Crop Yield Prediction Prediction Using Vertex AI, Pub/Sub, and BigQuery: An Automated GCP MLOps Approach

Crop Yield Prediction is an important aspect in Agriculture and revenue. This study develops a cloud-based machine learning model to predict the crop yield (in Tons) that the crop yield remain unchanged from the meteorological parameters temperature, humidity, Ph value , rain fall and crop type The model is developed using Google Cloud AutoML (Vertex AI) and the data storage and serving pipelines leverage BigQuery and Pub/Sub. The model is designed so that the training, evaluation, deployment, and prediction serving processes are automated into a scalable, serverless framework. The model exhibited strong predictive performance as evaluated by the R² and RMSE metrics. Thus, this work illustrates an effective application of cloud-native AI to Crop Yield Prediction