Crop Recommendation System & Worm Detection...

Crop Recommendation System & Worm Detection Using Ml

Author Name : Maitrey P. Khandizode, Prof. Meghraj Patil, Shreyas B. Beldar, Devraj P. Patil, Reena P. Tayade

ABSTRACT One important aspect of the study is the Worm Detection System, which detects worms in crops using Convolutional Neural Networks (CNNs). This technology recognizes and notifies farmers about potential worm infestations based on images of crops using sophisticated image processing algorithms. This work makes a significant contribution to precision agriculture by offering efficient, environmentally friendly, and cutting-edge technology answers to contemporary farming problems. Soil analysis component's primary goal is to evaluate the soil's condition and nutrient levels. Using soil sensors, key parameters including pH, moisture content, temperature, and nutrient concentrations can be found. The third pillar of the approach is crop recommendation. By combining data from crop databases, historical climate data, aerial photos, worm detection, and soil analysis, the system provides farmers with personalized crop recommendations.