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Modeling occupant behavior in buildings
In the last four decades several methods have been used to model occupants' presence and actions (OPA) in buildings according to different purposes, available computational power, and technical solutions. This study reviews approaches, methods and key findings related to OPA modeling in buildin...
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| Main Authors: | , , , , , , , , , , , , , , , , , , |
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| Format: | Default Article |
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2020
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| Online Access: | https://hdl.handle.net/2134/11988171.v1 |
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| _version_ | 1818167680869335040 |
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| author | Salvatore Carlucci Marilena De Simone Steven Firth Mikkel B Kjærgaard Romana Markovic Mohammad Saiedur Rahaman Masab Khalid Annaqeeb Silvia Biandrate Anooshmita Das Jakub Wladyslaw Dziedzic Gianmarco Fajilla Matteo Favero Martina Ferrando Jakob Hahn Mengjie Han Yuzhen Peng Flora Salim Arno Schlüter Christoph van Treeck |
| author_facet | Salvatore Carlucci Marilena De Simone Steven Firth Mikkel B Kjærgaard Romana Markovic Mohammad Saiedur Rahaman Masab Khalid Annaqeeb Silvia Biandrate Anooshmita Das Jakub Wladyslaw Dziedzic Gianmarco Fajilla Matteo Favero Martina Ferrando Jakob Hahn Mengjie Han Yuzhen Peng Flora Salim Arno Schlüter Christoph van Treeck |
| author_sort | Salvatore Carlucci (8580942) |
| collection | Figshare |
| description | In the last four decades several methods have been used to model occupants' presence and actions (OPA) in buildings according to different purposes, available computational power, and technical solutions. This study reviews approaches, methods and key findings related to OPA modeling in buildings. An extensive database of related research documents is systematically constructed, and, using bibliometric analysis techniques, the scientific production and landscape are described. The initial literature screening identified more than 750 studies, out of which 278 publications were selected. They provide an overarching view of the development of OPA modeling methods. The research field has evolved from longitudinal collaborative efforts since the late 1970s and, so far, covers diverse building typologies mostly concentrated in a few climate zones. The modeling approaches in the selected literature are grouped into three categories (rule-based models, stochastic OPA modeling, and data-driven methods) for modeling occupancy-related target functions and a set of occupants’ actions (window, solar shading, electric lighting, thermostat adjustment, clothing adjustment and appliance use). The explanatory modeling is conventionally based on the model-based paradigm where occupant behavior is assumed to be stochastic, while the data-driven paradigm has found wide applications for the predictive modeling of OPA, applicable to control systems. The lack of established standard evaluation protocols was identified as a scientifically important yet rarely addressed research question. In addition, machine learning and deep learning are emerging in recent years as promising methods to address OPA modeling in real-world applications. |
| format | Default Article |
| id | rr-article-11988171 |
| institution | Loughborough University |
| publishDate | 2020 |
| record_format | Figshare |
| spelling | rr-article-119881712020-02-28T00:00:00Z Modeling occupant behavior in buildings Salvatore Carlucci (8580942) Marilena De Simone (8580945) Steven Firth (1171635) Mikkel B Kjærgaard (8580948) Romana Markovic (8580951) Mohammad Saiedur Rahaman (8580954) Masab Khalid Annaqeeb (8580957) Silvia Biandrate (8580960) Anooshmita Das (8580963) Jakub Wladyslaw Dziedzic (8580966) Gianmarco Fajilla (8580969) Matteo Favero (8580972) Martina Ferrando (8580975) Jakob Hahn (8580978) Mengjie Han (8580981) Yuzhen Peng (8580984) Flora Salim (8580987) Arno Schlüter (6521593) Christoph van Treeck (8580990) Occupant behavior Data-driven methods Deep learning Machine learning Stochastic methods PRISMA In the last four decades several methods have been used to model occupants' presence and actions (OPA) in buildings according to different purposes, available computational power, and technical solutions. This study reviews approaches, methods and key findings related to OPA modeling in buildings. An extensive database of related research documents is systematically constructed, and, using bibliometric analysis techniques, the scientific production and landscape are described. The initial literature screening identified more than 750 studies, out of which 278 publications were selected. They provide an overarching view of the development of OPA modeling methods. The research field has evolved from longitudinal collaborative efforts since the late 1970s and, so far, covers diverse building typologies mostly concentrated in a few climate zones. The modeling approaches in the selected literature are grouped into three categories (rule-based models, stochastic OPA modeling, and data-driven methods) for modeling occupancy-related target functions and a set of occupants’ actions (window, solar shading, electric lighting, thermostat adjustment, clothing adjustment and appliance use). The explanatory modeling is conventionally based on the model-based paradigm where occupant behavior is assumed to be stochastic, while the data-driven paradigm has found wide applications for the predictive modeling of OPA, applicable to control systems. The lack of established standard evaluation protocols was identified as a scientifically important yet rarely addressed research question. In addition, machine learning and deep learning are emerging in recent years as promising methods to address OPA modeling in real-world applications. 2020-02-28T00:00:00Z Text Journal contribution 2134/11988171.v1 https://figshare.com/articles/journal_contribution/Modeling_occupant_behavior_in_buildings/11988171 CC BY-NC-ND 4.0 |
| spellingShingle | Occupant behavior Data-driven methods Deep learning Machine learning Stochastic methods PRISMA Salvatore Carlucci Marilena De Simone Steven Firth Mikkel B Kjærgaard Romana Markovic Mohammad Saiedur Rahaman Masab Khalid Annaqeeb Silvia Biandrate Anooshmita Das Jakub Wladyslaw Dziedzic Gianmarco Fajilla Matteo Favero Martina Ferrando Jakob Hahn Mengjie Han Yuzhen Peng Flora Salim Arno Schlüter Christoph van Treeck Modeling occupant behavior in buildings |
| title | Modeling occupant behavior in buildings |
| title_full | Modeling occupant behavior in buildings |
| title_fullStr | Modeling occupant behavior in buildings |
| title_full_unstemmed | Modeling occupant behavior in buildings |
| title_short | Modeling occupant behavior in buildings |
| title_sort | modeling occupant behavior in buildings |
| topic | Occupant behavior Data-driven methods Deep learning Machine learning Stochastic methods PRISMA |
| url | https://hdl.handle.net/2134/11988171.v1 |