Green cloud computing architectures and technologies for smart and sustainable agriculture: A systematic literature review, taxonomy, and research agenda (2020–2025)

Abstract

Cloud computing provides scalable computing resources, flexible data storage, and data-analysis capabilities for processing heterogeneous data generated by Internet of Things (IoT) sensors, unmanned aerial vehicles, and digital farming platforms in smart agriculture. Within the 2020–2025 evidence corpus, cloud-only and hybrid cloud–edge/fog architectures coexist with AI-based decision-making, irrigation, crop-monitoring, and other digital-agriculture applications; however, their computational performance improvements do not necessarily constitute evidence of environmental sustainability. This paper presents a systematic literature review (SLR) of cloud-based solutions for smart agriculture covering the period 2020 – 2025. Following a structured and reproducible review process based on the PRISMA 2020 framework, the selected studies were analyzed and classified using a new taxonomy that integrates cloud service and deployment models, agricultural application domains, enabling technologies, and sustainability dimensions. Based on 47 selected studies, the analysis highlights ongoing issues related to interoperability, energy-efficient resource management, security and privacy, socio-economic impact assessment, and the still-developing state of digital twin–based agricultural systems. Computing/data efficiency was the most frequently coded sustainability-related dimension (30/47 studies; 63.8%), whereas explicit energy/resource efficiency was reported in 13/47 studies (27.7%) and water/resource efficiency in 5/47 studies (10.6%). These findings indicate that explicit evidence of Green Cloud environmental benefits remains more limited than evidence of computational or data-processing efficiency. Based on the identified gaps, this review proposes a research agenda highlighting critical directions for enhancing scalability, energy efficiency, and sustainability in cloud-enabled agricultural systems. The findings provide practical guidance for researchers and practitioners aiming to design robust, energy-efficient, and sustainable cloud-based solutions for smart agriculture.