The increasing demand for intelligent and automated security solutions has accelerated the development of smart surveillance systems. This research presents an advanced Smart Intruder Detection System that integrates Internet of Things (IoT), edge computing, and artificial intelligence to enhance security monitoring and intrusion detection accuracy. The proposed system combines motion sensors, high-resolution camera modules, and embedded processors to continuously monitor protected environments in real time. When suspicious activity is detected, the system performs edge-level data processing and utilizes deep learning–based image analysis to verify potential intrusions and reduce false alarms. Upon confirmation, instant alerts are transmitted to users through cloud-based services, mobile applications, or automated alarms. The system also captures and stores visual evidence for future analysis and security auditing. Compared with conventional surveillance systems, the proposed approach offers improved detection accuracy, faster response time, enhanced scalability, and better energy efficiency. Experimental evaluation demonstrates that the system effectively identifies unauthorized access while minimizing false positives. This intelligent security framework provides a cost-effective and reliable solution for residential, commercial, and industrial environments, contributing to the advancement of next-generation smart security infrastructures

This research presents the design and implementation of a Smart Intruder Detection System that enhances security through automated monitoring, sensor-based detection, and real-time alert mechanisms. The proposed system integrates motion sensors, camera modules, and communication technologies to detect unauthorized access and notify users instantly. Experimental results demonstrate that the system provides reliable intrusion detection with minimal response time while reducing false alarms through visual verification. The use of cost-effective hardware components makes the system suitable for residential, commercial, and industrial applications. Overall, the proposed solution offers an efficient, scalable, and practical approach to improving modern security systems through intelligent monitoring and automation.

{{references}}

© 2025 International Journal of Engineering and Techniques (IJET).

Digital Object Identifier (DOI)

IJET assigns a unique DOI to every accepted article via Zenodo for persistent linking and citation. Your article’s DOI: https://doi.org/{{doi}}

Open DOI About Zenodo DOI

Close