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Amro Al-Akkad, & Zimmermann, A. (2011). User study: Involving civilians by smart phones during emergency situations. In E. Portela L. S. M.A. Santos (Ed.), 8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011. Lisbon: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: This paper concerns a preliminary user study to determine the acceptance of a mobile application that is supposed to involve civilians during emergencies. In particular, the focus is on bystanders. Their intervention during emergencies constitutes a delicate issue, since they were traditionally considered as a rather annoying party being merely observers of incidents. However, with the ubiquity and ever-increasing capabilities of cell phones there might emerge a great potential to flip the coin and to benefit from bystanders playing from now on a contributive role. To examine this hypothesis, we conducted semi-structured interviews with 24 persons. The result of our study shows that people are willing to use such mobile assisting system, and thus we take it as a positive starting signal to continue our research into this direction considering the elicited user constraints.
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Jaziar Radianti, Julie Dugdale, Jose J. Gonzalez, & Ole-Christoffer Granmo. (2014). Smartphone sensing platform for emergency management. In and P.C. Shih. L. Plotnick M. S. P. S.R. Hiltz (Ed.), ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management (pp. 379–383). University Park, PA: The Pennsylvania State University.
Abstract: The increasingly sophisticated sensors supported by modern smartphones open up novel research opportunities, such as mobile phone sensing. One of the most challenging of these research areas is context-aware and activity recognition. The Smart Rescue project takes advantage of smartphone sensing, processing and communication capabilities to monitor hazards and track people in a disaster. The goal is to help crisis managers and members of the public in early hazard detection, prediction, and in devising risk-minimizing evacuation plans when disaster strikes. In this paper we suggest a novel smartphone-based communication framework. It uses specific machine learning techniques that intelligently process sensor readings into useful information for the crisis responders. Core to the framework is a content-based publish-subscribe mechanism that allows flexible sharing of sensor data and computation results. We also evaluate a preliminary implementation of the platform, involving a smartphone app that reads and shares mobile phone sensor data for activity recognition.
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Yan Wang, Hong Huang, Lida Huang, Minyan Han, Yiwu Qian, & Boni Su. (2017). An Agile Framework for Detecting and Quantifying Hazardous Gas Releases. In eds Aurélie Montarnal Matthieu Lauras Chihab Hanachi F. B. Tina Comes (Ed.), Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management (pp. 42–49). Albi, France: Iscram.
Abstract: In response to the threat of hazardous gas releases to public safety and health, we propose an agile framework for detecting and quantifying gas emission sources. Emerging techniques like high-precision gas sensors, source term estimation algorithms and Unmanned Aerial Vehicles are incorporated. The framework takes advantage of both stationary sensor network method and mobile sensing approach for the detection and quantification of hazardous gases from fugitive, accidental or deliberate releases. Preliminary results on street-level detection of urban natural gas leakage is presented. Source term estimation is demonstrated through a synthetic test case, and is verified using Cramér-Rao bound analysis.
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