VibWall: Smartphone’s Vibration Challenge-response for Wall Crack Detection

Abstract

As the building ages, the wall structure may become deteriorated (e.g., wall cracks, discontinuities, and corrosion) due to the variation of the environment (i.e., temperature and humidity). Moreover, these wall cracks, discontinuities, and corrosion will affect the living comfort and coziness. As such, the wall health diagnostic becomes crucial for the safety and comfort of modern buildings. However, the existing wall health detection techniques (e.g., UWB radars, acoustic sensing, and sensor embedding techniques) are high-cost, not ubiquitous, and not robust to the variation of the environment. In this article, we propose VibWall, a system that can use the smartphone’s sensors (i.e., accelerometer, gyroscope, and vibrator) to detect the wall’s structural health. Specifically, the wall cracks can be detected for living safety, comfort, and coziness. Our key idea is that the smartphone’s vibration is absorbed, reflected, and propagated disparately based on the physical structure of the wall. To be specific, we employ a novel challenge-response scheme, where the challenge is a sequence of heterogeneous vibration patterns from the smartphone’s vibrator, and the responses to these vibrations are sensed by the smartphone’s gyroscope and accelerometer sensors. Then, the machine learning-based classifier (e.g., random forest classifier) will be used to discriminate between the healthy wall and the wall with cracks, discontinuities, or corrosion based on these responses. Our experimental results show good performance on the wall’s structural health detection with the wall specimen and real-world walls.