This paper proposes the development of a smart security system that utilizes microwave and piezoelectric sensors to detect unauthorized entry into a restricted area. The sensor data is sent to the cloud platform, which triggers the activation of a camera to capture the face of the intruder. The system is designed to be cost-effective, easy to install, and highly accurate in detecting unauthorized access. The system uses the Internet of Things (IoT) technology to connect the sensors to the cloud platform, where machine learning algorithms are used to analyses the sensor data and trigger the camera activation. The proposed system has significant potential for use in various applications, such as home security, industrial security, and public safety. The project aims to provide a reliable, scalable, and affordable solution for securing restricted areas. The system's performance is evaluated using various metrics, including accuracy, precision, and false positive rate. The results demonstrate that the proposed system is highly effective in detecting unauthorized access and can be easily integrated with existing security systems. The proposed smart security system offers an innovative solution for addressing security challenges and has significant potential for future research and development.