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EWIDS (Very large wireless sensor networks for well-being)


EWiDs in a nutshell

EWiDS is concentrating on extreme wireless distributed systems. In EWiDS, we aim at a better understanding of using wireless, user-centric sensor technology to monitor and manage the behavior of people. To this end, we use crowd management as our application domain. Our goal is to:

  • Use body-worn sensors to measure proximity between people, leading to a so-called proximity graph.
  • Automatically extract a proximity graph from a mobile sensor network consisting of thousands of people, to process the extracted data in real time and offline.
  • The extracted data consists of a series of evolving graphs. We aim at developing new techniques for large-scale dynamic network analysis.

Once analysis has been done, we will use the obtained information to provide feedback to a crowd of people, thus leading to actual crowd management. To get a better idea of what a proximity graph actually is, take a look at this description.

Proximity graphs may be enriched with additional information such as sensed audio signals.

What we stand for

EWiDS is all about ICT research and to solving societal problems. We use applications to steer our research, yet we do not aim at perfect engineering of those applications. Yet is extremely important to us that our research results find their way to real solutions. For this reason, academic and industrial partners, big and small, collaborate intensely. We are also continuously seeking for new partners who can inspire and guide our solutions.

What we do 

Within EWiDS we do experimental applied ICT research toward finding solutions for the following problems:

  • Using radio communication in highly dense sensor networks for detecting the presence of pairs of nodes.
  • Decentralized detection and processing of audio signals in very large wireless sensor networks.
  • In-network aggregation of sensed data, such as estimating network sizes, in order to allow for efficient offline and real-time data processing.
  • Very large-scale analysis and simulation of dynamic networks representing crowds of people aimed at crowd management.
  • How to provide effective feedback to a crowd of people in order to intervene in the current structure.


Biggest results so far

Wireless crowd monitoring in Arnhem

Wifi-tuin Arnhem
Monitoring the movements of crowds in cities can lead to improved city plan­ning, more efficient traffic flows and safer crowd management. As camera surveil­lance might lead to privacy violations, we use wireless sensor networks to measure who is close to whom. In particular, we use ordinary smartphones as sensors. We make sure that the data of individuals are anonymized. More.

ICT science question: how can we reliably detect mobile devices and realistically project their trajectories onto a city plan? One of the problems is that there are many false and missed detections, originating from very different sources. Identifying trajectories is difficult as there may be many alternatives paths between two subsequent detections of the same device at different locations.

Involved COMMIT/partners: Gemeente Arnhem, Wireles Arnhem, VU.

Measuring crowd densities for safety and efficiency

View presentation by clicking on this image
Events like concerts, festivals and sport­ing competitions often attract a crowd of people. The same can be the case for institutions like museums, hospitals and amusement parks. We have developed a real-time visualization of how the density of a crowd changes. More.

ICT science question: the scientific challenge is how to reliably estimate the number of people that are in the neighbour­hood of each person. Each person is a node in a constantly changing network. This estimation is a scientifically hard problem, because we consider mobile networks with high densities: each node has typically hundreds of neighbours.

Involved COMMIT/partners: Van Mierlo, VU, TUDelft.