IoT-Smart Agriculture: Comparative Study on Farming Applications and Disease Prediction of Apple Crop using Machine Learning

Authors

  • Shahidul Islam Department of Computer Sciences, Baba Ghulam Shah Badshah University, Rajouri, Jammu & Kashmir, India https://orcid.org/0000-0002-3707-739X
  • Sanjay Jamwal Department of Computer Sciences, Baba Ghulam Shah Badshah University, Rajouri, Jammu & Kashmir, India https://orcid.org/0000-0003-3746-5509
  • Mahmood Hussain Mir Department of Computer Sciences, Baba Ghulam Shah Badshah University, Rajouri, Jammu & Kashmir, India https://orcid.org/0000-0002-8497-9126
  • Qamar Rayees Khan Department of Computer Sciences, Baba Ghulam Shah Badshah University, Rajouri, Jammu & Kashmir, India https://orcid.org/0000-0002-7628-173X

DOI:

https://doi.org/10.24996/ijs.2022.63.12.37

Keywords:

IoT, Precision agriculture, Crop diseases, Apple, Machine learning

Abstract

     Recently, the Internet of Things has emerged as an encouraging technology that is scaling up new heights towards the modernization of real word physical objects into smarter devices in several domains. Internet of Things (IoT) based solutions in agriculture drives farming into a smart way through the proliferation of smart devices to enhanced production with minimal human involvement. This paper presents a comprehensive study of the role of IoT in prominent applications of farming, wireless communication protocols, and the role of sensors in precision farming. In this research article, the existing frameworks in IoT-based agriculture systems with relevant technologies are presented. Furthermore, the comparative analysis of the apple disease prediction system concerning different types of disease found in the apple crop are discussed. In addition, this paper presents the contributions made by numerous researchers over the past few years in the apple disease prediction system. The aim of this research is to support the development of smart agriculture applications that would be helpful in precision farming for the optimization of resources with the help of IoT in agriculture and early disease prediction in apple crops.

Downloads

Download data is not yet available.

Downloads

Published

2022-12-30

Issue

Section

Computer Science

How to Cite

IoT-Smart Agriculture: Comparative Study on Farming Applications and Disease Prediction of Apple Crop using Machine Learning. (2022). Iraqi Journal of Science, 63(12), 5520-5533. https://doi.org/10.24996/ijs.2022.63.12.37

Similar Articles

1-10 of 450

You may also start an advanced similarity search for this article.