method comprises the steps that enterprise operation data are collected in real time through a multi-protocol adapter, abnormity is dynamically cleaned and detected, and data standardization is achieved in combination with statistical process control and BERT sentiment analysis; in the hierarchical stream processing architecture, edge nodes pre-aggregate data and filter anomalies, a center engine dynamically divides time windows to generate minute-level / second-level indexes, and a self-adaptive rolling window and dual-threshold session cutting support inventory monitoring and user behavior analysis; the incremental machine learning model updates prediction in real time based on a sliding window, screens a dynamic optimization decision tree through Hoeffering splitting conditions and feature importance, and triggers fine tuning or full training when data distribution drift is detected; and the cross-source data association engine fuses real-time and historical data, calculates a KPI anomaly score, and triggers hierarchical early warning.

The invention relates to the technical field of intelligent traffic, in particular to a traffic abnormal event dynamic detection method and system based on trajectory analysis, and the method comprises the steps: receiving original space-time trajectory data; preprocessing the original spatio-temporal trajectory data, and mapping the original spatio-temporal trajectory data to a road section sequence of a road network through a map matching algorithm; constructing a behavior model based on the track sequence after map matching, learning the track sequence of the normal behavior mode on the road section, and establishing an observation emission model and a state transition matrix; in the online stage, the log-likelihood value of an observation sequence and / or the similarity between the observation sequence and a normal behavior pattern cluster are / is calculated for a real-time track in a set sliding window, and when the log-likelihood value and / or the similarity exceed a set threshold value, the track is marked as abnormal; performing time-space aggregation on abnormal trajectories of the same road section or intersection in unit time according to single vehicle abnormality judgment, and triggering group abnormal event alarm when aggregation data exceed a preset value.

A system is provided for use with over-the-air (OTA) analytic data corresponding to OTA aggregate data associated with an OTA push of a software update to a plurality of devices. The system includes: a data receiver configured to receive the OTA aggregate data; a memory having instructions stored therein; and a processor configured to execute the instructions stored in the memory to cause the system to: store the received OTA aggregate data into the memory; analyze the OTA aggregate data to determine an optimized time period for the OTA push; predict a future OTA push time period based on the optimized time period; and generate a future OTA push instruction based on the predicted future OTA push time period.

The invention relates to a photovoltaic panel control management system, and belongs to the technical field of photovoltaic power generation. The system comprises an edge sensing unit, a string optimization unit and a central control unit. The edge sensing unit is deployed on each photovoltaic panel and is used for acquiring electrical parameters, environmental parameters and physical states in real time; the string optimization unit is connected with the edge sensing unit in the same string and executes dynamic working point matching and fault isolation; and the central control unit is connected with the string optimization unit through a communication network to execute whole-station monitoring and strategy scheduling. The string optimization unit is divided into a plurality of communication areas, each area is provided with an area agent node for gathering data, and the data is transmitted to the central control unit in a random backoff mode so as to avoid channel conflicts. And when the regional agent node fails, the child node is automatically switched to the direct connection communication mode. The system improves the power generation efficiency and reliability of a photovoltaic system through a multi-layer architecture and an intelligent communication mechanism.

The invention relates to a segmented aggregated hash table read-write method and system based on a graph database, and the method comprises the steps that an original hash table is separated into a hash entry table and a data load block, the hash entry table is used for storing hash entry data, and the data load block is used for storing aggregated data. And in response to the received write-in data instruction, positioning the hash entries in the hash entry table according to the hash value of the write-in data. Based on the data storage state of the hash entry, the write data is stored in the data load block through linear detection, and the hash entry is updated. And in response to receiving a data reading instruction, obtaining target aggregation data corresponding to the read data through linear detection according to the hash value of the read data. Therefore, the read-write performance of the hash table is improved, and the problem of low performance in the conventional read-write process of the hash table in a large data volume scene is solved.

The invention relates to a terminal protection and baseline inspection method and device based on a complex asset network, and the method comprises the steps: constructing a multi-dimensional holographic network topological graph, and determining the position association of a terminal; the method comprises the steps of semantic analysis of data, risk feature mining and database establishment, generation of an intelligent protection strategy according to a terminal role, a data sensitive level and risk assessment, generation of a dynamically adjustable baseline template by summarizing data, real-time monitoring of a terminal during operation, intelligent check by comparing the template and the strategy, rapid early warning of abnormity, and finally feedback of monitoring data. And optimizing a risk library, a strategy and a template. According to the scheme, the risk can be accurately identified, efficient protection and inspection are realized, and the security of the complex asset network terminal is improved.

