scholarly journals Smart Meter Evaluation System Based on Big Data

2021 ◽  
Vol 2143 (1) ◽  
pp. 012039
Author(s):  
Yu Zhou ◽  
Xuesong Shao ◽  
Zhuowen Mu ◽  
Qixin Cai ◽  
Yue Li ◽  
...  
Keyword(s):  
Big Data ◽  
Data Storage ◽  
Evaluation System ◽  
Clustering Algorithm ◽  
Massive Data ◽  
Smart Meter ◽  
Smart Meters ◽  
Multiple Systems ◽  
Material Resources ◽  
Big Data Technology

Abstract Aiming at the problem of unstable operation of smart meters, this paper proposes a smart meter evaluation system based on big data. First introduce big data related technologies, such as data storage, analysis, mining, etc.. Secondly, design the big data smart meter evaluation system model. Finally, use big data technology and clustering algorithm to realize the design of the big data smart meter operation evaluation system. The system can convert massive data from multiple systems into operational evaluation reports, which helps to reduce the waste of human and material resources.

Research of Smart Meter Massive Data Storage Based on Cloud Computing Platform

2013 ◽  
Vol 341-342 ◽  
pp. 1434-1438
Author(s):  
Weng Ting Li ◽  
Yan Zheng ◽  
Shao Bo Liu ◽  
Zhao Zhi Long ◽  
Zhi Cheng Li
Keyword(s):  
Cloud Computing ◽  
Smart Grid ◽  
Data Storage ◽  
Massive Data ◽  
Smart Meter ◽  
Smart Meters ◽  
Computing Platform ◽  
Cloud Computing Platform ◽  
Distributed Computing Platform ◽  
Grid Operation

With the comprehensive construction of the smart grid, the smart grid operation control and interactive service system will be initially formed. The smart terminal of smart grid are smart meters, and they produce a large number of various data all the time. That how to most effectively manage these massive data storage is an important research point for improving the intelligence service. This paper studies the smart meter massive data storage management based on cloud computing platform. The Hadoop distributed computing platform for smart meter massive data management is reliable, efficient, scalable storage.

scholarly journals A review: evolution of big data in developing country

2019 ◽  
Vol 3 (1) ◽  
pp. 30-37
Author(s):  
Bayu Prasetyo ◽  
Faiz Syaikhoni Aziz ◽  
Kamil Faqih ◽  
Wahyu Primadi ◽  
Roni Herdianto ◽  
...  
Keyword(s):  
Developing Countries ◽  
Big Data ◽  
Developing Country ◽  
Data Storage ◽  
Human Life ◽  
Large Data ◽  
Big Data Technology

The development of technology from year to year is increasingly rapid and diverse. All systems that exist in human life began to be designed with technology that requires large data storage. Big Data technology began to be developed to accommodate very large data volumes, rapid data changes, and very varied. Developing countries are starting to use Big Data a lot in developing their systems, such as healthcare, agriculture, building, transportation, and various other fields. In this paper, it explains the development of Big Data applied to the sectors previously mentioned in developing countries and also the challenges faced by developing countries in the process of developing their systems.

scholarly journals The Construction and Thinking of Cloud Computing and Big Data Technology in Smart Campus

2019 ◽  
Vol 3 (2) ◽  
pp. 152
Author(s):  
Xianglan Wu
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Storage ◽  
Information Technologies ◽  
Rapid Development ◽  
Smart Campus ◽  
Huge Data ◽  
New Information ◽  
Big Data Technology

<p>In today's society, the rise of the Internet and rapid development make every day produce a huge amount of data. Therefore, the traditional data processing mode and data storage can not be fully analyzed and mined these data. More and more new information technologies (such as cloud computing, virtualization and big data, etc.) have emerged and been applied, the network has turned from informationization to intelligence, and campus construction has ushered in the stage of smart campus construction.The construction of intelligent campus refers to big data and cloud computing technology, which improves the informatization service quality of colleges and universities by integrating, storing and mining huge data.</p>

scholarly journals Big Data on Machine Learning – A Review

2021 ◽  
Vol 8 (3) ◽  
Author(s):  
Balasree K ◽  
Dharmarajan K
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
Data Storage ◽  
Data Analytics ◽  
Rapid Development ◽  
Learning Algorithms ◽  
Big Data Analytics ◽  
Machine Learning Algorithms ◽  
Data Sets ◽  
Big Data Technology

In rapid development of Big Data technology over the recent years, this paper discussing about the Machine Learning (ML) playing role that is based on methods and algorithms to Big Data Processing and Big Data Analytics. In evolutionary fields and computing fields of developments that both are complementing each other. Big Data: The rapid growth of such data solutions needed to be studied and provided to handle then to gain the knowledge from datasets and extracting values due to the data sets are very high in velocity and variety. The Big data analytics are involving and indicating the appropriate data storage and computational outline that enhanced by using Scalable Machine Learning Algorithms and Big Data Analytics then the analytics to reveal the massive amounts of hidden data’s and secret correlations. This type of Analytic information useful for organizations and companies to gain deeper knowledge, development and getting advantages over the competition. When using this Analytics we can predict the accurate implementation over the data. This paper presented about the detailed review of state-of-the-art developments and overview of advantages and challenges in Machine Learning Algorithms over big data analytics.

