Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Analyzing Potential Risk of Wind-Induced Damage in Construction Sites and Neighboring Communities Using Large-Scale Visual Data from Drones
Dynamic and complex construction sites including incomplete structures and unsecured resources are among the most vulnerable environments to windstorms such as hurricanes. To better secure unstructured construction sites, this paper aims at proposing a new vision-based method to analyze potential risk of wind-induced damage in construction sites. First, by leveraging large-scale images collected from drones, we reconstruct a 3D point cloud model of construction sites and perform the semantic segmentation to categorize potential wind-borne debris. Then, we identify the positions of the potential wind-borne debris given wind speeds and perform the volumetric measurement on such vulnerable objects. Finally, building on the position and the volume of the potential wind-borne debris, we quantify the associated threat level in the context of their kinetic energy in wind situations. A case study was conducted on a real construction site to validate the proposed method. The proposed imaging-to-simulation framework enables practitioners to automatically flag vulnerable objects/areas in construction sites with respect to the severity of wind events, which helps better secure their jobsites in a timely manner before potential extreme wind events in order to minimize the associated damage.
Analyzing Potential Risk of Wind-Induced Damage in Construction Sites and Neighboring Communities Using Large-Scale Visual Data from Drones
Dynamic and complex construction sites including incomplete structures and unsecured resources are among the most vulnerable environments to windstorms such as hurricanes. To better secure unstructured construction sites, this paper aims at proposing a new vision-based method to analyze potential risk of wind-induced damage in construction sites. First, by leveraging large-scale images collected from drones, we reconstruct a 3D point cloud model of construction sites and perform the semantic segmentation to categorize potential wind-borne debris. Then, we identify the positions of the potential wind-borne debris given wind speeds and perform the volumetric measurement on such vulnerable objects. Finally, building on the position and the volume of the potential wind-borne debris, we quantify the associated threat level in the context of their kinetic energy in wind situations. A case study was conducted on a real construction site to validate the proposed method. The proposed imaging-to-simulation framework enables practitioners to automatically flag vulnerable objects/areas in construction sites with respect to the severity of wind events, which helps better secure their jobsites in a timely manner before potential extreme wind events in order to minimize the associated damage.
Analyzing Potential Risk of Wind-Induced Damage in Construction Sites and Neighboring Communities Using Large-Scale Visual Data from Drones
Kamari, Mirsalar (Autor:in) / Ham, Youngjib (Autor:in)
Construction Research Congress 2020 ; 2020 ; Tempe, Arizona
Construction Research Congress 2020 ; 915-923
09.11.2020
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
| British Library Online Contents | 2017