The invention discloses a city platform and method based on a national network identity authentication public service, and relates to the field of smart cities, and the method comprises the steps: firstly completing user identity authentication through the national network identity authentication public service, so as to establish a trusted access basis; and constructing a data request contract, and storing an evidence after a user confirms authorization, thereby forming a transparent and traceable authorization mechanism. And then generating a data token for limiting access based on a user authorization range, obtaining required cross-source data based on a unified data aggregation service, realizing on-demand aggregation and safe circulation of the data, automatically auditing the aggregated data through business logic to obtain an auditing result, and finally returning the auditing result to the user. In this way, the business process can be simplified, the problems of repeated authorization and data islands are solved, meanwhile, the user data control right is guaranteed, and the intelligence and efficiency of urban platform business handling are improved.

A distributed mobile network traffic data decomposition and forecasting computer-implemented method, comprising:using a geo-location preserving mobile network representation. Locations of mobile network elements are received and converted into a graph representation. Relative distances between adjacent network elements are preserved using respective weights on graph edges; input data is received comprising aggregate network traffic data from network elements corresponding to the network elements locations. The aggregate data includes traffic data corresponding to a plurality of services operating over the network. A graph-based neural network based on the geo-location is used, preserving mobile network representation and configured to capture spatial and temporal correlations in the input data, including at least a spatio-temporal concentration block (STCB) and a parallel prediction block (PPB); loss functions train the graph-based neural network using the input data, to provide network per-service traffic forecasting, the loss functions including an operator cost function configured to capture operator costs.

Some aspects relate to technologies for employing metadata identifiers for part item listings on a listing platform to generate inventory intelligence. In accordance with some aspects, textual analysis of listing data for each of a plurality of part item listings on a listing platform is performed to assign a metadata identifier to each part item listing. The metadata identifier for each part item listing comprises a combination of an inventory segment identifier, a category identifier, and fitment data. For a first metadata identifier, a set of part item listings having the first metadata identifier is identified. Demand data and / or supply data is aggregated for the set of part item listings to provide aggregated data. A user interface with one or more metrics is generated using the aggregated data, and the user interface is communicated over a network to a computing device for presentation.

The invention provides a method for monitoring the temperature of a semiconductor process cavity. The method comprises the following steps: S1, providing a monitoring process program for monitoring the condition of the process cavity; s2, selecting monitoring process temperature control output curves, calculating an output temperature average value avgs and a standard deviation sigma s after each step of each monitoring process temperature control output curve is stable, calculating a total average value avg0 and a standard deviation sigma 0 of each step of all the monitoring process temperature control output curves in the period based on each avgs, and calculating unstable time Ts to obtain sample data; s3, removing abnormal data in the sample data to obtain summarized data; s4, according to the summarized data and a calculation rule, the unstable time T, the maximum average value, the minimum average value, the average standard deviation and the maximum standard deviation of all the steps are obtained through calculation, and management and control data are obtained; and S5, setting a management and control rule according to the management and control data, and monitoring the temperature of the process cavity. High-sensitivity and low-false-alarm-rate monitoring of temperature control output in the production process is achieved.

The invention discloses a power equipment control method and device and a nonvolatile storage medium. The method comprises the following steps: collecting target power data and target environment parameters corresponding to power equipment in a target park; based on the edge computing terminal, aggregating the target power data and the target environment parameters to obtain aggregated data; based on the cloud, predicting future target power data of the power equipment according to the aggregated data; based on the cloud, generating an optimization instruction according to the future target power data and a preset power optimization target; and issuing the optimization instruction to the power equipment. The technical problems of energy waste and poor management effect caused by difficulty in overall management and control of multiple pieces of power equipment in the park at present are solved.

The embodiment of the invention provides a railway vehicle-mounted sensing system data acquisition system and method based on multi-source triggering, and the system comprises a satellite communication system which is used for obtaining the current position information of a train in real time; the vehicle-mounted ATO system is used for acquiring current state information and running condition information of the train; the ground trackside sensing unit is used for sensing the ground trackside environment through sensing equipment deployed along the railway and acquiring ground trackside environment sensing information; the vehicle-mounted sensing system is used for sensing a headroom area in front of running of a train through a vehicle-mounted sensor, acquiring sensing information of the headroom area in front of running, acquiring information of the satellite communication system, the vehicle-mounted ATO system and the ground trackside sensing unit, and sending the information to the data acquisition cloud platform; and the data acquisition cloud platform is used for acquiring the information sent by the vehicle-mounted sensing system, performing data summarization, and issuing data acquisition triggering information to each train according to data acquisition requirements based on the summarized data.

