ieee big data 2021




Big Data is a collection of data that is huge in volume, yet growing exponentially with time. It is a data with so large size and complexity that none of traditional data management tools can store it or process it efficiently. Big data is also a data but with huge size.

Big Data helps the organizations to create new growth opportunities and entirely new categories of companies that can combine and analyze industry data. These companies have ample information about the products and services, buyers and suppliers, consumer preferences that can be captured and analyzed.

Variety of Big Data refers to structured, unstructured, and semistructured data that is gathered from multiple sources. While in the past, data could only be collected from spreadsheets and databases, today data comes in an array of forms such as emails, PDFs, photos, videos, audios, SM posts, and so much more.

The Role of AI, Machine Learning, and Big Data in Digital Twinning: A Systematic Literature Review, Challenges, and Opportunities
free download

Digital twinning is one of the top ten technology trends in the last couple of years, due to its high applicability in the industrial sector. The integration of big data analytics and artificial intelligence/machine learning (AI-ML) techniques with digital twinning, further enriches its There are many possibilities for smart buildings that have well provisioned and managed internet of things (IoT) frameworks where seamless data acquisition from sensors, processing to analytics can bring benefits to vast domains. Specifically, in building

Distributed Tree-Based Machine Learning for Short-Term Load Forecasting With Apache Spark
free download

However, with the huge increase in data size, sophisticated models have to be created which require big data platforms Parallel computing is demanded to allow for optimal resource utilization in dealing with smart grid big data Decentralized storage powered by blockchain is becoming a new trend that allows data owners to outsource their data to remote storage resources offered by various storage providers. Unfortunately, unqualified storage providers easily encounter unpredictable

Deep learning-based short-term load forecasting approach in smart grid with clustering and consumption pattern recognition
free download

The Open Access Funding was provided by Qatar National Library. ABSTRACT Different aggregation levels of the electric grids big data can be helpful to develop highly accurate deep learning models for Short-term Load Forecasting (STLF) in electrical networksCloud deployment architectures have become a preferable computation model of Big Data (BD) operations. Their scalability, flexibility, and cost-effectiveness motivated this trend. In a such deployment model, the data are no longer physically maintained under the users direct This paper proposes a cooperative multi-agent deep reinforcement learning (MADRL) algorithm for energy trading among multiple unmanned aerial vehicles (UAVs) in order to perform big data processing in a distributed manner. In order to realize UAV-based aerial There is very limited study available to predict the various disease using big data framework Spark using deep learning spark is an open source fast, flexible and developer friendly unified analytics engine for large scale data processing for Bigdata machine learning of bigdata analytic approaches, Published in: International Conference on Computing, Communication and Automation (ICCCA), Publisher: IEEE, DOI: 10.1109/CCAA.2017.822982 Accession Number: 17449090 [17] M. Ambigavathi ; D. Sridharan, Big Data Analytics in Traditional digital signal processing technology based on DSP and FPGA is more suitable for real-time signal processing, and is limited by data scale and frequency resolution, making it unsuitable for offline data processing, analysis and mining under large-scale data In this paper, Heterogeneous Fair Resource Allocation and Scheduling (HFRAS) for cloud based Big Data Streams, is proposed. In this algorithm, a weight value is determined for the user for each of the requested resource, based on the resource priorities. Then each task is

Randomized algorithms for computation of Tucker decomposition and higher order SVD (HOSVD)
free download

ABSTRACT Big data analysis has become a crucial part of new emerging technologies such as the internet of things, cyber-physical analysis, deep learning, anomaly detection, etc Randomized algorithms are efficient tools for handling big data tensors

Wireless Telecommunication Links for Rainfall Monitoring: Deep Learning Approach and Experimental Results
free download

empirical computational methods are less adequate representation of the actual data . Therefore, deep learning models are proposed for the analysis of big data and give more accurate representation of real measurements

A multiprocessing-based sensitivity analysis of machine learning algorithms for load forecasting of electric power distribution system
free download

INDEX TERMS Big data applications, machine learning algorithms, parallel processing, load forecast, smart grids Big data analytics with artificial intelligence techniques are key for proper understanding and utilization of smart meter data In the context of the rapid development of informatization and electronics, the Internet is becoming more and more popular, and C2C e-commerce is developing faster and faster. However, C2C e-commerce still has some problems in the tax management process, which

On the Use of Google Earth Engine and Sentinel Data to Detect“LostSections of Ancient Roads. The Case of Via Appia
free download

Index Terms Big data Copernicus, Google earth engine (GEE), Sentinel 1 (S-1), Remote sensing for archeology, Sentinel 2 (S-2). I. INTRODUCTION BIG Earth Observation (EO) data emerged in the past few years as powerful tools in archeology serving numerous

