Open AccessAgrocompanion: A Smart Farming Approach Based on Iot and Machine Learning
Author(s) -
Mandeep Kaur,
Mr. Havish Kodali,
Manjul Dutt,
M. Jaya Bharata Reddy
Publication year - 2020
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.l7984.1091220
Subject(s) - internet of things , agricultural engineering , computer science , agriculture , machine learning , yield (engineering) , production (economics) , random forest , humidity , artificial intelligence , water content , environmental science , real time computing , embedded system , engineering , meteorology , materials science , geotechnical engineering , macroeconomics , economics , metallurgy , biology , ecology , physics
Agriculture is one of the cardinal sectors of the Indian Economy. The proposed system offers a methodology to efficiently monitor and control various attributes that affect crop growth and production. The system also uses machine learning along with the Internet of Things (IoT) to predict the crop yield. Various weather conditions such as temperature, humidity, and soil moisture are monitored in real-time using IoT sensors. IoT is also used to regulate the water level in the water tanks, which helps in reducing the wastage of water resources. A machine learning model is developed to predict the yield of the crop based on parameters taken from these sensors. The model uses Random Forest Regressor and gives an accuracy of 87.5%. Such a system provides a simple and efficient way to maintain and monitor the health of the crop.