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

翻译：边境安全一直是国际边界的持续性问题，特别是在防止武器、违禁品、毒品非法流动以及打击非法或无证移民问题方面，同时又要确保合法贸易、经济繁荣以及国家主权在边境得到维护。在本研究工作中，我们利用开源计算机视觉（Open CV）和AdaBoost算法开发了一个模型，该模型能够远距离检测移动物体、对其进行分类、自动分别捕捉个体的全身图像和面部图像，然后对个体进行针对全球数据库的背景核查，同时预测该个体是否为潜在威胁、有意移民者、潜在恐怖分子或极端分子，并发出声音警报。我们的模型可以部署在任何摄像设备上，并安装在任何国际边境。模型涉及两个阶段：首先，我们基于Open CV计算机视觉算法开发了一个模型，能够远距离检测人类活动，自动分别捕捉个体的面部和全身图像；第二阶段是自动触发对移动物体的背景核查。这确保模型能针对移动物体在全球多个数据库中进行核查，并远距离判断该个体的可入境性。如果个体不可入境，系统会自动向边境官员发出警报，提供该个体的图像和其他详细信息；如果个体绕过边境官员，系统能够检测到并向当局发出警报，提供其图像和其他详细信息。所有这些操作都在个体到达边境之前由人工智能驱动的摄像头远距离完成。