584results about "Data acquisition and logging" patented technology

Techniques are discussed herein for generating and evaluating autonomous vehicle control systems. In examples, a driving scenario is determined and log data, e.g., generated from user-supported vehicles travelling in an environment, may be used to determine instances in which vehicles experience the driving scenario. Based on the log data, an exposure metric, a severity metric, and / or a controllability metric may be determined. A safety goal can be determined from the metric(s) and vehicle control parameters are determined to comport with the safety goal. The vehicle control parameters may be used to control an autonomous vehicle in the environment.

The invention discloses a fire fighting system intelligent management method and device based on intelligent property management, and relates to the technical field of data management. The intelligent management method and device for the fire fighting system based on the intelligent property management comprises the following steps: S1, dynamically triggering and collecting a multi-source fire fighting data set through multiple protocols, and temporarily storing the multi-source fire fighting data set at the edge in a normalized manner; s2, constructing an event full-period window and a ternary association index of the event, the time sequence data and the original message; s3, performing double-track storage of the semantic analysis data and the original message, and constructing multi-dimensional index association; s4, reconstructing a visual playback alarm process through edge cloud increment synchronization and a multi-dimensional time sequence chain; and S5, performing transient analysis, protocol upgrading and responsibility evidence obtaining based on the cloud data collaborative link and the original message data set. According to the method, the complete acquisition of the fire-fighting data and the reproducibility of the event process are effectively improved, and the problem that in the prior art, only polling recording of single-point alarm is carried out, and an original message is discarded, so that the transient process and message-level evidence is lost is solved.

Disclosed in the present invention is a lightweight active online modeling method fusing mechanism and dynamic memory, which comprises the following steps: S1, data preprocessing and model initialization; S2, online data representativeness evaluation based on dynamic memory of process data; S3, online data informativeness evaluation based on dynamic memory of label data; S4, online monitoring of a mechanism state; S5, parallel hybrid active sampling policy; and S6, online modeling of a soft sensor model. The present invention separately designs memory policies for process data and label data and only reserves high-value data, thereby satisfying a lightweight hardware requirement; in addition, the present invention designs a time delay-based mechanism state online monitoring method to detect a real concept drift of the process, and further provides the parallel hybrid active sampling policy for detecting both a real concept drift and a false concept drift; in combination with dynamic memory and a kernel incremental regression method, the computation amount for model updating and the hardware overhead for edge deployment are reduced.

Methods and apparatuses for athletic training optimization are disclosed. In one example, a fitness level change is identified. In one example, a current training intensity is updated to reflect an updated user fitness level.

The present disclosure provides an in-vehicle monitoring and tracking system for rental vehicles that detects smoking events within a vehicle cabin and logs these events with associated location data. The system employs specialized detection algorithms to accurately identify various types of smoke while minimizing false positives. Additional functionality includes accident detection through rapid deceleration monitoring, and animal presence detection through acoustic sensing. When events are detected, the system can either store the information for later retrieval or transmit real-time notifications with precise location data to rental company servers, enabling prompt response to policy violations and facilitating vehicle recovery after accidents.

A method can include receiving input for a field scenario that comprises fluid dynamics and chemical phenomena, where the input defines substances amenable to speciation; executing a fluid dynamics simulator to perform timesteps for transport of the substances while calling a chemical phenomena framework that determines speciation of the substances; and generating results for the field scenario based on the executing.

The invention provides a multi-source heterogeneous data collection method and device, a storage medium and equipment. The method comprises the steps that a central scheduling module generates a data collection instruction according to a preset triggering condition; the central scheduling module awakens at least one RPA execution unit in the central scheduling module according to the data acquisition instruction, so that the awakened RPA execution unit calls the data acquisition module according to the data acquisition instruction, and sends the data acquisition instruction to the called data acquisition module; the data acquisition module generates at least one data calling signal according to the data acquisition instruction, and sends the data calling signal to at least one RPA acquisition unit in the data acquisition module, so that the RPA acquisition unit calls specific data from the processing platform subsystem according to the data calling signal; the data acquisition module sends the called data to the central scheduling module; and the central scheduling module integrates the called data, and sends the integrated data to the data storage module for storage according to a preset rule.

