Quantum-Enhanced AI Robotics for Sustainable Agriculture: Pioneering Autonomous Systems in Precision Farming

Quantum computing, artificial intelligence (AI), and robots are all coming together to make sustainable agriculture possible by making it possible to build advanced self-driving systems for precision farming. This paper looks at how quantum-enhanced AI might be able to make farming much more productive, use resources more efficiently, and protect the environment. In traditional farming, old techniques are often still used, which can waste resources and hurt the environment. By combining quantum computing with AI and robotics, we can use the power of quantum algorithms to process huge amounts of agricultural data faster than with traditional systems. This makes it possible to create smart decision-making tools that increase crop yields while lowering costs and damage to the environment. Quantum computing has unmatched computer power, which makes it possible to analyze large files from a variety of sources, such as earth monitors, weather forecasts, and satellite images. Because of this feature, complex prediction models can be made that can accurately predict how crops will do in different situations. The paper study used suggested model along with AI to handle important farming jobs like planting, watering, and gathering by using robots with advanced sensors and machine learning algorithms. With the use of self-driving robots in farming not only makes operations more efficient, but it also cuts down on the need for physical labor, which helps the agricultural sector deal with its lack of workers.