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Aditya Irfansyah, Adam Widera, Mark Haselkorn, & Bernd Hellingrath. (2020). Current Trends and Future Challenges in Congestion Management. In Amanda Hughes, Fiona McNeill, & Christopher W. Zobel (Eds.), ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management (pp. 622–636). Blacksburg, VA (USA): Virginia Tech.
Abstract: Traffic congestion creates multidimensional impacts that require stakeholders' integration and coordination. This paper tries to close the research gaps in congestion management by examining a case study of integrated solutions of congestion measures and analyzing future challenges in congestion management based on two selected factors. The authors develop the result from the literature study and an expert interview that provides a better perspective on the case study. The study generates a new perspective on reviewing the organizational aspect of integrated congestion management measures. Secondly, it starts a discussion on future challenges in congestion management and connects the domain of future mobility with congestion theories as an independent discussion.
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Imane Benkhelifa, Samira Moussaoui, & Nadia Nouali-Taboudjemat. (2013). Locating emergency responders using mobile wireless sensor networks. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 432–441). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Emergency response in disaster management using wireless sensor networks has recently become an interest of many researchers in the world. This interest comes from the growing number of disasters and crisis (natural or man-made) affecting millions of lives and the easy-use of new and cheap technologies. This paper details another application of WSN in the post disaster scenario and comes up with an algorithm for localization of sensors attached to mobile responders (firefighters, policemen, first aid agents, emergency nurses, etc) while assisted by a mobile vehicle (fire truck, police car, or aerial vehicle like helicopters) called mobile anchor, sent to supervise the rescue operation. This solution is very efficient and rapidly deployable since no pre-installed infrastructure is needed. Also, there is no need to equip each sensor with a GPS receiver which is very costly and may increase the sensor volume. The proposed technique is based on the prediction of the rescuers velocities and directions considering previous position estimations. The evaluation of our solution shows that our technique takes benefit from prediction in a more effective manner than previous solutions. The simulation results show that our algorithm outperforms conventional Monte Carlo localization schemes by decreasing estimation errors with more than 50%.
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Raffaele Bruno, Marco Conti, & Andrea Passarella. (2008). Opportunistic networking overlays for ICT services in crisis management. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 689–701). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: ICT infrastructures are a critical asset in today's Information society. Legacy telecommunication systems easily collapse in the face of disruptions due to security incidents or natural disasters. Hence, there is an urgent demand for new architectures and technologies ensuring a more efficient and dependable support for various security missions, such as disaster relief initiatives, first responder operations, critical infrastructure protection, etc. In this paper we advocate the opportunistic networking paradigm to build a self-organizing overlay ICT infrastructure for supporting dependable crisis management services. Our opportunistic framework to “glues together” surviving parts of the pre-existing infrastructure with networks deployed on-demand and users devices, and supports dependable distribution of coherent, updated, and non-contradictory information distribution. Finally, to show the potential advantages of our solution, we present initial results on the performance of different types of opportunistic infrastructures, by particularly highlighting the gains of context-aware systems.
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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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Olof Görnerup, Per Kreuger, & Daniel Gillblad. (2013). Autonomous accident monitoring using cellular network data. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 638–646). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Mobile communication networks constitute large-scale sensor networks that generate huge amounts of data that can be refined into collective mobility patterns. In this paper we propose a method for using these patterns to autonomously monitor and detect accidents and other critical events. The approach is to identify a measure that is approximately time-invariant on short time-scales under regular conditions, estimate the short and long-term dynamics of this measure using Bayesian inference, and identify sudden shifts in mobility patterns by monitoring the divergence between the short and long-term estimates. By estimating long-term dynamics, the method is also able to adapt to long-term trends in data. As a proof-of-concept, we apply this approach in a vehicular traffic scenario, where we demonstrate that the method can detect traffic accidents and distinguish these from regular events, such as traffic congestions.
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Humasak Simanjuntak, & Fabio Ciravegna. (2019). Semantic Understanding of Human Mobility Lifestyle to support Crisis Management. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: In this paper, we propose a method for understanding the semantics of mobility (mainly related to lifestyle)
patterns based on stay point detection from tracking data. The method identifies the context (trip purpose and
visited point of interest) of tracking data by using large-scale data collection infrastructure. We evaluate our
method with a tracking dataset in Birmingham (European project SETA) generated by 534 users from
September 2017 to September 2018. To this end, we compare insights from the tracking data with check-in
mobility in social media. The results show that both data capture rich human lifestyle features related to the
visited point of interest. Our study provides solid evidence that lifestyle patterns from tracking and social media
data can indeed be useful for understanding and gauging the level of disruption after a crisis, as it is possible to
check the deviation of habits from normal conditions and post-crisis.
