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Author (up) Andrew Sherson; S Uma; Raj Prasanna
Title The effect of localised factors on water pipe repair times post-earthquake Type Conference Article
Year 2018 Publication Proceedings of ISCRAM Asia Pacific 2018: Innovating for Resilience – 1st International Conference on Information Systems for Crisis Response and Management Asia Pacific. Abbreviated Journal Iscram Ap 2018
Volume Issue Pages 366-380
Keywords Lifelines, Earthquake, Localised factors, repair times
Abstract In the Wellington Region, many lifelines are at risk, because they are in vulnerable narrow corridors close to active faults. In an earthquake, it is expected that these lifelines will be significantly damaged and unusable for extended periods of time. Because of this risk, many studies have been conducted to investigate the resulting downtimes. These studies, despite their usefulness, do not incorporate or make significant assumptions about localised factors. This paper summarises a thesis that aimed to improve the current predictive models, by including these local, and contextual influences. Multiple stakeholders who manage and repair the lifelines were interviewed to identify these factors which were then included into one of the current predictive models, and the influence on repair times was recorded. It was discovered that localised impacts such as staff logistics, land sliding, the land gradient, interdependency, and access doubled previous predicted repair times.
Address Joint Centre for Disaster Research / Massey University; Stantec; GNS Science
Corporate Author Thesis
Publisher Massey Univeristy Place of Publication Albany, Auckland, New Zealand Editor Kristin Stock; Deborah Bunker
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-0-473-45447-0 Medium
Track Understanding Risk, Risk Reduction, Consequences and Forecasting Expedition Conference ISCRAM Asia Pacific 2018: Innovating for Resilience - 1st International Conference on Information Systems for Crisis Response and Management Asia Pacific
Notes sherson.andrew@gmail.com Approved no
Call Number Serial 1685
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Author (up) Marion Lara Tan; Raj Prasanna; Kristin Stock; Emma Hudson-Doyle; Graham Leonard; David Johnston
Title Enhancing the usability of a disaster app: exploring the perspective of the public as users Type Conference Article
Year 2019 Publication Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management Abbreviated Journal Iscram 2019
Volume Issue Pages
Keywords usability inquiry, mobile application, disasters, alerts, public perspective
Abstract Limited research has studied how citizens? perspectives as end-users can contribute to improving the usability of disaster apps. This study addresses this gap by exploring end-user insights with the use of a conceptual disaster app in the New Zealand (NZ) context. NZ has multiple public alerting authorities that have various technological options in delivering information to the population?s mobile devices; including social media platforms, apps, as well as the Emergency Mobile Alert system. However, during critical events, the multiplicity of information may become overwhelming. A disaster app, conceptualised in the NZ context, aims to aggregate, organise, and deliver information from official sources to the public. After the initial conceptual design, a usability inquiry was administered by interviewing members of the public. Partial results of the inquiry show that the public?s perspective has value; in the process of understanding the new user?s viewpoint, usability highlights and issues are identified.
Address Massey University, New Zealand;GNS Science, New Zealand
Corporate Author Thesis
Publisher Iscram Place of Publication Valencia, Spain Editor Franco, Z.; González, J.J.; Canós, J.H.
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3387 ISBN 978-84-09-10498-7 Medium
Track T8- Social Media in Crises and Conflicts Expedition Conference 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019)
Notes Approved no
Call Number ISCRAM @ idladmin @ Serial 1946
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Author (up) Marion Lara Tan; Raj Prasanna; Kristin Stock; Emma Hudson-Doyle; Graham Leonard; David Johnston
Title Usability Factors Affecting the Continuance Intention of Disaster Apps Type Conference Article
Year 2018 Publication Proceedings of ISCRAM Asia Pacific 2018: Innovating for Resilience – 1st International Conference on Information Systems for Crisis Response and Management Asia Pacific. Abbreviated Journal Iscram Ap 2018
Volume Issue Pages 326-338
Keywords disaster apps, usability, continuance intention
Abstract Multiple disaster mobile applications (apps) already exist for public use; however, availability does not automatically translate to continued usage. Limited research has explored whether disaster apps are usable and whether the apps' usability affects users' intent for continued use. The paper presents a work-in-progress study that aims to test a usability-continuance intention model for the specific context of disaster apps. The study theorises seven usability factors that influence continued intention to use. An online usability survey was used to gather user experience data on disaster apps. Initial findings, through structural equational modelling, showed that five of the seven usability factors have a significant relationship to continuance intention. Although the relationships have different weights and directions, key influencers to users' intent to continue usage are app utility, app dependability, interface output, interface input, and interface graphics. The next step of the study will investigate the mediating effects of the factors and the moderating effects of users' experience and technological comfort.
