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Research on the Construction of an Evaluation Index System for Onboard Equipment Status Based on real-time data analysis

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INFORMATION 2025年第1期16卷 15-15页

作者： Zou, Fumin Ye, Ting Guo, Feng Fujian Univ Technol Fujian Key Lab Automot Elect & Elect Drive Fuzhou 350118 Peoples R China Fujian Univ Technol Renewable Energy Technol Res Inst Fuzhou 350118 Peoples R China

The research explores methods for onboard real-time data analysis and health status assessment, focusing on the working principles and status assessment theory of onboard equipment in the electronic toll collection (ETC) system. By applying AHP, fuzzy comprehensive evaluation method, entropy method, and Delphi method, a practical health status assessment model for onboard equipment has been established, providing an innovative path for dynamic real-time monitoring of onboard devices. The research first constructs an indicator system and assessment model, combining expert scoring with fuzzy judgment to objectively quantify the status of onboard equipment, ultimately resulting in a health status assessment indicator system for the objects under evaluation. During the assessment process, expert scoring is used to determine the subjective weights via AHP, and the combined weights are derived by incorporating objective weights, with instance results showing that the comprehensive weights of various indicators lie between the subjective and objective weights. The research also utilizes the Weibull distribution to simulate the failure rate of onboard equipment, indicating that the failure modes of the onboard devices are closely related to their operational status, providing a theoretical basis for future technological improvements. Through empirical analysis of the assessment model, the research verifies the superiority of the comprehensive weights and emphasizes its new approach in health status assessment of onboard devices, opening up new avenues for research in related fields.

关键词： health status evaluation of onboard equipment real-time data analysis analytic hierarchy process fuzzy comprehensive evaluation entropy method Delphi method

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real-time data analysis in Enterprise Information-Based Intelligent Manufacturing

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Procedia Computer Science 2025年 261卷 879-886页

作者： Liping Yu Xiande Zhuo Chengdu Industry And Trade College Chengdu 611731 Sichuan China

Enterprise informatization and intelligent manufacturing, functioning as a pivotal impetus for industrial upgrading, necessitate the stable operation of their core equipment, which is of utmost significance for production efficiency. As the volume of data surges exponentially and the real - time requisites escalate, the traditional data - processing approaches have gradually manifested issues such as being time - consuming, labor - intensive, and having subpar real - time performance. Consequently, this paper commences with a profound analysis of the application of real - time data analysis within the realm of enterprise informatization and intelligent manufacturing. It comprehensively and systematically amasses diverse types of real - time data from the intelligent manufacturing system, employs data - acquisition techniques to precisely obtain the data, and utilizes machine - learning algorithms to conduct an in - depth real - time analysis of the collected real - time data. Subsequently, the efficacy of the proposed method is validated through experiments. During the experimental process, the system gathers various real - time data from the intelligent manufacturing system and applies data - acquisition technology and machine - learning algorithms to execute real - time data analysis. The experimental outcomes demonstrate that this method boasts high real - time capabilities and a high degree of accuracy in data analysis, reduces processing time, and offers crucial support for enhancing enterprise production efficiency and competitiveness.

关键词： real-time data analysis enterprise informatization intelligent manufacturing machine learning data collection

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real-time data analysis in ClowdFlows

Real-Time Data Analysis in ClowdFlows

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IEEE International Conference on Big data (Big data)

作者： Kranjc, Janez Podpecan, Vid Lavrac, Nada Jozef Stefan Inst Ljubljana 1000 Slovenia

ISBN: (纸本)9781479912926;9781479912933

ClowdFlows is an open cloud based platform for composition, execution, and sharing of interactive data mining workflows. In this paper we extend the ClowdFlows platform with the ability to mine real-time data streams. This functionality was implemented by creating a specialized type of workflow component and a stream mining daemon that delegates the execution of workflows in real-time. In this way, we have transformed a batch data processing platform into a real-time stream mining platform with an intuitive user interface. The real-time analytics aspect of the platform is demonstrated in a Twitter sentiment analysis use case where the sentiment of tweets about whistleblower Edward Snowden was monitored for approximately one month.

关键词： data mining platform stream mining real-time data analysis web application workflows sentiment analysis

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real-time data analysis, Significance, Architectures and Applications for Informed Decision-Making

Real-Time Data Analysis, Significance, Architectures and App...

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2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Sharma, Kanhaiya Madhavi, Bindu G. Goyal, Ankur Parashar, Deepak Shrotriya, Lalit Gupta, Anurag Pune India Geethanjali College of Engineering and Technology Keesara Medchal Hyderabad Cheeryal501301 India Gl Bajaj Institute of Technology and Management Greater Noida India

ISBN: (纸本)9798350357769

real-time data analysis (RDA) represents dynamically evolving discipline that is revolutionizing decision-making processes across diverse industries. The capability to process data in real-time empowers organizations to make well-informed decisions instantaneously, granting them a substantial competitive edge. This paper furnishes an exhaustive examination of RDA, encompassing its significance, architectural underpinnings, and wide-ranging applications. Commencing with an exploration of RDA's contextual backdrop and its consequential importance, this paper underscores the criticality of timely insights in a world where data is being generated at an unprecedented pace. Its aim is to furnish readers with a comprehensive comprehension of RDA and its manifold potential uses. This paper is anticipated to captivate the interest of researchers, practitioners, and anyone eager to delve deeper into this cutting-edge domain. © 2023 IEEE.

关键词： Big data data Mining Decision support system Decision-making real-time data analysis

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Design of real-time data analysis system based on Impala

Design of real-time data analysis system based on Impala

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IEEE Workshop on Advanced Research and Technology in Industry Applications (WARTIA)

作者： Li, Jingmin Wuyi Univ Sch Comp Sci Jiangmen Guangdong Peoples R China

ISBN: (纸本)9781479969890

With the continuous development of Internet technology, from a mass of data real-time, efficient analysis and dig out the valuable information, especially important for enterprises. At present, relatively common practice is built up data analysis system in the Hadoop environment based on Hive. But it is more suitable for the batch processing in large data of clusters, and is not suitable for the real-time processing of large data requirements brought about by the development of the business adjustment. This paper presents a real-time data analysis system based on Impala. It can be used as a good supplement scheme. This paper will explain the thought and method of the construction of the real-time data analysis system based on Impala, from the system selection, system architecture, and practical.

关键词： Hadoop Impala Big data real-time data analysis

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Cloud-Based Knowledge Extraction (CBEx) System: A Solution for real-time data analysis for Rapid Decision Making

Cloud-Based Knowledge Extraction (CBEx) System: A Solution f...

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Annual IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)

作者： Falardeau, Julian Hadzagic, Melita Shahbazian, Elisa OODA Technol Inc Montreal PQ Canada

ISBN: (纸本)9798350323979

This paper introduces CBEx, a novel Cloud-Based knowledge Extraction system that efficiently and effectively ingests data from various sensor platforms across disparate domain Command and Control (C2) constructs and sensors. It employs pre-processing techniques tailored to each data type, ensuring consistent analysis and structuring according to a unified taxonomy. The structured data is stored in a unified format in a database, enabling real-time decision support based on Essential Elements of Information (EEIs). This solution offers tools to enhance multi-domain situational awareness by integrating data sources from multiple domains and by employing advanced Artificial Intelligence (AI)/Machine Learning (ML) analytics for accurate and rapid decision-making throughout the mission cycle. The feasibility of CBEx is demonstrated through three realistic scenarios, showcasing its ability to integrate a variety of data sources effectively while providing decision support in real-time.

关键词： real-time data analysis decision making multi-domain operations cloud-based ML/AI heterogeneous data processing

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Stuck-Pipe Prediction by Use of Automated real-time Modeling and data analysis

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SPE DRILLING & COMPLETION 2017年第3期32卷 184-193页

作者： Salminen, Kent Cheatham, Curtis Smith, Mark Valiullin, Khaydar Weatherford Houston TX USA

A real-time method is presented to predict impending stuck pipe with sufficient warning to prevent it. The new method uses automated analysis of real-time modeling coupled with real-time data analysis. It can be applied to all well types for any well operation, including drilling, casing running, completion activities, and reentries. The method uses leading indicators of stuck pipe that were identified by use of historical data sets of 36 stuck-pipe incidents in the Eagle Ford, Utica, and Permian and in the Gulf of Mexico. Two case histories show the utility of the new method in shale and carbonate horizontal wells for both drilling and offbottom operations. The new method combines two types of analysis: use of hydraulics and torque- and- drag (T&D) software to determine deviation of real-time data from the real-time model, and trend analysis (i.e., rate of change) of real-time data. Parameters used are pump pressure, flow rate, torque, rotary speed, hookload and drag, and weight on bit (WOB), along with static inputs such as bottomhole-assembly (BHA) and drillstring configuration and directional surveys. Additional parameters, such as downhole equivalent circulating density (ECD), are used when available and improve the results. But the method is designed to monitor all well types and provide a stuck-pipe-risk log even by use of only basic instrumentation. A novel algorithm predicts the probability of stuck pipe, which is presented in a real-time log. Results demonstrate that there is no single leading indicator in all stuck-pipe incidents. Our early-detection method, called the stuck-pipe-risk (SPR) log, relies on multiple indicators to strengthen the likelihood of detecting impending stuck pipe while avoiding false alerts. A key element to automating the process is the use of filtering for rig activity. The first indicator is deviation of actual data from model predictions. A second indicator is trend analysis (specifically, rate-of-change calculations), which pr

