Hydroponics, an innovative and sustainable agricultural technique, involves cultivating plants without soil by utilizing nutrient-rich water solutions. This project aims to revolutionize traditional hydroponic systems by integrating advanced technologies such as machine learning algorithms (Lasso's regression, KNN, and ANN) and Internet of Things (IoT) devices. The goal is to create a smart hydroponic system that optimizes crop production by accurately monitoring and controlling crucial parameters like nutrient levels, pH, and humidity.

The proposed system leverages Lasso's regression, KINN, and ANN methods to develop intelligent algorithms capable of analyzing environmental data and providing real-time adjustments. These algorithms contribute to the precision and efficiency of crop cultivation, resulting in healthier and faster-growing crops compared to conventional farming methods.

To address the potential issue of water-borne diseases in hydroponic systems, a key drawback, the project proposes a strategic modification. An anti-bacterial setup will be integrated into the system, utilizing carefully selected chemicals that effectively combat pathogens without adversely affecting crop health. This innovative measure ensures a safer and more hygienic hydroponic environment, mitigating the risk associated with water-borne diseases.

| DOI: 10.17148/IARJSET.2025.125385