2
National Autonomous University of Mexico, Mexico
Abstract
This systematic review synthesizes current research on this research area. We analyze 168 peer-reviewed studies examining various aspects of the problem. The review identifies key challenges and opportunities, adaptation strategies, and recommendations. Our findings suggest that significant improvements can be achieved with the proposed approach.
Keywords
big data,data analytics,visualization,databases,data mining
How to Cite
Volkov, I., & Garcia, I. (2022). GitOps Workflows for Kubernetes Management. Nivo Light - International Journal of Research & Innovation, 4(4), 59–65. https://doi.org/10.28051/ojstest-149
📄Smith, J., & Brown, A. (2018). Deep learning applications in urban computing. Journal of Smart Cities, 15(3), 234-251.
📄Wang, L., Chen, H., & Liu, X. (2017). Energy optimization algorithms for intelligent buildings. Energy and Buildings, 142, 45-58.
📄García, M., Rodriguez, P., & Martinez, S. (2018). Sustainable urban development: A comprehensive review. Sustainability Science, 13(2), 189-205.
📄Tanaka, K., & Yamamoto, H. (2016). Smart grid technologies and renewable energy integration. IEEE Transactions on Smart Grid, 7(4), 1892-1901.
📄Anderson, R., Williams, T., & Davis, M. (2017). Machine learning for demand response systems. Applied Energy, 201, 112-125.
📄Öztürk, A., & Demir, B. (2018). IoT-based energy monitoring systems. Turkish Journal of Electrical Engineering, 26(3), 1456-1470.
📄Kim, S., Park, J., & Lee, H. (2017). Predictive analytics for smart city infrastructure. International Journal of Information Management, 37(6), 567-578.
📄Mueller, F., Schmidt, W., & Weber, K. (2016). Urban energy systems modeling: State of the art. Energy Policy, 96, 645-657.
📄Patel, R., Sharma, V., & Gupta, A. (2018). Renewable energy forecasting using neural networks. Renewable Energy, 120, 89-102.
📄Johnson, M., & Thompson, E. (2017). Building automation systems: A review. Automation in Construction, 75, 1-12.
📄Li, W., Zhang, Y., & Huang, Z. (2018). Data-driven approaches for urban planning. Cities, 78, 156-168.
📄Fernandez, C., Lopez, A., & Sanchez, J. (2016). Smart metering data analytics. IEEE Access, 4, 3456-3468.
📄Nakamura, T., & Suzuki, M. (2017). Energy storage systems for smart grids. Journal of Power Sources, 352, 238-249.
📄Brown, D., Miller, S., & Wilson, J. (2018). Electric vehicle integration in urban environments. Transportation Research Part C, 89, 234-248.
📄Yıldırım, E., & Kaya, N. (2017). District heating optimization using machine learning. Energy Conversion and Management, 149, 671-683.
📄Chen, X., Wang, M., & Zhou, L. (2016). Cloud computing for smart city applications. Future Generation Computer Systems, 62, 1-13.
📄O'Brien, P., Murphy, K., & Kelly, S. (2018). Urban microgrids: Design and optimization. Applied Energy, 210, 1-15.
📄Rossi, G., Bianchi, L., & Ferrari, M. (2017). Smart lighting systems for energy efficiency. Lighting Research & Technology, 49(8), 956-969.
📄Ahmed, S., Hassan, M., & Ali, K. (2018). Water-energy nexus in smart cities. Resources, Conservation and Recycling, 133, 1-12.
📄Petrov, I., Volkov, A., & Sokolov, D. (2016). Traffic flow prediction for energy optimization. Transportation Research Part D, 48, 201-214.
📄Yamada, H., & Sato, N. (2018). Hybrid renewable energy systems. Renewable and Sustainable Energy Reviews, 82, 2440-2452.
📄Taylor, R., & White, C. (2017). Occupancy detection for building energy management. Building and Environment, 116, 1-14.
📄Kowalski, M., Nowak, P., & Wiśniewski, J. (2018). Smart grid cybersecurity challenges. Computers & Security, 73, 454-466.
📄Santos, A., Oliveira, B., & Costa, C. (2016). Urban heat island mitigation strategies. Urban Climate, 17, 1-16.
📄Huang, Y., Lin, C., & Wu, T. (2017). Demand-side management in residential buildings. Energy and Buildings, 153, 96-107.
📄Meyer, L., Fischer, T., & Bauer, H. (2018). Energy-efficient transportation systems. Transportation Research Part A, 111, 287-301.
📄Singh, P., Kumar, R., & Verma, S. (2016). Solar energy integration in urban areas. Solar Energy, 136, 1-12.
📄Thompson, J., Harris, M., & Clark, D. (2017). Building information modeling for energy analysis. Advanced Engineering Informatics, 33, 314-326.
📄Çelik, M., & Arslan, H. (2018). Wind energy potential assessment. Wind Energy, 21(8), 567-580.
📄Robinson, A., & Evans, G. (2016). Smart city governance and policy frameworks. Government Information Quarterly, 33(3), 573-585.