Authors :
Aparna U; Athira B; Anuja M V; Aswathy Ramakrishnan; Divya R
Volume/Issue :
Volume 5 - 2020, Issue 8 - August
Google Scholar :
http://bitly.ws/9nMw
Scribd :
https://bit.ly/3lqcOi9
DOI :
10.38124/IJISRT20AUG459
Abstract :
Collapse of man-made structures, such as
buildings and bridges earth quakes and fire accident,
occur with varying frequency across the world. In such a
scenario, the survived human beings are likely to get
trapped in the cavities created by collapsed building
material. During post disaster rescue operations, searchand-rescue crews have a very limited or no knowledge of
the presence, location, and number of the trapped
victims. Deep learning is a fast-growing domain of
machine learning, mainly for solving problems in
computer vision. One of the implementation of deep
learning is detection of objects including humans, based
on video stream. Thus, the presence of a human buried
under earthquake rubble or hidden behind barriers can
be identified using deep learning. This is done with the
help of USB camera which can be inserted into the
rubble. Spotter also gives an audio message about the
location of the human presence and gives the area where
the human is likely to be present. Human detection is
done with the help of Computer Vision using OpenCV.
Keywords :
USB, CV, rubble, OpenCV
Collapse of man-made structures, such as
buildings and bridges earth quakes and fire accident,
occur with varying frequency across the world. In such a
scenario, the survived human beings are likely to get
trapped in the cavities created by collapsed building
material. During post disaster rescue operations, searchand-rescue crews have a very limited or no knowledge of
the presence, location, and number of the trapped
victims. Deep learning is a fast-growing domain of
machine learning, mainly for solving problems in
computer vision. One of the implementation of deep
learning is detection of objects including humans, based
on video stream. Thus, the presence of a human buried
under earthquake rubble or hidden behind barriers can
be identified using deep learning. This is done with the
help of USB camera which can be inserted into the
rubble. Spotter also gives an audio message about the
location of the human presence and gives the area where
the human is likely to be present. Human detection is
done with the help of Computer Vision using OpenCV.
Keywords :
USB, CV, rubble, OpenCV
