Impact Factor (2025): 6.9
DOI Prefix: 10.47001/IRJIET
Vol 7 No 11 (2023): Volume 7, Issue 11, November 2023 | Pages: 632-637
International Research Journal of Innovations in Engineering and Technology
OPEN ACCESS | Research Article | Published Date: 25-11-2023
Capsicum has become more economically viable and has the potential to cure various diseases, so it is appropriate to grow it in greenhouses for maximum yield, but our research showed that farmers in Sri Lanka lack extensive knowledge about growing capsicum crops in greenhouses. This paper gives a simulation of an IoT-based resolve to the identified research problem which utilizes machine learning and image processing to provide analyzed data to greenhouse owners via a web application. This study focuses on how environmental changes and diseases associated with the capsicum crop impact the greenhouse production process. Detecting changes in temperature, light, and soil moisture with precise real-time data using smart technology is critical for disease detection and product quality detection. This is due to Sri Lankan farmers' lack of comprehension regarding choosing an appropriate variety, fertilizing, watering, harvesting, and properly detecting a disease. Because crops can be produced under controlled conditions, greenhouse cultivation is known as safe cultivation.
Machine learning, Image processing, Support Vector Mashine, Internet of Things, You Look Only Once Algorithm
Anushka Fernando, Kaweesha Madhusanka, Odeesha Gamage, Prasadi De Silva, Devanshi Ganegoda, Sathira Hettiarachchi, “Automated Plant Nursery and Disease Detection System for Green Houses Capsicum Plant” Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 7, Issue 11, pp 632-637, November 2023. Article DOI https://doi.org/10.47001/IRJIET/2023.711083
This work is licensed under Creative common Attribution Non Commercial 4.0 Internation Licence