Gonzalez, J. J., & Eden, C. (2023). Devising Mitigation Strategies With Stakeholders Against Systemic Risks in a Pandemic. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 1000–1013). Omaha, USA: University of Nebraska at Omaha.
Abstract: Understanding and managing systemic risk has huge importance for disaster risk reduction in our globally connected world. The COVID-19 pandemic is a prominent case for the global impact of systemic risk. Did so the added urgency of the pandemic systemic risk trigger such paradigm shift? The use of qualitative modelling of systemic risk has progressed the field, particularly when policy makers need support urgently and want to utilize a range of interdisciplinary expertise. We have extended to disaster risk reduction a method for causal mapping for problem solving and strategy development targeting complex project management. Our approach delivers useful, useable, and used mitigation to systemic risk in a pandemic using participatory modelling with practitioners, domain experts and power-brokers.
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Fatehkia, M., Imran, M., & Weber, I. (2023). Towards Real-time Remote Social Sensing via Targeted Advertising. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 396–406). Omaha, USA: University of Nebraska at Omaha.
Abstract: Social media serves as an important communication channel for people affected by crises, creating a data source for emergency responders wanting to improve situational awareness. In particular, social listening on Twitter has been widely used for real-time analysis of crisis-related messages. This approach, however, is often hindered by the small fraction of (hyper-)localized content and by the inability to explicitly ask affected populations about aspects with the most operational value. Here, we explore a new form of social media data collected through targeted poll ads on Facebook. Using geo-targeted ads during flood events in six countries, we show that it is possible to collect thousands of poll responses within hours of launching the ad campaign, and at a cost of a few (US dollar) cents per response. We believe that this flexible, fast, and affordable data collection can serve as a valuable complement to existing approaches.
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Vangelis Pitidis, Joao Porto de Albuquerque, Jon Coaffee, & Fernanda Lima. (2022). Enhancing Community Resilience through Dialogical Participatory Mapping. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 495–503). Tarbes, France.
Abstract: Citizen generated data can play an important role in enhancing community resilience. However, the relationship between data and community resilience has only been partly addressed in existing resilience scholarship, predominantly from the perspective of data utilisation in response to unfolding crises. Yet, in this study we attempt to highlight a different pathway for data-enabled contributions to community resilience, focusing on the process of data generation and its capacity to constitute a transformative moment itself. By exploring the case of the marginalized flood-prone community of M’Boi Mirim in São Paulo, Brazil, we introduce the concept of dialogical participatory mapping, and we argue that the process of generating geospatial data can empower local communities and assist in nourishing a resilience spirit among community members.
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Enrique Caballero, Angel Madridano, Dimitrios Sainidis, Konstantinos Konstantoudakis, Petros Daras, & Pablo Flores. (2021). An automated UAV-assisted 2D mapping system for First Responders. In Anouck Adrot, Rob Grace, Kathleen Moore, & Christopher W. Zobel (Eds.), ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management (pp. 890–902). Blacksburg, VA (USA): Virginia Tech.
Abstract: Recent advances in the Unmanned Aerial Vehicles (UAVs) sector have allowed such systems to carry a range of sensors, thus increasing their versatility and adaptability to a wider range of tasks and services. Furthermore, the agility of these vehicles allows them to adapt to rapidly changing environments making them an effective tool for emergency situations. A single UAV, or a swarm working in collaboration, can be a handy and helpful tool for First Responders (FRs) during mission planning, mission monitoring, and the tracking of evolving risks. UAVs, with their on-board sensors, can, among other things, capture visual information of the disaster scene in a safe and quick manner, and generate an up-to-date map of the area. This work presents a system for UAV-assisted mapping optimized for FRs, including the generation of routes for the UAVs to follow, data collection and processing, and map generation.
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Bruna Diirr, Vânia de Oliveira Neves, Marcus Vinícius Vasconcelos de Almeida Cunha, Ana Beatriz Kapps dos Reis, & Jairo Francisco de Souza. (2021). Software Requirements for Disaster Management Systems. In Anouck Adrot, Rob Grace, Kathleen Moore, & Christopher W. Zobel (Eds.), ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management (pp. 1042–1054). Blacksburg, VA (USA): Virginia Tech.
Abstract: Disasters are a major global problem and a serious threat to sustainable development. In this context, the development of disaster management systems becomes a complex activity, both due to the unpredictability of the events to be treated and the difficulty in extracting or identifying these systems users' needs (requirements). This study aims to understand the requirements usually elicited for disaster management systems and how such requirements are identified. Thus, a systematic mapping of literature (SM) and an open-source repository mining (RM) were performed. Results bring benefits both to academics and practitioners, as detail several characteristics of disaster management systems that could assist these systems development and decision-making, besides providing inputs to guide further research.
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