This review provides a comprehensive discussion on AI-driven smart farming and its role in achieving climate-smart and sustainable agriculture. While the paper effectively highlights key technologies like IoT, machine learning, remote sensing, and variable-rate technology (VRT), several areas require further clarification.
1. The review extensively discusses AI applications but lacks empirical validation. Have real-world case studies or long-term field trials been analyzed to verify the effectiveness of these AI-driven approaches in various agricultural systems? Without practical evidence, the proposed benefits remain largely theoretical.
2. The paper mentions cost barriers and technical limitations, but a deeper discussion on data ownership, digital divide among farmers, and AI model interpretability is missing. How do smallholder farmers, who often lack the infrastructure for AI-based solutions, benefit from these advancements?!!
3. The review promotes AI as a solution for resource optimization, but it does not critically discuss the environmental impact of AI deployment, such as energy consumption from AI models and the carbon footprint of IoT devices. If I were I prefer to address the sustainability of AI infrastructure itself in agriculture.
4. While smart farming is emphasized, the study does not include a quantitative comparison between AI-based methods and traditional farming techniques in terms of cost-effectiveness, yield improvements, and long-term sustainability. A meta-analysis or comparative discussion could strengthen the argument.
5. The study briefly acknowledges the need for supportive policies, but does not analyze existing legislative or data protection measures surrounding AI adoption in agriculture. But, it is not clearly mentioned what role do governments and global organizations play in standardizing AI-based smart farming practices.