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Towards Applications of Machine Learning Algorithms for Sustainable Systems and Precision Agriculture

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Data Analytics for Smart Grids Applications—A Key to Smart City Development

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 247))

Abstract

Agriculture plays an indispensable role in each country, serving as a major driving force for economic development. It holds the responsibility for producing the majority of the world’s sustenance for the increasing world population, which is expected to reach 9.8 billion by 2050. With the expected population growing substantially, and the lack of precise knowledge from farmers regarding climactic factors, irrigation demand, soil types, yield, market demand, pesticide use, and livestock needs, the farming process is under scrutiny to produce efficient solutions. The recent advances in Machine Learning (ML) have witnessed an extensive number of applications in agriculture to address the issues. ML falls under the category of Artificial Intelligence (AI) where statistical models enable programmable machines to automatically learn from a dataset. This paper surveys various ML algorithms applicable across sub-domains in agriculture, namely, crop management, water management, soil management, and livestock management. This paper discusses the various problems associated with adopting traditional methods such as soil sampling, laboratory analysis, etc. In addition, the ML algorithms proposed by other authors for forecasting or detection are discussed in detail. At last, the future directions for the application of ML in agriculture are illustrated.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, School of Engineering and Technology, Sharda University, Greater Noida, Uttar Pradesh, 201310, India

    Aayush Juyal & Bharat Bhushan

  2. Department of Computer Engineering, Istinye University, Istanbul, Turkey

    Alaa Ali Hameed

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  1. Aayush Juyal
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  2. Bharat Bhushan
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  3. Alaa Ali Hameed
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Correspondence to Bharat Bhushan .

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  1. Delhi - NCR Campus, SRM Institute of Science and Technology, Ghaziabad, India

    Devendra Kumar Sharma

  2. Delhi - NCR Campus, SRM Institute of Science and Technology, Ghaziabad, India

    Rohit Sharma

  3. Dept. of Embedded Systems Engineering, Incheon National University, Incheon, Korea (Republic of)

    Gwanggil Jeon

  4. Computer Science&Engineering, GIET University, Gunupur, Gunupur, India

    Raghvendra Kumar

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Juyal, A., Bhushan, B., Hameed, A.A. (2023). Towards Applications of Machine Learning Algorithms for Sustainable Systems and Precision Agriculture. In: Kumar Sharma, D., Sharma, R., Jeon, G., Kumar, R. (eds) Data Analytics for Smart Grids Applications—A Key to Smart City Development. Intelligent Systems Reference Library, vol 247. Springer, Cham. https://doi.org/10.1007/978-3-031-46092-0_18

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