Location

Online

Event Website

https://hicss.hawaii.edu/

Start Date

4-1-2021 12:00 AM

End Date

9-1-2021 12:00 AM

Description

The main purpose of Activity Recognition Systems - ARS is to improve the quality of human life. An ARS uses predictive models to identify the activities that individuals are performing in different environments. Under data-driven approaches, these models are trained and tested in experimental environments from datasets that contain data collected from heterogeneous information sources. When several people interact (multi-occupation) in the environment from which data are collected, identifying the activities performed by each individual in a time window is not a trivial task. In addition, there is a lack of datasets generated from different data sources, which allow systems to be evaluated both from an individual and collective perspective. This paper presents the SaMO – UJA dataset, which contains Single and Multi-Occupancy activities collected in the UJAmI Smart Lab of the University of Jaén (Spain). The main contribution of this work is the presentation of a dataset that includes a new generation of sensors as a source of information (acceleration of the inhabitant, intelligent floor for location, proximity and binary-sensors) to provide a new point of view on the multi-occupancy problem

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Jan 4th, 12:00 AM Jan 9th, 12:00 AM

UJA Human Activity Recognition multi-occupancy dataset

Online

The main purpose of Activity Recognition Systems - ARS is to improve the quality of human life. An ARS uses predictive models to identify the activities that individuals are performing in different environments. Under data-driven approaches, these models are trained and tested in experimental environments from datasets that contain data collected from heterogeneous information sources. When several people interact (multi-occupation) in the environment from which data are collected, identifying the activities performed by each individual in a time window is not a trivial task. In addition, there is a lack of datasets generated from different data sources, which allow systems to be evaluated both from an individual and collective perspective. This paper presents the SaMO – UJA dataset, which contains Single and Multi-Occupancy activities collected in the UJAmI Smart Lab of the University of Jaén (Spain). The main contribution of this work is the presentation of a dataset that includes a new generation of sensors as a source of information (acceleration of the inhabitant, intelligent floor for location, proximity and binary-sensors) to provide a new point of view on the multi-occupancy problem

https://aisel.aisnet.org/hicss-54/da/soft_computing/5