The invention relates to the technical field of information acquisition, and particularly discloses a cluster type textile machine information acquisition method and system based on a robot, and the method comprises the steps: receiving a time-containing signal uploaded by each module, and generating a signal matrix containing an identification label and a time label; identifying the signal matrix containing the identification label and the time label, and determining the anomaly degree of each textile machine; determining an information acquisition path of the robot based on the anomaly degree of each textile machine, and sending the information acquisition path to the robot; when the robot returns, reading collected data of the robot; the robot is additionally arranged between the data total end and the textile machine, the robot moves to the position close to the textile machine to carry out high-frequency data collection, the data total end carries out low-frequency collection on data of all the textile machines, and then the data collection process of the robot is adjusted, in this architecture, the collection frequency of the data total end can be very low, and the collection efficiency is high. And the resource consumption is greatly reduced.

Systems and methods are described, and an example system includes an AI enhanced multi-source health data integration logic that receives a first source electronic health record (EHR) data from a first EHR system and a second source EHR data from a second EHR system, and transforms, according to a knowledge representation schema, health-related information content of the first source EHR data and the second source EHR data to a first source transformed health data and second source transformed health data. The system includes a collaboration platform, configured to host a multi-source transformed health data database, including the transformed first source health data and the transformed second source health data, and hosts AI-enhanced, multiple level telecollaborative analyses by a plurality of participants of the multi-source transformed health data database, generating health management data.

The invention relates to the technical field of data processing, in particular to a remote management system for experimental detection data of a traffic road section, which comprises a state acquisition and occupancy calculation module, a time sequence storage structure, a state acquisition and occupancy calculation module and a state acquisition and occupancy calculation module, the fluctuation characteristic gradient analysis module calculates the difference between the current occupancy rate and the historical occupancy rate to generate a fluctuation degree value, the sampling period dynamic decision module compares the fluctuation value with a threshold value to generate a target sampling interval, and the hardware servo and data packaging module adjusts the scanning frequency and generates a detection data packet. According to the method, a time sequence storage structure is constructed, the traffic flow fluctuation degree is quantified, the sampling interval is intelligently decided according to the fluctuation numerical value, the scanning frequency is adjusted in real time, the frequency is reduced to reduce redundancy when the traffic flow is stable, sampling is encrypted to capture features when fluctuation is violent, the data integrity is guaranteed, and the storage and transmission pressure is reduced. And efficient utilization of monitoring resources is realized.

According to one embodiment, a method, computer system, and computer program product for log compression is provided. The embodiment comprises receiving a log stream from an instance of an application executed within a container of a remote computational system via a network connection. The log stream comprises metadata. The metadata comprises an application identifier. The application identifier uniquely identifies the executable code of the application. The embodiment further comprises searching a compression dictionary library for a current compression dictionary using the application identifier. The application identifier uniquely identifies the current compression dictionary for the application. The embodiment further comprises sending the current compression dictionary to the remote computational system via the network connection.

Systems, methods, and non-transitory computer readable mediums are provided for testing and measuring the behavior or logic of one or more cloud services associated with a simulated autonomous vehicle (AV). For example, a system may be configured to receive log data of a simulated AV. In some examples, the log data may characterize one or more events that occurred during a simulation of the simulated AV. Additionally, the system may instantiate an AV bot based on the log data. Moreover, the system may generate, by the instantiated AV bot, a first set of messages. In some examples, the first set of messages may be based on the log data. Further, the system may provide the first set of messages to a cloud service.

A method for biosignal data transformation can include: determining a set of biosignal data, determining a brain state representation (e.g., an embedding) based on the biosignal data, and determining a biomarker value based on the brain state representation. The method can optionally include training a model (e.g., training a model used to determine the brain state representation), and / or any other suitable steps. A system for biosignal data transformation can include a biosignal device and a computing system.

A maintenance system for a medical device includes a user device configured to communicate with the medical device and execute maintenance tasks on the medical device and communicate with a user via a user interface of the user device or the medical device. The maintenance tasks may be executed by either device or both devices, and communication with a user may occur via a user interface of either device or both devices. The system may also include a server configured to communicate with one or both of the user device and the medical device. The maintenance tasks may include an electrical safety check, a physical check, a performance check, and a functional check. Examples of functional checks include validation of a transient current detector and a thermal cutout.

A computer implemented method of log compression comprises receiving a log stream from an instance of an application executed within a container of a remote computational system via a network connection 300. The log stream comprises metadata comprising an application identifier which uniquely identifies the executable code of the application. The method further comprises searching a compression dictionary library for a current compression dictionary using the application identifier wherein the application identifier uniquely identifies the current compression dictionary for the application 302. The method further comprises sending the current compression dictionary to the remote computational system via the network connection 304.

The invention relates to the technical field of data processing, and discloses a salt cavern gas storage brine discharging pipeline operation data processing method and system, and the method comprises the steps: periodically receiving a link detection data packet which is transmitted by a collection device and is provided with a transmission timestamp, and recording the arrival time of the link detection data packet; according to the sending timestamp and the arrival time, transmission characteristics of the link detection data packet are analyzed, and the transmission characteristics comprise transmission delay, jitter dispersion and out-of-order conditions; adaptively predicting a time offset pattern based on the transmission characteristics; generating a real-time calibration parameter according to the time migration mode; and receiving an actual data packet, and adjusting the timestamp of the actual data packet by using the real-time calibration parameter. According to the method, the limitation of traditional fixed compensation parameters is overcome, the time alignment precision of pressure and flow data flow is remarkably improved, leakage misinformation caused by time deviation is avoided, and the reliability and the operation and maintenance efficiency of a salt cavern gas storage brine discharging pipeline operation monitoring system are improved.

A battery information management system, comprises: a battery; and a server that establishes communication with the battery via a network. The battery includes: a storage unit configured to store maintenance information for maintenance of the battery, user information related to personal data of a user of the battery, and usage history information of the battery; an information communication unit configured to transmit the user information and the usage history information from the storage unit to the server; and a control unit configured to control the storage unit and the information communication unit.

Provided is a data logger. A data logger includes a sensor configured to sense a change in a gravitational acceleration of the data logger and a change in a rotation angle of the data logger, and generate a sensing signal, a communication module configured to receive configuration information including a sensing period and threshold values of the data logger from a portable reader, and a microprocessor unit configured to receive the sensing signal from the sensor, receive the sensing period and the threshold values from the communication module, generate sensing values corresponding to the sensing signal, compare the sensing values with the threshold values, determine whether an abnormal state occurs in the data logger according to a result of the comparison, generate and transmit to a server normal log information at each of the sensing period when the abnormal state does not occur in the data logger, and generate and transmit to the server abnormal log information whenever the abnormal state occurs regardless of the sensing period.

The present disclosure provides an inversion method for determining a pollution source list based on artificial intelligence and big data, an inversion system for determining the pollution source list based on artificial intelligence and big data, and applications thereof, which provides basic data support for government sectors to formulate relevant environmental protection measures. The specific technical solution employed in the present disclosure is as follows: finding out an emission source that makes the highest contribution to the pollutant concentration of any cell with an advanced 3D CNN artificial intelligence algorithm based on artificial intelligence and big data, establishing a model of the relationship between pollutant concentration and emission, and finding out the relationship between pollutant concentration and emission with machine learning technology, i.e., estimating an emission from a given pollutant concentration, and estimating a pollutant concentration from a given emission.

Embodiments described herein disclose methods and systems for community item distribution. In some implementations, the community item distribution system includes a platform for users to post information regarding items they want to share with the community. The community item distribution system can categorize the information and establish donation parameters for the shared items. The donation parameters can include where and when items can be donated or retrieved, what types of items can be donated, and who can request the donated items. In some cases, the community item distribution system can generate a user interface listing the available items that users can request. Upon request of an item, the community item distribution system can schedule a drone to transport the item, in a secured container with ultraviolet lights to disinfect the item, from the storage location to the delivery location.

A bond log analysis apparatus and system and method for use of the same are disclosed. In one embodiment, the system receives a Cement Bond Log (CBL) including a Variable Density Log (VDL) and at least one Secondary Data Track (SDT). The system conducts an initial analysis of the VDL to identify characteristics and patterns related to cement bonding conditions at a specified depth. If a possible discontinuity is identified, the system sequentially analyzes VDL data from adjacent depths to determine the vertical extent of the anomaly. For the identified vertical extent, the system performs a detailed analysis using SDT data to characterize the cement bonding issues. The system then synthesizes the VDL and SDT data to generate a report providing an analysis of the cement integrity around the wellbore casing. The method follows similar steps for bond log analysis.

Novel systems and methods for infrastructure management are described herein. Exemplar novel systems and methods include using a network of sensors for measuring fluid condition attribute at constraint locations inside infrastructure, a fluid flow controller for calculating stress at the constraint locations and a flow-redistributing component for redistributing fluid flow through one or more routes inside infrastructure to relieve stress at the constraint locations. Novel systems and methods for implementing infrastructure management strategies are also described herein. They include structural components to carry out features like obtaining data and / or estimated values, calculating and / or estimating stress values, developing flow redistributing strategies for relieving stress in infrastructure, and implementing these strategies to relieve stress. Novel systems and methods to adapt flow control to the changing storm conditions are also described herein. These systems and methods adjust flow redistributing strategies, in real time, in response to the changing storm severity.

