## 2 Literature Collection Methodology  
This review is grounded in the systematic collection of recent and high-quality literature to ensure its comprehensiveness and relevance to current trends in RFEH. A meticulous search was conducted across major scholarly databases, including IEEE Xplore, Elsevier (ScienceDirect), SpringerLink, MDPI, Wiley Online Library, Taylor & Francis, and ACM Digital Library. These platforms were selected for their broad coverage of peer-reviewed journal articles and conference proceedings in areas like electrical engineering, communication systems, energy harvesting, and embedded systems. To identify relevant studies, a combination of advanced Boolean search strategies and domain-specific keywords was employed. Search queries typically included phrases such as \"RF energy harvesting\", \"wireless power transfer\", \"retenna design\", \"ambient energy scavenging\", \"SWIPT\", \"AI-based energy optimization\", \"metamaterial antenna\", \"impedance matching\", and \"5G/6G energy harvesting.\" For example, a search query like \"RF energy harvesting and 6G and rectifier\" returned targeted results focused on recent innovations in rectenna circuits within next-generation wireless systems. Additional filtering ensured that only publica \begin{table}
\begin{tabular}{l l c c c c} \hline \hline \multirow{2}{*}{**Reference**} & \multirow{2}{*}{**Coverage of Applications**} & **Review** & **Focus on** & **Inclusion of** & **Comparative** & **Future Opportunities** \\  & & **Period** & **AI/ML** & **SWIPT** & **Technique Analysis** & **Discussed** \\ \hline
[8] & IoT sensors & 2015–2020 & No & No & Partial & Yes \\
[9] & Biomedical + IoT & 2016–2021 & Minimal & No & No & Yes \\
[10] & Biomedical + IoT & 2017–2021 & Yes & No & Yes \\
[11] & Smart cities + IoT & 2017–2021 & Yes & No & Partial & Yes \\
[12] & Biomedical + IoT & 2018–2021 & Yes & No & No & Yes \\ This work & Smart cities, biomedical, industrial, WSN, satellite & 2019–2025 & Yes & Yes & Yes & Yes \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Key differences between this review and the related literature. tions between 2019 and 2025 were retained for relevance and timeliness. The inclusion criteria required that articles be published in peer-reviewed journals or reputable conference proceedings and focus on technical developments, applications, challenges, or future opportunities in RFEH. Studies were included if they provided experimental, simulation-based, or validated theoretical results. Publications were excluded if they appeared before 2019, lacked technical depth, or offered purely speculative commentary without substantial analysis or modelling. In total, 167 articles were initially gathered. After removing duplicates, screening abstracts, and conducting full-text evaluations, 132 articles were selected for final inclusion. They covered the use of RFEH in diverse domains such as smart cities, biomedical devices, industrial IoT, satellite communication, and AI-integrated systems. The distribution of selected publications across the years is shown in Figure 1, which illustrates that steady growth is evident from 2021, with 2024 marking the highest publication volume, indicative of maturing interest and investment in RF energy-harvesting technologies. The data shows a clear trajectory of increasing innovation and scholarly focus in this domain. To further enhance this review's analytical depth, the 132 selected articles were categorized based on the primary RF energy-harvesting techniques or themes they addressed. These include single-band and multi-band rectenna designs, SWIPT-enabled architectures, AI/ML-assisted energy optimization, and hybrid energy-harvesting systems. Table 2 summarizes the number of publications per category. Figure 1: Distribution of selected publications on RF energy harvesting. The analysis shows that improving rectenna designs is still the focus of most studies. However, more recent research is starting to explore the use of AI and combinations of RF with other energy sources.