ArticleSensors (Basel, Switzerland)2022
Monitoring and Identification of Road Construction Safety Factors via UAV.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The trial behind it
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Who cites it
7 citing papers in PubMed.
- A Hybrid Deep Learning and Improved SVM Framework for Real-Time Railroad Construction Personnel Detection with Multi-Scale Feature Optimization.Sensors (Basel, Switzerland) · 2025Article
- Investigation of Unsafe Construction Site Conditions Using Deep Learning Algorithms Using Unmanned Aerial Vehicles.Sensors (Basel, Switzerland) · 2024Article
- Unmanned Aerial Vehicle-Based Structural Health Monitoring and Computer Vision-Aided Procedure for Seismic Safety Measures of Linear Infrastructures.Sensors (Basel, Switzerland) · 2024Article
- Artificial Intelligence Methods for the Construction and Management of Buildings.Sensors (Basel, Switzerland) · 2023Review
- A Real-Time Semantic Segmentation Method Based on STDC-CT for Recognizing UAV Emergency Landing Zones.Sensors (Basel, Switzerland) · 2023Article
- Cognitive Video Surveillance Management in Hierarchical Edge Computing System with Long Short-Term Memory Model.Sensors (Basel, Switzerland) · 2023Article
- UAV's Status Is Worth Considering: A Fusion Representations Matching Method for Geo-Localization.Sensors (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
The safety of road construction is one of the most important concerns of construction managers for the following reasons: long-span construction operation, no fixed monitoring cameras, and huge impacts on existing traffic, while the managers still rely on manual inspection and a lack of image records. With the fast development of Unmanned Aerial Vehicle (UAV) and Artificial Intelligence (AI), monitoring safety concerns of road construction sites becomes easily accessible. This research aims to integrate UAVs and AI to establish a UAV-based road construction safety monitoring platform. In this study, road construction safety factors including constructors, construction vehicles, safety signs, and guardrails are defined and monitored to make up for the lack of image data at the road construction site. The main findings of this study include three aspects. First, the flight and photography schemes are proposed based on the UAV platform for information collection for road construction. Second, deep learning algorithms including YOLOv4 and DeepSORT are utilized to automatically detect and track safety factors. Third, a road construction dataset is established with 3594 images. The results show that the UAV-based monitoring platform can help managers with security inspection and recording images.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.