Resumé
| Originalsprog | Engelsk |
|---|---|
| Titel | DATA’19 ’19: Proceedings of the Second Workshop on Data Acquisition To Analysis, Co-hosted at BuildSys/SenSys 2019 |
| Forlag | Association for Computing Machinery |
| Publikationsdato | 2019 |
| DOI | |
| Status | Udgivet - 2019 |
Fingeraftryk
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Dataset: Occupancy Presence and Trajectory Data from an Instrumented Public Building. / Das, Anooshmita; Schwee, Jens Hjort; Kolvig-Raun, Emil Stubbe; Kjærgaard, Mikkel Baun.
DATA’19 ’19: Proceedings of the Second Workshop on Data Acquisition To Analysis, Co-hosted at BuildSys/SenSys 2019. Association for Computing Machinery, 2019.Publikation: Bidrag til bog/antologi/rapport/konference-proceeding › Konferencebidrag i proceedings › Forskning › peer review
TY - GEN
T1 - Dataset: Occupancy Presence and Trajectory Data from an Instrumented Public Building
AU - Das, Anooshmita
AU - Schwee, Jens Hjort
AU - Kolvig-Raun, Emil Stubbe
AU - Kjærgaard, Mikkel Baun
PY - 2019
Y1 - 2019
N2 - The ability to accurately estimate the presence and counts of occupants inside a monitored area has many notable and compelling applications, e.g., efficient space utilization, intelligent building operations, comfortable indoor environment, safety, and evacuation. Significant research on design approaches and methods have been implemented to extrapolate rich information on occupant behavior and actions. However, these methods are evaluated based on a subset of divergent data collected from heterogeneous sensing modalities available in instrumented public buildings. Comprehensive baseline datasets are lacking which can serve for benchmarking and performance comparison despite the potential inconsistencies. In this paper, we present a dataset collected from three 3D Stereo Vision Cameras for 13 full days, with a total of 5,485,350 readings and 1242 estimated occupants in the summer of 2019 from a public building. The dataset contains occupancy presence and trajectory data. The dataset can serve for benchmarking and foster data-driven research in occupant presence and behavior modeling. This dataset would help to extract the inter-relationships of different factors influencing occupant behavior and trajectory patterns. Furthermore, high fidelity information about actions can be extrapolated from the presented dataset.
AB - The ability to accurately estimate the presence and counts of occupants inside a monitored area has many notable and compelling applications, e.g., efficient space utilization, intelligent building operations, comfortable indoor environment, safety, and evacuation. Significant research on design approaches and methods have been implemented to extrapolate rich information on occupant behavior and actions. However, these methods are evaluated based on a subset of divergent data collected from heterogeneous sensing modalities available in instrumented public buildings. Comprehensive baseline datasets are lacking which can serve for benchmarking and performance comparison despite the potential inconsistencies. In this paper, we present a dataset collected from three 3D Stereo Vision Cameras for 13 full days, with a total of 5,485,350 readings and 1242 estimated occupants in the summer of 2019 from a public building. The dataset contains occupancy presence and trajectory data. The dataset can serve for benchmarking and foster data-driven research in occupant presence and behavior modeling. This dataset would help to extract the inter-relationships of different factors influencing occupant behavior and trajectory patterns. Furthermore, high fidelity information about actions can be extrapolated from the presented dataset.
KW - Dataset
KW - Occupancy Presence
KW - Trajectories
U2 - https://doi.org/10.1145/3359427.3361909
DO - https://doi.org/10.1145/3359427.3361909
M3 - Article in proceedings
BT - DATA’19 ’19: Proceedings of the Second Workshop on Data Acquisition To Analysis, Co-hosted at BuildSys/SenSys 2019
PB - Association for Computing Machinery
ER -