Ph.D. Proposal Defense

Holistic Home Energy Management:
From Sensing to Data Analytics

David Lachut

2:00pm Tuesday, 11 August 2015, ITE 325b

As home automation tools become more prevalent, they provide great potential to assist energy conservation and promote sustainable energy use in a way that increases users’ quality of life. This paper proposes the Greenhome System: a software system for using off-the-shelf home automation components and back-end data analytics to provide intelligent home energy management capabilities primarily targeted to renewable powered homes. The system will take input from various sensors and user input to detect user activities, predict home energy consumption, and make energy consumption recommendations to users. To accomplish the project goals, the Greenhome system requires in-home hardware and software components, a mobile component for user interaction, and a server component to tie them together. These components will accomplish tasks of data collection and analysis, activity and anomaly detection, prediction, planning, and recommendation.

This project builds on prior research in several areas, combining such diverse fields as predictive analytics, data visualization and annotation, planning, and recommender systems into a holistic approach. Combining these fields will result in new adaptations and make the overall Greenhome System a novel contribution. Work has begun on the Greenhome System preliminary to this proposal, with published work on residential sensor system design and implementation, data annotation collection, and energy demand prediction. It remains to incorporate automated self-maintenance, user activity detection, and personalized recommendations into a holistic system for home energy management.

Committee: Drs. Nilanjan Banerjee (chair), Ting Zhu, Charles Nicholas, Nirmalya Roy