Aeroponics Techniques for Improved Farming Using Artificial and Deep Learning techniques
C. Amuthadevi, E. Afreen Banu, S. Sampath Kumar, S. Karthick, A. Kistan, M. Sudhakar · Advances in environmental engineering and green technologies book series · 2025
This chapter will delve into the integration of aeroponics into artificial intelligence and deep learning techniques for agricultural productivity and its sustainability. This is a no-soil farming method where plants grow in a nutrient-rich mist. Therein lies a couple of major advantages: water efficiency and an accelerated pace of plant growth. The reasoning behind the inclusion of AI and deep learning techniques lies in the computer vision and predictive analytics ability—how best it can help determine if this has the potential to optimally run aeroponic systems. Monitoring the health of a plant and the environmental state in real time, using AI-driven sensors and deep learning for analytics, is capable of identifying data patterns in predicting growth and optimizing practices for the delivery of nutrients. Some specific successful cases and novel innovations are exemplified next, showing how new breakthroughs can solve the existing challenges of agriculture, improve yield quality, and ultimately reduce resource consumption.