Regular Wi-Fi can now be used to detect weapons, bombs

Apart from connecting us with the world, Wi-Fi can also be used to detect weapons or bombs for keeping us safe in public areas.

As per a recently conducted study by Rutgers University, our ordinary Wi-Fi technology can soon be used in real-life public areas where it can effectively and cheaply detect bombs, weapons or explosive chemicals contained within bags.

The paper detailed that the most dangerous objects contain metals or liquids that interfere with Wi-Fi signals in a way that researchers can detect. Also, the baggage used to carry such devices is normally made of materials like paper or fiber through which Wi-Fi signals can pass easily, wrote Futurism.

The researchers created a Wi-Fi weapon detection system that can analyze what happened to Wi-Fi signals as they come across a nearby object or material. Upon testing the system on 15 types of objects and six types of bags, the researchers discovered that 99% of the time it could differentiate hazardous objects from the non-dangerous ones. 90% of the dangerous materials could be identified, with accurately identifying metals 98% of the time, and liquids 95% of the time.

Moreover, the bag the object was presented in was an original backpack and the system detected the object with a 95% accuracy rate. When wrapped in something else before being put in the bag, the accuracy rate, however, dropped out to 90%.

Explaining the difficulty of installing expensive instruments, co-author Yingying Chen said, “In large public areas, it’s hard to set up expensive screening infrastructure like what’s in airports. Manpower is always needed to check bags, and we wanted to develop a complementary method to try to reduce manpower.”

BBC News reported, the system can be used in stadiums, theme parks, museums, festivals, schools and other locations with potential public risks. “This could have a great impact in protecting the public from dangerous objects. There’s a growing need for that now,” Chen added.

For the time being, the team is planning to focus on improving the system’s accuracy in order to make it able enough to better detect an object’s shape, and modifying it to estimate the volume of liquids contained within the bags.