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Author |
Kenneth Johnson; Javier Cámara; Roopak Sinha; Samaneh Madanian; Dave Parry |
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Title |
Towards Self-Adaptive Disaster Management Systems |
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Conference Article |
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Year  |
2021 |
Publication |
ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2021 |
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Pages |
49-61 |
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Keywords |
disaster management, self-adaptive systems, formal verification, probabilistic model checking, constraint solving |
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Abstract |
Disasters often occur without warning and despite extensive preparation, disaster managers must take action to respond to changes critical resource allocations to support existing health-care facilities and emergency triages. A key challenge is to devise sound and verifiable resourcing plans within an evolving disaster scenario. Our main contribution is the development of a conceptual self-adaptive system featuring a monitor-analyse-plan-execute (MAPE) feedback loop to continually adapt resourcing within the disaster-affected region in response to changing usage and requirements. We illustrate the system's use on a case study based on Auckland city (New Zealand). Uncertainty arising from partial knowledge of infrastructure conditions and outcomes of human participant's actions are modelled and automatically analysed using formal verification techniques. The analysis inform plans for routing resources to where they are needed in the region. Our approach is shown to readily support multiple model and verification techniques applicable to a range of disaster scenarios. |
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Address |
Auckland University of Technology; University of York; Auckland University of Technology; AUT university; Auckland University of Technology |
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Publisher |
Virginia Tech |
Place of Publication |
Blacksburg, VA (USA) |
Editor |
Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
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Language |
English |
Summary Language |
English |
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ISSN |
978-1-949373-61-5 |
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Track |
AI and Intelligent Systems for Crises and Risks |
Expedition |
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Conference |
18th International Conference on Information Systems for Crisis Response and Management |
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Notes |
kenneth.johnson@aut.ac.nz |
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no |
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Call Number |
ISCRAM @ idladmin @ |
Serial |
2312 |
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Author |
Samaneh Madanian; David Airehrour; Marianne Cherrington; NikhilKumar Patil |
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Title |
Smart Cap for Visually Impaired in Disaster Situations |
Type |
Conference Article |
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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 |
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Pages |
317-325 |
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Keywords |
Visually Impaired, Resilience, Disaster, Smart Cap, Internet of Things. |
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Abstract |
Natural and manmade disasters pose a myriad of challenges, which are more severe for individuals with disabilities. Ordinarily to perform daily activities, the disabled get support from assistive technological devices and services; these are commonly disrupted during and after disasters. A proposed solution to support those with visual impairment is a cost-effective wearable 'Smart Cap'. The Smart Cap provides narratives about the surrounding environment while establishing communication between the user (the visually impaired) and a rich online reservoir of knowledge base system capable of vocalising narratives. As a proof-of-concept, this study is implemented using Raspberry Pi, the Amazon Web Services and a P-Cap fitted with a camera. The aim of this research work is to provide an assistive technology to help the visually impaired navigate their way out of any potentially disastrous situation like other citizens would. The proposed system and its usage in disaster situations is an innovative, cost-effective solution specifically addressing the needs of visually impaired persons. |
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Address |
Nmit; Nmit; Aut; Nmit |
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Publisher |
Massey Univeristy |
Place of Publication |
Albany, Auckland, New Zealand |
Editor |
Kristin Stock; Deborah Bunker |
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Language |
English |
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Human centred design for collaborative systems supporting 4Rs (Reduction, Readiness, Response and Recovery) |
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no |
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Serial |
1661 |
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