Artificial Intelligence (AI) and photonic sensing technologies are marching toward a convergence yielding intelligent high-performance sensing systems for next generation applications. The photonic sensors with the high sensitivity, fast response and immune to electromagnetic interference can serve for healthcare monitoring, environmental sensing, industrial automation and smart infrastructure including passive optical waveguide and nano thin-film coating, fiber-optic sensors of various types such as surface plasmon resonance (SPR) based sensor, photonic crystal fiber (PCF). Over the past few years, fusion of AI techniques such as machine learning and deep learning offer automated signal processing, feature extraction, anomaly detection and predictive analytics to drastically improve sensing accuracy and enable real-time decisions. Moreover, when leveraging synergies of AI with the Internet of Things (IoT) but also edge computing and integrated photonics, autonomous, adaptive, real-time and data-driven optical sensing platforms will emerge. These advances are laying the foundation of smart optical sensing technologies that can solve complicated problems in biomedical, environmental, and industrial fields.
This Research Topic aims to capture the recent advancements, pilot developments, and original applications of AI-enabled photonic sensors for meeting the increasing need for intelligent, accurate, and real-time sensing systems. Despite enormous headway in photonic sensing to date, complex signal interpretation, noise from environmental effects, sensor calibration drift and related data management challenges often restrict the performance of traditional optical sensing systems. The integration of artificial intelligence (AI) methods such as machine learning, deep learning, and explainable AI may be potential solutions that can help solve these limitations through automated analysis of health data, adaptive sensing for diagnostics and predication, and intelligent decision making. This Research Topic focuses on combining contributions regarding novel sensor designs, AI-assisted signal processing, photonic integrated circuits, optical biosensors, fiber-optic sensing as well IoT-enabled sensing platforms deployed with the functionality of edge AI for photonics. Promoting interdisciplinary collaboration, the collection will fast-track the development of reliable smart optical sensing systems with scalability and autonomy for healthcare, environmental monitoring, industrial automation, precision agriculture and smart infrastructure.
This Research Topic invites original research articles, review papers, mini-reviews, perspectives and case studies on the development and applications of AI-based photonic sensors and intelligent optical sensing techniques. Areas of interest include, but are not limited to, AI-assisted optical signal processing; machine learning and deep learning for photonic sensing; photonic crystal fiber (PCF) sensors; surface plasmon resonance (SPR) sensors; integrated photonics; optical biosensors; fiber-optic sensing; nanophotonic sensors, photonic integrated circuits (PICs), IoT-enabled optical sensing, edge AI, explainable AI for sensing, sensor fusion, digital twins; autonomous intelligent monitoring system (AIMS) for healthcare/environmental surveillance/industrial automation/precision agriculture/smart city systems. Theoretical approaches, applied studies, experimental demonstrations and data based modeling creating pathways to new types of sensor architectures that enhance intelligence in optical sensing systems are especially encouraged for next generation instrumentation, computational modeling, methods for real-time implementations and interdisciplinary applications.
Article types and fees
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
- Brief Research Report
- Editorial
- FAIR² Data
- Mini Review
- Original Research
- Perspective
- Review
- Technology and Code
Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.
Keywords: Artificial Intelligence, Machine Learning, Photonic Sensors, Optical Sensing, Smart Optical Sensors, Intelligent Sensing Systems, Photonic Crystal Fiber
Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
