Name
Abstract | ||
|---|---|---|
In this paper, the trend as an important component in activities of daily living is modelled and integrated to a single-occupant occupancy simulator. Therefore, in the occupancy signal generated by the simulator, both seasonality and trend are included in occupant's movements. As the result of trends integrated to the simulator, occupancy signals with different types of trends such as increasing, decreasing, cyclic and chaotic trends can be generated. Different types of the trend in occupancy signal improves the occupancy modelling by enabling the model to incorporate long term differentiation in occupant's behaviour i.e. ageing, health, and other changes in his/her activities of daily living. In this paper, the effect of trends in the occupancy signal generated by the modified simulator is tested by applying autocorrelation function. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/UKSIM.2011.38 | UKSim |
Keywords | Field | DocType |
modified simulator,elderly lifestyle,chaotic trend,autocorrelation function,occupancy signal,trend modelling,single-occupant occupancy simulator,different type,daily living,occupancy simulator,long term differentiation,important component,data models,uncertainty,data model,home automation,smart home,gaussian distribution,correlation,layout | Data modeling,Activities of daily living,Simulation,Seasonality,Home automation,Occupancy,Environmental science,Chaotic,Autocorrelation | Conference |
Citations | PageRank | References |
8 | 0.62 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sawsan Mahmoud | 1 | 60 | 4.93 |
| M. Javad Akhlaghinia | 2 | 10 | 1.37 |
| Ahmad Lotfi | 3 | 88 | 20.21 |
| Caroline Langensiepen | 4 | 61 | 6.12 |