• Chilukuri Saketh
• N Sai Harshith
• Dr R.Usharani

India's economy and job market heavily rely on agriculture. The most frequent issue Indian farmers deal with is choosing their crops without considering the soil's requirements, which causes them to experience significant output losses. Precision farming can be used to solve this issue. several factors are considered by this method: soil types, features, and crop recommendation data gathering based on these factors that recommend a suitable crop for the farmer to produce. Apart from the benefits listed below, such as improved agricultural decision-making and, precision agriculture also contributes to a decrease in unsuitable crop production, thereby increasing productivity. This method uses artificial intelligence (AI) to generate recommendations for crops based on soil parameters that are very specific, accurate, and efficient. Random Forest was used in the recommendation because it is typically better for a recommendation system, with accuracy gained 87% and accuracy for KNN is 85%. Random Forest is used here with the accuracy of 87%.

Crop Recommendation, Artificial Intelligence, Soil Characteristics, Water Recommendation, Agriculture, Random Forest, KNN.

"Innovative Agriculture Crop Recommendation system utilizing IOT and ML", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 2, page no.c435-c441, February-2025, Available :http://www.jetir.org/papers/JETIR2502252.pdf

"Innovative Agriculture Crop Recommendation system utilizing IOT and ML", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 2, page no. ppc435-c441, February-2025, Available at : http://www.jetir.org/papers/JETIR2502252.pdf