Plant Health Monitoring System Using Machine Learning - Anand Kumar Dohare; Adnan Ahmad Khan (International Journal of Engineering and Management Research, 2024)
Agriculture has transformed into more than just a means to feed growing populations; it's a crucial sector in India, engaging over 70% of the workforce and ensuring sustenance for a vast number of people. Plants play a pivotal role in ecosystems, supporting human life and wildlife by providing food. Preserving plant health is imperative, particularly in detecting diseases, as it directly impacts the quality and quantity of agricultural yields. This paper focuses on the technologies that are being used in plant health monitoring system which is being adopted nowadays in agriculture to make farming easy, for example image processing approaches for plant disease detection. Manually monitoring plant diseases is a difficult task. A manual plant disease monitoring system needs additional processing time and plant disease knowledge. As a result, a method for identifying plant diseases that is quick, automated, and accurate is required. As a result, image processing techniques are utilised to detect, process, and identify plant diseases since they are quick, automated, and accurate. Visualization is a traditional way of identifying diseases in plants, however it is not as effective in detecting diseases linked with plants. As a result, we can give a superior option, one that is both fast and precise, by employing image processing techniques that are more trustworthy than certain older methods.