Open AccessPlant Variety and Weed Growth Identification: Trending Towards Machine Learning
Author(s) -
Prof.Dr.S. Andrews,
Mr. K. Ramesh,
T.Kamalraj T.Nandhakumar
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.b3293.078219
Subject(s) - automation , identification (biology) , weed , precision agriculture , computer science , artificial intelligence , weed control , process (computing) , machine vision , agriculture , machine learning , agricultural engineering , engineering , agronomy , ecology , biology , mechanical engineering , operating system
An important module in the agriculture 4.0 based plant monitoring is the weed growth control. In order to achieve the optimum profit on vegetable plantations the control of weeds plays an important role to ensure the precision of yield. Previous studies uses, ariel or portrait images in groups to identify the plants, weed infestation as well as intrusion detection. The motivation in this work of automation is to make the process as an autonomous system to upgrade it to agriculture 4.0 standards, by introducing Artificial Intelligence components in plant monitoring process to help the farmers with the trending technologies. This proposed research approach improves the accuracy of finding plant features from the images captured on vantage angles of the plant .We tried to classify the plants as well as the weeds through inclusion of portrait and ariel images for better classification and to aid automation that uses machine learning in plant and weed identification. Results obtained from the proposed AI system found to be appropriate and accurate in every classes of comparison.