A Binocular Vision Application in IoT: Realtime Trustworthy Road Condition Detection System in Passable Area

Abstract
The structural information detection of road conditions, which is adopted for
improving driving comfort, patrol inspection, road maintenance, and accident
rescue. In order to improve the trustworthiness of road condition detection, a
real-time artificial intelligence road detection system based on binocular vision
sensors is investigated in this article. The system is deployed on the low
power edge computing platform, which can upload the processing results to
the cloud through the Internet
disparity information and image
to enhance the detection robustness and accuracy in the industrial Internet
Things application scenarios. Considering the small training dataset, a
data labeling regularization and training strategy have also been proposed for
training this network. In addition, we employ multiframes feature matching and
measurement data filtering to enhance the measurement accuracy. The
ntelligence Internet-of-Things devices. The authors use binocular
image-based lightweight deep segmentation network
lowpower
s. Internet-of-
special
experimental results demonstrate that our monocular–binocular fusion
framework is robust and efficient.