Through the continual application of sensors, wireless networking, network communication and cloud computing technology, vast volumes of data are increasingly collected in the energy sector which needs to be utilized for effective management. In this project, the overall perspective is to analyze energy consumption data collected from households’ smart meters in London and combining it with the application of cloud data technology. I will explore and utilize a state-of-the-art cloud service infrastructure to analyze and make smart decisions on managing energy usage. There is interest in using data mining techniques and time series for machine learning modelling to deliver a predictive measurement approach for forecast consumption. The cloud service proposed is Amazon Web Services (AWS) which will be used as statistical data for daily energy use, it can collect, analyze, and implement machine learning models to learn a user’s behaviors and enhance energy efficiency by automatically alerting the user when necessary in real-time. There needs to be a warning mechanism such as a web-based and mobile application which can interact with users through energy dashboards and SMS/emails, that way alerting the user and utility companies on excess consumption which is recommended in this research.
Professional Studies (MS)
Department, Program, or Center
Graduate Programs & Research (Dubai)
Al Zubairi, Ghaith Ahmed, "Implementation of cloud services by using real-time analysis to reduce energy consumption" (2020). Thesis. Rochester Institute of Technology. Accessed from