Article poster: Occupancy Count Prediction for Model Predictive Control in Buildings

Fisayo Caleb Sangogboye, Mikkel Baun Kjærgaard

Research output: Chapter in Book/Report/Conference proceedingConference abstract in proceedingsResearchpeer-review

Abstract

The concept of model predictive control (MPC) has been proposed as a method for optimizing energy consumption in buildings. MPC promises to deliver optimized building management without impeding indoor climatic properties. However, critical to the deployment of MPC are several factors such as weather forecasts and building occupancy predictions. In this poster, we focus on the latter and we present a method for predicting the number of people in buildings. The method relies on the availability of previous datasets of occupancy counts to accurately predict future occupancy counts in a building. In this poster we have utilized datasets from deployed 3D stereo-vision cameras in two rooms. We present the prediction accuracy of our method compared to both ground-truth data and the observed camera counts in the prediction period.

Original languageEnglish
Title of host publicationProceedings of the 4th ACM International Conference on Systems for Energy-Efficient Built Environments
EditorsRasit Eskicioglu
Place of PublicationNew York
PublisherAssociation for Computing Machinery
Publication date8. Nov 2017
Article number40
ISBN (Print)978-1-4503-5544-5
ISBN (Electronic)9781450354769
DOIs
Publication statusPublished - 8. Nov 2017
Event4th ACM International Conference on Systems for Energy-Efficient Built Environments - Delft, Netherlands
Duration: 8. Nov 20179. Nov 2017
Conference number: 4

Conference

Conference4th ACM International Conference on Systems for Energy-Efficient Built Environments
Number4
Country/TerritoryNetherlands
CityDelft
Period08/11/201709/11/2017

Keywords

  • Building occupancy, camera counters, count estimation, occupancy prediction

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