<![CDATA[The urgency of this research is to increase efficiency, transparency and sustainability in increasingly complex and challenging agribusiness supply chains. The aim of this research is to develop an integrated system that combines IoT capabilities in collecting agricultural data in real-time, AI to analyze data and provide recommendations for action, as well as security and transparency guaranteed by blockchain technology. The method used is a mixed methods approach , this approach combines qualitative and quantitative elements to obtain a deeper understanding. A qualitative approach is used to gain a contextual perspective, while a quantitative approach is used to measure performance empirically. This research uses a case study design on a sensor-based agricultural monitoring system because of its ability to provide in-depth and holistic insights. The research population consists of users and stakeholders in sensor-based agricultural monitoring systems. The sample was selected purposively to cover various aspects of the supply chain. Data was collected through in-depth interviews, direct observation, surveys of system users and collection of sensor and transaction data from agricultural monitoring systems. The research results show that the integration of IoT, AI, and blockchain significantly improves operational efficiency in agribusiness supply chains. Implementation of this integrated system resulted in an increase in productivity of up to 22%, a reduction in pesticide use by 35%, an increase in water use efficiency by 30%, and a reduction in operational costs by 18%. Statistical analysis confirmed a strong positive correlation between the use of integrated technology and increased operational efficiency (R=0.85, p<0.01).]]>
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