Identifying everyday objects with a smartphone knock

Abstract

We use smartphones and their apps for almost every daily activity. For instance, to purchase a bottle of water online, a user has to unlock the smartphone, find the right e-commerce app, search the name of the water product, and finally place an order. This procedure requires manual, often cumbersome, input of a user, but could be significantly simplified if the smartphone can identify an object and automatically process this routine. We present Knocker, an object identification technique that only uses commercial off-the-shelf smartphones. The basic idea of Knocker is to leverage a unique set of responses that occur when a user knocks on an object with a smartphone, which consist of the generated sound from the knock and the changes in accelerometer and gyroscope values. Knocker employs a machine learning classifier to identify an object from the knock responses. A user study was conducted to evaluate the feasibility of Knocker with 14 objects in both quiet and noisy environments. The result shows that Knocker identifies objects with up to 99.7% accuracy. Copyright held by the owner/author(s).