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Julian Zobel, Patrick Lieser, Tobias Meuser, Lars Baumgärtner, Mira Mezini, & Ralf Steinmetz. (2021). Modeling Civilian Mobility in Large-Scale Disasters. 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. 119–132). Blacksburg, VA (USA): Virginia Tech.
Abstract: When disasters destroy critical communication infrastructure, smartphone-based Delay-Tolerant Networks (DTNs) can provide basic communication for civilians. Although field tests have shown the practicability of such systems, real-world experiments are expensive and hardly repeatable. Simulations are therefore required for the design and extensive evaluation of novel DTN protocols, but meaningful assertions require realistic mobility models for civilians. In this paper, trace files from a large-scale disaster field test are analyzed to identify typical human behavior patterns in a disaster area. Based on this, we derive a novel civilian disaster mobility model that incorporates identified behaviors such as group-based movement and clustering around points-of-interests such as hospitals and shelters. We evaluate the impact of mobility on DTN communication performance by comparing our model with other established mobility models as well as the trace file dataset in a simulative evaluation based on the field test scenario. In general, our mobility model leads to a more realistic assessment of DTN communication performance compared to other mobility models.
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Julius Bañgate, Julie Dugdale, Carole Adam, & Elise Beck. (2017). A Review on the Influence of Social Attachment on Human Mobility During Crises. 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. 110–126). Albi, France: Iscram.
Abstract: Human behaviour during crisis evacuations is soial in nature. In particular, social attachment theory posits that proximity of familiar people, places, objects, etc. promotes calm and a feeling of safety, while their absence triggers panic or flight. In closely bonded groups such as families, members seek each other and evacuate as one. This makes attachment bonds necessary in the development of realistic models of mobility during crises. In this paper, we present a review of evacuation behaviour, theories on social attachment, crises mobility, and agent-based models. We found that social attachment influences mobility in the dierent stages of evacuation (pre, during and post). Based on these findings, we intend to develop a multi-agent model of mobility during seismic crises, using the belief, desire and intention (BDI) agent architecture.
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Konstantinos Koufos, Krisztina Cziner, & Pekka Parviainen. (2007). Multicast video performance evaluation for emergency response communications. In K. Nieuwenhuis P. B. B. Van de Walle (Ed.), Intelligent Human Computer Systems for Crisis Response and Management, ISCRAM 2007 Academic Proceedings Papers (pp. 595–604). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Group-oriented services including data dissemination, group calls and real-time video transmission are considered as an important application in public safety communications. The main interest is in one-way real-time video transmission from the hot spot to multiple recipients. This is important for efficient emergency response. The changing topology of the multi-hop communication links in a public safety environment makes routing and multicasting extremely challenging task. The purpose of this paper is to study the performance of wireless mobile ad-hoc networks with one-way multicast video traffic. To consider a realistic public safety scenario, the effect of extensive unidirectional links is investigated. The system performance study of various ad-hoc network configurations is done by simulations. For wireless multicast routing, the On Demand Multicast Routing Protocol is used. The performance results are compared with the requirements provided by Statement of Requirement document of standardization project MESA.
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Faisal Luqman, & Martin Griss. (2011). Leveraging mobile context for effective collaboration and task management. 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: Collaboration and task management is challenging in distributed, dynamically-formed teams, typical in large scale disaster response scenarios. Ineffective collaboration may potentially result in poor performance and loss of life. The increased adoption of sensor rich mobile devices allow for mobile context to be leveraged. In this paper, we present Overseer, an agent-based system that exploits context information from mobile devices to facilitate collaboration and task allocation. We describe how mobile context can be used to create dynamic role-based assignments to enhance collaboration and effective task management.
