The private network project reports 20–30% yield improvement and up to 25% resource savings. Could you share what operational changes on farms made these results possible?
Speaker: Bhaskara
One of the biggest challenges farmers face, especially those managing large-scale operations of 1,500 to 2,000 acres, is efficiently moving equipment and optimizing timing for critical activities like yield cutting, spraying, and processing. These logistics directly affect productivity and costs.
Through our enterprise private network, we are enabling farmers to create digital twins of their operations. This allows them to visualize and plan field activities more precisely. They can identify optimal time windows for spraying and harvesting based on real-time data, environmental conditions, and predictive analytics.
A key operational shift has been the transition from reactive to proactive crop management. Traditionally, farmers would respond to problems after they occurred—such as disease, weather damage, or nutrient deficiency. With continuous monitoring and real-time data from IoT sensors and AI analytics, they can now anticipate and prevent issues before they escalate. This proactive approach has been central to improving yields by 20–30%.
Additionally, better management of machinery and logistics has led to significant cost savings. By optimizing equipment usage—ensuring tractors, sprayers, and harvesters are deployed efficiently—farmers have reduced both fuel consumption and wear on machinery. Overall, these changes not only enhance productivity but also reduce operational expenses, contributing to up to 25% resource savings.
