Title: Radio frequency-based periodic cloud data analysis for smart farming

Authors: A. Jayanthiladevi; Sudhanshu Maurya; Sivaram Murugan; M. Deva Brinda; R. Kannadasan; R. Narmadha

Addresses: Computer Science and Information Science, Srinvas University, Karnataka, India ' Ministry of Education Malaysia, School of Computing, Universiti Malaysia Perlis, Malaysia; Graphic Era Hill University, Bhimtal Campus, Uttarakhand, India ' College of Engineering and Computer Science, Lebanese French University, Erbil, Iraq ' Electrical and Electronics Engineering, AMET University, Chennai, India ' School of Computer Science and Engineering (SCOPE), Vellore Institute of Technology (VIT) University, Vellore, India ' School of Electrical and Electronics Engineering, Sathyabama Institute of science and technology, Chennai, India

Abstract: Radio frequency-based smart farming is revolutionising agriculture. To meet the growing demand of food, farm productivity should be improved by predicting crop performance in diverse environmental conditions. Farming becomes smarter with automation and radio frequency technology. Radio frequency collect and manage data about crop performance, climate change, livestock welfare, resource shortages and atmosphere that frequently influence farming construction via smartphone applications where the data container remains and is retrieved wherever. It also aids in animal nursing and termination. With smart sensors and equipment, farmers can increase crop production with reduced cost and time. Smart farming along with sensors offers the guarantee of expanding efficiency while diminishing generation costs and limiting ecological effects. The sensor data will be collected and stored in the cloud. Analysis of farming is done with computing the data stored in the cloud. Based on these cloud data, farmers perform farming in a proper annual time. Cloud-based storage is more appropriate for these computations. Various climatic conditions for farming are analysed with these cloud data.

Keywords: agricultural sector; automation; radio frequency; smart farming.

DOI: 10.1504/IJCC.2022.128702

International Journal of Cloud Computing, 2022 Vol.11 No.5/6, pp.568 - 577

Received: 14 Mar 2020
Accepted: 17 Dec 2020

Published online: 02 Feb 2023 *

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