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"Development of a Common Sensor Platform for the D.. (CommonSense)
"Development of a Common Sensor Platform for the Detection of IED ""Bomb Factories"""
(CommonSense)
Date du début: 1 janv. 2011,
Date de fin: 31 déc. 2013
PROJET
TERMINÉ
The detection of IED manufacturing facilities is crucial for the security of citizens, as well as infrastructures and utilities. Current sensing methods suffer from susceptibility to false positive results due to environmental contaminants, or false negative results to interfering compounds. The need exists for a single distributed network, with a common interface and communications protocol, to manage and communicate with a variety of different sensor technologies, and use the combined sensor data to produce clear and unequivocal results with low false positive/negative readings.The goal of the CommonSense project is to create and demonstrate this sensor network, through the simultaneous and parallel development of novel materials, portable sensors and a wireless communications network, which uses chemometric data processing algorithms to “learn” to recognise trace amounts of explosives, and differentiate them from interferents. The partners will produce a series of novel organic, polymeric and nanocrystalline materials with tuned optoelectronic properties and surface affinities to be used as the active sensor elements. These elements will be incorporated into devices based on optical, electrical, and other readout mechanisms, for detection of airborne and waterborne analytes.The CommonSense project will also incorporate radiation detectors to detect this growing security threat of “dirty bombs”, where sub-critical amounts of radioactive materials, obtained from medical waste or other sources, are incorporated into IEDs. The key point in the use of such a variety of sensor technologies is that no one substance can act as an interferent to all of the sensors, thus reducing false positives and negatives. Eliminating the remaining false readings will be achieved through use of the chemometric algorithms in order to teach itself to recognise the “fingerprint” sensor response to different explosives types and ignore interfering compounds.
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