Address Joint Centre for Disaster Research, Massey University; Joint Centre for Disaster Research, Massey University; Institute of Natural and Mathematical Sciences, Massey University; Joint Centre for Disaster Research, Massey University; GNS Science; Joint Centre for Disaster Research, Massey University; GNS Science
Corporate Author Thesis
Publisher Massey Univeristy Place of Publication Albany, Auckland, New Zealand Editor Kristin Stock; Deborah Bunker
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Track Human centred design for collaborative systems supporting 4Rs (Reduction, Readiness, Response and Recovery) Expedition Conference
Notes Approved no
Call Number Serial 1643
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Author (up) Marion Lara Tan; Sara Harrison; Julia S. Becker; Emma E.H. Doyle; Raj Prasanna
Title Research Themes on Warnings in Information Systems Crisis Management Literature Type Conference Article
Year 2020 Publication ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2020
Volume Issue Pages 1085-1099
Keywords Early Warnings Systems, Literature Review, Ethics, Social Media.
Abstract Early Warning Systems (EWS) are crucial to mitigating and reducing disaster impacts. Furthermore, technology and information systems (IS) are key to the success of EWSs. This systematic literature review investigates the research topics and themes from the past six years of Information Systems for Crisis Response and Management (ISCRAM) conference proceedings and seeks to identify the research developments and directions for EWSs to steer a discourse to advance the research in this field. Findings from a sample size of 60 papers show that there are technical, social, and topical considerations to using and advancing technology for EWSs. While technology has advanced EWSs to new levels, it is important to consider the influence of technology in the successful operation of EWSs. The results are based on the ISCRAM proceedings literature and may be broader or have different prioritization if a wider disciplinary body of literature was explored. This will be considered in the future.
Address Massey University; Massey University; Massey University; Massey University; Massey University
Corporate Author Thesis
Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Amanda Hughes; Fiona McNeill; Christopher W. Zobel
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 978-1-949373-27-98 ISBN 2411-3484 Medium
Track Visions for Future Crisis Management Expedition Conference 17th International Conference on Information Systems for Crisis Response and Management
Notes M.L.Tan@massey.ac.nz Approved no
Call Number Serial 2299
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Author (up) Nadeera Ahagama; Raj Prasanna
Title Disaster Knowledge Transfer in Networks: Enablers and Barriers Type Conference Article
Year 2018 Publication Proceedings of ISCRAM Asia Pacific 2018: Innovating for Resilience – 1st International Conference on Information Systems for Crisis Response and Management Asia Pacific. Abbreviated Journal Iscram Ap 2018
Volume Issue Pages 110-122
Keywords Disaster, Knowledge Transfer, networks, Knowledge Management models
Abstract Most countries are now establishing multi-stakeholder, multi-institutional networks and partnerships to respond to flood disasters. The paucity of research directed towards knowledge transfer in networks keeps some important research questions unanswered. These include (1) how the knowledge of a certain disaster management stakeholder (or a group) is transferred to other stakeholders during the disaster response, and (2) what are the barriers and enablers of knowledge transfer in multi-stakeholder environments. This article analyses knowledge transfer practices employed by a selected local government agency and a community group in Sri Lanka and reflects on the practices with the help of Hedlund's Knowledge Management Model (1994). The grounded theory analysis was used in this study to present the enablers and barriers of knowledge transfer in this context and the findings have a great potential to be used in future research towards developing knowledge management models specific to disaster response.
Address University of Colombo; Joint Centre for Disaster Research / Massey University
Corporate Author Thesis
Publisher Massey Univeristy Place of Publication Albany, Auckland, New Zealand Editor Kristin Stock; Deborah Bunker
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Track Data Issues for Situation/Disaster Awareness Expedition Conference
Notes Approved no
Call Number Serial 1686
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Author (up) Nilani Algiriyage; Raj Prasanna; Emma E H Doyle; Kristin Stock; David Johnston
Title Traffic Flow Estimation based on Deep Learning for Emergency Traffic Management using CCTV Images Type Conference Article
Year 2020 Publication ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2020
Volume Issue Pages 100-109
Keywords CCTV Big Data, YOLOv3, Traffic Flow Estimation.
Abstract Emergency Traffic Management (ETM) is one of the main problems in smart urban cities. This paper focuses on selecting an appropriate object detection model for identifying and counting vehicles from closed-circuit television (CCTV) images and then estimating traffic flow as the first step in a broader project. Therefore, a case is selected at one of the busiest roads in Christchurch, New Zealand. Two experiments were conducted in this research; 1) to evaluate the accuracy and speed of three famous object detection models namely faster R-CNN, mask R-CNN and YOLOv3 for the data set, 2) to estimate the traffic flow by counting the number of vehicles in each of the four classes such as car, bus, truck and motorcycle. A simple Region of Interest (ROI) heuristic algorithm is used to classify vehicle movement direction such as \quotes{left-lane} and \quotes{right-lane}. This paper presents the early results and discusses the next steps.
Address Joint Centre for Disaster Research, Massey University; Joint Centre for Disaster Research, Massey University; Joint Centre for Disaster Research, Massey University; Institute of Natural and Mathematical Sciences, Massey University; Joint Centre for Disaster Research, Massey University;
Corporate Author Thesis
Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Amanda Hughes; Fiona McNeill; Christopher W. Zobel
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 978-1-949373-27-10 ISBN 2411-3396 Medium
Track AI Systems for Crisis and Risks Expedition Conference 17th International Conference on Information Systems for Crisis Response and Management
Notes r.nilani@massey.ac.nz Approved no
Call Number Serial 2211
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Author (up) Nilani Algiriyage; Raj Prasanna; Kristin Stock; Emma Hudson-Doyle; David Johnston; Minura Punchihewa; Santhoopa Jayawardhana
Title Towards Real-time Traffic Flow Estimation using YOLO and SORT from Surveillance Video Footage Type Conference Article
Year 2021 Publication ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2021
Volume Issue Pages 40-48
Keywords Computer Vision, Traffic Flow, YOLOv4, CCTV Big Data
Abstract Traffic emergencies and resulting delays cause a significant impact on the economy and society. Traffic flow estimation is one of the early steps in urban planning and managing traffic infrastructure. Traditionally, traffic flow rates were commonly measured using underground inductive loops, pneumatic road tubes, and temporary manual counts. However, these approaches can not be used in large areas due to high costs, road surface degradation and implementation difficulties. Recent advancement of computer vision techniques in combination with freely available closed-circuit television (CCTV) datasets has provided opportunities for vehicle detection and classification. This study addresses the problem of estimating traffic flow using low-quality video data from a surveillance camera. Therefore, we have trained the novel YOLOv4 algorithm for five object classes (car, truck, van, bike, and bus). Also, we introduce an algorithm to count the vehicles using the SORT tracker based on movement direction such as ``northbound'' and ``southbound'' to obtain the traffic flow rates. The experimental results, for a CCTV footage in Christchurch, New Zealand shows the effectiveness of the proposed approach. In future research, we expect to train on large and more diverse datasets that cover various weather and lighting conditions.
Address Massey University; Massey University; Massey University; Joint Centre for Disaster Research, Massey University; Joint Center of Disaster Research, Massey University Wellington; University of Kelaniya; Univerity of Kelaniya
Corporate Author Thesis
Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 978-1-949373-61-5 ISBN Medium
Track AI and Intelligent Systems for Crises and Risks Expedition Conference 18th International Conference on Information Systems for Crisis Response and Management
Notes rangika.nilani@gmail.com Approved no
Call Number ISCRAM @ idladmin @ Serial 2311
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Author (up) Nilani Algiriyage; Rangana Sampath; Raj Prasanna; Kristin Stock; Emma Hudson-Doyle; David Johnston
Title Identifying Disaster-related Tweets: A Large-Scale Detection Model Comparison Type Conference Article
Year 2021 Publication ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2021
Volume Issue Pages 731-743
Keywords Tweet Classification, Machine Learning, Deep Learning, Disasters
Abstract Social media applications such as Twitter and Facebook are fast becoming a key instrument in gaining situational awareness (understanding the bigger picture of the situation) during disasters. This has provided multiple opportunities to gather relevant information in a timely manner to improve disaster response. In recent years, identifying crisis-related social media posts is analysed as an automatic task using machine learning (ML) or deep learning (DL) techniques. However, such supervised learning algorithms require labelled training data in the early hours of a crisis. Recently, multiple manually labelled disaster-related open-source twitter datasets have been released. In this work, we create a large dataset with 186,718 tweets by combining a number of such datasets and evaluate the performance of multiple ML and DL algorithms in classifying disaster-related tweets in three settings, namely ``in-disaster'', ``out-disaster'' and ``cross-disaster''. Our results show that the Bidirectional LSTM model with Word2Vec embeddings performs well for the tweet classification task in all three settings. We also make available the preprocessing steps and trained weights for future research.
