Conventional WiFi Can Detect Bombs, Weapons And Explosive Chemicals

  • Researchers develop a new method that allows conventional WiFi to detect dangerous objects. 
  • It uses channel state information (CSI) from off-the-shelf WiFi to determine the risk level of suspicious materials. 
  • This inexpensive method can be easily deployed in public places. 

The portable dangerous items like homemade weapons have posed a rising threat to public security. You might remember April 2018 shooting incidence happened in a Florida high school, which killed 17 people. The school has made it mandatory to carry transparent and clear backpacks on campus.

However, such measures aren’t effective: they can’t prevent future attacks and also infringe on people’s privacy. To decrease such threats while preserving privacy, researchers at Rutgers University, Binghamton University and Indiana University-Purdue University Indianapolis have developed a new method that enables traditional WiFi to detect suspicious objects in backpacks and luggage.

The existing screening system requires expensive equipment (like CT and X-ray) and high staffing levels, whereas this new object detection machine is cheap and easy to set up. It can be deployed at stadiums, theme parks, schools, museums and other public places.

Since it’s very difficult to set up a costly screening infrastructure that you commonly see in airports, researchers wanted to build a complementary methodology that doesn’t require any manual checking.

How Did They Develop This?

WiFi signals are powerful enough to penetrate bags and extract the dimensions of dangerous objects. They can determine the volume of fluids, including acidic alcohol and explosive chemicals.

Credit: Data Analysis and Information Security Lab | Professor Yingying Chen

These inexpensive devices usually have up to 3 antennas and can be easily connected with current WiFi networks. They emit wireless signals that penetrate vision-blocked baggage and bounce off objects. Then, the system analyzes these reflected signals to estimate what’s actually inside the bag.

To build this system, researchers used channel state information (CSI) from off-the-shelf WiFi. It consists of 2 crucial components:

  1. It identifies the suspicious material using reconstructed CSI complex value, which includes amplitude as well as phase data.
  2. Then, it estimates the dimension of the object by using CSI complex of reflected signals to determine the risk level.

Researchers demonstrated that the object’s pure reflection can be obtained from the imperfect CSI (slightly distorted due to unforeseen shifts) in the WiFi device without having to modify transmissions or install large antenna array.

Reference: IEEE ConferenceRutgers University

Results

Courtesy of researchers 

To find how accurate these devices are, they experimented with 6 types of bags and 15 kinds of objects. The accuracy rates were pretty impressive: 95% for liquid substance, 98% for metal and 99% for dangerous materials.

Moreover, the system achieved the average errors of 0.5 cm and 16 ml when evaluating the shape/volume of the metal and fluid objects. For usual backpacks and luggage, the accuracy reached more than 95% but dropped to 90% when the materials inside bags were wrapped.

Read: New IC Technology Could Enable 400 Gbps Wireless Transmission

In the next study, researchers will try to improve the estimation process to increase the accuracy of identifying objects/liquids.

Written by
Varun Kumar

Varun Kumar is a professional science and technology journalist and a big fan of AI, machines, and space exploration. He received a Master's degree in computer science from Indraprastha University. To find out about his latest projects, feel free to directly email him at [email protected] 

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