is a public-private research community solving grand challenges in information and communication science shaping tomorrow's society
- INFINITI (Information retrieval for information services)
- IUALL (Interaction for Universal Access)
- SenseI (Sensor based Engagement for Improved Health)
- Virtual worlds for well-being
- SEALINCMedia (Socially-enriched access to linked cultural media)
- SWELL (Smart Reasoning Systems for Well-being at Work and at Home)
- SENSAFETY (Sensor Networks for Public Safety)
- EWIDS (Very large wireless sensor networks for well-being)
- ALLEGRIO (Composable Embedded Systems for Healthcare)
- METIS (Dependable Cooperative Systems for Public Safety)
- THeCS (Trusted Healthcare Services)
- TimeTrails (Spatiotemporal Data Warehouses for Trajectory Exploitation)
- IV-e (e-Infrastructure Virtualization for e-Science Applications)
- Data2Semantics (From Data to Semantics for Scientific Data Publishers)
- e-BIOBANKING (e-Biobanking with Imaging for Healthcare
- e-FOOD (e-Foodlab)
EWIDS (Very large wireless sensor networks for well-being)
Recent history has shown that being in a crowd of people can be pleasurable or dangerous with a fine line distinguishing the two. It’s not just about festivals and events; it’s also about everyday activities like for instance taking a train.
The Extreme Wireless Distributed Systems (EWiDS) project takes its inspiration from managing and controlling large crowds of people. Its uniqueness lies in the way observations take place. Traditionally, crowds are monitored through a few tens of cameras placed at strategic locations, leading to global, external observations. In contrast, in EWiDS we assume that thousands of sensing devices are present inside a crowd, leading to local, internal observations. A sensing device is typically a (special) smartphone (now owned by many people) or (low cost) electronic badge. By harnessing devices people already own we would be able to monitor crowds without large infrastructure investments.
The scientific ICT challenge for EWiDS is automatically extracting and analyzing the evolving structure of a crowd from internal sensors: electronic badges, smartphones, etc. To this end, we assume that each person carries a special device capable of detecting the presence of another nearby device. These devices may typically be part of, or added on to a smartphone. By detecting which devices are close to each other, and when, we obtain a picture of a crowd from within a crowd; a picture that continuously changes as people move.
An important specific ICT challenge is transferring massively distributed continuous streams of low-level, highly faulty radio-based proximity detections from very simple sensor nodes to an external analysis system, transforming those streams into a highly reliable and continuously up-to-date view on dynamic augmented proximity graphs. The EWiDS project of course starts off small. During its first year, much effort has been put into developing and testing the basic means for internal sensing. Highlights include experiments with electronic badges (a first one with some 200 people celebrating 30 years of Informatics in Amsterdam; a second one at ICTOpen with 150 participants). Data has been gathered that now forms the basis for validating some of our fundamental approaches in identifying crowd structures.