Understanding the Challenges and Assisting Developers with Developing Spark Applications
free download

Abstract To process data more efficiently, big data frame- works provide data abstractions to developers To uncover the challenges in using big data frameworks, we first conduct an empirical study on 000 Apache Spark-related questions on Stack Overflow

Quantifying Spatiotemporal Changes in Human Activities Induced by COVID-19 Pandemic Using Daily Nighttime Light Data
free download

The high consistency between the big data of travel intensity and NTL further proved the validity of the results of this study Population migration big data of Baidu map (PMBD) is supported by Baidu (Chinas largest integrated internet ser- vice company)

A survey of machine learning applications to handover management in 5G and beyond
free download

I. INTRODUCTION Wireless communication networks have been witnessing an unprecedented demand in terms of bandwidth and number of connections in this so-called information age in par- ticular the age of big data 1 where data is regarded as new oil . It is reported in

Guest Editorial: Sustainable and intelligent precision agriculture
free download

Abstract The fourth industrial revolution is ongoing, that is characterized by a fusion of emerging technologies such as Industry 4.0, Internet of Things, cloud/edge computing, big data artificial intelligence, and blockchain. Correspondingly Therefore, how to choose a suitable network model and improve the data classification accuracy in heterogeneous networks is a big challenge The data fusion technology in the heterogeneous net- work is of great significance to the processing of big data (Corresponding author: Lei Li.) Lei Li and Ping Ding are with the Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology), Ministry of Education, China, Intelligent Interconnected Systems Laboratory of Anhui Province (Hefei Univer- sity of decryption stages. Index Terms IIoT, Blockchain, Big Data Smart Factory, Data Sharing, Traceable and Revocation. This work was supported in part by the National Natural Science Foundation of China under Grant No. 61373162

A survey on deep learning for datadriven soft sensors
free download

Index Terms Soft Sensor, Deep Learning, Industrial Big Data Datadriven Modeling, Neural Networks In contrast, in big data regions where there are very large training sets, it can be more consistently seen that large NN dominates the other approaches Abstract Large data centers are currently the mainstream infrastructures for big data processing As the core operations in these systems, distributed data operators such as join and aggregation are widely used for big data computing

An efficient data access approach with queue and stack in optimized hybrid join
free download

and business intelligence on basis of real-time data warehouse (RTDW) . Decision support systems are dependent on RTDW, Enterprise Service Bus (ESB) applications and big data : a repository of complex and large data that can be analyzed for decision making

Review of Data Fusion Methods for Real-Time and Multi-Sensor Traffic Flow Analysis
free download

The associate editor coordinating the review of this manuscript and approving it for publication was Sotirios Goudos . flow analysis [17], Internet of Things (IoT) [18] and Big Data , just to name a few It con- tributes to big data growth in general

Towards a service-oriented architecture for the energy efficiency of buildings: A Systematic Review
free download

However, current BMSs are incapable of managing a massive amount of data ( big data ) and therefore cannot extract knowledge or make intelligent decisions in quasi real time Does the article present characteristics of an architecture based on big data This confirms that remote sensing data have entered the big data era . To be more specific, we summarize, in the following, the properties that qualify remote sensing data as a kind of big data . 1) Data Volume: As mentioned before, remote sensing data in the optical, radarScientific data have traditionally been distributed via downloads from data server to local computer. This way of working suffers from limitations as scientific datasets grow toward the petabyte scale. A cloud-native data repository, as defined in this article, offers several model and random perturbation strategies. In , the authors leveraged DP to prevent data privacy leak- age in wireless big data collection and analysis, and proposed two perturbation schemes. One scheme adds noise to perturbMeta Knowledge Graph is mainly a knowledge graph formed by the most basic concept entity and its synonymous relationship, which is the most direct entry to show the basic knowledge of the industry. However, due to the complexity of its data sources and the lack of

Multi Model Implementation on General Medicine Prediction with Quantum Neural Networks
free download

Naimul Mefraz Khan et al., Transfer learning with intelligent training data selection for and V. Dutt, Improving Health Care by Help of Internet of Things and Bigdata Analytics and FSBi-LSTM, Volume 201 IEEE Access SHAH NAZIR et al., Big Data Visualization in With the development of smart grid, IOT devices in the field of power control are widely used. The diversity of types, features and functions of IOT devices not only integrates detailed big data but also challenges the real-time, compatibility and big data processing capability ofmanufacturing environment. In the current manufacturing environment, there is a problem due to the server load caused by big data . In order to solve this problem, studies on various aspects of data processing are being conducted. We

Guest Editorial: Special Issue on AI-Enabled Internet of Dependable and Controllable Things
free download

