Atharva Joshi,Dnyaneshwari Sahane,Yashika Gujar,Prof Priti Kale

Using modern machine learning and AgroAI: predictive soil analysis and crop optimization using machine learning; to revolutionize agriculture. This study predicts the best crops and their potential yields by examining various information about soil, climate and crops. Farmers receive practical recommendations for careful management of resources that promote ecological practices. Ushering in a new era of data-driven agriculture and a more promising agricultural future, ”AgroAI” aims to increase productivity, reduce waste and promote sustainable agriculture. AgroAI is an innovative approach to modern agriculture that uses predictive soil analysis and machine learning to achieve optimal yield results. In the face of a growing world population and climate change, AgroAI integrates advanced sensor technologies to collect comprehensive soil data, including nutrient levels, moisture content, pH and temperature. This information forms the basis of an effective machine learning model. Using a combination of supervised and unsupervised learning algorithms, AgroAI predicts yields based on historical data and discovers hidden patterns in soil data. The model is constantly improving its predictions, adapting to changing environmental conditions and evolving agricultural practices. AgroAI is highly adaptable and allows adaptation to different crops, soil types and climates, making it a versatile tool worldwide. The integration of real-time weather data improvesits forecasting capabilities, allowing farmers to make informed decisions about irrigation, fertilization and pest control.

https://doi.org/10.58357/jedcs.2024.v3.i3.21