Automatic Irrigation Model Powered by Smart Rain Prediction Device in India

Automatic Irrigation Model Powered by Rain Prediction Device

Authors

  • Geeta Ambildhuke K L E F, Hyderabad
  • Gupta Banik Barnali

Keywords:

Precision Agriculture, Deep Learning, Machine Learning, Automatic Irrigation, Rain prediction

Abstract

This paper presents a simple rain prediction device-based automatic irrigation management algorithm using a combination of weather parameters and soil moisture measurements for the water balance required for a crop at each condition during its growing phase that will reduce farmer intervention for irrigation and avoid unnecessary irrigation by predicting the rainfall before starting the motor for irrigating the field. This device is powered by various technologies like deep learning to classify clouds responsible for rain, machine learning models to predict rainfall based on atmospheric parameters and the Internet of Things (IoT) using different sensors to collect data from the field. This algorithm is very appropriate for farmers who are in remote locations and are not able to use the internet and WIFI due to its unavailability. The device will be attached to the motor, will take the data from sensors and will do the rain prediction at device level only and will switch ON/OFF the motor based on the soil moisture value and rain prediction without any human intervention.  

Author Biography

Gupta Banik Barnali

Department of Computer Science & Engineering, Koneru Lakshmaiah Education Foundation, deemed to be University, Hyderabad

References

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Published

2023-01-21

How to Cite

Ambildhuke, G., & Barnali, G. B. (2023). Automatic Irrigation Model Powered by Smart Rain Prediction Device in India: Automatic Irrigation Model Powered by Rain Prediction Device . Journal of Agricultural Extension, 27(1), 94–110. Retrieved from https://journal.aesonnigeria.org/index.php/jae/article/view/3486

Issue

Section

General Extension and Teaching Methods