Detecting suspicious objects in baggage using common Wi-Fi
Their study – “Towards In-baggage Suspicious Object Detection Using Commodity WiFi” – demonstrates a low-cost Wi-Fi-based technology for security screening at public venues like stadiums, theme parks and schools. The suspicious object detection system, say the researchers, is easy to set up, reduces security screening costs, and avoids invading privacy such as occurs when screeners open and inspect bags, backpacks, and luggage.
“This could have a great impact in protecting the public from dangerous objects,” says Yingying (Jennifer) Chen, co-author of the study and a professor in the Department of Electrical and Computer Engineering in Rutgers–New Brunswick’s School of Engineering. “There’s a growing need for that now.”
Ubiquitous Wi-Fi wireless signals in most public places, say the researchers, can penetrate bags to get the dimensions of dangerous metal objects and identify them, including weapons, aluminum cans, laptops and batteries for bombs. Wi-Fi can also be used to estimate the volume of liquids such as water, acid, alcohol and other chemicals for explosives, according to the study.
The low-cost object detection system system requires a Wi-Fi device with two to three antennas and can be integrated into existing Wi-Fi networks. The system analyzes what happens when wireless signals penetrate and bounce off objects and materials.
The system uses the fine-grained channel state information (CSI) from off-the-shelf Wi-Fi. This information describes how a signal propagates from the transmitter to the receiver and represents the combined effect of such effects as scattering, fading, and power decay with distance.
The system first detects the existence of suspicious objects and identifies the dangerous material type based on the reconstructed CSI complex value (including both amplitude and phase information). It then determines the risk level of the object by examining the object’s dimension – that is, a liquid volume or metal object’s shape – based on the reconstructed CSI complex of the signals reflected by the object.
Experiments with 15 types of objects and six types of bags demonstrated detection accuracy rates of 99% for dangerous objects, 98% for metal and 95% for liquid, say the researchers. For typical backpacks, the accuracy rate exceeds 95% and drops to about 90% when objects inside bags are wrapped.
Looking ahead, say the researchers, next steps include trying to boost accuracy in identifying objects by imaging their shapes and estimating liquid volumes.
Related articles:
3D through-wall imaging achieved with drones and Wi-Fi
Holography with Wi-Fi yields 3D images for object tracking
Compact terahertz source offers security detection at room temps
AI smart home system sees through walls
New light-trapping sensor promises improved drug, bomb detection
If you enjoyed this article, you will like the following ones: don't miss them by subscribing to :
