Toward Next-Generation Nanowire-Based Gas Sensors and Photodetectors: Quantum-Engineered Heterostructures, Defect Engineering, and AI-Machine-Learning-Driven Detection

• Tunable nanowires with engineered bandgaps and defect control significantly improve sensitivity and selectivity. • Hybrid structures combining quantum dots, 2D materials, and plasmonics enable multifunctional sensing capabilities. • Integration of machine learning introduces intelligent features like drift correction, pattern recognition, and predictive sensing. • Next-generation “sense–learn–act” systems overcome traditional limitations and offer adaptive, self-learning functionalities. • These advanced sensors hav wide applications in healthcare, environmental monitoring, industrial safety, and smart city IoT systems. Nanowires (NWs) have become key building blocks in modern sensor technology, enabling the development of ultra-sensitive and highly miniaturized gas sensors and photodetectors. Their high aspect ratios, quantum confinement effects, and efficient charge transport make them especially effective for detecting weak optical signals and trace-level gaseous analytes. This review focuses on nanowire-based gas sensors and photodetectors, emphasizing performance enhancement through quantum engineering and artificial intelligence (AI). Recent progress in plasmonically enhanced designs, quantum dot–NW hybrid structures, and defect-state engineering is examined for its impact on spectral selectivity and sensing accuracy. In parallel, the integration of AI and machine learning (ML) introduces a shift toward intelligent sensing systems capable of real-time data analysis, automated drift correction, and adaptive pattern recognition. By connecting materials engineering, quantum phenomena, and data-driven methodologies, this review outlines the current state of the art and identifies future directions toward scalable, self-learning, and multifunctional gas sensors and photodetectors for environmental monitoring, biomedical diagnostics, and industrial safety applications.