Visual Infrastructure Monitoring With NeRF-Based Defect Detection and Urban Sensing

Abstract

Visual infrastructure monitoring increasingly relies on robust image processing, 3D representation, and multimodal sensing. NeRF-based defect detection provides a neural representation approach for identifying structural anomalies, while rain adaptation and continual rain removal improve outdoor image reliability. LiDAR-guided hyperspectral band selection and image classification add another sensing pathway for urban monitoring, especially where spatial-spectral information can support environmental or infrastructure assessment. Flood relocation research provides the climate adaptation context, showing why resilient urban monitoring matters for hazard-prone communities. Urban sub-center studies identify where infrastructure and adaptation interventions may be most important within metropolitan areas. Web3 governance research contributes a civic coordination perspective by examining how decentralized communities form social capital and respond to collective issues. This literature cluster supports integrated visual infrastructure systems combining defect detection, weather-robust imaging, multimodal sensing, and civic governance.