AI-driven grain storage solutions: Exploring current technologies, applications, and future trends

摘要

The integration of artificial intelligence (AI) and machine learning (ML) technologies is revolutionizing the food grain industry, particularly in the storage and quality management. This work provides a comprehensive review on the integration of AI and ML in the food grain industry, focusing on current technologies, applications, and future advancements. Various AI technologies including artificial neural networks (ANNs), fuzzy logic systems, and ML methods such as deep learning, supervised learning, and anomaly detection have been discussed. The practical applications of these technologies in addressing critical areas such as pest and insect damage detection, grain classification, crop disease detection, mycotoxin contamination, and supply chain management are highlighted. Applications of innovative technological approaches, including edge computing, digital twins, Internet of Things (IoT), and blockchain, have been discussed for their impact on enhancing grain storage quality management. The review also critically examines the challenges and limitations associated with AI and ML, such as data privacy, inaccuracies, and regulatory concerns. In addition, the emerging trends that are set to revolutionize grain quality management such as smart sensors, robotics, remote sensing, and augmented reality are discussed. By synthesizing current knowledge and future prospects, this review aims to provide a holistic understanding of AI's transformative potential in the grain industry. • This review covers a wide range of AI techniques used in the food grain industry. • AI improves grain storage through applications like pest detection and quality assessment. • Integrating AI with IoT, blockchain, and digital twins leads to smart grain management. • The review addresses challenges in AI adoption, such as data privacy and regulatory issues. • Future trends include smart sensors, robotics, and augmented reality in grain storage.