Artificial intelligence-driven solar smart irrigation for sustainable agriculture: Trends, challenges, and SDG implications – A systematic review
Nurmalitasari Nurmalitasari, Nurchim Nurchim, Retna Dewi Lestari
Abstract
The convergence of artificial intelligence (AI) with solar-powered smart irrigation offers a transformative solution to global agricultural challenges, enabling improved water management, higher crop productivity, and enhanced climate resilience. This study presents a systematic literature review (SLR) of 29 peer-reviewed articles published between 2016 and 2025, following the PRISMA 2020 framework. The review examines the technological innovations, resource-use efficiency outcomes, implementation barriers, and sustainability impacts of AI-driven, solar-powered smart irrigation systems. Eight key technological clusters are identified, including IoT-based environmental sensing, machine learning algorithms, solar photovoltaic (PV) pumping systems, real-time monitoring, and cloud–satellite integration—together forming a foundation for precision irrigation. The findings highlight water-use efficiency improvements of up to 70%, crop yield increases of 15–40%, and significant reductions in energy consumption and greenhouse gas emissions. These advancements directly contribute to several Sustainable Development Goals: especially SDG 2 (Zero Hunger) through improved food production, SDG 6 (Clean Water and Sanitation) via efficient water use, SDG 7 (Affordable and Clean Energy) by utilizing renewable solar energy, and SDG 13 (Climate Action) by mitigating carbon emissions. Despite these benefits, major challenges persist in real-world adoption, particularly in developing regions—such as inadequate infrastructure, high initial costs, and limited digital literacy. To address these challenges, the review proposes a future roadmap emphasizing modular and open system architectures that integrate predictive analytics, soil–climate modeling, and renewable energy optimization. Such AI-powered irrigation systems must be adaptive, scalable, and inclusive to support climate-resilient and sustainable agriculture. The insights from this review are crucial for guiding future research, informing policy, and accelerating the development of smart irrigation technologies aligned with global sustainability goals.