Transforming Saffron Cultivation With Smart Hydroponics: An Artificial Intelligence of Things Approach to Crops and Nutrients Management

Abstract

Agriculture is changing with the aid of new technologies, particularly in several Asian countries. This research applies Artificial Intelligence (AI) and the Internet of Things (IoT) to traditional farming, particularly focusing on saffron cultivation using hydroponics. Hydroponics is especially useful as a city grows, because it not only saves space but also nourishes the plants directly through the roots - no soil is needed. This study demonstrates a new paradigm through the application of AI integrated with IoT for precise crop recommendation, along with monitoring essential environmental parameters, and adjusting them for maximum growth conditions. We employed various AI models, such as Random Forests, Decision Trees, Support Vector Machines (SVM), K-Nearest Neighbors (KNN), and XGBoost on data from the Indian Chamber of Food and Agriculture. Random forest model outdid the rest, reporting a prediction accuracy of 97.5%, by far the strongest in optimizing cultivation techniques. The goal of this work is to reduce the multiplicity of steps involved in the automation of environmental control and crop recommendation for increased saffron yield, and economic growth in the regions where this crop is crucial will boost and contribute towards sustainability.