Address Massey University; Massey University; Massey University; Massey University; Joint Centre for Disaster Research, Massey University; Joint Center of Disaster Research, Massey University Wellington
Corporate Author Thesis
Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 978-1-949373-61-5 ISBN Medium
Track Social Media for Disaster Response and Resilience Expedition Conference 18th International Conference on Information Systems for Crisis Response and Management
Notes rangika.nilani@gmail.com Approved no
Call Number ISCRAM @ idladmin @ Serial 2368
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Author (up) Raj Prasanna; Lili Yang; Malcolm King
Title Evaluation of a software prototype for supporting fire emergency response Type Conference Article
Year 2011 Publication 8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011 Abbreviated Journal ISCRAM 2011
Volume Issue Pages
Keywords Information systems; Software prototyping; Emergency response; Fire and rescue services; Fire emergencies; Fire fighters; First responders; Human computer interaction (HCI); Human computer interfaces; Situation awareness; Human computer interaction
Abstract Despite recent work on information systems, many first responders in the UK Fire and Rescue Services (FRSs) are unable to develop sufficient understanding of the situation to enable them to make good decisions. As a partial requirement of the development of information system for the UK fire and rescue services, a software prototype consisting of a number of human computer interfaces are developed and subsequently evaluated to explore how to present useful information for firefighters during their response operations. This paper exclusively discusses the findings arising from end-user demonstration sessions conducted via participative type of prototype evaluation which is aimed to understand the appropriateness and usefulness of the proposed software prototype. This paper contributes to improve the designing of the human computer interfaces and human computer interaction for supporting fire fighters during fire emergency response.
Address Loughborough University, United Kingdom
Corporate Author Thesis
Publisher Information Systems for Crisis Response and Management, ISCRAM Place of Publication Lisbon Editor M.A. Santos, L. Sousa, E. Portela
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3387 ISBN 9789724922478 Medium
Track User Centred Design Process for EMIS Expedition Conference 8th International ISCRAM Conference on Information Systems for Crisis Response and Management
Notes Approved no
Call Number Serial 854
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Author (up) Raj Prasanna; Lili Yang; Malcolm King
Title GDIA: A cognitive task analysis protocol to capture the information requirements of emergency first responders Type Conference Article
Year 2009 Publication ISCRAM 2009 – 6th International Conference on Information Systems for Crisis Response and Management: Boundary Spanning Initiatives and New Perspectives Abbreviated Journal ISCRAM 2009
Volume Issue Pages
Keywords Information systems; Job analysis; Cognitive task analysis; Cta; Development and applications; Emergency response; Fire and rescue services; First responders; Gdia; Information requirement; Emergency services
Abstract As a partial requirement of the development of an information system for the UK fire and rescue services, this paper describes the development and application of a protocol capable of capturing the information requirements of fire and rescue first responders. After evaluating the existing techniques commonly used in difficult decision-making environments, a Goal Directed Information Analysis (GDIA) protocol is proposed. The clearly defined, repeatable steps of GDIA make it a requirements-gathering protocol which can be easily administered by an investigator without any prior knowledge or experience of the tool. This makes GDIA one of the very few information requirements-gathering protocols capable of capturing the requirements of the emergency-related domains.
Address Business School, Loughborough University, United Kingdom
Corporate Author Thesis
Publisher Information Systems for Crisis Response and Management, ISCRAM Place of Publication Gothenburg Editor J. Landgren, S. Jul
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3387 ISBN 9789163347153 Medium
Track Research Methods Expedition Conference 6th International ISCRAM Conference on Information Systems for Crisis Response and Management
Notes Approved no
Call Number Serial 855
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Author (up) Yasir Imtiaz Syed; Raj Prasanna; S Uma; Kristin Stock; Denise Blake
Title A Design Science based Simulation Framework for Critical Infrastructure Interdependency Type Conference Article
Year 2018 Publication Proceedings of ISCRAM Asia Pacific 2018: Innovating for Resilience – 1st International Conference on Information Systems for Crisis Response and Management Asia Pacific. Abbreviated Journal Iscram Ap 2018
Volume Issue Pages 516-524
Keywords Infrastructure, interdependency, electricity, road, restoration.
Abstract Critical Infrastructures (CI) such as electricity, water, fuel, telecommunication and road networks are a crucial factor for secure and reliable operation of a society. In a normal situation, most of the businesses operate on an individual infrastructure. However, after major natural disasters such as earthquakes, the conflicts and complex interdependencies among the different infrastructures can cause significant disturbances because a failure can propagate from one infrastructure to another. This paper discusses the development of an integrated simulation framework that models interdependencies between electricity and road infrastructure networks of Wellington region. The framework uses a damage map of electricity network components and integrates them with road access time to the damaged components for determining electricity outage time of a region. The results can be used for recovery planning, identification of vulnerabilities, and adding or discarding redundancies in an infrastructure network.
Address Institute of Natural and Mathematical Sciences, Massey University; School of Psychology, Massey University; Joint Centre for Disaster Research, Massey University; GNS Science; Joint Centre for Disaster Research, Massey University
Corporate Author Thesis
Publisher Massey Univeristy Place of Publication Albany, Auckland, New Zealand Editor Kristin Stock; Deborah Bunker
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Track Enhancing Resilience of Natural, Built, and Socio-economic Environment Expedition Conference
Notes Approved no
Call Number Serial 1645
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