Critique of Occupancy Schedules Learning Process Through a Data Mining Framework

AbstractIn this paper I will be reviewing and evaluating the work of Simona D'Oca and Tianzhen Hong of the Lawrence Berkeley National Laboratory, entitled _Occupancy Schedules Learning Process Through a Data Mining Framework_, published in the Journal of Energy and Buildings in February 2015. After a brief summary of the paper and its findings, I present the author's background and related previous work - to find that their results are hard to interpret quantitatively, but potentially can be useful for qualitative workspace improvement. Subsequenlty I conduct a brief overview of related work and possible improvements, followed by my personal reflections and suggested future work pathways. I finish with a brief conclusion.

Keywords: building occupancy, decision tree model, building energy consumption

Summary

n this paper I will be reviewing and evaluating the work of Simona D'Oca and Tianzhen Hong of the Lawrence Berkeley National Laboratory, entitled Occupancy Schedules Learning Process Through a Data Mining Framework (OSL), published in the Journal of Energy and Buildings in February 2015