Experimental study enhances CCTV systems through smart camera features, indicating vast potential for automation.
This article endeavors to improve surveillance systems, especially CCTV systems, by transforming standard cameras into smart cameras with advanced features. It is divided into three phases: the first phase expands the knowledge about CCTV systems and their applications; the second provides a reference for the development of home automation systems; and the third provides a camera tracking system (CSS) using Java libraries (OpenCV, JavaCV, and JavaFX). Java was chosen for its platform independence, multi-channel support, powerful image processing capabilities, and modern user interface capabilities of JavaFX. The system includes features such as face detection, motion detection, zooming, and video recording for an additional fee. The article also explores the potential of smart cameras to detect human behaviour within an artificial intelligence framework autonomously.
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Kesavan et al. (2026) studied this question.
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