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  1. Research Research
  2. enerFACEpredict - energy consumtion prediction with human interaction enerFACEpredict - energy consumtion prediction with human interaction

enerFACEpredict - energy consumtion prediction with human interaction

With a combination of machine learning and user interaction the energy consumption of buildings shall be predicted realistically.

Brief information

School:

Engineering and Architecture

Status:

Completed

Period:

01.12.2019 - 30.06.2021

Overview

In this project, the uncertainties in forecasting the energy consumption of buildings are to be countered with user interactions and a self-learning ML-algorithm. The system forecasts can be adapted by the user to his actual planning and validated immediately in a real-time simulation with regard to energy efficiency and comfort requirements. The self-learning mechanism ensures that the system continuously adapts and optimizes itself to the specific conditions.

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Facts

Type of project

Forschung

Internal organisations involved
  • iHomeLab
External project partner
  • planergie ag
External project funder
  • Innosuisse
Funding
  • Innosuisse - HSLU als Hauptforschungspartnerin (Main Research Partner)
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Persons involved: internal

Project manager
  • Guido Kniesel
Member of project team
  • Martin Biallas
  • Edith Birrer
  • Daniel Bolliger
  • Martin Camenzind
  • Patric Eberle
  • Patrick Huber Mittler
  • Clemens Nieke
  • Andrew Paice
  • Andreas Rumsch
  • Benjamin Vera
  • Stefan Winterberger
  • Martin Wüthrich

Brief information

School:

Engineering and Architecture

Status:

Completed

Period:

12/01/2019 - 06/30/2021

Project Head

Guido Kniesel

Senior Research Associate

+41 41 349 33 27

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