SemAI: Semantic Artificial Intelligence-Enhanced DNA Storage for Internet of Things

In the wake of the swift evolution of technologies, such as the Internet of Things (IoT), the global data landscape is undergoing an exponential surge, propelling DNA storage into the spotlight as a prospective medium for contemporary cloud storage applications. This article introduces a semantic artificial intelligence-enhanced DNA storage (SemAI-DNA) paradigm, distinguishing itself from prevalent deep learning (DL)-based methodologies through two key modifications: 1) embedding a semantic extraction module at the encoding terminus, facilitating the meticulous encoding and storage of nuanced semantic information and 2) conceiving a forethoughtful multireads filtering model at the decoding terminus, leveraging the inherent multicopy propensity of DNA molecules to bolster the system fault tolerance, coupled with a strategically optimized decoder's architectural framework. Numerical results demonstrate the SemAI-DNA's efficacy, attaining 2.61 dB peak signal-to-noise ratio (PSNR) gain and 0.13 improvement in structural similarity index (SSIM) over conventional DL-based approaches.