Coupling crowdsourcing, earth observations, and E-GNSS in a novel flood emergency service in the cloud

Rossi, Claudio; Stemberger, Wolfgang; Bielski, Conrad; Zeug, Gunter; Costa, Nina; Spaltro, Emiliano; Dominici, Fabrizio

doi:10.1109/igarss.2015.7326371

Cited by 9 publications

(6 citation statements)

References 3 publications

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“…Similarly to [16], we propose to implement a specific mobile application to: 1) Increase citizens? awareness related to wildfires: users can be invited to build up their knowledge on wildfires in a "passive" manner, e.g.…”

Section: ) Wildfire Hazard Nowcasting and Forecastingmentioning

confidence: 99%

Coupling early warning services, crowdsourcing, and modelling for improved decision support and wildfire emergency management

Bielski¹,

O'Brien²,

Whitmore³

et al. 2017

2017 IEEE International Conference on Big Data (Big Data)

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Abstract-The threat of a forest fire disaster increases around the globe as the human footprint continues to encroach on natural areas and climate change effects increase the potential of extreme weather. It is essential that the tools to educate, prepare, monitor, react, and fight natural fire disasters are available to emergency managers and responders and reduce the overall disaster effects. In the context of the I-REACT project, such a big crisis data system is being developed and is based on the integration of information from different sources, automated data processing chains and decision support systems. This paper presents the wildfire monitoring for emergency management system for those involved and affected by wildfire disasters developed for European forest fire disasters.

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Section: ) Wildfire Hazard Nowcasting and Forecastingmentioning

confidence: 99%

Coupling early warning services, crowdsourcing, and modelling for improved decision support and wildfire emergency management

Bielski¹,

O'Brien²,

Whitmore³

et al. 2017

2017 IEEE International Conference on Big Data (Big Data)

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“…14,15 A full specification of FLOODIS is given in a previous study, 16 while the flood nowcast and forecast algorithms are detailed in a previous study. The latter is user to extract the area of interest, which is the area affected by the flood.…”

Section: Floodismentioning

confidence: 99%

A service oriented cloud‐based architecture for mobile geolocated emergency services

Rossi

Heyi

Scullino

2016

Concurrency and Computation

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Despite the growing development of space-based systems aimed at monitoring and studying natural hazards, they continue to harm humankind worldwide, causing enormous human and economic losses. In a view of improving the effectiveness and the timeliness of existing emergency systems, we propose a service-oriented cloud-based software architecture for mobile sensing applications. Exploiting existing Global Navigation Satellite Systems and public Cloud Computing services, we implement a set of mobile geolocated services enabling mobile devices to send real-time in-field observations. Such observations could be used by authorities and first responders for both Early Warning and Emergency Response services complementing in real time the situational assessment provided by existing means, eg, remote sensed information and in-situ sensors. We propose a Service Oriented Architecture that can be used as a reference for implementing the back end of mobile applications requiring to send crowdsourced geolocated reports.We fully implement a real application, and we evaluate its performances with Microsoft Azure varying the user load and the main deployment parameters. Our results can be taken as reference to assess the capability of future applications with similar requirements.

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“…The original version of this Augmentation Module is described in [10][11][12]. The development of the algorithm started from the analysis of some datasets taken in different environments (open sky, country, hill mostly covered with vegetation and urban) with a consumer grade GNSS receiver (a u-blox LEO 8U).…”

Section: The Local Integrity Algorithm Implementation For Emergency Smentioning

confidence: 99%

Positioning integrity computation for consumer grade GNSS receivers

Marucco

Margaria

2017

Proceedings of the First CoNEXT Workshop on ICT Tools for Emergency Networks and DisastEr Relief

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This paper describes the generalization of a method for the estimation of the reliability of the positioning information provided by consumer-grade devices exploiting the Global Positioning System (GPS) and the other Global Navigation Satellite Systems (GNSS) in a wide range of situations and environments. Principles are introduced, and a description of the implementation is detailed. Data collection and analysis necessary for the environmental characterization are reported. The algorithm was validated with some test carried out in different conditions.

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Coupling crowdsourcing, earth observations, and E-GNSS in a novel flood emergency service in the cloud

Cited by 9 publications

References 3 publications

Coupling early warning services, crowdsourcing, and modelling for improved decision support and wildfire emergency management

Coupling early warning services, crowdsourcing, and modelling for improved decision support and wildfire emergency management

A service oriented cloud‐based architecture for mobile geolocated emergency services

Positioning integrity computation for consumer grade GNSS receivers

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