The invention discloses a batch data reconciliation method and device, equipment, a storage medium and a product, and relates to the technical field of data comparison, and the batch data reconciliation method comprises the steps of obtaining database batch data in response to a batch reconciliation instruction; summarizing the database batch data to obtain first to-be-checked summarized data; obtaining second to-be-checked summarized data, checking the first to-be-checked summarized data with the second to-be-checked summarized data, and determining a checking result; and if the checking result is inconsistent, performing detail checking, confirming difference data, updating and supplementing the first to-be-checked summarized data based on the difference data, and returning to the step of comparing the first to-be-checked summarized data with the second to-be-checked summarized data until the checking result is consistent, and confirming that the batch reconciliation result is a balance reconciliation result. According to the method and the device, the batch data of the database is summarized for checking, and the account checking data is aligned through detail checking and supplementing, so that the account checking efficiency is improved.

An improved in-vehicle infotainment (IVI) system and methodology facilitating the display, computation, receipt and transmission of enhanced data elements and data files. System and methodology comprising an improved IVI system with an enhanced series of software and firmware capable of communicating with external data servers, processing enhanced protocols, transmitting data elements in report form with data attachments, and displaying the received enhanced data elements onto callout icons overlaid onto a GPS navigation interface. Additional system and methods include protocols for external servers to receive, encode, decode, compress, decompress, store, compute and transmit emergency reports and aggregate data files.

The invention relates to the technical field of operation management, and discloses an electric power spot market environment analysis system for virtual power plant management. Comprising the steps of screening out effective participants from original participants, analyzing a real-time stability level of an electric power spot market, collecting environment summary data of the electric power spot market in an analysis interval, predicting a supply and demand state value of a next analysis interval, identifying management data from the environment summary data, and analyzing the management data. Providing management suggestions for effective participants in the virtual power plant; compared with the prior art, the method can improve the environment analysis threshold of the electric power spot market, can predict whether the future supply and demand state of the electric power spot market is balanced or not in advance, and provides management suggestions for the power supply party and the power utilization party in the virtual power plant according to the prediction result. Therefore, the negative phenomenon that the environment of the electric power spot market is unbalanced is avoided, and the hysteresis caused by the real-time analysis and judgment mode of the current electric power spot market is also solved.

Techniques for optimized aggregation of a data source are described. A server device receives a request from a data source for aggregating thereof and compares each of a set of hardware metrics corresponding to hardware configuration of the server device with a corresponding threshold hardware metric. The server device is classified as a small-configuration device or a high-configuration device and complete aggregation of the data source or partial aggregation of the data source is allowed based on the classification. A set of utilized hardware metrics of the server device that corresponds to hardware resources of the server device that is being utilized is determined. One or more operations corresponding to the transmission of data of the data source that is to be performed by the server device is blocked if at least one of the set of utilized hardware metrics is higher than a corresponding threshold operational soft limit.

The invention discloses a safety early warning method, device and equipment, and the method comprises the steps: a lightweight model carries out the function abnormality detection according to a fusion result, and transmits a function abnormality detection result and collection data to a cloud server through a network transmission layer; the cloud server summarizes the collection data and the anomaly detection results sent by the edge nodes to obtain summarized data; and the cloud server carries out overall anomaly detection according to the summarized data through a deployed detection model, and carries out safety early warning according to an overall anomaly detection result. According to the method, initial anomaly detection is carried out by deploying a lightweight model at an edge node, and real-time response is carried out according to detection data, so that an industrial scene with a high real-time requirement is met, and multi-dimensional sensor data can be effectively fused to improve the accuracy of monitoring and early warning; the collected data and the detection result of each edge node are summarized through the cloud server so as to carry out anomaly detection on the whole, thereby improving the comprehensiveness and the accuracy of safety early warning.

To provide a server for supporting calculation of an index data set related to an ESG.SOLUTION: A program for calculating an index data set related to an ESG, the program causes a server (2) to execute: a transmission step of transmitting an input request of ESG-related data necessary for calculating the index data set to a request destination terminal (4) on the basis of the index set related to the ESG designated by a request source terminal 3; an acquisition step of acquiring aggregated data calculated in the request destination terminal (4) on the basis of the ESG-related data input to the request destination terminal (4) that has received the input request; and a calculation step of calculating the index data set on the basis of the acquired aggregated data.SELECTED DRAWING: Figure 1

The invention discloses a safety production performance evidence storage verification method based on ZKP and multi-dimensional verification. The method comprises the steps of daily data aggregation and commitment generation, zero knowledge proof generation, optimistic summarization and batch uplink, data availability guarantee, time trigger automatic presumption and multi-dimensional verification execution. According to the method, zero-knowledge proof, optimistic summary, data availability sampling, Vickers tree and other frontier cryptography and block chain capacity expansion technologies are fused, and the method has the advantages of low cost, high efficiency and verifiability.