Example implementations described herein involve, for receipt of time series data from sensors of one or more assets in a system, executing feature extraction on the received time series data; identifying event types from the feature extraction; identifying pairs of event type and a window of the time series data; clustering motifs of the identified pairs to update a motif dictionary; estimating a likelihood of an event from the event types based on one or more discovered motifs from the time series data and an associated time series motif of the event; using a language model to generate associated event descriptions; providing, through a user interface, the estimated likelihood of the event, the associated time series motif, sequencing of the associated time series motif, and a recommendation; and for an acceptance of the recommendation through the user interface, executing the recommendation for the one or more assets in the system.

Embodiments of the present disclosure relate to automated optimization and / or evaluation of parameterizable models. With respect to optimization, some embodiments record or collect data according to a user instruction during the optimization of the parameterizable model. Based on such recording or collection, some embodiments then update a parameter during optimization, such as via local and / or global optimization. With respect to evaluation, some embodiments perform validation and / or benchmarking based on a type of parameterizable model and one or more performance metrics. Some embodiments perform local validation and / or global validation as part of the validation and / or benchmarking.

A data logger comprising a sensor interface for connecting at least one sensor or actuator to the data logger; an accessible memory (SD card) for storing data received from said at least one sensor or actuator; and a controller for controlling operation of the data logger wherein said data logger comprises a plurality of modules, each module having a housing electrically and mechanically connectable to a housing of an adjacent module; and wherein at least one module comprises the sensor interface and acts as a logging and / or actuation module (LAM) including at least a portion of said accessible memory (SD card); and at least one module connected to said at least one LAM acts as a control and communications module (CCM) and comprises the controller that controls communications within and external to the data logger.

The invention relates to a system and a method applied to real-time circulating storage of a high-speed data acquisition system, which are mainly used for solving the technical problems of huge fan-out quantity of a core clock, more cross clock domains and lack of accurate description of sampling data trigger time information in the prior art when the use amount of core clock resources is reduced. The device comprises a control logic unit, a first buffer, a second buffer, a memory, a time measurement unit and at least one clock manager, a double-cache structure of a small-capacity first cache and a large-capacity second cache is adopted, only one clock manager is needed at least, and the problem that a time sequence is not converged in time information of a high-speed sampling data waveform is solved. The double-cache structure can reduce the stored core clock resource quantity, the distributed clock domain and the like as much as possible, time sequence convergence with high robustness is realized, and stable and reliable sampling data storage is ensured.

In some implementations, a device may receive, by device, information identifying a data lineage for a plurality of datasets, the data lineage including, for a dataset of the plurality of datasets, information identifying one or more hops associated with the dataset, each hop, of the one or more hops, corresponding to a transformation of the dataset corresponding to a data processing process. The device may generate a plurality of data lineage metrics for a plurality of hops associated with a plurality of data processing processes to which the plurality of datasets is subjected in association with the data lineage. The device may generate an overall data lineage metric based on the plurality of data lineage metrics, the overall data lineage metric having a plurality of components. The device may transmit an output associated with the overall data lineage metric.

The invention relates to an electronic device, a computer readable recording medium and a log recording method. The log recording method is stored in the computer readable recording medium and executed by the electronic device. The method comprises the following steps of: recording a log into a log document by enabling a button; performing context annotation through an annotation button based on the context determination; storing the context labels into a time sequence of the log document; judging whether a situation label exists in the log document or not; and when the judgment result is yes, displaying the log section corresponding to the situation annotation. Therefore, when the log is recorded, the time point of the error event can be quickly marked to facilitate subsequent tracking.

Embodiments of the present disclosure provide a log parsing method and device. The log parsing method comprises: determining a log to be parsed, and carrying out tokenization processing on said log to obtain a log tokenization sequence; matching the log tokenization sequence with nodes in a prefix tree, and determining a candidate syntax template corresponding to the log tokenization sequence, wherein the prefix tree is constructed by the nodes and paths, the nodes are tokens in a log syntax template, each path represents an association relationship of tokens in the log syntax template, and the log syntax template is determined on the basis of an initial log; matching the log tokenization sequence with the candidate syntax template on the basis of a preset matching policy to obtain a matching result; and when the matching result does not satisfy a preset matching condition, using a large language model to parse said log, to obtain a parsing result. The method can improve the log parsing accuracy and reduce log parsing costs.

Provided are a vehicle data consistency verification system and method allowing verification of validity and consistency of various vehicle data collected to improve vehicle quality and service. Provided are a vehicle data consistency verification system and method allowing vehicle data stored in a server to be efficiently used by improving accuracy and reliability of vehicle data through inspection of data validity and data consistency for various vehicle data transmitted from a vehicle and collected and stored on a server.