<![CDATA[Wetland agriculture is vital for global food security but faces unique challenges that hinder conventional mechanization. This study employs a systematic literature review and bibliometric analysis to map the research landscape of autonomous agricultural machinery (ALSINTAN) for wetlands. Following the PRISMA protocol, 195 documents were initially identified, from which 55 relevant articles were analyzed from 2015–2025. Results identified five key research clusters: IoT and real-time monitoring, robotic and autonomous vehicles, artificial intelligence, digital twins, and economics and sustainability, with an annual publication growth of 18.7%. A critical finding reveals that only 22% of autonomous ALSINTAN research specifically addresses wetland contexts, indicating a significant bias toward dryland applications. Major gaps include unreliable sensor and algorithm performance under extreme wetland conditions and a lack of socio-economic adoption studies. The study concludes that a more balanced approach, integrating advanced technical innovation with in-depth socio-economic research, is urgently needed. This is conceptualized in the proposed Wetland-Specific Autonomous Farming System (WSAFS) framework to develop resilient and inclusive autonomous farming systems for wetlands.]]>
Copyrights © 2026
