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E-MOBILIWTYO: ME-ETNRAINCTOERCSH
expected to contribute significantly. Weed control is difficult, labour intensive, and, if not efficiently implemented, contributes to the use of more water and depletion of soil nutrients. Crop rotation is a partial solution but cannot eliminate the need for herbicides or manual weed control. Weed management robots that combine machine vision with AI and ML are being tested. These small machines also minimise soil compaction. Farm OS and fleets of autonomous equipment The agriculture industry is looking toward a future where fully autonomous farms will be controlled by a sophisticated operating system (OS) capable of managing mixed fleets, including both autonomous and standard farm equipment, plus land-based machines and drones, to maximise productivity and sustainability (Figure 5). Those fleets will be operated in coordination to help control capital expenses, minimise labour needs, and provide the big data necessary to enable autonomous execution and precision agriculture. In addition, the farm OS of the future will be standardised and optimised to support a diverse range of equipment from numerous suppliers. Adopting the ISObus is only the first step toward an open-source and standardised approach to
farm automation.
Additional benefits expected from the proposed farm OS are reduced CO2 emissions, lower fuel consumption, and optimisation of battery charging and management. Big data analytics will also play an important role in the future of agriculture. Large amounts of real-time data directly from the field will be used to continuously train the AI and ML algorithms required for decision-making, control, and operational planning to optimise precision agriculture. Summary It’s still in the early days for the development of autonomous farm vehicles and sustainable precision agriculture. The industry has started down the path with ISObus. The next generation of ISObus will support increased interoperability and help lead to more complex and interconnected fleets of farm equipment. The goal is the development of a farm OS that can take those fleets of farm equipment, combine them with massive real-time sensor data using AI and ML algorithms and deploy them as formations of coordinated ground and flying machines producing high levels of sustainability and productivity.
Figure 5. Swarms of coordinated ground and flying autono- mous agricultural machines will lead to higher levels of sustainability. (Image source: Illustration by Scharfsinn86 via Getty Images)
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