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Sensing group proximity dynamics of firefighting teams using smartphones


Feese, Sebastian; Arnrich, Bert; Tröster, Gerhard; Burtscher, Michael J; Meyer, Bertolt; Jonas, Klaus (2013). Sensing group proximity dynamics of firefighting teams using smartphones. In: ACM International Joint Conference on Pervasive and Ubiquitous Computing, Zürich, 9 September 2013 - 12 September 2013, 97-104.

Abstract

Firefighters work in dangerous and unfamiliar situations under a high degree of time pressure and thus team work is of utmost importance. Relying on trained automatisms, firefighters coordinate their actions implicitly by observing the actions of their team members. To support training instructors with objective mission data, we aim to automatically detect when a firefighter is in-sight with other firefighters and to visualize the proximity dynamics of firefighting missions. In our approach, we equip firefighters with smartphones and use the built-in ANT protocol, a low-power communication radio, to measure proximity to other firefighters. In a second step, we cluster the proximity data to detect moving sub-groups. To evaluate our method, we recorded proximity data of 16 professional firefighting teams performing a real-life training scenario. We manually labeled six training sessions, involving 51 firefighters, to obtain 79 minutes of ground truth data. On average, our algorithm assigns each group member to the correct ground truth cluster with 80% accuracy. Considering height information derived from atmospheric pressure signals increases group assignment accuracy to 95%.

Abstract

Firefighters work in dangerous and unfamiliar situations under a high degree of time pressure and thus team work is of utmost importance. Relying on trained automatisms, firefighters coordinate their actions implicitly by observing the actions of their team members. To support training instructors with objective mission data, we aim to automatically detect when a firefighter is in-sight with other firefighters and to visualize the proximity dynamics of firefighting missions. In our approach, we equip firefighters with smartphones and use the built-in ANT protocol, a low-power communication radio, to measure proximity to other firefighters. In a second step, we cluster the proximity data to detect moving sub-groups. To evaluate our method, we recorded proximity data of 16 professional firefighting teams performing a real-life training scenario. We manually labeled six training sessions, involving 51 firefighters, to obtain 79 minutes of ground truth data. On average, our algorithm assigns each group member to the correct ground truth cluster with 80% accuracy. Considering height information derived from atmospheric pressure signals increases group assignment accuracy to 95%.

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Additional indexing

Item Type:Conference or Workshop Item (Paper), not refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Psychology
Dewey Decimal Classification:150 Psychology
Uncontrolled Keywords:firefighting, group clustering, mobile sensing, radio-based proximity
Language:English
Event End Date:12 September 2013
Deposited On:27 Oct 2014 10:27
Last Modified:08 Dec 2017 07:47
Publisher:ACM
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1145/2493988.2494332

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