Objective
Project SNIFFER envisions the design and development of a network of distributed detection
devices, capable of rapid, on-site detection of multiple kinds of agents and CBR agents with high
sensitivity and specificity throughout the most vulnerable stages of the food supply chain (such as
farms, large collection centers, wholesalers, etc…). The project will address both available sensor
technology and new, complementary sensor devices that shall be used for the detection of
hazardous CBR agents within the food supply chain. The sensor devices to be developed are
characterized by their portability, easiness to use and reusability. Another important feature of the
new device will be its modular design, i.e. the device is formed by several independent modules
(sensors, communication device, on-board computing, etc), combined through generalized and
standardized connections. The network of sensor devices will be designed as a centralized
architecture, in which all the data from the devices will be sent to a command center. An operator
of the SNIFFER system will also have the ability to remotely control and command the sensor
devices using a specific interface from the command center.
Project SNIFFER will also envision the creation of a set of guidelines, which presents the
countermeasures and procedures that shall be used within the European Union whenever a food or feed borne incident is detected within the food supply chain. The guidebook will provide help to
the appropriate entities in employing the corrective counter-measures in order to mitigate, restrain or ultimately eradicate the hazardous agent. The aforementioned objectives of the project will be
directed to achieve the final goal of providing means of countermeasure to mitigate a possible
incident of CBR health hazardous agents in the food supply chain and to increase the security
within all the steps that constitute the food supply chain.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensors
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Call for proposal
FP7-SEC-2012-1
See other projects for this call
Funding Scheme
CP-FP - Small or medium-scale focused research projectCoordinator
2500-750 Caldas Da Rainha
Portugal