Precision Agriculture in Hydroponics: An IoT and AI-Based Smart Nutrient Mixing Machine

Abstract

Global agriculture grapples with soil degradation, water scarcity, and rising food demand, particularly in urban areas, where manual nutrient management in hydroponics is labor-intensive and error-prone. This study proposes a Smart Hydroponic Nutrient Mixing Machine to automate nutrient delivery, aiming to enhance efficiency and sustainability in soilless farming. The objectives include designing a cost-effective, compact system integrating IoT and AI for urban and rural applications, optimising resource use, and fostering a sustainable agriculture startup. Through a conceptual design approach, the system employs IoT sensors to monitor pH, electrical conductivity, temperature, and humidity, paired with a locally hosted AI model for offline decision-making and a cloud-based interface for remote control. A systematic review of secondary sources, including research on hydroponics, IoT, and smart farming, identified the need for automated nutrient management. The proposed design is compact, capable of tailoring nutrient solutions to crop needs, potentially reducing water usage and labor. Simulations suggest improved nutrient precision and plant growth consistency, though empirical validation is needed. This solution aligns with Industry 4.0, offering scalability for diverse farming contexts. The study recommends prototyping and testing to verify performance, supporting commercialization. By addressing SDG 2 (Zero Hunger) and SDG 12 (Responsible Consumption), this research promotes accessible, sustainable farming innovations with entrepreneurial potential.