Smart Card Auto-Selection Using GPS and WiFi Fingerprints for Smartphones

Smartphones equipped with NFC are increasingly emerging as favored alternatives to traditional physical smart cards. The E-wallet App on the phone mimics and stores digital credentials such as payment cards, transit cards, and door access cards. Thus it eliminates the need to carry multiple physical cards. However, users must scroll the screen and select the correct smart card manually before they tap the smartphone to the NFC terminal. It is not easy to correctly predict the smart card to be used because a user may swipe different cards in a short time, where a typical scenario is to tap an autogate at the entry of a building and open the NFC locks on the doors of the different office rooms inside the building. The key problem is to identify the NFC terminal to be tapped accurately and efficiently regardless of location. This motivates the need for a new approach to smart card selection. This paper proposes a method to identify the specific NFC terminal when the smartphone gets close to it and decide the most appropriate smart card automatically. It collects the GPS and WiFi fingerprints and stores them in the smartphone for a smart card when the phone is first bound to a terminal offline. During the online phase, the best-matched card is selected for tapping. Extensive tests are carried out on five mainstream Android smartphones in various indoor and outdoor environments to demonstrate the good performance of our proposed method.