关键词： stuck pipe real-time model prediction drilling optimization non-productive time real-time data analysis

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KRILLSCAN: An automated open-source software for processing and analysis of echosounder data from the Antarctic krill fishery

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FISHERIES MANAGEMENT AND ECOLOGY 2025年第1期32卷

作者： Menze, Sebastian Macaulay, Gavin J. Zhang, Guosong Lowther, Andrew D. Krafft, Bjorn A. Inst Marine Res Bergen Norway Aqualyd Ltd Wakefield New Zealand Norwegian Polar Res Inst Tromso Norway

Krillscan software was developed to automatically process echosounder data and achieve an accelerated and transparent analysis of backscatter data that allows calculation of target biomass. Herein, the fishery for Antarctic krill (Euphausia superba, Henceforth Krill) was used as a case study to develop the approach. Implementation of a sustainable management strategy for the krill fishery is complicated by a lack of regularly updated krill abundance data on spatiotemporal scales of the fishery. To increase krill biomass data availability, automatic echosounder data processing and swarm detection software was tested against traditional manual scrutinization with LSSS software and agreed with only minor offsets in estimated nautical area scattering coefficients. In addition to automatic processing and data transfer, Krillscan also has a graphical user interface to supervise automatic krill swarm detection. Echogram size can be compressed up to 100 times and raw data are processed faster than generated, thereby enabling near-real time analysis and data transfer. Compressed data can be transmitted online to allow fishing vessels to conduct surveys without having scientific personnel with special expertise on board.

关键词： Antarctic krill echosounders platforms of opportunity python real-time data analysis

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The Medical Knowledge Cockpit: real-time analysis of Big Medical data Enabling Precision Medicine

The Medical Knowledge Cockpit: Real-time Analysis of Big Med...

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IEEE International Conference on Bioinformatics and Biomedicine - Medical Informatics and Decision Making

作者： Schapranow, Matthieu-P. Kraus, Milena Perscheid, Cindy Bock, Cornelius Liedke, Franz Plattner, Hasso Hasso Plattner Inst Enterprise Platform & Integrat Concepts August Bebel Str 88 D-14482 Potsdam Germany

ISBN: (纸本)9781467367981

Significant medical knowledge has been generated over past decades, but is stored in databases distributed all over the globe using individual data formats. Detailed diagnostic tests result in steadily growing patient data. Consequently, medical experts are facing challenges outside of their field of expertise, e. g. analyzing, interpreting and linking medical data. In this contribution, we share details about our Medical Knowledge Cockpit, an application designed in an interdisciplinary cooperation with medical experts to improve the identification of relevant knowledge. Built upon latest in memory database technology, it offers medical experts a unique starting point to link and analyze medical data on their own in real time. Result sets providing links back to primary data sources are assembled using patient specifics.

关键词： In-Memory database Technology Precision Medicine Heterogeneous data Sources real-time data analysis

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BASIS FOR A FLEXIBLE LOW-COST AUTOMATED RESISTIVITY data-ACQUISITION AND analysis SYSTEM

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COMPUTERS & GEOSCIENCES 1995年第8期21卷 993-999页

作者： MEJU, MA MONTAGUE, M Environmental and Industrial Geophysics Research Group Department of Geology University of Leicester Leicester LE1 7RH U.K.

An efficient and versatile automatic resistivity data acquisition and analysis (ARDAA) system has been developed for use with any 4-electrode output resistivity meter. The acquisition hardware comprises a low-cost Digital Switching Unit (DSU) or an '' electronic switch box'' which can be interfaced to a portable field microcomputer and a resistivity meter for automatic ground resistivity measurements. data analysis can be effected in real-time using a simple effective direct inversion scheme that converts each apparent resistivity-electrode spacing data pair into a corresponding effective resistivity-depth information at a rate that is faster than that of acquisition leading to unhindered productivity. The DSU is software programmable thus allowing for easy reconfiguration for the electrode array-type deemed appropriate for a given field survey or for extension to other geophysical techniques where automatic multiple switching is required. Detailed discussions of the system design, practical considerations, time- and cost-savings, and an adaption to the ABEM SAS300 terrameter are provided. A practical evaluation of the infield data-analysis scheme is given and suggestions are offered for extending the basic system for remote-site monitoring applications.

关键词： RESISTIVITY SURVEYING AUTOMATIC data ACQUISITION real-time data analysis

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