Title: Soil utilisation prediction for farmers using machine learning

Authors: Abdul Qadir Zakir; Anushka Singhal; Gurkirat Singh; Pracheesh Pandey; Suresh Sankaranarayanan

Addresses: Department of Information Technology, SRM Institute of Science and Technology, SRM Nagar, Kattankulathur, Chennai, India ' Department of Information Technology, SRM Institute of Science and Technology, SRM Nagar, Kattankulathur, Chennai, India ' Department of Information Technology, SRM Institute of Science and Technology, SRM Nagar, Kattankulathur, Chennai, India ' Department of Information Technology, SRM Institute of Science and Technology, SRM Nagar, Kattankulathur, Chennai, India ' Department of Information Technology, SRM Institute of Science and Technology, SRM Nagar, Kattankulathur, Chennai, India

Abstract: Soil is necessary for the growth of the plant and there is a need to know the plant that can be grown. Methods are used for soil analysis by taking soil samples in the lab. Soil indicators analyse the soil remotely from the field. The literature review indicates that no work has been done using machine learning for analysing the soil features for soil utility prediction. We have done an in-depth soil utility analysis by employing deep learning and comparing it with other machine learning models for soil utility prediction resulting in the best prediction model.

Keywords: soil sample; soil analysis; soil utility; machine learning; deep learning.

DOI: 10.1504/IJSAMI.2021.113469

International Journal of Sustainable Agricultural Management and Informatics, 2021 Vol.7 No.1, pp.67 - 75

Received: 15 Jul 2020
Accepted: 14 Dec 2020
Published online: 05 Mar 2021 *

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