Machine Learning and IoT for Smart Agriculture: A Comprehensive ‎Review

Preety Chaudhary; Preeti Gulia; Nasib Singh Gill

doi:10.14419/8fb5k746

Article Details

Machine Learning and IoT for Smart Agriculture: A Comprehensive ‎Review

Authors:

Preety Chaudhary | Preeti Gulia | Nasib Singh Gill

Publisher:

Science Publishing Corporation

Journal:

International Journal of Basic and Applied Sciences Vol.14 Issue 7, pp.187-198

Document Type:

Article

Publication Date:

5/2025

Document Language:

English

Document ID (Org No.):

2001387570

pISSN:

2227-5053

DOI:

10.14419/8fb5k746

Keywords:

Abstract:

 The world's population will grow faster than ever in the next ten years. After this, food will be ‎even more important. The old ways of growing won't be able to feed everyone when they need ‎to. This is why it's important to use cutting-edge technologies to address the issues that arise ‎when there are more people and more food. Smart agriculture heavily relies on AI and IoT for ‎various farming tasks. Smart agriculture serves as the most sustainable approach for modern ‎farms. Farmers use various monitors, including those that measure temperature, water levels, ‎and rainfall. This study explores the potential applications of IoT and machine learning in ‎farming. Another part of this study examines the usefulness and accuracy of various machine ‎learning methods. Machine learning is a valuable tool for predicting the growth of various ‎crops, selecting the most suitable ones for cultivation, and monitoring their progress. These ‎algorithms consider diverse factors such as soil composition and compatibility classification to ‎optimize crop selection for productive and sustainable farming practices‎.

Article Details

Machine Learning and IoT for Smart Agriculture: A Comprehensive ‎Review

Authors:

Preety Chaudhary | Preeti Gulia | Nasib Singh Gill

Publisher:

Science Publishing Corporation

Journal:

International Journal of Basic and Applied Sciences Vol.14 Issue 7, pp.187-198

Document Type:

Article

Publication Date:

5/2025

Document Language:

English

Document ID (Org No.):

2001387570

pISSN:

2227-5053

DOI:

10.14419/8fb5k746

Smart Agriculture

IoT

Machine Learning

IoT Sensors

Crop yield Prediction

Issues

Article Details

Machine Learning and IoT for Smart Agriculture: A Comprehensive ‎Review

Authors: Preety Chaudhary | Preeti Gulia | Nasib Singh Gill

Publisher: Science Publishing Corporation

Journal: International Journal of Basic and Applied Sciences Vol.14 Issue 7, pp.187-198

Document Type: Article

Publication Date: 5/2025

Document Language: English

Document ID (Org No.): 2001387570

pISSN: 2227-5053

DOI: 10.14419/8fb5k746

Smart Agriculture

IoT

Machine Learning

IoT Sensors

Crop yield Prediction

Issues

Authors:

Preety Chaudhary | Preeti Gulia | Nasib Singh Gill

Publisher:

Science Publishing Corporation

Journal:

International Journal of Basic and Applied Sciences Vol.14 Issue 7, pp.187-198

Document Type:

Article

Publication Date:

5/2025

Document Language:

English

Document ID (Org No.):

2001387570

pISSN:

2227-5053

DOI:

10.14419/8fb5k746