Big data-driven agriculture: a novel framework for resource management and sustainability

As the global population grows, urbanization depletes water resources and significantly reduces cropland available for agriculture. This study proposes a Big Data Analytics-Integrated Agriculture Resource Management Framework (BDA-ARMF) to optimize resource utilization and enhance farm sustainability. The integration of BDA in agriculture offers substantial advantages, including improved management of consumer demand, enhanced farm operations, sustainable food production and better alignment of supply with demand. The framework combines BDA with the Internet of Things and cloud computing to improve accuracy, intelligence and sustainability in agriculture. Efficient data-driven farming requires actionable insights to minimize resource waste and environmental contamination. The proposed model outperforms previous approaches, delivering significant improvements in water management (97.8%), prediction accuracy (97.6%), production efficiency (96.4%), resource consumption reduction (11.5%) and risk assessment enhancement (94.7%). The proposed framework reduces resource waste and mitigates environmental impact, enabling sustainable agricultural systems and efficient, data-driven farming practices.