  Border security had been a persistent problem in international border
especially when it get to the issue of preventing illegal movement of weapons,
contraband, drugs, and combating issue of illegal or undocumented immigrant
while at the same time ensuring that lawful trade, economic prosperity coupled
with national sovereignty across the border is maintained. In this research
work, we used open source computer vision (Open CV) and adaboost algorithm to
develop a model which can detect a moving object a far off, classify it,
automatically snap full image and face of the individual separately, and then
run a background check on them against worldwide databases while making a
prediction about an individual being a potential threat, intending immigrant,
potential terrorists or extremist and then raise sound alarm. Our model can be
deployed on any camera device and be mounted at any international border. There
are two stages involved, we first developed a model based on open CV computer
vision algorithm, with the ability to detect human movement from afar, it will
automatically snap both the face and the full image of the person separately,
and the second stage is the automatic triggering of background check against
the moving object. This ensures it check the moving object against several
databases worldwide and is able to determine the admissibility of the person
afar off. If the individual is inadmissible, it will automatically alert the
border officials with the image of the person and other details, and if the
bypass the border officials, the system is able to detect and alert the
authority with his images and other details. All these operations will be done
afar off by the AI powered camera before the individual reach the border
