Use of Big Data Tools and Industrial Internet of Things: An Overview

Big data is ever playing an important role in the industry as well as many other organizations. With the passage of time, the volume of data is increasing. This increase will create huge bulk of data which needs proper tools and techniques to handle its management and organization. Different techniques and tools are being used to properly handle the management of data. A detailed report of these techniques and tools is needed which will help researchers to easily identify a tool for their data and take help to easily manage the data, organize the data, and extract meaningful information from it. The proposed study is an endeavour toward summarizing and identifying the tools and techniques for big data used in Industrial Internet of Things. This report will certainly help researchers and practitioners to easily use the tools and techniques for their need in an effective way.

[1]  Yingfeng Zhang,et al.  A big data-driven framework for sustainable and smart additive manufacturing , 2021, Robotics Comput. Integr. Manuf..

[2]  Georges Kaddoum,et al.  A Big Data-Enabled Consolidated Framework for Energy Efficient Software Defined Data Centers in IoT Setups , 2020, IEEE Transactions on Industrial Informatics.

[3]  Liyana Shuib,et al.  The impact of big data on firm performance in hotel industry , 2020, Electron. Commer. Res. Appl..

[4]  Der-Jiunn Deng,et al.  Concept Drift Detection and Adaption in Big Imbalance Industrial IoT Data Using an Ensemble Learning Method of Offline Classifiers , 2019, IEEE Access.

[5]  Sirkka-Liisa Jämsä-Jounela,et al.  Industry 4.0 based process data analytics platform: A waste-to-energy plant case study , 2020, International Journal of Electrical Power & Energy Systems.

[6]  Anass Cherrafi,et al.  Understanding Big Data Analytics for Manufacturing Processes: Insights from Literature Review and Multiple Case Studies , 2019, Comput. Ind. Eng..

[7]  Habib Ullah Khan,et al.  Big data analytics: does organizational factor matters impact technology acceptance? , 2017, Journal of Big Data.

[8]  Iván García-Magariño,et al.  A Comprehensive Analysis of Healthcare Big Data Management, Analytics and Scientific Programming , 2020, IEEE Access.

[9]  Rusli Abdullah,et al.  An Integrated SEM-Neural Network Approach for Predicting Determinants of Adoption of Wearable Healthcare Devices , 2019, Mob. Inf. Syst..

[10]  Ali Kashif Bashir,et al.  A Parallel Military-Dog-Based Algorithm for Clustering Big Data in Cognitive Industrial Internet of Things , 2021, IEEE Transactions on Industrial Informatics.

[11]  Arun Kumar Sangaiah,et al.  Big Data Cleaning Based on Mobile Edge Computing in Industrial Sensor-Cloud , 2020, IEEE Transactions on Industrial Informatics.

[12]  John G. Breslin,et al.  Big data and stream processing platforms for Industry 4.0 requirements mapping for a predictive maintenance use case , 2020 .

[13]  Francesco Calza,et al.  Big data and natural environment. How does different data support different green strategies? , 2020 .

[14]  Peng Jiang,et al.  An Intelligent Outlier Detection Method With One Class Support Tucker Machine and Genetic Algorithm Toward Big Sensor Data in Internet of Things , 2019, IEEE Transactions on Industrial Electronics.

[15]  Tao Zhu,et al.  An architecture for aggregating information from distributed data nodes for industrial internet of things , 2017, Comput. Electr. Eng..

[16]  Chin-Yin Huang,et al.  A Realization of Cyber-Physical Manufacturing Control System Through Industrial Internet of Things , 2019 .

[17]  Dimitris Mourtzis,et al.  Architecture and development of an Industrial Internet of Things framework for realizing services in Industrial Product Service Systems , 2018 .

[18]  Moneer Helu,et al.  Scalable data pipeline architecture to support the industrial internet of things , 2020 .

[19]  Yingfeng Zhang,et al.  A comprehensive review of big data analytics throughout product lifecycle to support sustainable smart manufacturing: A framework, challenges and future research directions , 2019, Journal of Cleaner Production.

[20]  Laurence T. Yang,et al.  ADTT: A Highly Efficient Distributed Tensor-Train Decomposition Method for IIoT Big Data , 2021, IEEE Transactions on Industrial Informatics.

