Agritech Pro: Empowering Farmers With AI-Driven Solutions For Crop Health And Yield Enhancement.

Autor: Suresh Babu, Ch., V Subrahmanyam, P. L., Akhila, R., Keerthana, Y. Hepsibha, Subhash, S. Eswar
Zdroj: Journal of Advanced Zoology; 2024, Vol. 45 Issue 2, p299-305, 7p
Abstrakt: Image Processing, Machine Learning, and Deep Learning concepts were used to assist farmers. Our application includes features such as early detection of plant disease, which is accomplished through a variety of methods. Following evaluation, the results revealed that the Convolutional Neural Network performed better for plant disease detection with high accuracy. It also assists the farmer in forecasting the weather to determine the best time for agricultural activities such as harvesting and plucking. To prevent disease reoccurrence due to soil mineral loss, a crop specific fertiliser calculator is included, which can calculate the amount of urea, diammonium phosphate, and muriate of potash required for a given area. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index