Machine learning in smart agriculture

Title

Machine learning in smart agriculture

Creator

Raja A.T.; Arunachalam A.S.; Gobinath R.

Description

Agriculture is the cultivation of the soil, the growth of crops and the raising of livestock. Agriculture is critical to the economic development of a country. Farming generates nearly 58% of a country's primary income. Previously, cultivators had accepted conventional farming practices. Because these methods were imprecise, they produced less and took longer time. Precise farming boosts productivity by precisely determining which steps must be completed at what time. Precision farming entails forecasting the weather, analyzing soil, recommending crops for cultivation and calculating the amount of fertilizer and pesticides that must be used. Precise farming uses advanced technologies such as IoT, data mining, data analytics, and machine learning (ML) to collect data, train systems and predict outcomes. Precision farming employs technology to reduce manual labor and boost productivity. Farmers have recently faced several difficulties, such as crop failure due to insufficient rainfall, soil infertility and so on. The proposed work in determining the soil, managing crops and harvesting efficiently can solve the problems caused by environmental changes. It guides a person's farming strategy to produce better results through a proper prediction process. The goal of this research is to assist an individual in efficiently cultivating crops, resulting in high productivity at a low cost. It also assists in estimating the total cost of cultivation and forecasting the likely economic barriers. This would help a person plan activities prior to cultivation, resulting in an integrated farming solution. 2023 River Publishers. All rights reserved.

Source

Advanced Technologies for Smart Agriculture, pp. 129-151.

Date

2023-01-01

Publisher

River Publishers

Coverage

Raja A.T., Directorate of Distance Education (DDE), SRM Institute of Science and Technology (SRMIST), India; Arunachalam A.S., Department of Computer Science, Vels Institute of Science Technology and Advanced Studies (VISTAS), India; Gobinath R., Department of Computer Science, Christ University, India

Rights

Restricted Access

Relation

ISBN: 978-877022883-1; 978-877022848-0

Format

Online

Language

English

Type

Book chapter

Identifier

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175664510&partnerID=40&md5=3978f937b9670179127fd193ad12736a