[21]  Mohamed Elhoseny,et al.  Challenges and recommended technologies for the industrial internet of things: A comprehensive review , 2020 .

[22]  Derek McAuley,et al.  Avoiding the Internet of Insecure Industrial Things , 2018, Comput. Law Secur. Rev..

[23]  Shah Nazir,et al.  Big Data Visualization in Cardiology—A Systematic Review and Future Directions , 2019, IEEE Access.

[24]  Shah Nazir,et al.  Deep Learning Algorithms and Multicriteria Decision-Making Used in Big Data: A Systematic Literature Review , 2020, Complex..

[25]  Joe Cunningham,et al.  The industrial internet of things (IIoT): An analysis framework , 2018, Comput. Ind..

[26]  Javier Villalba-Diez,et al.  Challenges and Opportunities for Publishing IIoT Data in Manufacturing as a Service Business , 2019 .

[27]  Devarshi Shah,et al.  Feature engineering in big data analytics for IoT-enabled smart manufacturing - Comparison between deep learning and statistical learning , 2020, Comput. Chem. Eng..

[28]  Lamia Chaari,et al.  A New Architecture for Cognitive Internet of Things and Big Data , 2019, KES.

[29]  Dingfu Jiang,et al.  The construction of smart city information system based on the Internet of Things and cloud computing , 2020, Comput. Commun..

[30]  Habib Ullah Khan,et al.  Security Analysis of IoT Devices by Using Mobile Computing: A Systematic Literature Review , 2020, IEEE Access.

[31]  Daoqu Geng,et al.  Big Data-Based Improved Data Acquisition and Storage System for Designing Industrial Data Platform , 2019, IEEE Access.

[32]  Joel J. P. C. Rodrigues,et al.  Data management techniques for Internet of Things , 2020 .

[33]  Guan Huang,et al.  Research on the optimization of IIoT data processing latency , 2020, Comput. Commun..

[34]  Sylwia Gierej,et al.  The Framework of Business Model in the Context of Industrial Internet of Things , 2017 .

[35]  Mingdong Tang,et al.  A Secure FaBric Blockchain-Based Data Transmission Technique for Industrial Internet-of-Things , 2019, IEEE Transactions on Industrial Informatics.

[36]  Victor I. Chang,et al.  Applicability of Big Data Techniques to Smart Cities Deployments , 2017, IEEE Transactions on Industrial Informatics.

[37]  Mamoona Humayun,et al.  Internet of things and ransomware: Evolution, mitigation and prevention , 2020, Egyptian Informatics Journal.

[38]  Wei Chen,et al.  Intelligent manufacturing production line data monitoring system for industrial internet of things , 2020, Comput. Commun..

[39]  Victor Chang,et al.  IoT, big data and HPC based smart flood management framework , 2017, Sustain. Comput. Informatics Syst..

[40]  V. Józsa,et al.  Application of big data analysis technique on high-velocity airblast atomization: Searching for optimum probability density function , 2020 .

[41]  Lihui Wang,et al.  Big Data Driven Edge-Cloud Collaboration Architecture for Cloud Manufacturing: A Software Defined Perspective , 2020, IEEE Access.

[42]  Majaz Moonis,et al.  Mobile cloud computing based stroke healthcare system , 2019, Int. J. Inf. Manag..

[43]  T. Zagloel,et al.  Knowledge growth and development: internet of things (IoT) research, 2006–2018 , 2019, Heliyon.

[44]  Jing Huang,et al.  A secure and efficient data sharing scheme based on blockchain in industrial Internet of Things , 2020, J. Netw. Comput. Appl..

[45]  Jin Wang,et al.  Statistical process monitoring as a big data analytics tool for smart manufacturing , 2017, Journal of Process Control.

[46]  Shah Nazir,et al.  Big Data Features, Applications, and Analytics in Cardiology—A Systematic Literature Review , 2019, IEEE Access.

[47]  Prem Prakash Jayaraman,et al.  The Role of Big Data Analytics in Industrial Internet of Things , 2019, Future Gener. Comput. Syst..

[48]  Kim-Kwang Raymond Choo,et al.  Multimedia big data computing and Internet of Things applications: A taxonomy and process model , 2018, J. Netw. Comput. Appl..