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Aamir Mahmood, Konstantinos Koufos, & Krisztina Cziner. (2008). Multicast voice performance within a public safety cell. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 18–24). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: In public safety communications the first responders are getting directions about the tactical action plan with multicast voice whereas they can report back to the dispatcher with unicast voice. In this paper, the aim is to find the maximum number of voice calls for situation reporting in the presence of multicast voice for tactical coordination. In order to increase the reliability of our analysis we verify our simulator against a test bed prototype consisting of three 802.11 terminals. The simulation study is applied within a mobile cell. The proposed mobility model applies for initial deployment in emergency scenarios. We investigate the statistical properties of the model by simulations.
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Wang, R., & Li, N. (2023). Revealing social disparities under natural disasters using large-scale mobility data: A dynamic accessibility perspective. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 797–807). Omaha, USA: University of Nebraska at Omaha.
Abstract: Accessibility is an essential indicator for measuring the functions and equity of urban services, and could be harnessed to provide insights into the social disparities in urban residents’ interaction with urban services. In this study, we attempt to measure urban residents’ accessibility patterns to urban services during natural disasters using an improved gravity model method. Firstly, by analyzing human digital trace data in the Wilmington metropolitan area over three months, we assessed the residents’ accessibility levels of grocery stores and restaurants before, during and after Hurricane Florence, and captured the diverse trends of residents’ responses to the hurricane. Then, we identified and statistically tested the social disparities in residents’ accessibility behaviors in response to the hurricane. The findings may provide new insights for city planners and policymakers in terms of equity evaluations of resource accessibility and resource allocations among different communities and improvement of their resilience against natural disasters.
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Xinyuan Zhang, & Nan Li. (2020). Assessment of the Correlation between Extreme Weather Event-Induced Human Mobility Perturbation in Urban Areas and their Spatial Characteristics based on Taxi Trajectories. In Amanda Hughes, Fiona McNeill, & Christopher W. Zobel (Eds.), ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management (pp. 366–380). Blacksburg, VA (USA): Virginia Tech.
Abstract: Extreme weather events (EWEs) are significant threats to urban regions. One major reflection of such impact is the EWE-induced perturbation to urban human mobility, which has been documented in a number of recent studies. This study aims to examine the spatial distribution of such perturbation within a city among different areas that are characterized by the type of function and the distance to city center. A case study was conducted on a major rainstorm in the City of Nanjing, China in 2017, based on trajectories of all taxis in the city before and during the rainstorm. It was found that the rainstorm caused decrease in people's travel demand throughout the city, although the magnitude of perturbation and level of resilience notably differed among areas of different functional types. In addition, the urban mobility in areas distant from the city center were relatively less influenced by the rainstorm.
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Yan Wang, & John E. Taylor. (2017). Tracking urban resilience to disasters: a mobility network-based approach. 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. 97–109). Albi, France: Iscram.
Abstract: Disaster resilience is gaining increasing attention from both industry and academia, but difficulties in operationalizing the concept remain, especially in the urban context. Currently, there is scant literature on measuring both spatial and temporal aspects of resilience empirically. We propose a bio-inspired quantitative framework to track urban resilience to disasters. This framework was built upon a daily human mobility network, which was generated by geolocations from a Twitter Streaming API. System-wide metrics were computed over time (i.e. pre-, during and post-disasters). Fisher information was further adopted to detect the perturbation and dynamics in the system. Specifically, we applied the proposed approach in a flood case in the metropolis of São Paulo. The proposed approach is efficient in uncovering the dynamics in human movements and the underlying spatial structure. It adds to our understanding of the resilience process in urban disasters.
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Yan Wang, Qi Wang, & John Taylor. (2021). Loss of Resilience in Human Mobility across Severe Tropical Cyclones of Different Magnitudes. 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. 755–765). Blacksburg, VA (USA): Virginia Tech.
Abstract: Severe tropical cyclones impose threats on highly populated coastal urban areas, thereby, understanding and predicting human movements plays a critical role in evaluating disaster resilience of human society. However, limited research has focused on tropical cyclones and their influence on human mobility resilience. This preliminary study examined the strength and duration of human mobility perturbation across five significant tropical storms and their affected eight urban areas using Twitter data. The results suggest that tropical cyclones can significantly perturb human movements by changing travel frequencies and displacement probability distributions. While the power-law still best described the pattern of human movements, the changes in the radii of gyration were significant and resulted in perturbation and loss of resilience in human mobility. The findings deepen the understanding about human-environment interactions under extreme events, improve our ability to predict human movements using social media data, and help policymakers improve disaster evacuation and response.
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