Key points are not available for this paper at this time.
Abstract The Internet of Things has evolved in our smart environment, smart devices can function without human involvement. As a result, homes can be converted into intelligent home automation systems that execute computations automatically. This paper mainly focuses on exploring and designing a state-of-the-art Smart Security System by implementing the latest machine learning algorithms and IoT devices. The research highlights the integration of piezo sensors for precisely detecting pressure changes within the household and using a variety of Arduino boards to transmit this signal to a control system. The paper also examines how to trigger cameras equipped with image recognition technology to identify unfamiliar faces or suspicious behaviours, along with motion-based multiple object tracking and face identification when pressure changes are detected. Additionally, the paper discusses future developments, such as deep-learning-based object recognition and enhanced encryption methods, to uphold accuracy, privacy, and security.
Nandi et al. (Wed,) studied this question.