Over the years there has been a continuous swelling in the world’s population and is expected to reach up to 9.7 billion in 2050 due to which the cultivable and arable land is getting smaller and the demand for food production would increase by 50%, according to UN’s Food and Agriculture Organization. Hydroponics, a soilless farming system, offers a solution but lacks real-time monitoring and adaptive control, leading to inefficiencies in resource utilization. This project presents Smart Hydroponics—an innovative, IoT and Machine Learning (ML)-driven sustainable farming system—as a transformative and sustainable solution to address the global challenges of food production, water scarcity and lack of fertile agricultural land. By integrating Internet of Things, real-time data analytics, and predictive ML algorithms, Smart Hydroponics optimizes resource efficiency, reduces water consumption, and maximizes crop yields. This innovative project directly contributes to SDG 2 (Zero Hunger) by enhancing food security, SDG 9 (Industry, Innovation and Infrastructure) by advancing agricultural infrastructure through IoT and ML-driven innovation, SDG 12 (Responsible Consumption and Production) by reducing resource waste, and SDG 13 (Climate Action) by minimizing carbon footprints associated with traditional farming.
Tools: Python,MicroPython,Arduino,ESP-IDF,VS Code,Google Sheets,C/C++,ESP32
Department: Department of Electrical Engineering
Project Poster
