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Wi-metal: Detecting metal by using wireless networks

With an increasing need for worldwide counter-terrorism, security is becoming a top priority on the agenda of local governments. Governments has enforced patrols, security forces, and security equipments such as door frame detectors, screens and hand-held detectors in public places like railway stations and airports. The main purpose of these security equipments is to detect potentially dangerous metal objects. And the way to detect metal is mainly based on electromagnetic induction and X-rays. On the one hand, detectors based on electromagnetic induction needs to be placed close to the examined objects and on the other hand, detectors based on X-rays are usually large, expensive, complex, harmful and the detecting distance is limited on many occasions. For the above reasons, current metal detection equipments cannot be deployed on a large scale with a low cost scheme. But with the popular use of Wi-Fi in public areas, low-cost and large-scale deployment is possible if we could use Wi-Fi to detect metal. Since the dielectric constant and the reflection coefficient of metal are different from those of nonmetal objects, the effect of Wi-Fi signal reflection caused by metal objects is different from nonmetal items as well. Thus we attempt to use this observation to enable metal detection. But using Wi-Fi to detect metal will encounter some challenges. Factors such as the interference caused by multi-path effect and other signal sources, shapes, materials and surface smoothness of the target, as well as the angle of reflection will cause great impact on a detecting result. However, we implement a system by using a series of methods to eliminate most of the interferences and use machine learning algorithm to identify metal. We implement this system in commercial products. We conduct several experiments and their average accuracy and false alarm are respectively more than 90% and less than 10% in 1 meter detecting distance.