New technologies can help providing a rapid and efficient response to and management of the climate disasters such as fires, floods, earthquakes and heatwaves. ICMT welcomes novel research work that presents the most recent methods for forecasting, early warning, collection, processing, and transmission of the emergency data, analysis of multimodal data and coordination between the first responders and the authorities.
The workshop aims at bringing together practitioners and researchers, both from crisis management and technical domains, to share ideas and experiences in designing and implementing novel intelligent techniques and tools to support crisis management.
Jan 15Jan 28, 2018: Due date for workshop papers submission
Jan 25Feb 5, 2018: Notification of paper acceptance to authors
Mar 4, 2018: Camera-ready of accepted papers
April 15, 2018:Author advance registration
Co-located with 2018 ISCRAM International Conference on Information Systems for Crisis Response and Management (ISCRAM 2018)
Raising awareness on the provision of public safety services through the most diverse ICT technologies is a key opportunity and one of the most urgent challenges in the field of today’s communication networks.
Relevant scenarios include the disasters such as earthquakes, fires or floods that disrupt traditional communication infrastructures, or that displace large crowds, overloading what is left of the communication infrastructure. In these scenarios, people are in need of directions, advice, updates on the current situation and they often need to send out requests for help or to make their location known to rescue teams. Ideally, users should be able to communicate directly between themselves, even in the absence of a cellular infrastructure – a common occurrence in disaster scenarios. However, it is also crucial that solutions and platforms are developed to integrate emergency management data coming from multiple sources, including feeds provided by citizens through social media and crowdsourcing.
The I-TENDER workshop will aim at capturing the research and technology trends that enable such awareness by soliciting contributions along three main directions. First, solutions that leverage the widespread availability of handheld devices (smartphone, tablets) that act as the prime contact point to alert the population of impending dangers and as a locating device for rescue teams. Secondly, data analysis techniques that take into account the pervasive role of social networks in collecting and spreading information and provide accurate checking using appropriate tools. And, finally, emerging networking paradigms that go beyond the traditional infrastructure-based model, rather leveraging disruption-tolerant models and device-to-device communication, such as Wi-Fi direct and LTE-D2D. The workshop seeks original work presented in the form of research papers describing new research approaches and results. Highly disruptive work-in-progress and position papers are welcome, provided they focus on particularly innovative solutions or applications for emergency and disaster relief. We also invite authors to submit papers presenting extensive experiences with implementation, deployment, and operation.
Sept 25, 2017 submission deadline
Oct 9, 2017 Notification to Authors
Oct 27, 2017 Camera Ready
Co-located with the 13th International Conference on emerging Networking EXperiments and Technologies (ACM CoNEXT 2017)
Society as a whole is increasingly exposed and vulnerable to disasters because extreme weather events, exacerbated by climate change, are becoming more frequent and longer. To address this global issue, novel advanced data analytics solutions able to cope with heterogeneous big data sources are needed. The huge amount of data generated by people and automatic systems during natural hazard events (e.g., social network data generated by citizens and first responders, satellite images of the affected areas, flood maps generated by drones), is typically referred to as Big Crisis Data. To transform this overload of heterogeneous information into valuable knowledge, we need to integrate it and extract knowledge in near-real time by means of novel data analytics solutions. Currently, the analysis is focused on one single type of data (e.g., social media data, or satellite images). Their integration into big data analytics systems capable of building accurate predictive nowcast and forecast models will provide effective support for emergency management.
The workshop aims at involving researchers, practitioners and environmental and governmental bodies to foster discussion on emergency management analytics open issues and provide interesting insights for future actions in the natural hazard management area.
