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Green and Sustainable Smart City and role of green Computing: A Survey

by Shailesh Kumar, Md. Athar
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 186 - Number 12
Year of Publication: 2024
Authors: Shailesh Kumar, Md. Athar
10.5120/ijca2024923474

Shailesh Kumar, Md. Athar . Green and Sustainable Smart City and role of green Computing: A Survey. International Journal of Computer Applications. 186, 12 ( Mar 2024), 3-7. DOI=10.5120/ijca2024923474

@article{ 10.5120/ijca2024923474,
author = { Shailesh Kumar, Md. Athar },
title = { Green and Sustainable Smart City and role of green Computing: A Survey },
journal = { International Journal of Computer Applications },
issue_date = { Mar 2024 },
volume = { 186 },
number = { 12 },
month = { Mar },
year = { 2024 },
issn = { 0975-8887 },
pages = { 3-7 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume186/number12/green-and-sustainable-smart-city-and-role-of-green-computing-a-survey/ },
doi = { 10.5120/ijca2024923474 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-03-23T00:18:14.240136+05:30
%A Shailesh Kumar
%A Md. Athar
%T Green and Sustainable Smart City and role of green Computing: A Survey
%J International Journal of Computer Applications
%@ 0975-8887
%V 186
%N 12
%P 3-7
%D 2024
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The smart city provides several services to its citizens. Among them, communication is one of the essential services. Due to the requirement for a high-quality user experience, it is required to deploy dense cellular base stations. The increasing number of cellular base stations raises the issue of energy preservation and smart power scheduling of the base station. To formulate the solution for this green computing issue first a review of recent techniques of energy preservation has been studied. Based on the conducted review a proactive resource scheduling technique has been proposed and their key components have been discussed. Soon, the formulated solution has been implemented and their influence on power saving has been proposed measure.

References
  1. S. Daniel, M. A. Doran, “geoSmartCity: geomatics contribution to the Smart City”, The Proceedings of the 14th Annual International Conference on Digital Government Research, June 17–20, 2013, Quebec City, QC, Canada. ACM.
  2. R. Lea, M. Blackstock, “Smart Cities: an IoT-centric Approach”, IWWISS '14, September 01 - 02 2014, Saint Etienne, France, ACM.
  3. A. Naim, “New Trends in Business Process Management: Applications of Green Information Technologies”, British Journal of Environmental Studies, 1(1): 12-23, 08 Oct. 2021.
  4. G. P. Hancke, B. de Carvalho e Silva, G. P. Hancke Jr., “The Role of Advanced Sensing in Smart Cities”, Sensors 2013, 13, 393-425.
  5. M. Jayachandran, Ch. R. Reddy, S. k. Padmanaban, A. H. Milyani, “Operational planning steps in smart electric power delivery system”, Sci. Rep.,11, 17250, 2021
  6. O. Shurdi, L. Ruci, A. Biberaj, G. Mesi, “5G Energy Efficiency Overview”, European Scientific Journal, Vol.17, No.3, January 2021
  7. N. K. Suryadevara, G. R. Biswal, “Smart Plugs: Paradigms and Applications in the Smart City-and-Smart Grid”, Energies, 12, 1957, 2019
  8. S. K. Rao, R. Prasad, “Impact of 5G Technologies on Smart City Implementation”, Wireless Pers Commun, 100, 161–176, 2018
  9. R. S. Sofana, T. Dragiˇcevi´c, P. Siano, S. R. S. Prabaharan, “Future Generation 5G Wireless Networks for Smart Grid: A Comprehensive Review”, Energies, 12, 2140, 2019
  10. Y. Liu, C. Yang, L. Jiang, S. Xie, Y. Zhang, “Intelligent Edge Computing for IoT-Based Energy Management in Smart Cities”, IEEE Network, 2019
  11. H. C. Leligou, T. Zahariadis, L. Sarakis, E. Tsampasis, A. Voulkidis, T. E. Velivassaki, “Smart Grid: a demanding use case for 5G technologies”, IEEE International Conference on Pervasive Computing and Communications Workshops, 2018
  12. K. C. Chang, K. C. Chu, H. C. Wang, Y. C. Lin, J. S. Pan, “Energy Saving Technology of 5G Base Station Based on Internet of Things Collaborative Control”, IEEE Access, Vol 8, 2020.
  13. E. Baccarelli, M. Scarpiniti, A. Momenzadeh, “Fog-Supported Delay-Constrained Energy-Saving Live Migration of VMs Over MultiPath TCP/IP 5G Connections”, IEEE Access, Vol 6, 2018.
  14. Y. Wang, “Energy-saving Scheme of 5G Base Station Based on LSTM Neural Network”, 2nd International Conference on Applied Physics and Computing, Journal of Physics: Conference Series, 2083, 032026, 2021
  15. T. Yigitcanlar, R. Mehmood, J. M. Corchado, “Green Artificial Intelligence: Towards an Efficient, Sustainable and Equitable Technology for Smart Cities and Futures”, Sustainability, 13, 8952, 2021
  16. J. T. deSouza, A. C. deFrancisco, C. M. Piekarski, G. F. doPrado, “Data Mining and Machine Learning to Promote Smart Cities: A Systematic Review from 2000 to 2018”, Sustainability, 11, 1077, 2019
  17. C. Mahapatra, A. K. Moharana, V. C. M. Leung, “Energy Management in Smart Cities Based on Internet of Things: Peak Demand Reduction and Energy Savings”, Sensors, 17, 2812, 2017
  18. Q. Zhou, Y. Sun, H. Lu, K. Wang, “Learning-based Green Workload Placement for Energy Internet in Smart Cities”, Jour. of Mod. Pow. Sys. and Clean Energy, Vol. 10, No. 1, Jan. 2022
  19. H. Sharma, A. Haque, F. Blaabjerg, “Machine Learning in Wireless Sensor Networks for Smart Cities: A Survey”, Electronics, 10, 1012, 2021
  20. A. Sharif, J. Li, M. Khalil, R. Kumar, M. I. Sharif, A. Sharif, “Internet of Things- Smart Traffic Management System For Smart Cities Using Big Data Analytics”, IEEE, 2017
  21. İ. Kok, M. U. Şisek, S. Özdemir, “A deep learning model for air quality prediction in smart cities”, IEEE International Conference on Big Data (BIGDATA), 2017
  22. N. Zhang, H. Chen, X. Chen, J. Chen, “Semantic Framework of Internet of Things for Smart Cities: Case Studies”, Sensors, 16, 1501, 2016
  23. A. D. L. Heras, A. L. Sendra, F. Z. Polo, “Machine Learning Technologies for Sustainability in Smart Cities in the Post-COVID Era”, Sustainability, 12, 9320, 2020
  24. D. Iskandaryan, F. Ramos, S. Trilles, “Air Quality Prediction in Smart Cities Using Machine Learning Technologies Based on Sensor Data: A Review”, Appl. Sci., 10, 2401, 2020
  25. M. Dey, S. P. Rana, S. Dudley, “A Case Study Based Approach for Remote Fault Detection Using Multi-Level Machine Learning in A Smart Building”, Smart Cities, 3, 401–419, 2020
Index Terms

Computer Science
Information Sciences

Keywords

Data analytics Green AI Green Computing Machine Learning Smart city

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