Palakshappa, Anitha
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Journal : Bulletin of Electrical Engineering and Informatics

Smart irrigation with crop recommendation using machine learning approach Palakshappa, Anitha; Kyathanahalli Nanjappa, Sowmya; Mahadevappa, Punitha; Sinchana, Sinchana
Bulletin of Electrical Engineering and Informatics Vol 13, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i3.6103

Abstract

Increasing crop yield with sustainable growth is the primary requirement for farmers with a growing population. Effective management and conservation of depleting natural resources is a priority task. Decrease in manpower due to migrating population has forced automation in agriculture. In this work, an automatic water irrigation and an effective crop recommendation system is proposed. Gypsum blocks based soil sensor is used to measure dielectric permittivity associated with the tested soil. The water-potential present in soil, along with potassium (K), nitrogen (N), phosphorus (P), potential of hydrogen (pH) helps to quantify the soil nutrients available and the suitable crop that can be considered for harvesting in a specified demography and environment. Sensory data indicating soil quality obtained is used to recommend crops by utilizing machine learning approaches. Telegram application is linked to the recommendation model to assist decision making and to ensure farmer-friendliness by sending notifications periodically.