Artificial intelligence - The promise for an agricultural revolution in new era

Reshma J. Murugan, B. N. Bindhya, G. Sreedaya
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Abstract

Agriculture is slowly becoming digital. The adoption of Artificial Intelligence (AI) and Machine Learning (ML) both in terms of agricultural products and in-field farming techniques are increasing. Artificial Intelligence in agriculture is emerging in three major areas, namely agricultural robotics, soil and crop monitoring and predictive analytics. The use of sensors and soil sampling techniques are increasing day by day which helps in gathering of data. In turn, this data is stored in farm management system which is better processed and analysed. Thus, the data available along with other related data paves a way to successfully deploy AI in agriculture. AI in agriculture is emergingin cognitive computing and it has all the scope to become the most disruptive technology in agriculture services as it is able to understand, learn and respond to different situations (based on learning) to increase efficiency. The areas where the use of cognitive solutions can benefit agriculture are growth driven by IOT, image-based insight generation, identification of optimal mix for agronomic products, health monitoring of crops and automation techniques in irrigation and enabling farmers. In addition, the drone based solutions have significant impact in terms of productivity gains, coping with adverse weather conditions, yield management and precision farming.The emergence of new age technologies like Artificial Intelligence (AI), Cloud Machine Learning, Satellite Imagery and advanced analytics are creating an ecosystem for smart farming. Fusion of all this technology is enabling farmers achieve higher average yield and better price control.
人工智能——新时代农业革命的希望
农业正在慢慢走向数字化。人工智能(AI)和机器学习(ML)在农产品和田间耕作技术方面的应用正在增加。农业领域的人工智能正在三个主要领域出现,即农业机器人、土壤和作物监测以及预测分析。传感器和土壤取样技术的使用日益增加,这有助于收集数据。反过来,这些数据被存储在农场管理系统中,以便更好地处理和分析。因此,可用的数据以及其他相关数据为在农业中成功部署人工智能铺平了道路。农业领域的人工智能正在认知计算领域兴起,它有可能成为农业服务领域最具颠覆性的技术,因为它能够理解、学习和应对不同的情况(基于学习),以提高效率。使用认知解决方案可以使农业受益的领域包括物联网驱动的增长、基于图像的洞察生成、农用产品的最佳组合识别、作物健康监测和灌溉自动化技术以及农民。此外,基于无人机的解决方案在提高生产力、应对恶劣天气条件、产量管理和精准农业方面具有重大影响。人工智能(AI)、云机器学习、卫星图像和高级分析等新时代技术的出现正在为智能农业创造一个生态系统。所有这些技术的融合使农民能够实现更高的平均产量和更好的价格控制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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