Enhancing Crop Yield Prediction using IoT and Machine Learning Techniques

Authors

  • Ujjawala Hemant Mandekar  Lecturer, Department of Computer Technology, Government Polytechnic, Sakoli India
  • Pradnya S. Borkar  Assistant professor, Department of Computer science and Engineering, Priyadarshini J. L. College of Engineering, Nagpur, India
  • Dr. Vijaya Balpande  Assistant Professor, Department of Computer science and Engineering, Priyadarshini J. L. College of Engineering, Nagpur, India

Keywords:

crop yield prediction, agriculture, Internet of Things (IoT), machine learning, support vector machine (SVM), decision trees (DT), random forest (RF), data collection, sustainable agriculture.

Abstract

The ability to accurately forecast crop yields is essential to the development of modern agriculture because it enables farmers to more effectively manage their resources and develop more efficient farming practices. Through the use of Internet of Things (IoT) and machine learning strategies, this study investigates innovative approaches to enhance agricultural production forecast. The Internet of Things (IoT) delivers data in real time on many aspects of the surrounding environment, and machine learning algorithms offer prediction skills that have the potential to radically alter the way farmers make choices. This abstract provides a condensed summary of the significant themes that were discussed in this research project. It places an emphasis on the importance of predicting agricultural production, the role that IoT plays in the collection of data, and the prospect that machine learning approaches might be used to make accurate forecasts. The ultimate purpose of the research is to educate farmers with actionable information that will improve agricultural production and maintain agricultural sustainability.

References

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International Journal of Scientific Research in Science, Engineering and Technology

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Published

2017-10-30

Issue

Volume 3, Issue 6, September-October-2017

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Ujjawala Hemant Mandekar, Pradnya S. Borkar, Dr. Vijaya Balpande, " Enhancing Crop Yield Prediction using IoT and Machine Learning Techniques, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 3, Issue 6, pp.1246-1255, September-October-2017.