Big Data and Visuality

2017 ◽  
Author(s):  
Janet Chan
Keyword(s):  
Big Data ◽  
Criminal Justice ◽  
Data Storage ◽  
Data Visualization ◽  
Crime Control ◽  
Big Data Analytics ◽  
Emotional Impact ◽  
Predictive Tool ◽  
The Impact ◽  
Big Data Technology

Internet and telecommunications, ubiquitous sensing devices, and advances in data storage and analytic capacities have heralded the age of Big Data, where the volume, velocity, and variety of data not only promise new opportunities for the harvesting of information, but also threaten to overload existing resources for making sense of this information. The use of Big Data technology for criminal justice and crime control is a relatively new development. Big Data technology has overlapped with criminology in two main areas: (a) Big Data is used as a type of data in criminological research, and (b) Big Data analytics is employed as a predictive tool to guide criminal justice decisions and strategies. Much of the debate about Big Data in criminology is concerned with legitimacy, including privacy, accountability, transparency, and fairness. Big Data is often made accessible through data visualization. Big Data visualization is a performance that simultaneously masks the power of commercial and governmental surveillance and renders information political. The production of visuality operates in an economy of attention. In crime control enterprises, future uncertainties can be masked by affective triggers that create an atmosphere of risk and suspicion. There have also been efforts to mobilize data to expose harms and injustices and garner support for resistance. While Big Data and visuality can perform affective modulation in the race for attention, the impact of data visualization is not always predictable. By removing the visibility of real people or events and by aestheticizing representations of tragedies, data visualization may achieve further distancing and deadening of conscience in situations where graphic photographic images might at least garner initial emotional impact.

Design of Computer Multimedia Intelligent Platform Using Big Data Analysis

2022 ◽  
Author(s):  
Zhenna Chen
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Multimedia Information ◽  
Real Time ◽  
Data Storage ◽  
Big Data Analysis ◽  
Intelligent Vehicle ◽  
Time Data ◽  
Vehicle Operation ◽  
Big Data Technology

This exploration aims to transfer, process and store multimedia information timely, accurately and comprehensively through computer comprehensive technology processing, and organically combine various elements under the background of big data analysis, so as to form a complete intelligent platform design for multimedia information processing and application. In this exploration, the intelligent vehicle monitoring system is taken as an example. Data acquisition, data transmission, real-time data processing, data storage and data application are realized through the real-time data stream processing framework of [Formula: see text] of big data technology. Data interaction is realized through Spring, Spring MVC, VUE front-end framework, and Ajax asynchronous communication local update technology. Data storage is achieved through Red is cache database, and intelligent vehicle operation supervision system is achieved through multimedia information technology processing. Its purpose is to manage the vehicle information, real-time monitor the running state of the vehicle and give an alarm when there are some problems. The basic functions of vehicle operation monitoring and management system based on big data analysis are realized. The research on the design of vehicle operation monitoring and management system based on big data analysis shows that big data technology can be applied to the design of computer multimedia intelligent platform, and provides a reference case for the development of computer multimedia intelligent platform based on big data analysis.

An HBase-Based Platform for Massive Power Data Storage in Power System

2014 ◽  
Vol 1070-1072 ◽  
pp. 739-744
Author(s):  
Zi Jian Yan ◽  
Peng Sun ◽  
Xiao Mei Liu
Keyword(s):  
Data Storage ◽  
Rapid Development ◽  
Database System ◽  
Massive Data ◽  
Huge Data ◽  
Sample Data ◽  
Design Software ◽  
Power Application ◽  
Data Design ◽  
Big Data Technology

With the rapid development of the grid scale, there are huge data generated in grid, which include many sample data, alarm data used for real-time monitor and analysis, the traditional dispatching system can’t meet the demands of big capacity storage very well. In recent years, big data technology develop very fast, among it the distributed column-oriented database system is rising gradually with the vigorous development of cloud computing. Considering the character of power data, this paper studies how to use distributed column-oriented database system in power application for storing massive increasing data. The paper design massive data storage structure of power data, design software frame and deployment of massive power data storage. Through experiment it is feasible for distributed column-oriented database to be applied in EMS system through experiment.

scholarly journals The Analysis and Implementation of the K - Means Algorithm Based on Hadoop Platform

2018 ◽  
Vol 11 (1) ◽  
pp. 98
Author(s):  
Liu Xiang Wei
Keyword(s):  
Big Data ◽  
Data Storage ◽  
Clustering Algorithm ◽  
Experimental Results ◽  
Mode Of Operation ◽  
Cluster Configuration ◽  
Hadoop Platform ◽  
Kmeans Algorithm

In today's society has entered the era of big data, data of the diversity and the amount of data increases to the data storage and processing brought great challenges, Hadoop HDFS and MapReduce better solves the these two problems. Classical K-means algorithm is the most widely used one based on the partition of the clustering algorithm. At the completion of the cluster configuration based on, the k-means algorithm in cluster mode of operation principle and in the cluster mode realized kmeans algorithm, and the experimental results are research and analysis, summarized the k-means algorithm is run on the Hadoop platform's strengths and limitations.

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