Abstract:

This study presented a cost- optimised smart wireless surveillance system based on Internet of Things (IoT) technology for real-time monitoring and motion detection using the ESP32-CAM module. Conventional surveillance systems are constrained by wired infrastructure, high installation costs, and limited remote accessibility, which restrict their deployment in dynamic and resource-constrained environments. To address these limitations, the proposed system integrates an ESP32-CAM module with a passive infrared (PIR) motion sensor and built-in Wi-Fi communication to enable automated monitoring and real-time data transmission. The system adopts a layered IoT architecture comprising sensing, processing, network, and application layers. The sensing layer captures visual and motion data, while the processing layer, implemented within the ESP32-CAM, performs data handling and event triggering. The network layer facilitates wireless communication for live video streaming and alert delivery, and the application layer provides user access through web-based and mobile interfaces. The system was developed using the Arduino Integrated Development Environment and implemented as a functional prototype. Experimental evaluation demonstrated that the system achieved real-time video streaming with a response time of 1.3 seconds, motion detection accuracy of 91%, and low power consumption of 0.85 W. These results indicate reliable performance and suitability for deployment in residential and small-scale commercial environments. The findings confirm that IoT-based surveillance systems provide a scalable, energy-efficient, and cost-effective alternative to traditional security solutions. Future work will focus on integrating artificial intelligence for intelligent detection, implementing robust security mechanisms, and incorporating cloud-based analytics to enhance system performance and scalability.