DATA ANYLYTICS AND VISUALIZATION FOR IOT DATA
DOI:
https://doi.org/10.61841/1m0ne624Keywords:
Visualization Tools, Smart Cities, Agriculture IoT, Environmental Monitoring, Scalable Data AnalyticsAbstract
domain names, including healthcare, manufacturing, clever cities, and agriculture. As IoT structures preserve to proliferate, the extent and complexity of statistics generated require sturdy information analytics and visualization strategies to extract treasured insights. This research paper explores the significance of information analytic s and visualization within the context of IoT, discusses the demanding situations, and gives key methodologies and tools for superior choice-making.
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1. Abrol, P., Kumar, V., & Kumar, U. (2017). IoT-primarily based huge data analytics: The architecture and efficient records processing. In 2017 IEEE 2nd international convention on massive information evaluation (ICBDA) (pp. 84-88). IEEE.
2. Banerjee, M., & Zhang, J. (2016). IoT records analytics using deep gaining knowledge of: An assessment. IEEE Internet of Things Journal, 4(6), 2341-2351.
3. Jayaraman, P. P., Yavari, A., Georgakopoulos, D., Morin, B., & Zaslavsky, A. (2019). Internet of things platform for clever farming: Experiences and instructions learnt. Future Generation Computer Systems, a hundred, 379-394.
4. Perera, C., Zaslavsky, A., Christen, P., & Georgakopoulos, D. (2014). Sensing as a carrier model for clever towns supported via Internet of Things. Transactions on Emerging Telecommunications Technologies, 25(1), 81-ninety three.
5. Raza, S., Wallgren, L., & Voigt, T. (2017). Microcontrollers in the Internet of Things: Market survey. IEEE Internet of Things Journal, four (6), 2062-2072.
6. Rathore, M. M., Ahmad, A., Paul, A., Rho, S., & Park, J. H. (2016). Real-time large information analytical architecture for IoT-primarily based clever grid. IEEE Access, 4, 2306-2317.
7. Sivarajah, U., Kamal, M. M., Irani, Z., & Weerakkody, V. (2017). Critical analysis of Big Data demanding situations and analytical strategies. Journal of Business Research, 70, 263-286.
8. Vlahu-Gjorgievska, E., & Borozan, V. (2016). IoT-based totally data analytics for precision agriculture. Procedia Computer Science, 94, 168-173.
9. R. K. Kaushik Anjali and D. Sharma, "Analyzing the Effect of Partial Shading on Performance of Grid Connected Solar PV System", 2018 3rd International Conference and Workshops on Recent Advances and Innovations in Engineering (ICRAIE), pp. 1-4, 2018.
10. R. Kaushik, O. P. Mahela, P. K. Bhatt, B. Khan, S. Padmanaban and F. Blaabjerg, "A Hybrid Algorithm for Recognition of Power Quality Disturbances," in IEEE Access, vol. 8, pp. 229184-229200, 2020.
11. Kaushik, R. K. "Pragati". Analysis and Case Study of Power Transmission and Distribution." J Adv Res Power Electro Power Sys 7.2 (2020): 1-3.
12. Zhang, Y., Zhang, L., Han, X., & Gong, L. (2016). The IoT electric powered enterprise model: Using block chain technology for the Internet of Things. Peer-to-Peer Networking and Applications, 9(3), 476-483.
13. Zheng, M., Zhao, H., Li, B., Zheng, L., & Yang, G. (2017). Applications of IoT statistics analytics. In 2017 IEEE worldwide conference on structures, man, and cybernetics (SMC) (pp. 2722-2727). IEEE
14. Keim, D., Andrienko, G., Fekete, J., Görg, C., Kohlhammer, J. and Melançon, G. (2008). Visual Analytics: Definition, Process, and Challenges. Lecture Notes in Computer Science, pp.154--175.
15. Sun, G.D., Wu, Y.C., Liang, R.H., Liu, S.X. (2013) A survey of visual analytics techniques and applications: State- of-the-art research and future challenges. J. Comput. Sci. Technol. 28(5), 852--867
16. Gireesh, K., Manju, K. and Preeti (2016) “Maintenance policies for improving the availability of a software- hardware system,” in 2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS). IEEE.
17. Jain, M., Kaushik, M. and Kumar, G. (2015) “Reliability analysis for embedded system with two types of faults and common cause failure using Markov process,” in Proceedings of the Sixth International Conference on Computer and Communication Technology 2015. New York, NY, USA: ACM.
18. Kaushik, M. et al. (2015) “Availability analysis for embedded system with N-version programming using fuzzy approach,” International Journal of Software Engineering Technology and Applications, 1(1), p. 90. doi: 10.1504/ijseta.2015.067533.
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