Oct 6, 2017: Due date for workshop papers submission
Nov 1, 2017: Notification of paper acceptance to authors
Early detection and information extraction for weather-induced floods using social media streams. C. Rossi,F.S. Acerbo,K. Ylinen,I. Juga,P. Nurmi,A. Bosca,F. Tarasconi,M. Cristoforetti,A. Alikadic. International Journal of Disaster Risk Reduction vol. 30, part A 145-157, doi: 10.1016/j.ijdrr.2018.03.002 [More]
Area Formation and Content Assignment for LTE Broadcasting. Claudio Casetti, Carla-Fabiana Chiasserini, Francesco Malandrino, Carlo Borgiattino. Computer Networks 126, 174-186, doi: 10.1016/j.comnet.2017.07.006 [More]
A service oriented cloud-based architecture for mobile geolocated emergency services. C. Rossi, M. H. Heyi, F. Scullino. Concurrency and Computation: Practice and Experience 29/11, e4051, doi: 10.1002/cpe.4051 [More]
Review on computer vision techniques in emergency situations Laura Lopez-Fuentes, Joost van de Weijer, Manuel González-Hidalgo, Harald Skinnemoen, Andrew D. Bagdanov. Multimedia Tools and Applications, 1-39, doi: 10.1007/s11042-017-5276-7 [More]
Scaling associative classification for very large datasets Luca Venturini, Elena Baralis, Paolo Garza. Journal of Big Data, 4:44, 1-24, doi: 10.1007/s11042-017-5276-7 [More]
Methods to Remove the Border Noise From Sentinel-1 Synthetic Aperture Radar Data: Implications and Importance For Time-Series Analysis Iftikhar Ali, Senmao Cao, Vahid Naeimi, Christoph Paulik, Wolfgang Wagner. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 1-10, doi: 10.1109/JSTARS.2017.2787650
Publications in conferences and workshops
Multi-modal Deep Learning Approach for Flood Detection Laura Lopez-Fuentes, Joost van de Weijer, Marc Bolaños, Harald Skinnemoen. MediaEval, 2017 – Multimedia Benchmark Workshop [More]
Quantifying and Minimizing the Impact of Disasters on Wireless Communications C.F. Chiasserini, F. Malandrino. ACM Workshop on ICT Tools for Emergency Networks and DisastEr Relief (I-TENDER 2017), Co-located with ACM CoNEXT 2017, 26-30, doi: 10.1145/3152896.3152902 [More]
Filtering Informative Tweets during Emergencies: A Machine Learning Approach F. Acerbo, C. Rossi. ACM Workshop on ICT Tools for Emergency Networks and DisastEr Relief (I-TENDER 2017), Co-located with ACM CoNEXT 2017, 43106, doi: 10.1145/3152896.3152897 [More]
Co-design of a Crowdsourcing Solution for Disaster Risk Reduction Q. Nguyen, A. Frisiello, C. Rossi. ACM Workshop on ICT Tools for Emergency Networks and DisastEr Relief (I-TENDER 2017), Co-located with ACM CoNEXT 2017, 43293, doi: 10.1145/3152896.3152898 [More]
Localization of Emergency First Responders Using UWB/GNSS with Cloud-based Augmentation S. Tadic, L. Vurdelja, M. Vukajlovic, C. Rossi. ACM Workshop on ICT Tools for Emergency Networks and DisastEr Relief (I-TENDER 2017), Co-located with ACM CoNEXT 2017, 24-25, doi: 10.1145 /3152896.3152901 [More]
Positioning Integrity Computation for Consumer Grade GNSS Receivers G. Marucco, D. Margaria. ACM Workshop on ICT Tools for Emergency Networks and DisastEr Relief (I-TENDER 2017), Co-located with ACM CoNEXT 2017, 18-23, doi: 10.1145/3152896.3152900 [More]
River segmentation for flood monitoring Laura Lopez-Fuentes, Claudio Rossi, and Harald Skinnemoen: Workshop on Data Science for Emergency Management (DSEM), co-located with IEEE International conference on Big Data 2017, 3664-3667 [More]
