Logo Cids

Centre for Innovation in Distributed Systems
Industry Partners

Research outcomes and application enhancements for real-world solutions demand rigorous proof of functionality as well as feasibility studies. CIDS has created partnerships with MNCs and SMEs in order to benefit from their market experience. CIDS in partnership with industry and business, gains pragmatic knowledge through pilot implementation of CIDS proof of concept in the real-world rather than only in laboratories . These mutually beneficial partnerships have been created through EU and nationally funded mechanisms. Some of our partner companies are listed below.

Altobridge

GE Global Research (US)
Claymon Biomnis

Universal Trace
Jettainer Punto Qualita (Italy)
Thales

Animal Reproductive Technologies (UK)
Neotech Software Systems

vanta Global (Bel)
 
RFID in Europe - Leuven 2012

RFID in Europe is holding a Conference with 3 Workshops on Privacy/Security, Academic Activity and Business Development to launch the new RFID in Europe organisation. The event takes place on the 23rd and 24th of May in Leuven Brussels. For further details go to www.rfidineurope.eu

Projects

Bio-sample Tracking

CIDS  have developed in conjunction with Universal Trace Ltd. an advanced system for automated tracking and monitoring of pathology samples based on RFID. This project was supported by Enterprise Irelands Innovation Voucher Scheme.
iPhone Development

CIDS have developed and deployed advanced applications for iPhone and iPad devices in conjunction with our Industry Partner companies. CIDS are available to discuss R&D requirements that you have for mobile applications using any of the popular platforms.
System of Systems

System of Systems describes the interaction between different independent systems to achieve an overall goal that is greater than the sum of each component part. CIDS is a currently researching in the area of SoS.  
Reality Mining

Currently we are researching the feasibility of combining Internet Of Things (IoT) technologies and Reality Mining techniques to provide for systems where the actions of smart objects may be monitored and predicted.