Human Intruder Detection System (IDS) for Restricted Security Area: A Systematic Literature Review

  • Yadhurani Dewi Amritha Universitas Pendidikan Nasional, Denpasar, Indonesia
  • I Made Yogaswara Dipta Otoritas Bandar Udara Wilayah IV, Badung, Indonesia
Keywords: Human Intruder Detection System, Internet of Things, Neural Network, SLR

Abstract

Ensuring security in sensitive areas such as airports, military bases, and nuclear facilities is critical to prevent unauthorized access. Traditional reliance on security personnel is often inefficient and insufficient for continuous monitoring. Intruder Detection Systems (IDS), which utilize devices or sensors to detect unauthorized entry, have emerged as essential tools for safeguarding high-security environments. However, there is a lack of comprehensive understanding that systematically synthesizes existing research on human intruder detection. This study aims to conduct a systematic literature review (SLR) on human IDS to provide a structured overview of current methodologies, technologies, and challenges in the field. Using established SLR protocols, relevant studies were collected, analyzed, and categorized to identify prevailing trends and gaps. The results highlight various object detection techniques and their effectiveness in real-world security applications. Despite the advances, challenges such as limited environmental adaptability and real-time accuracy remain. The findings of this review offer valuable insights for professionals and future researchers, guiding the development of more robust and efficient human intruder detection solutions.

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How to Cite
Amritha, Y. D., & Dipta, I. M. Y. (2025). Human Intruder Detection System (IDS) for Restricted Security Area: A Systematic Literature Review. International Journal of Engineering Technology and Natural Sciences, 7(2), 116-126. https://doi.org/10.46923/ijets.v7i2.457