Gamified Crowdsourcing for Disaster Risk Management Antonella Frisiello, Quynh Nhu Nguyen, Claudio Rossi, and Fabrizio Dominici Workshop on Data Science for Emergency Management (DSEM), co-located with IEEE International conference on Big Data 2017, 3645-3651 [More]
A Language-agnostic Approach to Exact Informative Tweets during Emergency Situations Jacopo Longhini, Claudio Rossi, Claudio Casetti, and Federico Angaramo Workshop on Data Science for Emergency Management (DSEM), co-located with IEEE International conference on Big Data 2017 3657-2663 [More]
Coupling Early Warning Services, Crowdsourcing, and Modelling for Improved Decision Support and Wildfire Emergency Management C.Bielski, V.O’Brien, C.Whitmore, K.Ylinen, I.Juga, P.Nurmi, J.Kilpinen, I.Porras, J.M.Sole, P.Gamez, M.Navarro, A.Alikadic, A.Gobbi, C.Furlanello, G.Zeug, M.Weirather, J.Martinez, R.Yuste, S.Castro, V.Moreno, T.Velin,and C.Rossi. Workshop on Data Science for Emergency Management (DSEM), co-located with IEEE International conference on Big Data 2017, 3623-3630 [More]
All in a twitter: self-tuning strategies for a deeper understanding of a crisis tweet collection Evelina Di Corso, Francesco Ventura, and Tania Cerquitelli.Workshop on Data Science for Emergency Management (DSEM), co-located with IEEE International conference on Big Data 2017, 3640-3644 [More]
Summarization of emergency news articles driven by relevance feedback Luca Cagliero.Workshop on Data Science for Emergency Management (DSEM), co-located with IEEE International conference on Big Data 2017, 3631-3639 [More]
Analyzing spatial data from Twitter during a disasterLuca Venturini, Evelina Di Corso. Workshop on Data Science for Emergency Management (DSEM), co-located with IEEE International conference on Big Data 2017, 3697-3701 [More]
A Heat Wave Forecast System for Europe Andrea Gobbi, Azra Alikadic, Cesare Furlanello, Ylinen Kaisa, Federico Angaramo. Workshop on Data Science for Emergency Management (DSEM), co-located with IEEE International conference on Big Data 2017, 3652-3656 [More]
The Role of Unstructured Data in Real-Time Disaster-related Social Media Monitoring Francesco Tarasconi, Michela Farina, Alessio Bosca, Antonio Mazzei. Workshop on Data Science for Emergency Management (DSEM), co-located with IEEE International conference on Big Data 2017, 3687-3696 [More]
SQL versus NoSQL Databases for Geospatial Applications Elena Baralis, Andrea Dalla Valle, Paolo Garza, Claudio Rossi, Francesco Scullino The 2nd IEEE International Workshop on Big Spatial Data (BSD), Co-located with IEEE Big Data 2017, 3306-3315 [More]
Forecasting European Wildfires Today and in the Future Maria Navarro Abellan, Ignasi Porras, Josep Maria Sole, Pedro Gamez, Conrad Bielski and Pertti Nurmi. EGU General Assembly Conference Abstracts, 19, 7924 [More]
Improving European Wildfire Emergency Information Services Conrad Bielski, Ceri Whitmore, Victoria O’Brien, Gunter Zeug, Milan Kalas, Ignasi Porras, Josep Maria Solé, Pedro Gálvez, Maria Navarro, Pertti Nurmi, Juha Kilpinen, Kaisa Ylinen, Cesare Furllanelo, Valerio Maggio, Azra Alikadic, Claudia Dolci. EGU General Assembly Conference Abstracts, 19, 17946 [More]
Calibrating ensemble weather forecasts for warnings of extreme weather events Kaisa Ylinen, Juha Kilpinen. European Meteorological Society (EMS) Annual Meeting 2017, 14, 85 [More]
I-REACT in a nutshell
I-REACT is an innovation project funded by the European Commission. We aim to use social media, smartphones and wearables to improve disaster management.