Data mining, big data analysis and predictive modelling for intelligent geyser system scheduler
Masters in Engineering Student
Project: Intelligent Geyser System
Bio:Marcel has an engineering bachelor degree in Electrical and Electronic Engineering. He has a passion for all tech related aspects and how to use them to improve lives on a daily basis. From an early age he has had a fascination with computers and the capabilities they provide to assist people with a multitude of areas in their lives. With many things in life, he eagerly tinkers to find out what makes things tick, and how to improve them.
My research ties in with the Intelligent Geyser System (IGS) project, on the side of dynamic scheduling. Currently, users of an IGS are able to remotely control their geysers through a web site and a mobile phone application, where control schemes are recommended to minimise “standing losses”. This process also provides a prediction of expected savings based on changes to the control scheme. My contribution will be to further expand this functionality by optimising the energy efficiency for each individual geyser by minimising the “standing losses”, taking into account the previous usage patterns and modifying the recommended control scheme to more optimally follow the habits of the end user. The aim is to provide a control algorithm which enables maximum energy savings without the user realising their geyser is on a schedule, a ‘set and forget’ idea. This is set to happen autonomously with little to no human interaction required. During my work I cover fields relating mainly to data sciences, which involve the development of a data cleaning framework and the subsequent exploration and mining of the obtained data. This forms the basis of predictive analysis for better decision making accuracy. Statistical machine learning will be used to perform the predictive analysis on the database data. Finally, after the predictions have been made, this will be used in conjunction with the electric water heater model to obtain an efficiency model to optimise energy usage of the geyser.