[dtn-interest] [Deadline Extended] IEEE ICT-DM 2023, Cosenza, Italy - Sept. 13-15, 2023

Ru-Jun Wang <allenw84@gapp.nthu.edu.tw> Wed, 31 May 2023 15:40 UTC

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Subject: [dtn-interest] [Deadline Extended] IEEE ICT-DM 2023, Cosenza, Italy - Sept. 13-15, 2023
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[Our apologies for multiple copies of this email]
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The 8th International Conference on Information and Communication
Technologies for Disaster Management (ICT-DM) - Cosenza, Italy, 13-15
September 2023

https://ict-dm2023.inria.fr/index.html
<https://gapp-nthu-edu-dot-yamm-track.appspot.com/2Mug7yFE-FT8Co_E2u0_GU1cxxqFyYeKRvXGtQNUJR9LagndyiAHs637mYpAmEf5ke6XcXkNTnE_dAa579fjPXm7KPZHQVZh7ss5xjJTNcQ7gu1Hg8BUIzybMaSm0qlixjybWvNFnjCPAtJAIP1Lix0CNASM0RCJy8XbFOe2C3FxBgKk25Rer_PRgvjkDd2R454VFgc7bu5c>

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Track 4: Crowdsourcing and social media for disaster & crisis management
https://ict-dm2023.inria.fr/tracks/four.html
<https://gapp-nthu-edu-dot-yamm-track.appspot.com/2Ci_Y8CQCjSZN5nKALr60TkWjDzGiP-jopX_rkq_NZS_egndyiAFKK_q7IkZUE1V_TwVyeVquZJzN9dRyfHfrTJ-Gi2lqixU-Yo2Z4nr-bZ5Kv3YoYRK66nxMenOexsMG6mkPR_Pj20U_IB0QKG4tQlT2KagJTfSG0yPe5nxHCQySAUJBP39LaVfsoKSLYzcFd5ODWWwIL-ccKHCoQKgC>

Scope: Natural disasters like flooding and earthquakes, as well as
terrorism attacks and industrial disasters, should be dealt with in a fast
and effective manner. In such scenarios, first responders, news agencies
and the victims are used to exploit social media as a first “communication
channel” to disseminate situational information in a reliable way, reaching
a huge pool of users. Similarly, crowdsourcing applications engage user
communities in emergency response and disaster management for natural
hazards. However, some drawbacks may occur in such social tools, thus
limiting authorities and disaster management stakeholders to use social
media data to make decisions. As an instance, social media crowdsourcing
data should be georeferenced to improve situational awareness, and the
positioning error should be very low. In addition, social media data should
be merged with other external data sources and authoritative data to
establish geographic relationships between the disaster event and social
media messages. Also, the dissemination of a message should occur between
trusted and reliable nodes, in order to be sure the disseminated
information is secure. As a solution, the main goal is to handle a set of
learning materials such as methods, tools and guidelines on the use of
social media and crowdsourcing in disasters in an effective manner,
especially for what concerns security and trustworthiness of data
information.

So, this track wants to stimulate the scientific community to propose new
technical studies that may address different topics such as:

   - Secure and reliable communications in social media and crowdsourcing
   for disaster & crisis management
   - Opportunistic data dissemination in social media and crowdsourcing
   tools
   - Network architectures for social media and crowdsourcing
   - Machine learning techniques in social media and crowdsourcing for
   disaster & crisis management
   - Energy harvesting, storage, recycling, and wireless power transfer for
   social IoTs in disaster and crisis
   - Fog/edge computing and social IoT convergent services, systems,
   infrastructure, and techniques for disaster and crisis management
   - Agile, intelligent, and resilient aerial (swarm) social-inspired
   communications and control in disaster crisis
   - Localization and positioning with social IoT in disaster/crisis areas
   - Social-aware self-organizing network optimization for efficient
   crowdsourcing in mobile social networks
   - Security, privacy, and trust in social IoT-assisted disaster/crisis
   management systems
   - Disaster/crisis data aggregation, dissemination, collection, and
   mining via crowdsourcing and social media in multi-hop heterogeneous
   networks
   - Crowdsourcing, gamification, and social media incentivization for
   natural hazard prevention, mitigation, and management
   - Real-time query processing, data fusion, and event summarization for
   multi-source disaster data and social media
   - Big data analysis, AI and machine/deep learning models with Age of
   Information (AoI) in crowdsourcing and social media analysis
   - Innovative crowdsourcing applications and social network services for
   disaster and crisis management

Track Chair
Anna Maria Vegni, University of Roma Tre, Italy
De-Nian Yang, Institute of Information Science, Academia Sinica, Taiwan

Important dates
Full/short paper submission: June 7, 2023 (extended)
Acceptance notification: July 23, 2023
Camera ready: August 20, 2023
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