Sensors and Artificial Intelligence Learning: Emerging Trends and Applications (SAIL-26)

Recent advances in sensors and artificial intelligence (AI) have revolutionized modern technology, enabling intelligent data acquisition, processing, and decision-making in diverse applications. The fusion of AI with sensing platforms has led to transformative progress in healthcare diagnostics, environmental monitoring, robotics, communication systems, and smart cities. These innovations are shaping the next generation of intelligent systems capable of learning, adapting, and interacting autonomously. The Global Conference on Sensors & Artificial Intelligence Learning (SAIL-26) aims to bring together researchers, technologists, and academicians to explore the latest breakthroughs and challenges in these rapidly evolving domains.This Research Topic seeks to address the convergence of sensor technology and artificial intelligence, focusing on how learning algorithms can enhance sensing performance, efficiency, and interpretability. The goal is to provide a platform for publishing high-quality research presented during SAIL-26 that advances the theoretical foundations, materials, device design, system integration, and application development of intelligent sensors. We aim to identify emerging frontiers such as self-learning sensors, neuromorphic computing, autonomous sensing networks, and AI-driven signal processing. By collecting state-of-the-art contributions, this Research Topic will foster interdisciplinary collaboration between material scientists, engineers, and computer scientists to drive innovation in smart sensing systems.This Research Topic welcomes original research, review, and perspective papers presented at SAIL-26, covering areas including but not limited to: novel sensor materials and architectures; data-driven sensor modeling; AI and machine learning algorithms for sensing and signal interpretation; wearable and biomedical sensors; Internet of Things (IoT) and cyber-physical systems; and AI-enabled smart manufacturing. Contributions that integrate experimental and computational methodologies or demonstrate practical applications of intelligent sensing in energy, environment, and healthcare are particularly encouraged. Topic editors: Shengli Pu, Dr. Sujit Kumar Ghosh, Sajal Biring, Huanyu Cheng Source: https://www.frontiersin.org/research-topics/76496/sensors-and-artificial-intelligence-learning-emerging-trends-and-applications-sail-26