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DIGITAL TECHNOLOGY
formance. Similarly, by coupling AI technologies with data streams from advanced sensors, these sys- tems can support yield forecasting, harvest date prediction, and con- tinuous data collection—fueling a new era of data-driven, intelligent agriculture. Ultimately, these added capabilities redefine the value proposition of autonomous machinery. They are not sim- ply tools for automating single tasks; they are strategic plat- forms for transformation—inte- grating operations, intelligence, and adaptability. When viewed through this lens, their initial cost is not an obstacle but an investment in a smarter, more resilient, and more sustainable agricultural future.
monitoring performance, de- tecting faults, and responding in real time. Autonomous machines, however, must embed this intelli- gence through advanced sensing and monitoring systems capable of detecting, for example, chan- ges in tire pressure, system mal- functions, or structural failures. This shift from operator-depend- ent reliability to system-embed- ded intelligence represents a profound transformation in agri- cultural practice. To unlock the full promise of autonomy, the launch process itself must be reimagined. Au- tonomous operations should not require extensive prepara- tion or specialized skill. Instead, next-generation software must offer farm-specific, adaptive solutions that make initiating complex operations as simple as pressing a button. This ease of use will be critical to building confidence and driving adoption among farmers. Beyond their core functions, autonomous machines provide an unparalleled platform for cre- ating additional value. Their in- tegrated sensors and actuators can host specialized payloads to perform multiple tasks simultan- eously—including those outside traditional agriculture—thereby amplifying their eco nomic impact. For example, in agri-voltaic systems where farmland is shared with solar infrastructure, an autonomous platform can mow vegetation while monitoring solar panel per-
spot-spraying machine designed to control weeds. To be truly au- tonomous, the machine must not only perform the spraying itself but also leave its shed, navigate farm roads to the target field, initiate and complete the spraying operation, and return to its parked position—all with- out human intervention. When this entire operational sequence is examined, several practical challenges emerge. Many machines can now suc- cessfully navigate from the shed to the field, avoid obstacles such as animals and vehicles, and re- turn once the task is complete. Yet, they are not designed to handle seemingly simple but critical interactions—such as opening gates or traversing trenches dug for new irrigation lines. These gaps highlight an important insight: autonomy is not achieved by the machine alone, but through a symbiosis between technology and the environment. By reshaping the physical farm environment—re- moving clutter, standardizing layouts, and introducing struc- tured pathways—farmers can dramatically increase the reli- ability, efficiency, and uptime of autonomous systems. Every autonomous agricultural machine is built on three essen- tial pillars: software, electrical/ electronic systems, and mech- anical hardware. In conventional machinery, a human operator acts as the intelligent interface—
Associate Professor Jayantha Katupitiya is from the School of Mechanical and Manufacturing Engineering at the University of NSW.
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