  Assistive technology for visually impaired individuals is extremely useful to
make them independent of another human being in performing day-to-day chores
and instill confidence in them. One of the important aspects of assistive
technology is outdoor navigation for visually impaired people. While there
exist several techniques for outdoor navigation in the literature, they are
mainly limited to obstacle detection. However, navigating a visually impaired
person through the sidewalk (while the person is walking outside) is important
too. Moreover, the assistive technology should ensure low-energy operation to
extend the battery life of the device. Therefore, in this work, we propose an
end-to-end technology deployed on an edge device to assist visually impaired
people. Specifically, we propose a novel pruning technique for transformer
algorithm which detects sidewalk. The pruning technique ensures low latency of
execution and low energy consumption when the pruned transformer algorithm is
deployed on the edge device. Extensive experimental evaluation shows that our
proposed technology provides up to 32.49% improvement in accuracy and 1.4 hours
of extension in battery life with respect to a baseline technique.
