Harnessing Artificial Intelligence and IoT to Revolutionize Crop Yield and Sustainability in Modern Agriculture

This review explores the transformative impact of Artificial Intelligence (AI) and the Internet of Things (IoT) in modern agriculture, addressing critical challenges such as crop yield optimization, resource efficiency, and sustainability. The integration of AI and IoT technologies has revolutionized traditional farming methods, enabling data-driven decision-making to improve productivity and reduce environmental impact. AI-powered algorithms, including machine learning and deep learning models, are being utilized for early pest and disease detection, optimizing irrigation schedules, and predicting crop yields with high accuracy. Additionally, IoT devices, such as smart sensors and drones, play a crucial role in environmental monitoring by collecting real-time data on soil moisture, temperature, humidity, and nutrient levels. These advancements have significantly contributed to the rise of precision agriculture, allowing farmers to implement site-specific crop management strategies that maximize resource efficiency while minimizing waste. However, challenges remain, including concerns over data privacy, cybersecurity risks, high initial investment costs, and the need for digital literacy among farmers. Despite these hurdles, ongoing research and technological innovations continue to push the boundaries of AI and IoT applications in agriculture. Future trends suggest increased adoption of autonomous farming equipment, blockchain for secure data management, and AI-driven predictive analytics, all of which promise to redefine agricultural practices globally.