AIMay 19, 2016
Dynamic Bayesian Networks to simulate occupant behaviours in office buildings related to indoor air quality
arXiv:1605.05966v111 citations
Originality Synthesis-oriented
AI Analysis
This work addresses indoor air quality management for building occupants, but it is incremental as it adapts existing Bayesian methods to a specific domain.
The paper tackled modeling human behavior in office buildings using Dynamic Bayesian Networks, applying it to simulate CO2 concentration with occupant interactions.
This paper proposes a new general approach based on Bayesian networks to model the human behaviour. This approach represents human behaviour with probabilistic cause-effect relations based on knowledge, but also with conditional probabilities coming either from knowledge or deduced from observations. This approach has been applied to the co-simulation of the CO2 concentration in an office coupled with human behaviour.