Computer Science And Technology - Research Publications

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Author: search.filters.author.Kaur, AmandeepSubject: search.filters.subject.Artificial intelligence

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    A systematic review of artificial intelligence in agriculture
    (Elsevier, 2022-01-15T00:00:00) Singh, Parvinder; Kaur, Amandeep
    The current world population is 7.8 billion and is projected to reach 9.8 billion by 2050. The limited land area and strong need to produce more crop to feed the ever-increasing population is a major challenge today, especially for developing countries. The strong need to produce more crop from lesser land has led to several challenges in the field of agriculture. Reduction in agriculture yield due to climate change and global warming due to farming has become a vicious circle. Excessive use of chemicals in farms to increase soil fertility and reduce weeds and pests have adversely affected the environment and the human health. There is limited availability of natural resources like phosphorous and energy required in agriculture. Water scarcity and increase in plant diseases are other major concerns. Artificial intelligence (AI) has emerged as a promising technology in digital agriculture. Digital agriculture relates to using digital technologies for collecting, storing, and further analyzing the electronic agricultural data for better reasoning and decision-making using AI techniques. Precision agriculture is one such technique that monitors soil moisture and composition, temperature, and humidity and determines optimized fertilizer and water requirements for a specific crop and different areas of a farm. Then there are computer vision and machine learning techniques to detect diseases and deficiencies in plants, recognizing weeds that helps in spraying only those parts of land where the plants are disease-infected or where weeds are present instead of the whole field. Utilization of AI in agriculture is helping in developing agricultural methods capable of increasing crop yield and reducing the previously stated challenges. With merits of using AI, there are certain issues. The first major issue in using the AI techniques is the need for high computational power that, again, leads to global warming. Also, in developing countries, the internet infrastructure needs to be improved to use AI techniques effectively. Cost of using AI is high, and countries need AI experts to use the techniques to full potential. The focus of this chapter is to review how AI techniques are helping in increasing yield and overcoming limitations, like global warming, excessive use of fertilizers, limited availability of natural resources, plant disease, and water scarcity. The chapter concludes by discussing the issues and challenges in using AI, especially as it related to agriculture. � 2022 Elsevier Inc. All rights reserved.