Abstract
The progressive population ageing increases the participation of autonomous Elderly to the community life and their presence in public buildings. Such complex spaces are generally characterized by high occupants’ density, with different users’ types (including elderly) that additionally own a scarce familiarity with the emergency layout. Emergency safety levels (i.e.: fire) are significantly affected by man-environment interactions, especially for the hosted autonomous Elderly. Here, they tend to choose well-known paths, while group behaviours can provoke overcrowding and, hence, an increasing of the evacuation time. Cognitive Buildings can solve this issue, because they can suggest to people how to behave in relation to the monitored surrounding conditions. This study proposes a Cognitive Wayfinding System (Co-WayS) to be applied in such scenarios, with a low impact level. Co-Ways is composed by: individuals’ badges for their wi-fi tracking; building components including wi-fi tracking system and electrically-illumined signs (to dynamically address correct paths to evacuees); central processing unit to solve a density-based guidance algorithm for sign activation. Co-WaysS addresses the egress paths depending on monitored queueing conditions. A first validation in a significant public building is performed through egress drills. When using Co-WayS, the evacuation time decreases (−28%) while correct path choices (+17%) and individuals’ sign confidence (+58%) increases, with respect to standard signage.
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Notes
- 1.
Source: ISTAT, 2016 https://www.istat.it/it/files/2017/03/Indicatori-Demografici.pdf (in Italian - last access: 01/04/2019).
- 2.
E.g.: EVACLITE Dynamic and Adaptive Emergency Evacuation Signage: https://www.evaclite.com/ (last access 20/04/2019); Q. Li, T. Plocher, Time-dependent classification and signaling of evacuation route safety, US 7,683,793 B2, 2010 https://www.google.com/patents/US7683793 (last access 20/04/2019).
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Acknowledgements
The development of this work was supported by the MIUR (the Italian Ministry of Education, University, and Research) Project SHELL, Smart Living technologies (grant number: CTN01 00128 111357), part of the national cluster TAV (CTN01 00128) – Research Objective OR4 “Safety & Security Manager”. The authors would thank Eng. Giulia Gaetani and Dr. Giacomo Chelli for their support in system development, during the drills and in the preliminary data analysis.
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Bernardini, G., Ciabattoni, L., Quagliarini, E., D’Orazio, M. (2021). Cognitive Buildings for Increasing Elderly Fire Safety in Public Buildings: Design and First Evaluation of a Low-Impact Dynamic Wayfinding System. In: Monteriù, A., Freddi, A., Longhi, S. (eds) Ambient Assisted Living. ForItAAL 2019. Lecture Notes in Electrical Engineering, vol 725. Springer, Cham. https://doi.org/10.1007/978-3-030-63107-9_8
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