Event Prediction and Decision Support based on Hug.. (EPPICS)
Event Prediction and Decision Support based on Huge Data from Physical-Social Systems
Start date: Feb 1, 2014,
End date: Jan 31, 2017
Miniaturisation, progress with energy issues and cost reductions have resulted in rapid growth in deployment of networked devices and sensors, very strongly connecting the internet with the physical world. With wide adoption of smartphones and social media, also people have become key sources of information about the physical world, corresponding events and the intents and plans of many individuals. With more than a billion of people organizing their lives electronically and sharing information via social platforms on the Internet and with the number of devices connected to the Internet already exceeding the number of people on earth and still growing to an estimated 50 billion devices by 2020, handling these massive amounts of data becomes a huge challenge. Surmounting this challenge, however, may give us previously unattainable understanding of events and changes in our surrounding environments. EPPICS will develop large scale adaptive methods to enable pervasive modelling, monitoring and predicting of events in the real world by extracting and combining data and information from physical and social sensors. Such methods will be integrated into a platform that will support citizens, authorities and organizations in taking informed and timely decisions when tackling real world events. Application domains will cover the intelligent management in urban settings with a particular focus on city-wide events management as well as water management, specifically monitoring and reacting to widespread floods. EPPICS will provide the technological and methodological framework for the capturing, integrating, modeling and forecasting of the large-scale hybrid information deriving from hundreds of sensors, thousands of cars and large-scale social media. The technology will enable the authorities a huge leap in terms of the ability to manage large events where hundreds of thousands of people are involved at the same time.
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