The applications of nature‐inspired algorithms in Internet of Things‐based healthcare service: A systematic literature review

作者：Zahra Mohtasham‐Amiri, Arash Heidari, Mohammad Zavvar, Nima Jafari Navimipour, Mansour Esmaeilpour · 发表于：Transactions on Emerging Telecommunications Technologies · 年份：2024 · DOI：10.1002/ett.4969 · 被引用次数：103 · 研究领域：Advanced Technologies in Various Fields、IoT and Edge/Fog Computing、Internet of Things and AI

Abstract Nature‐inspired algorithms revolve around the intersection of nature‐inspired algorithms and the IoT within the healthcare domain. This domain addresses the emerging trends and potential synergies between nature‐inspired computational approaches and IoT technologies for advancing healthcare services. Our research aims to fill gaps in addressing algorithmic integration challenges, real‐world implementation issues, and the efficacy of nature‐inspired algorithms in IoT‐based healthcare. We provide insights into the practical aspects and limitations of such applications through a systematic literature review. Specifically, we address the need for a comprehensive understanding of the applications of nature‐inspired algorithms in IoT‐based healthcare, identifying gaps such as the lack of standardized evaluation metrics and studies on integration challenges and security considerations. By bridging these gaps, our paper offers insights and directions for future research in this domain, exploring the diverse landscape of nature‐inspired algorithms in healthcare. Our chosen methodology is a Systematic Literature Review (SLR) to investigate related papers rigorously. Categorizing these algorithms into groups such as genetic algorithms, particle swarm optimization, cuckoo algorithms, ant colony optimization, other approaches, and hybrid methods, we employ meticulous classification based on critical criteria. MATLAB emerges as the predominant programming language, constituting 37...