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International Journal of Disaster Risk Reduction
Article . 2024 . Peer-reviewed
License: CC BY
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Article . 2024
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http://dx.doi.org/10.1016/j.ij...
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The ERMES chatbot: A conversational communication tool for improved emergency management and disaster risk reduction

Authors: Urbanelli, Angelica; Frisiello, Antonella; Bruno, Luca; Rossi, Claudio;

The ERMES chatbot: A conversational communication tool for improved emergency management and disaster risk reduction

Abstract

The increased occurrence and severity of worldwide disasters, exacerbated by the impact of climate change, pose significant challenges to emergency management, calling for novel and more effective Disaster Risk Reduction (DRR) approaches. Despite the phenomenological differences of diverse hazards and the heterogeneity of local policies and governance structures, effective communication systems are needed to better manage the available resources in all phases of the emergency management cycle, especially in the case of cross-border events. In this work, we present the design, implementation, and validation of a novel tool for emergency management, i.e., the ERMES Chatbot: a mobile-based conversational communication system developed to facilitate real-time bidirectional communication between control centres, in-field forces, and citizens. The methodology used to create the ERMES Chatbot is grounded on the user-centred design approach, which entails end-user involvement in all key phases of the development, including the definition of the end-user requirements, the technical design, and the final validation of the proposed solution. The co-design approach involved several organisations belonging to the DRR domain, which includes a gamified experience for citizens and is iteratively validated through four in-field demonstration events based on realistic emergency scenarios with the involvement of emergency practitioners, volunteering organisations, and citizens.

Keywords

Crowdsourcing, Citizens engagement, Chatbot, Telegram, DRR, Conversational UI

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
16
Top 10%
Top 10%
Top 10%
Green
hybrid