Journal of ISMAC
IRO Journals
Volume 1 — Issue 1 — June 2019

TOWARDS SUSTAINABLE INDUSTRIALIZATION USING BIG DATA AND INTERNET OF THINGS

https://doi.org/10.36548/jismac.2019.1.003
Pages: 24-37
PDF
V. Suma
Professor Department of Information Science and Engineering, Dayananda Sagar College of Engineering,
PDF

How to Cite

Suma, V. 2019. “TOWARDS SUSTAINABLE INDUSTRIALIZATION USING BIG DATA AND INTERNET OF THINGS”. Journal of ISMAC 1 (1): 24-37. https://doi.org/10.36548/jismac.2019.1.003.
ACM ACS APA ABNT Chicago Harvard IEEE MLA Turabian Vancouver AMA

Download Citation

Endnote/Zotero/Mendeley (RIS) BibTeX

Keywords

— Internet of things
— Big-data
— Sustainability
— Industries
— Production
— Quality of life improvement
Published: 30-06-2019

Abstract

The developing nations requires to have sustainable developments in the industries to have new product development and continuous improvement in the social and economic levels paving way for the customer satisfaction. The Big data and the Internet of things are innovative technologies that have made their separate stand in the industrial sector of manufacturing and providing competitive edge to the companies. So the combining of two technologies would multiply anticipation and would create way for the enhanced productivity by satisfying the global needs of the business. Further, the internet of thing along with the big data analytics is also expected to provide with the enhanced security provision, quality of process and products with reduced production down time and financial risk. So the paper proposes the big data and IoT role in the industrial sector and evaluates its performance by analyzing the impacts of the big data and the internet of things in the industry to have sustainability in production process. The proposed framework also analyses the potential applications and the key advantages offered by the integration of the internet of things and the big data.

References

  1. De Mauro, Andrea, Marco Greco, and Michele Grimaldi. "What is big data? A consensual definition and a review of key research topics." In AIP conference proceedings, vol. 1644, no. 1, pp. 97-104. AIP, 2015.
  2. Jones, Matthew. "What we talk about when we talk about (big) data." The Journal of Strategic Information Systems 28, no. 1 (2019): 3-16.
  3. Mikalef, Patrick, Ilias O. Pappas, John Krogstie, and Michail Giannakos. "Big data analytics capabilities: a systematic literature review and research agenda." Information Systems and e-Business Management 16, no. 3 (2018): 547-578.
  4. Tonidandel, Scott, Eden B. King, and Jose M. Cortina. "Big data methods: Leveraging modern data analytic techniques to build organizational science." Organizational Research Methods 21, no. 3 (2018): 525-547.
  5. Sun, Zhaohao, Lizhe Sun, and Kenneth Strang. "Big data analytics services for enhancing business intelligence." Journal of Computer Information Systems 58, no. 2 (2018): 162-169.
  6. Amado, Alexandra, Paulo Cortez, Paulo Rita, and Sérgio Moro. "Research trends on Big Data in Marketing: A text mining and topic modeling based literature analysis." European Research on Management and Business Economics 24, no. 1 (2018): 1-7.
  7. Storey, Veda C., and Il-Yeol Song. "Big data technologies and management: What conceptual modeling can do." Data & Knowledge Engineering 108 (2017): 50-67.
  8. Akter, Shahriar, Samuel Fosso Wamba, Angappa Gunasekaran, Rameshwar Dubey, and Stephen J. Childe. "How to improve firm performance using big data analytics capability and business strategy alignment?" International Journal of Production Economics 182 (2016): 113-131.
  9. Akter, Shahriar, and Samuel Fosso Wamba. "Big data analytics in E-commerce: a systematic review and agenda for future research." Electronic Markets 26, no. 2 (2016): 173-194.
  10. Sivarajah, Uthayasankar, Muhammad Mustafa Kamal, Zahir Irani, and Vishanth Weerakkody. "Critical analysis of Big Data challenges and analytical methods." Journal of Business Research 70 (2017): 263-286.
  11. Hu, Jiankun, and Athanasios V. Vasilakos. "Energy big data analytics and security: challenges and opportunities." IEEE Transactions on Smart Grid 7, no. 5 (2016): 2423-2436.
  12. Lv, Zhihan, Houbing Song, Pablo Basanta-Val, Anthony Steed, and Minho Jo. "Next-generation big data analytics: State of the art, challenges, and future research topics." IEEE Transactions on Industrial Informatics 13, no. 4 (2017): 1891-1899.
  13. Zhou, Keliang, Taigang Liu, and Lifeng Zhou. "Industry 4.0: Towards future industrial opportunities and challenges." In 2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), pp. 2147-2152. IEEE, 2015.
  14. Kiel, Daniel, Julian M. Müller, Christian Arnold, and Kai-Ingo Voigt. "Sustainable industrial value creation: Benefits and challenges of industry 4.0." International Journal of Innovation Management 21, no. 08 (2017): 1740015.
  15. Sun, Yunchuan, Houbing Song, Antonio J. Jara, and Rongfang Bie. "Internet of things and big data analytics for smart and connected communities." IEEE access 4 (2016): 766-773.
  16. Witkowski, Krzysztof. "Internet of things, big data, industry 4.0–innovative solutions in logistics and supply chains management." Procedia Engineering 182 (2017): 763-769.
  17. Koo, Dan, Kalyan Piratla, and C. John Matthews. "Towards sustainable water supply: schematic development of big data collection using internet of things (IoT)." Procedia engineering118 (2015): 489-497.
  18. Maksimovic, M. "Greening the future: Green Internet of Things (G-IoT) as a key technological enabler of sustainable development." In Internet of things and big data analytics toward next-generation intelligence, pp. 283-313. Springer, Cham, 2018.
  19. Channe, Hemlata, Sukhesh Kothari, and Dipali Kadam. "Multidisciplinary model for smart agriculture using internet-of-things (IoT), sensors, cloud-computing, mobile-computing & big-data analysis." Int. J. Computer Technology & Applications6, no. 3 (2015): 374-382.
  20. Mourtzis, D., E. Vlachou, and N. Milas. "Industrial Big Data as a result of IoT adoption in manufacturing." Procedia Cirp 55 (2016): 290-295.