The invention relates to the technical field of electrical variable measurement, in particular to an intelligent ammeter data real-time acquisition system, which comprises a sensing module, a network transmission module and a management module, and is characterized in that the sensing module comprises an ammeter unit, a processing unit, a gathering unit and a storage unit, and the ammeter unit acquires voltage, current, power and electric energy pulse of a user in real time; the processing unit performs edge processing on the electrical parameters to obtain processing data; the summarizing unit summarizes the processing data of the users in the divided areas to obtain summarized data; the storage unit stores the summarized data and obtains local user data; the network transmission module transmits the local user data to the management module; the management module is used for controlling the operation of other modules, encrypting the local user data and preventing the local user data from being tampered, the acquisition system acquires the electric parameters of the user electric meter in real time and transmits the electric parameters to the management platform through the network, manual meter reading is not needed, and the data acquired in real time is more accurate.

An information processing device according to the present invention includes: a memory; and at least one processor coupled to the memory. The processor performs operations. The operations include: generating, based on inference target data include a detection target object, aggregate data smaller than the inference target data; and applying the aggregate data to a trained model to infer a first region that is a region of the detection target object in the aggregate data, generating packed data that is data packed with the first region or a region of the inference target data, applying the packed data to a trained model to infer a second region that is a region of the detection target object that is included, and inferring the detection target object in the inference target data based on the second region.

A method for providing alarm-related information in a security system comprises obtaining alarm indication(s) associated with alarm(s) triggered at a monitored location, obtaining media data related to the alarm(s), the media data acquired during a period of interest by media device(s) deployed at the monitored location, executing machine learning model (s)to obtain a textual description of event(s) captured in the media data, and outputting the textual description. A method for summarizing data comprises obtaining a data summary request, determining a period of interest associated therewith, identifying events that occurred at the monitored location during the period of interest, obtaining media data related to the events, the media data acquired by the media device(s) during the period of interest, executing machine learning model(s) to obtain, based on the media data, textual descriptions of events, executing the machine learning model(s) to generate summary(ies) based on the textual descriptions, and outputting the summary(ies).

The invention relates to the technical field of vehicle part strength simulation analysis verification, and discloses a strength load processing method and system based on a virtual test field, and the system comprises a model construction module, a data configuration module, a simulation execution module, a load processing core module, and a finite element interface module. The method comprises the following steps: constructing a virtual test field pavement model and a multi-body dynamic model; calling a programming tool to process the file; further converting the sub-working-condition load into a standardized load header file required by finite element strength analysis, and finally driving a finite element solver to execute batch working condition calculation and output stress-strain summarized data of the parts. According to the method, intelligent normalization processing of load data, dynamic coverage of critical working conditions and multi-system seamless integration are achieved, the efficiency and precision of component strength verification are improved, the development period is shortened, and a unified comparability reference is provided for fatigue life evaluation.

The invention provides a periodic statistical data metering method and device, equipment, a medium and a program product. Relates to the technical field of computers. The method comprises the following steps: for each subject, acquiring configuration parameters configured by a user for each subject feature from a data system, and recording the configuration parameters in an accessible space; accessing the accessible space to determine a subject source corresponding to the subject and a corresponding statistical deadline, querying a target data value corresponding to the periodic statistical data from the subject source, and determining statistical results of the corresponding target data values under different statistical deadlines based on the target data value and the corresponding statistical deadline; and determining a metering result of the periodic statistical data based on the statistical results of the target data values under different statistical deadlines and pre-counted summarized data. According to the scheme, efficient and accurate periodic statistical data metering can be realized under the condition that the configuration parameters are consistent with the metering range and the rules are consistent, and the reliability of the periodic statistical data is evaluated.

To optimize a server that handles frequently updated information.SOLUTION: A driving diagnosis system 1 comprises: a database 4 for storing information on detection values from vehicles; a driving diagnosis device 5A having a diagnosis unit 51 for conducting driving diagnosis on the basis of information from the database 4 and an aggregate data transmission unit 52 for aggregating and transmitting information on the driving diagnosis; and a user interface unit 6A including a monthly recommendation diagnosis unit 61 which is a second diagnosis unit, a monthly recommendation aggregation unit 62 which is a second aggregate data transmission unit, and a monthly recommendation transmission unit 63. The driving diagnosis device 5A belongs to a diagnosis server 5. The user interface unit 6A belongs to a user interface server 6 and performs diagnosis relating to a given period recommendation in the second diagnosis unit and aggregation and transmission of information relating to a given period recommendation in the second aggregation data transmission unit.SELECTED DRAWING: Figure 1