Abstract
Providing environmental and navigational safety to occupants in workplace, public venues, home and other environments is of a critical concern and has multiple applications for various end users. A framework, for monitoring movement, pose and behavior of elderly people for safe navigation in indoor environments is presented in this work. This framework, at the intersection of different disciplines has multiple functionalities. First, it provides a definition of human behavior in terms of joint point movements associated with Activities of Daily Living (ADL), while discussing two most common forms of human motions during stair navigation – upstairs and downstairs; second, it presents a two-fold approach – context-based and motion-based for accurate detection of these movements amongst other human motions associated with ADL; third, it consists of a methodology to study the Big Data associated with these movements and finally it also includes a rather comprehensive case study where the performance of multiple learning models are evaluated to identify the best learning model for development of this framework.
Keywords
- Big Data
- Behavior monitoring
- Elderly falls
- Smart homes
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Thakur, N., Han, C.Y. (2020). A Framework for Monitoring Indoor Navigational Hazards and Safety of Elderly. In: Stephanidis, C., Antona, M., Gao, Q., Zhou, J. (eds) HCI International 2020 – Late Breaking Papers: Universal Access and Inclusive Design. HCII 2020. Lecture Notes in Computer Science(), vol 12426. Springer, Cham. https://doi.org/10.1007/978-3-030-60149-2_56
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DOI: https://doi.org/10.1007/978-3-030-60149-2_56
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