383 results about "Aggregate data" patented technology

A system for real-time data aggregation and analysis within an Internet of Things (IoT) network, consisting of: a multitude of IoT sensor nodes configured to collect data from multiple sources, each sensor node comprising a data acquisition unit for capturing data in real time and a local processing unit for preprocessing the captured data by performing data filtering, normalization and compression prior to transmission; a centralized aggregation server communicating with the multitude of IoT sensor nodes, the aggregation server comprising: a data aggregation module configured to receive, integrate, and synchronize pre-processed data streams from the multitude of sensor nodes, thereby enabling consolidated data storage; a timestamped metadata indexing unit coupled with the data aggregation module and configured to add metadata to each data entry, including a unique identifier, a geographic location, and a timestamp; an analysis engine integrated into the aggregation server, which includes the following: a data processing unit configured to perform real-time analysis of the aggregated data by applying pattern recognition and anomaly detection techniques and to generate processed results based on predefined parameters; a predictive analytics module that is connected to the data processing unit and configured to perform predictive modeling tasks by extrapolating trends from historical and real-time data; a communication interface connected to the aggregation server, configured to enable bidirectional data exchange with external monitoring devices, user interfaces, or remote management systems via secure communication protocols; and a dynamic load balancing unit embedded in the aggregation server, configured to dynamically distribute computing resources between the data processing unit and the predictive analytics module depending on data volume and complexity.

A method for processing a query for data stored in a distributed database includes receiving, at an edge device, the query for data stored in the distributed database from a query device. The method includes causing, by the edge device, the query to be stored on a dynamic ledger maintained by the distributed database. The method includes detecting, by the edge device, that summary data has been stored on the dynamic ledger. The method includes generating, by the edge device, an approximate response to the query based on the summary data stored on the dynamic ledger. The method includes transmitting, to the query device, the approximate response.

The invention relates to the technical field of circuit board detection, in particular to a circuit board sensor nondestructive testing method based on big data, which comprises the following steps of: acquiring temperature, pressure, current and voltage data of key positions of a circuit board sensor, sending the data to a central database through real-time communication for summarizing, and synchronously performing data preliminary screening; and checking the integrity and availability of the data to form sensor summarized data. According to the method, the difference value between each data point and the adjacent data point is calculated, and the variation amplitude of the continuous data points is monitored, so that tiny abnormal fluctuation can be more sensitively captured, potential fault signals can be marked, an abnormal mode can be compared with a recorded fault case, and the fault mode and the frequent occurrence area of the fault mode can be identified; the fault mode is directly associated with the operation condition, the accuracy of fault prediction is enhanced, the dynamic adaptability of the detection system is ensured through monitoring adjustment of detailed fault analysis, and the efficiency of fault response is remarkably improved.

The embodiment of the invention discloses a boiler anti-wear and anti-explosion online early warning system based on a sensor and big data, and relates to the technical field of boiler safety monitoring, and the system comprises a sensor module which collects operation parameters in a boiler in real time; the data acquisition module is used for summarizing various data acquired by the sensor module; the data processing module is used for carrying out processing, analysis and trend prediction on the collected real-time data through a big data analysis technology; the early warning module is used for evaluating the anti-abrasion and anti-explosion risk of the boiler according to the analysis result output by the data processing module and generating an alarm when a risk threshold value is exceeded; and the display and interaction module is used for displaying the boiler operation state, the risk assessment result and the early warning information to an operator. According to the invention, intelligent monitoring and risk early warning of boiler equipment can be realized, and through accurate data analysis and prediction, the operation safety of the boiler can be improved, the occurrence of safety accidents can be reduced, and the maintenance strategy of the boiler can be optimized.

