Objective
The detection of illegal compounds is an important analytical problem which requires reliable, selective and sensitive detection method that provides the highest level of confidence in the result. Moreover, to contribute in the successful development the automated target acquisition, identification and signal processing of data from the sensor is mandatory. Enhancements to sensing methods, recognition ability and target detection time lead with the algorithms improvements in software that is complementary to improving sensor hardware. In the end, the sensing device should be portable, rapid, easy in use, highly sensitive, specific (minimal false positives), and low cost.
SEC.2012.1.6-1 Digital, minituarised, operational tool for investigation – Capability project would be suitable to our research activity. We aim in the end of the project to demonstrate a working sensing device that can be further developed into a portable, miniaturized, automated, rapid, low cost, highly sensitive, and simple, “sniffer” and detection unit based on a disposable micro-colorimetric chip, which can be used for identification of illegal drugs or drug precursors. The project will combine highly advanced disciplines, like organic chemistry, micro fabrication and hardware technology, machine learning and signal processing techniques, to support the development of a miniaturized sensor system that can be used for identification of illegal drugs or drug precursors providing custom officers, police etc. with an effective tool to control trafficking of illegal drugs and drug precursors.
Fields of science
- natural sciencescomputer and information sciencessoftware
- natural scienceschemical sciencesorganic chemistry
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsignal processing
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensors
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Topic(s)
Call for proposal
FP7-SEC-2012-1
See other projects for this call
Funding Scheme
CP-FP - Small or medium-scale focused research projectCoordinator
2800 Kongens Lyngby
Denmark