Cloud Based Irrigation System with IoT and Machine Learning

Authors

  • Devareddy Harsha Assistant Professor, Department of Electrical and Electronics Engineering, Chaitanya Bharathi Institute of Technology (A), Telangana, India Author
  • Ziyad Ahmed Mohammed Student, Department of Electrical and Electronics Engineering, Chaitanya Bharathi Institute of Technology (A), Telangana, India Author
  • Rashmith Reddy Arra Student, Department of Electrical and Electronics Engineering, Chaitanya Bharathi Institute of Technology (A), Telangana, India Author

Keywords:

Internet of Things, Machine Learning, Cloud, Terrace farms, SVM, Decision Tree

Abstract

There is a growing demand for electrical  energy requirements in India. Nowadays, people tend to  maintain home gardens, Terrace farms, and Mini farms.  This Maintenance growth has been possible because of a  timely and adequate supply of water. The irrigation  depends on the groundwater availability, but as per the  census of 2017, the groundwater levels have dropped down  by 61% from 2007. Therefore, water usage with effective  power consumption is of at most importance. Despite their  desire to maintain, people take a step back, owing to time  constraints, their busy lives, and the unavailability of a  person to look after farms. Hence, the Internet of Things  (IoT) and Machine Learning (ML) based smart irrigation  system with Cloud integration is employed to address the  farms. The system forecasts using SVM and reports  graphically, the irrigation requirement of the field using  several environmental parameters along with weather  forecasting that assists the growth of the crops with the  effective use of water and power conserving initiatives is  presented in this paper. 

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References

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Ahmed, Ziyad, & Reddy, Rashmith (2022). Cloud Based Irrigation System with Machine Learning and IoT (Version 1.0.0) [Computer software]. https://doi.org/10.5281/zenodo.1234

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Published

2022-06-30

How to Cite

Cloud Based Irrigation System with IoT and Machine Learning. (2022). International Journal of Innovative Research in Engineering & Management, 9(3), 106–111. Retrieved from https://acspublisher.com/journals/index.php/ijirem/article/view/10890