Efficient Image Synchronization and Change Detection Using XOR-Based PATCH Algorithms in Digital Twin Technology

This paper proposes an efficient XOR-based PATCH algorithm for real-time image synchronization and change detection in Digital Twin Technology. The primary objective is to minimize computational overhead, memory usage, and bandwidth by transmitting only pixel-level changes (PATCH) between physical and digital twins rather than entire image datasets. The proposed algorithm demonstrates versatility by effectively handling black and white, greyscale, and coloured images. Extensions of the algorithm for grey scale and coloured images involve applying XOR operations across intensity levels and RGB channels, respectively, ensuring minimal storage requirements while maintaining synchronization accuracy. Experimental results show that the algorithm scales linearly with image size, significantly improving bandwidth and memory efficiency, particularly in high-resolution images with sparse changes. The scalability and adaptability of the XOR-based PATCH algorithm make it highly suitable for real-time applications in resource-constrained environments, such as IoT-based remote monitoring systems.