He is the editor of six books, including Big Data Analytics for Cyber Physical Systems: Machine Learning for the Internet of Things (Elsevier), Smart Cities: Foundations, Principles, and Applications (Hoboken, NJ, USA: Wiley), Security and Privacy in Cyber Physical

Peer-to-Peer Energy Trading Mechanism based on Blockchain and Machine Learning for Sustainable Electrical Power Supply in Smart Grid
free download

How- ever, the on-demand use of energy is considered a big challenge to achieve the optimal cost for house- holds The smart contract enabled predictive analytics module aims to build a prediction model based on historical energy consumption data to predict short-term energy Therefore, it is unsuit- able for detecting anomalies in big data Moreover, its time complexity is O(n), which means it is a linear-time algorithm; therefore, it is suitable for anomaly detection in big data . However, iFor- est is not a perfect method despite its benefits

When the bad is good and the good is bad: Understanding cyber social health through online behavioral change
free download

The insights derived from this thick data modeling approach will contextualize the big data analytics at larger scale and provide deeper insights (see thick data modeling section for more.) Harmful content flows through online communi- ties, where information diffusion of such First, the raw vibration signals as well as envelope signals from source domain machine are obtained. Thereafter, these envelope signals are applied to NCNN for the learning of features from the big training data acquitted from the source domain On the basis of traditional evaluation methods, this paper puts forward the concept of big data for condition evaluation, aiming at introducing new concepts and algorithms into the traditional large power grid industry, so as to improve the reliability of the system Power grid

Machine learning in measurement part 1: error contribution and terminology confusion
free download

measurement system. This is of particular importance for measurement in the age of big data because we need to evaluate the trustworthi- ness of the available data and their impact on the derived conclusions and decision-making

Client Selection for Federated Learning With Non-IID Data in Mobile Edge Computing
free download

To obtain useful information from big data in IoT, machine learning techniques are often applied . Particularly, Federated Learning (FL) , , also known as federated optimization, allows multiple parties to collaboratively train a model without data sharing and gathering

A Gradient-Based Clustering for Multi-Database Mining
free download

This process is called clustering, which is an important unsupervised technique for big data mining. In this article, we present an effective approach to search for the optimal clustering of multiple transaction databases in a weighted undirected similarity graph

Collaborative intelligence: Challenges and opportunities
free download

Compared with the traditional cloud-centered data process- ing mode, the CI system faces many challenges for big data processing, such as latency constraints, and memory occu- pation. Big data processing for CI relies on huge computing resources

Bi-Tier Differential Privacy for Precise Auction-Based People-Centric IoT Service
free download

Page 1. SPECIAL SECTION ON INTELLIGENT BIG DATA ANALYTICS FOR INTERNET OF THINGS, SERVICES AND PEOPLE Received February 2 202 accepted March 1 202 date of publication March 1 202 date of current version April 1

IoT and Fog Computing based Predictive Maintenance Model for Effective Asset Management in Industry 4.0 using Machine Learning
free download

Virtual assets include the data produced from IIoT. One of the applications of the industrial big data is to predict the failure of manufacturing equipment Industrial big data generated from IIoT sensors promotes information visibility The impact reaches the understanding level of what the user is expecting from it . The medical data can be gathered using the advanced machine learning and big data tools like Hadoop, map reduce and map the variables which are needed security space. However, the assumption in many current works is that big training data is widely available and transferable to the main server because data is born at the edge and is generated continuously by IoT devices. This is

Software Engineering for IoT-Driven Data Analytics Applications
free download

tools, and technologies that transform raw data into useful information using software applications . The International Data Corporation forecasts that by the year 2022 the revenue generated by big data analytics will reach approximately 274.3 billion USD . Despite the In future we can trained our model on big data using Spark ML and even on deep learning bimodal approach to get better computation time [23-25]. In Table our proposed technique outperform the two literature works [2 29]

A Deep-Learning Model for Estimating the Impact of Social Events on Traffic Demand on a Cell Basis
free download

To this end, the latest SON platforms leverage massive performance data in the Operation Support System (OSS) by applying Big Data techniques to estimate QoE per connection , . Nonetheless, the large number of factorsA New Subspace Clustering Strategy for AI-Based Data Analysis in IoT System Zhihua Cui, Xuechun Jing, Peng Zhao, Wensheng Zhang, Jin Chen In order to reduce cost and reply promptly, we deploy artificial intelligence (AI) models for data analysis on edge servers

Improving the prediction of heart failure patients survival using SMOTE and effective data mining techniques
free download

death ratio is reduced . Data mining plays an immense role in extracting useful information from big data . It is widely used in almost every field of life like medicine, engineering, business, and educa- tion. Data mining is used