Fusion of Nano Sensors and AI Models for Real-Time Plant Health Monitoring in Agricultural Ecosystem

The integration of nanotechnology into sustainable agriculture signifies a transformative approach to enhancing crop productivity and health. ‎This review examines recent advancements in the application of engineered nanoparticles, nanobiotechnology, and nano sensors, emphasizing their roles in improving soil health, disease management, and real-time monitoring of plant conditions. By analyzing various methodolo‎gies and outcomes from current research, the paper highlights the benefits of using nanoparticles for nutrient uptake efficiency and disease ‎resistance while addressing the potential environmental risks and regulatory challenges associated with their use. Additionally, the use of ‎machine learning algorithms in conjunction with nano sensor data is explored to enhance precision, predictive capabilities, and decision-making in smart agricultural systems. The findings indicate that nanotechnology not only fosters sustainable agricultural practices but also ‎presents significant opportunities for innovation in plant science. However, barriers to widespread adoption, such as cost, safety concerns, ‎and ecological impacts, must be addressed. This review contributes to the growing discourse on the future of agriculture and the vital role of ‎nanotechnology in achieving sustainable food production‎.