| Sumario: | Higher production costs, declining profitability, labor shortages, increasing wages, environmental degradation, and freshwater scarcity are major issues in agriculture. Agriculture 4.0, a data-driven transformation, addresses these issues through modern technologies like Internet of Things (IoT), artificial intelligence (AI), big data analytics, unmanned aerial vehicles (UAVs), and agricultural robots. It automates farm operations, enhances crop yield, food quality, safety, traceability, resource use efficiency, early issue detection, and minimises waste. By collecting and analyzing real-time data on soil, crop, and weather, Agriculture 4.0 enables tailored soil and crop management, reducing external inputs cost, mitigating labor constraints, protecting environment, increasing climate resilience, and promoting long-term sustainability while safeguarding natural resources. Despite its potential, the adoption of Agriculture 4.0 remains slow and uneven, particularly in developing nations and among smallholder farmers. This review examines the key barriers to adoption and proposes strategies for scaling implementation. Major obstacles include high initial investment costs, fragmented land holdings, diverse cropping systems, limited farmer awareness, lack of technical skills, inadequate digital literacy, complex AI algorithms, unreliable infrastructure, insufficient high-quality training data, poor internet connectivity, data privacy concerns, and a lack of supportive government policies. To overcome these challenges, a multi-faceted approach is necessary. This includes developing cost-effective sensors, user-friendly algorithms, and versatile machinery tailored for small-scale farms. Additionally, investments in rural infrastructure, public-private partnerships, farmer training programs, and policy interventions, such as subsidies, tax incentives, and regulatory frameworks are critical to ensuring equitable access and maximizing the benefits of Agriculture 4.0 for sustainable and inclusive agricultural growth.
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