Reconfigurable Intelligent Surfaces: A Hardware-Centric Review of Structures, Implementation, Evaluation, and Integration With UAV and Machine Learning

Reconfigurable Intelligent Surfaces (RIS) have emerged as a transformative hardware innovation to shape the wireless propagation environment in Beyond-5G and 6G systems. This review provides a structured and hardware-centric analysis of recent advances in RIS technology, focusing on four key aspects: physical structures, hardware implementation, performance evaluation, and integration with emerging technologies. First, we examine the diversity of RIS architectures, including reflectarrays, transmittarrays, multifunctional metasurfaces, active RIS prototypes, and simultaneous transmitting and reflecting RIS, highlighting their operational principles and fabrication challenges. Second, we explore system-level performance analysis through power consumption modeling, channel estimation techniques, and experimental validation methods essential for practical deployment. Third, we emphasize integration with the Unmanned Aerial Vehicle (UAV), which offers mobility and flexible coverage, and with Machine Learning, which enables intelligent adaptation and control. Finally, we discuss open challenges in hardware design, scalability, and energy management, while outlining promising directions including software-defined metasurfaces and space-time modulation. This review aims to serve as a foundational reference for researchers and engineers focused on hardware-oriented RIS development and its integration into next-generation intelligent wireless systems.