TV broadcasts, Wi-Fi, and cellular base stations and converting them into usable DC power through RF-to-DC conversion [2]. The core components of an RFEH system include a receiving antenna that captures ambient RF signals, a matching network that optimizes power transfer efficiency, a rectifier circuit (rectenna) that converts RF signals into DC voltage, and an energy storage unit that stores harvested energy for later use. Recent advancements in rectenna design, impedance matching techniques, and high-efficiency rectifiers have significantly improved energy-harvesting efficiency [3]. However, challenges such as low power density, signal attenuation, and varying RF energy levels hinder widespread deployment. Furthermore, this review is motivated by the growing need for a consolidated and up-to-date analysis of RFEH developments across communication technologies, particularly considering emerging 6G requirements. Several studies have explored different approaches to enhancing RFEH performance. Researchers have developed multi-band rectennas that operate at multiple frequency bands to increase the amount of energy harvested. [PERSON] et al. [4] proposed a dual-band rectenna for 0.9 GHz and 1.8 GHz Wi-Fi signals, achieving over 70% RF-to-DC conversion efficiency. Recent studies have integrated metamaterials to enhance energy-harvesting efficiency. [PERSON] et al. [5] introduced a metamaterial-based rectenna that significantly improved power conversion by focusing and amplifying incoming RF signals. The integration of simultaneous wireless information and power transfer (SWIPT) enables wireless networks to transmit both power and information. [PERSON] et al. [6] investigated SWIPT-enabled 5G networks, where base stations simultaneously transfer RF energy and data to IoT devices. Machine learning (ML) models have also been applied to optimize energy harvesting by predicting RF energy availability in dynamic environments. [PERSON] et al. [7] designed an AI-based energy optimization framework for self-sustaining IoT networks, increasing overall energy efficiency. While these advancements have improved RF energy harvesting, several research gaps remain. Scalability remains a major concern, particularly in integrating RFEH into large-scale 5G and 6G infrastructures. Interference management poses another challenge in maximizing harvested RF energy without affecting primary communication signals. Energy storage efficiency remains a critical area in need of improvement, with researchers exploring new materials for ultra-low-power energy storage in RFEH systems. The purpose of this paper is to provide a thorough synthesis of recent innovations in RFEH techniques and architectures. Its objectives include presenting the underlying principles and configurations of modern RFEH systems, analyzing the latest applications across sectors, identifying prevailing challenges and research gaps, and proposing forward-looking research opportunities. The key contributions include a detailed analysis of existing RFEH techniques, including rectenna designs, impedance matching networks, and power management circuits; a review of recent developments in RFEH for IoT, smart cities, and biomedical applications; the identification of current challenges and research gaps in RF energy harvesting; and an exploration of future opportunities, including machine learning-based energy optimization and the role of 6G networks in wireless power transfer. Unlike prior review articles that focus either exclusively on rectifier design or system architecture, this paper uniquely integrates recent developments in AI-driven optimization and SWIPT techniques with practical implementation considerations, offering a broader and more application-oriented perspective. Table 1 summarizes the key differences between this review and the related literature. The scope of this review is limited to scholarly publications and technologies developed between 2019 and 2025, ensuring relevance and timeliness.