Reference number : GC-2017-Q1-00573, amendment number : , agreement type : G, recipient legal name : Nikolova, Natalia (McMaster University), recipient country : CA, recipient province : nan, recipient city : Ontario, recipient postal code : nan, program name english : Idea to Innovation, program name french : De l'idée à l'innovation, program purpose english : Crime and acts of terrorism are of great concern in modern society. The detection of on-body hidden weapons_x000D_
is of paramount importance for saving lives. Current detection technologies suffer from high false rates, both_x000D_
positive and negative, even if the scanned people cooperate. High cost and low throughput prevent deployment_x000D_
in busy public buildings such as schools, stadiums, etc. Covert scanning, where people are unaware that they_x000D_
are being scanned, is even more challenging and remains an unsolved problem. Yet such "covert" systems are_x000D_
sometimes needed to adequately protect civilians._x000D_
This project focuses on the development of a new product for real-time scanning and detection of concealed_x000D_
weapons using microwave radar. Research will focus on a software-defined radio platform that offers great_x000D_
flexibility during development, deployment and even operational phases. It allows for system improvements_x000D_
without hardware changes and for updates over secure network connections. This architecture is available as a_x000D_
system on a chip, which will reduce the size and the cost to the end-user. The system's hardware footprint will_x000D_
be roughly the size of a notebook._x000D_
The detection system is safe as the radiation is non-ionizing and low-power. Another advantage is that the_x000D_
concealed objects will be detected without generating an image of the body, thus avoiding privacy concerns._x000D_
A distinct feature of this product is its cognitive ability to continuously learn about the deployment site, about_x000D_
new threats (e.g. weapons), and about new non-threats (e.g. cell phones). Recognition is enabled by machine_x000D_
learning classifiers, which are "trained" by applying statistical analysis to large sets of radar responses to_x000D_
threats, non-threats, and background environments. Classification depends critically on these measurements,_x000D_
particularly those of the deployment site. Therefore, the product will continue to acquire new measurements_x000D_
after installation in order to improve the detection success. New threat/non-threat data, as well as novel_x000D_
classifiers, will also be provided via secure network updates., program purpose french : Crime and acts of terrorism are of great concern in modern society. The detection of on-body hidden weapons_x000D_
is of paramount importance for saving lives. Current detection technologies suffer from high false rates, both_x000D_
positive and negative, even if the scanned people cooperate. High cost and low throughput prevent deployment_x000D_
in busy public buildings such as schools, stadiums, etc. Covert scanning, where people are unaware that they_x000D_
are being scanned, is even more challenging and remains an unsolved problem. Yet such "covert" systems are_x000D_
sometimes needed to adequately protect civilians._x000D_
This project focuses on the development of a new product for real-time scanning and detection of concealed_x000D_
weapons using microwave radar. Research will focus on a software-defined radio platform that offers great_x000D_
flexibility during development, deployment and even operational phases. It allows for system improvements_x000D_
without hardware changes and for updates over secure network connections. This architecture is available as a_x000D_
system on a chip, which will reduce the size and the cost to the end-user. The system's hardware footprint will_x000D_
be roughly the size of a notebook._x000D_
The detection system is safe as the radiation is non-ionizing and low-power. Another advantage is that the_x000D_
concealed objects will be detected without generating an image of the body, thus avoiding privacy concerns._x000D_
A distinct feature of this product is its cognitive ability to continuously learn about the deployment site, about_x000D_
new threats (e.g. weapons), and about new non-threats (e.g. cell phones). Recognition is enabled by machine_x000D_
learning classifiers, which are "trained" by applying statistical analysis to large sets of radar responses to_x000D_
threats, non-threats, and background environments. Classification depends critically on these measurements,_x000D_
particularly those of the deployment site. Therefore, the product will continue to acquire new measurements_x000D_
after installation in order to improve the detection success. New threat/non-threat data, as well as novel_x000D_
classifiers, will also be provided via secure network updates., agreement title english : Cognitive microwave radar for the stand-off detection of on-body concealed weapons - phase IIb (partnership with a canadian company), agreement title french : Cognitive microwave radar for the stand-off detection of on-body concealed weapons - phase IIb (partnership with a canadian company), agreement number : I2IPJ, agreement value : 161321.0, agreement start date : 2017-06-14, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year. (2017-2018 to 2018-2019), additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2018-2019), owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada