Work

Evolution and Emerging Frontiers in Point Cloud Technology

Year: 2026

Type: article

Abstract: Point cloud intelligence integrates advanced technologies such as Light Detection and Ranging (LiDAR), photogrammetry, and Artificial Intelligence (AI) to transform transportation infrastructure management. This review highlights state-of-the-art advancements in denoising, registration, segmentation, and surface reconstruction. A detailed case study on three-dimensional (3D) mesh generation for railway fastener monitoring showcases how these techniques address challenges like noise and computational complexity while enabling precise and efficient infrastructure maintenance. By demonstrating practical applications and identifying future research directions, this work underscores the transformative potential of point cloud intelligence in supporting predictive maintenance, digital twins, and sustainable transportation systems.

Source: Electronics

DOI: 10.3390/electronics15020341

Authors: Wenjuan Wang, Haleema Ehsan, Shi Qiu, Tariq Ur Rahman, Jin Wang, Qasim Zaheer

Institutions: Capital University of Economics and Business, Central South University, Guangxi Transport Vocational and Technical College

Language: English

Topic: 3D Shape Modeling and Analysis

Subfield: Computational Mechanics

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Sustainable cities and communities

Open Access status: gold

Estimated APC paid: $2,896