The invention particularly relates to a data analysis method and system. The method comprises the steps of extracting original data corresponding to a target service from a target data source according to a pre-configured data extraction strategy of the target service, loading the original data to an operation data storage layer of a data warehouse, and storing the original data; operating a data storage layer to output the original data to a detail data layer; the detailed data layer performs data preprocessing on the original data to obtain basic data and outputs the basic data to the summarized data layer; the summarizing data layer performs aggregation processing on the basic data according to a current data processing task corresponding to the target business, obtains structured data corresponding to the target business, and outputs the structured data to the application data service layer; and the application data service layer performs data analysis on the structured data according to the service configuration information corresponding to the current data processing task, and outputs a corresponding data analysis result. According to the scheme, efficient and accurate data management and analysis can be realized.

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.

The present invention discloses a concrete intelligent material system, including a raw material detection module, which obtains aggregate data of sand and gravel aggregates in the raw materials of concrete; a concrete batching module, which is connected to the raw material detection module, obtains aggregate data of sand and gravel aggregates, and adopts a net slurry rheological threshold algorithm to obtain mixing image information; a ratio adjustment module, which is connected to the concrete batching module, obtains mixing image information, and adjusts the ratio of concrete to obtain ratio adjustment information; a feedback module, which is connected to the concrete batching module, and feeds back the ratio adjustment information to the concrete batching module. Through the above scheme, the present invention has the advantages of simple logic, accuracy and reliability, and has high practical value and promotion value in the field of concrete material management technology.

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 information processing device has an acquisition means for acquiring (1) expense data indicating the expenses invested in taking courses to develop members of an organization, (2) attendance data indicating the members' attendance at the courses, and (3) skill data indicating the skills the members acquired as a result of taking the courses, an aggregation means for aggregating the expenses invested in acquiring the skills as (4) aggregated data for each attribute of the members, and an output means for outputting the aggregated data.

An integrated circuit includes a set of N unit analog-to-digital converters (ADCs) having a common architecture, and which provide an aggregate data rate. Moreover, the integrated circuit includes control logic that selects subsets of the set of N unit ADCs in order to realize sub-ADCs of different data rates that can each be an arbitrary integer multiple of an inverse of N times the aggregate data rate of the N unit ADCs. Furthermore, the control logic may dynamically select the subsets on the fly or on a frame-by-frame basis. This dynamically selection may occur at boot time and / or a runtime. Additionally, the given different data rate may correspond to one or more phases of a multi-phase clock in the integrated circuit, where the multiphase clock may include a number of phases corresponding to a number of possible subsets, and given selected subsets may not use all of the available phases.

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.

The invention relates to the technical field of privacy protection, in particular to a bidirectional privacy protection method and system for an Internet of Vehicles intelligent agent, and the method comprises the steps: obtaining task constraint information and task personal information after a task distribution instruction is detected, the method comprises the steps of sending task constraint information and task personal information to an Internet of Vehicles crowdsourcing platform based on a preset block chain network, collecting an Internet of Vehicles agent list returned by the Internet of Vehicles crowdsourcing platform, determining an application Internet of Vehicles agent set and agent personal information, obtaining task demand information of a task publisher after a task execution instruction is detected, and sending the task demand information to the Internet of Vehicles crowdsourcing platform. And encrypting the task demand information to obtain the encrypted task demand information, performing request processing on the encrypted task demand information according to the application of the Internet of Vehicles intelligent agent set to obtain aggregated data, and sending the aggregated data to the target device for control display. According to the invention, the data interaction efficiency of the task publisher and the Internet of Vehicles intelligent agent is improved.

A user interface (UI) for visualizing search data provides techniques for grouping and organizing aggregate data that shows the categories of topics included in search queries from a large number of individual users. Raw search queries are categorized into one of a number of topical categories. The search queries are assigned to a geographic location based on geolocations of computing devices generating the search queries. The UI presents a map that shows the number of search queries per topical category for each geographic location displayed in the current UI view. As a result of this UI design, a user can easily understand the interaction between geographic location and frequency of search query topics. Trends in the geographic distribution of searches and in the categories of topics searched are also easily understood from this UI design by changing the time range of the search queries displayed.

