<p>Sugarcane (<i>Saccharum officinarum</i> L.) is a vital cash crop and a cornerstone of rural economies in South Asia, yet its cultivation remains highly resource-intensive, with heavy demands for irrigation and nitrogen fertilizer. Conventional practices such as flood irrigation and blanket fertilizer application often result in poor water productivity, low nutrient-use efficiency, and significant environmental losses. Precision farming tools, particularly unmanned aerial vehicles (UAVs), provide opportunities to address these challenges by enabling site-specific monitoring and targeted input management. In this study, a dual-UAV workflow was developed for sugarcane cultivation under subtropical conditions in northern India. A lightweight sensing drone equipped with a multispectral camera was used to monitor canopy vigor through NDVI and NDRE vegetation indices at key growth stages. Stress maps generated from these indices were processed into management grids and translated into fertigation schedules, which were executed by a small-class UAV equipped with variable-rate spraying capability. Compared with conventional farmer practice, the sensor-guided treatments demonstrated substantial improvements in input-use efficiency and crop performance while lowering water and nitrogen requirements. The approach highlights the potential of UAV-based sensing-to-actuation pipelines as a scalable, low-cost strategy for tall-stature crops, indicating potential pathways to enhance climate resilience, farm profitability, and environmental sustainability under the conditions tested. Beyond sugarcane, the workflow provides a replicable template for precision nutrient and water management in other resource-intensive cropping systems.</p>