INNOVATION IN AGRICUTURAL PRACTICES USING AI AND MACHINE LEARNING
DOI:
https://doi.org/10.53555/eijaer.v11i1.107Keywords:
AI in Agriculture, Machine Learning, Precision FarmingAbstract
food security, climate variability, and resource inefficiency. It emphasizes how artificial intelligence (AI) facilitates data-driven decision-making for effective and sustainable farming methods. The review explores at AI developments and uses, with particular attention to blockchain, IoT, and machine learning (ML). Precision farming, crop management, and post-harvest logistics are examined in relation to these technologies, with a focus on improving sustainability and resource efficiency. Artificial intelligence (AI) has shown great promise in transforming agricultural methods and providing answers to increase sustainability and output. Obstacles including high prices, a lack of technical know-how, and infrastructure deficiencies, especially for smallholder farmers, prevent its widespread implementation. The study highlights the need for AI solutions that are affordable, inclusive, and flexible in order to help smallholder farmers close the gap. It emphasizes how crucial ethical and regulatory frameworks are to guaranteeing fair access and scalability of AI technology in agriculture. This study suggests future directions for innovation while highlighting the innovative role of AI in handling global agriculture challenges. The report adds to the conversation on using AI to create a resilient and just agriculture sector by highlighting inclusion and sustainable growth.
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