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Mr. Vikrant Tapas serves as Workshop Superintendent in the Department of Mechanical Engineering at NMDC DAV Polytechnic, Dantewada, Chhattisgarh, India. His interests include Industrial Engineering, Energy Management, Manufacturing Systems, and Sustainable Technologies.
The rising demand for energy efficiency, sustainability, and intelligent resource management has propelled the implementation of cloud-based energy consumption analytics in residential, commercial, and industrial sectors. Conventional energy monitoring systems frequently exhibit deficiencies in scalability, real-time processing capabilities, and sophisticated analytical functions essential for contemporary energy management. Cloud computing offers a robust platform for the collection, storage, processing, and analysis of extensive energy consumption data produced by smart meters, IoT devices, sensors, and energy management systems. Integrating cloud technologies with artificial intelligence, machine learning, big data analytics, and edge computing enables organisations to derive actionable insights into energy consumption trends, optimise resource distribution, minimise operating expenses, and enhance sustainability. This chapter examines the architectures, methodology, applications, problems, and future trajectories of cloud-based energy consumption analytics, emphasising its significance in promoting smart energy ecosystems and sustainable development.