  Walking while using a smartphone is becoming a major pedestrian safety
concern as people may unknowingly bump into various obstacles that could lead
to severe injuries. In this paper, we propose ObstacleWatch, an acoustic-based
obstacle collision detection system to improve the safety of pedestrians who
are engaged in smartphone usage while walking. ObstacleWatch leverages the
advanced audio hardware of the smartphone to sense the surrounding obstacles
and infers fine-grained information about the frontal obstacle for collision
detection. In particular, our system emits well-designed inaudible beep signals
from the smartphone built-in speaker and listens to the reflections with the
stereo recording of the smartphone. By analyzing the reflected signals received
at two microphones, ObstacleWatch is able to extract fine-grained information
of the frontal obstacle including the distance, angle, and size for detecting
the possible collisions and to alert users. Our experimental evaluation under
two real-world environments with different types of phones and obstacles shows
that ObstacleWatch achieves over 92% accuracy in predicting obstacle collisions
with distance estimation errors at about 2 cm. Results also show that
ObstacleWatch is robust to different sizes of objects and is compatible with
different phone models with low energy consumption.
