Researchers detect weapons and chemicals in bags with Wi-Fi signals




Scientists from American Rutgers University have shown that hidden liquids and metal objects can be detected in luggage and identified with regular Wi-Fi signals.

According to the researchers, it is possible to use current Wi-Fi technology to scan public spaces for the presence of suspicious objects, without having to install special, expensive security devices. The scientists describe that their study shows that the use of signals from regular Wi-Fi devices is very suitable for this.

The scientists have conducted tests with fifteen different objects, and six different bags and some boxes, over a period of six months. The results show that the system used, which consists only of two wifi routers, each with two to three antennas, can correctly identify more than 95 percent of the suspect objects in different types of bags. In addition, it succeeded in identifying ninety percent of the hazardous material types.

In addition, scientists can use the Wi-Fi signals to map the average volume of liquids used during the study; in that case there was an average deviation of 16ml. When calculating the shape of metal objects, there was an average error deviation of 0.5 cm.

The detection of objects in bags works via the channel state information of Wi-Fi signals. This information describes the progress of a signal from the sender to the receiver. The effect of, for example, the strength and the scattering of the signals is taken into account in combination with the distance. Based on the degree of reflection, absorption and refraction, the researchers can map the properties of the materials irradiated with wifi signals; a fairly accurate estimate can also be made of the dimensions of the objects.

The researchers used two different set-ups, so that two things are separated: the refraction signals and the reflection signals from the channel state information on the one hand, and the recognition of the material and the shape of the object on the other. This made it possible to remove the phase noise in the channel state information and then reconstruct this information. Thus, the dominant interference of an object hidden in a bag can be accommodated.

According to the researchers, their approach is unique in the sense that they have taken into account the wireless interference caused by various factors of the irradiated objects, such as the type of material and the shape. Based on a risk estimation method based on the reflections, they can determine how risky a detected object is.

There are still some challenges when implementing the system in practice. For example, the material, shape, size and position of an object are factors that can influence the measurements. These disruptions can make the identification more difficult.

Further, Wi-Fi signals are not necessarily suitable for mapping objects, since both 2.4GHz and 5GHz Wi-Fi signals have relatively long wavelengths compared to the dimensions of the objects to be detected. This leads to a fairly high degree of refraction and therefore a low-resolution image. The measurement results must also take into account the effects that the different types of bags have on the identification of the objects.


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