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Fabio Ciravegna, Jerry Gao, Chris Ingram, Neil Ireson, Vita Lanfranchi, & Humasak Simanjuntak. (2018). Mapping Mobility to Support Crisis Management. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 305–316). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: In this paper we describe a method and an infrastructure for rapid mapping of mobility patterns, based on a combination of a mobile mobility tracker, a large-scale data collection infrastructure, and a data and visual analytics tool. The combination of the three enables mapping everyday mobility patterns for decision makers, e.g. city council, motorways authorities, etc. and can support emergency responders in improving their preparedness and the recovery in the aftermath of a crisis. The technology is currently employed over very large scale: (i) in England it is used by a public body to incentivise physical mobility (400,000 app downloads and hundreds of millions of data point since September 2017); (ii) in Sheffield UK, through the MoveMore initiative, tracking active mobility of users (5,000 downloads); and (iii) the European project SETA, to track multimodal mobility patterns in three cities (Birmingham, Santander and Turin).
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Fabio Ciravegna, Suvodeep Mazumdar, Neil Ireson, & Peter Cudd. (2016). Seeing through the Eyes of the Citizens during Emergencies. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: Availability and access to information is critical for providing a highly effective response to an ongoing event ? however, often information reported by citizens over the phone may be unclear, inaccurate, biased or subjective, based on the context of the reporter. This can often lead to inadequate response to an emergency, which can in turn result in loss of property or worse, lives. On the other hand, excessive response to an emergency can also result in a highly expensive exercise. Our solution to address this problem is to make the citizen act as a camera for the control room by exploiting the user?s mobile camera. The system is designed to provide a live view of the citizen?s immediate surroundings, while control room personnel can provide instructions. In this paper, we introduce the system and share initial insights from a focus group evaluation conducted within a separate but closely related domain.
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Simon Tucker, Vitaveska Lanfranchi, Neil Ireson, Alfonso Sosa, Gregoire Burel, & Fabio Ciravegna. (2012). Straight to the information I need: Assessing collational interfaces for emergency response. In Z.Franco J. R. L. Rothkrantz (Ed.), ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management. Vancouver, BC: Simon Fraser University.
Abstract: Collational interfaces gather information from a range of sources and present them to users. Information overload is tackled by processing information in the back-end and providing interactive means to filter and browse data. Such interfaces have applications in emergency response – giving users the right information to act effectively. In this paper we explore a collational interface for emergency response, carrying out a user study that compares it to a paper based interface and one which presents data without collating it. We demonstrate that a collational interface allows users to build a picture of an emergency, but not necessarily in less time. © 2012 ISCRAM.
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Suvodeep Mazumdar, Neil Ireson, & Fabio Ciravegna. (2016). Decision Graphs: Managing Decisions for Emergencies. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: Emergencies are highly complex situations that require careful consideration of information collected from a variety of sources, by a variety of individuals and agencies. Good situation awareness provides the basis for a highly effective decision-making process requiring large volumes of real time information. Processing this is a highly complex task, and the dynamic nature of emergencies introduces further challenges. Over the years, several initiatives have attempted to address this complexity by proposing a variety of solutions that have contributed to a growing field of research. While progress toward decision-making support has been significant, the process of managing decisions has received less attention. To learn from decisions, there needs to be a process of collecting, curating and analyzing decision-making itself. Information being collected via a large number of resources needs to be formalized and interpreted by the decision maker, who in turn combines the information collected with their own knowledge and experience to make critical, and often life-saving decisions. Many of the decisions need to be taken instantaneously, while some need careful consultation and consideration, in collaboration with experts only once good situation awareness is achieved. This process of taking decisions based on evidence and personal experience is often lost, mostly due to lack of appropriate archiving mechanisms (e.g. not digitizing paper-based decisions or recording informal decisions). Therefore post-event analysis and auditing activities can lose track of how decisions were made, their associated evidences and rationale. Recording decisions in real-time, as they are taken, can provide a step change in the way decision support systems can aid future events or post-event analyses. We address this aspect of decision support by proposing a real-time decision capture and monitoring approach, Decision Graphs. At the core of Decision Graphs resides a decision management framework, employing semantic web techniques to organise decisions, as and when they are taken. While Semantic Web approaches have been employed in the past in Decision-Making for Emergency Response, management of decisions using Semantic Technologies has been largely limited. Lightweight decision loggers are deployed in a variety of ways ? mobile applications available for all types of mobile devices, web browser-based plugins, and a dedicated web site. The decision loggers capture decisions and all related evidence and rationale from the decision maker, and make them available to the decision management framework. Following an event, a decision maker can then retrieve all decisions via a web-based solution. In this poster, we first present requirements gathered from interviews with a variety of stakeholders. We then address this need and propose a decision management framework that employs a variety of pervasive lightweight decision loggers and semantic web technologies for enriching and organizing decisions. Finally, we present our visualisation mechanisms to help look up events and decisions, during follow-up post event analyses activities.
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Suvodeep Mazumdar, Stuart N. Wrigley, Neil Ireson, & Fabio Ciravegna. (2015). Geo-fence driven crowd-sourcing for Emergencies. In L. Palen, M. Buscher, T. Comes, & A. Hughes (Eds.), ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management. Kristiansand, Norway: University of Agder (UiA).
Abstract: For some emergency situations an effective response can be reliant on sensor data (e.g. river level, traffic flow, weather conditions) to provide situation awareness, in order to help authorities make informed decisions. Gathering data in a traditional approach, i.e. using precise physical sensors, is a highly expensive task, involving procurement, installation and maintenance of a number of sensors. As a result, the coverage of sensors is limited and only the regions deemed most important by authorities are monitored. However, regions currently not being monitored can have an urgent need to be sensed depending on emergencies or situations. We present a high-level overview of the Locaware system, which employs a flexible geofencing approach to enable crowdsourcing by requesting citizens and volunteers to help authorities formulate a greater situation awareness of a region under consideration. While the Locaware system is motivated for water monitoring, our approach can be applied in other contexts.
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Vitaveska Lanfranchi, Stuart N. Wrigley, Neil Ireson, Uta Wehn, & Fabio Ciravegna. (2014). Citizens' observatories for situation awareness in flooding. 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. 145–154). University Park, PA: The Pennsylvania State University.
Abstract: Citizens' observatories are emerging as a means to establish interaction and co-participation between citizens and authorities during both emergencies and the day-to-day management of fundamental resources. In this paper we present a case study in which a model of citizens' observatories is being been translated into practice in the WeSenseIt project. The WeSenseIt citizens' observatory provides a unique way of engaging the public in the decision-making processes associated with water and flood management through a set of new digital technologies. The WeSenseIt citizens' observatory model is being implemented in three case studies based in the UK, the Netherlands and Italy. We describe the findings and our experiences following preliminary evaluations of the technologies and the model of co-participation and describe our future research plans.
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