Design and Development of Intrusion Detection System Using Two point Setup

This study focuses on the design and development of an intrusion detection system (IDS) using a two-point setup for enhanced surveillance. To overcome the limitations of traditional IDS, the current paper proposes to exploit such modern technologies as NVIDIA Jetson Nano platform as well as deep learning algorithms. The two cameras are equipped with technology for controlling access and keeping track of people in a place. The door opens automatically to allow authorized individuals inside if their face is recognized. Safety mechanisms may also be incorporated to identify possible harm inflicted on the door to maintain usability and safety of the user. The research explores the intricacies of integrating advanced object detection and facial recognition techniques within this framework to achieve real-time monitoring and accurate threat identification. Consideration is given to how effective and flexible the system is, especially in terms of detecting intrusions from different angles and optimize facial recognition across diverse viewpoints. By combining technological innovation with ethical principles, this study contributes to the advancement of intrusion detection systems, paving the way for more effective and ethically sound security solutions in diverse environments.