Systems and methods for maritime asset management. One system may comprise at least one data acquisition device; at least one server disposed in digital communication with the at least one data acquisition device; a cloud infrastructure configured to aggregate data and generate at least one maintenance insight; and at least one machine learning algorithm. Other systems may also comprise a software application, wherein the software application is configured to receive data from the at least one user and upload the data to the cloud infrastructure, the cloud infrastructure further configured to generate at least one other insight. Moreover, some embodiments of the present invention include a method comprising collecting data; sending the data to at least one server; uploading the data to a cloud infrastructure, the cloud infrastructure comprising at least one machine learning algorithm; analyzing the data; and generating at least one insight.

A preferred aggregate store for a multidimensional database receives and stores intermediate data generated as part of a larger query for avoiding repetitive or redundant data retrievals incurring costly data paths. Aggregates include intermediate tables and sets of data, often generated from a join of two or more distinct data tables, combined for generating a query result. In the event an aggregate is called for, certain storage locations may be preferable to others due to network distance, fees for storage and processing, as in the case of cloud storage, or write accessibility. Designation of a preferred aggregate store ensures that aggregates called for by the query processing are stored in a beneficial location for cost and efficiency.

A system is provided for automated computer software release validation and management. In particular, the system may receive and aggregate data from various computing resources within the network environment, such as computing applications. Based on the data, the system may determine which resources may be affected by a software release that is set to be deployed to the production environment. The system may further receive user inputs in the form of artifacts associated with one or more checkpoints used in a validation process associated with the software release. The system may then, through a reporting engine, provide a visualization of the data and checkpoints through a dashboard to provide a real-time status of the validation process. In this way, the system provides an efficient and transparent way to validate and manage computer software releases.

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.

The invention discloses an aggregation storage method and device for data return, equipment and a medium. The method comprises the steps that when real-time working condition data of a target vehicle is received, the type of a current part is recognized, and all target working condition configuration protocols associated with the type of the current part are recognized in a pre-constructed working condition configuration protocol library; setting a storage time point according to the return time of the real-time working condition data and the aggregation time point set of each target working condition configuration protocol, and caching the real-time working condition data; when the system time reaches a target time point in the aggregation time point set, identifying a plurality of pieces of cache working condition data; and after the multiple pieces of cached working condition data are merged into one piece of aggregated data, the aggregated data and the target vehicle are stored in a distributed database in an associated mode. According to the embodiment of the invention, the working condition configuration protocol is constructed, so that the working condition data which are originally scattered and are returned at high frequency are aggregated and stored, scattered data entries in big data storage are reduced, and the storage capacity demand is reduced.

The invention relates to the technical field of data analysis, in particular to a carbon emission monitoring management system based on industrial Internet of Things, which comprises a data acquisition module, a data processing module, a monitoring plan module, a parameter verification module and an enterprise management module. The system obtains summarized data of development data and carbon emission data of an enterprise through the data acquisition module, obtains carbon emission parameters through the data processing module, issues a carbon emission reduction plan through the plan issuing unit, and detects and analyzes the execution condition of carbon emission reduction through the plan monitoring unit to obtain plan execution parameters. The carbon emission reduction parameters and the plan execution parameters are verified through the parameter verification module, enterprises are classified and managed according to verification results, the management effect is more efficient, the carbon emission reduction plan is adjusted according to the verification results, and the carbon emission reduction plan is more adaptive to the development mode of the enterprises.

Systems and methods for location-based assignment of client device data are disclosed. A system can maintain data records associated with a player profile. The system can receive a request to access the player profile from a client device and determine location data of the client device. If the location data satisfies a first category, the system can filter the data records based on a data record type to generate a subset of data records and generate a first aggregate data record value based on a data record value of the subset of data records. If the location data satisfies a second location category, the system can generate a second aggregate data record value based on the data record value of each the data records. The system can provide, for display at the client device, an interface indicating the first aggregate data record value or the second aggregate data record value.

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.