Development of Semantic BIM for Supporting UAV-Based Reality Capture for Facilities Management Applications
开发语义 BIM,支持设施管理应用中基于无人机的现实捕捉
基本信息
- 批准号:521798-2017
- 负责人:
- 金额:$ 1.82万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Engage Grants Program
- 财政年份:2017
- 资助国家:加拿大
- 起止时间:2017-01-01 至 2018-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Reality capture (RC) of constructed facilities (e.g. buildings) is an important step towards developing reliableas-is models that can be used for facilities management. Traditionally, these models are developed based ondesign drawings and/or surveying data of the facilities. However, design drawings of existing facilities may bemissing or not reflecting the actual conditions of the facilities because of accumulated deterioration or becauseof maintenance and renovation activities that were not documented. On the other hand, conventional surveyingmethods are expensive, time consuming, and may not be safe in some cases (e.g. post-disaster inspection).Pegasus Research & Technologies (PRT) provides research and engineering services to the Canadian aerospaceand defense sector, such as simulation test-bed for Unmanned Aerial Vehicles (UAV) experimentation usingartificial intelligence. Recently, the service offering of PRT has grown to include RC for buildings facilitiesmanagement applications using a laser scanner mounted on the UAV. However, transforming the data collectedby the scanner to a useful Building Information Model (BIM) is a challenging task.This project assumes that a UAV equipped with a laser scanner is used for collecting the data needed forcreating a 3D model of the interior spaces in a building. Furthermore, it assumes that there is an algorithm forobject recognition/classification based on the sensory data collected by the UAV. The results of the recognitionare building components (e.g. wall, window, door, etc.) that are already defined in a semantic map. However, agap in this area is that there is currently no direct way of linking this semantic map with BIM. The project aimsto: (1) develop an interface between the semantic map and standard BIM classes; and (2) automatically create aBIM model based on the collected data in order to support the subsequent building inspection tasks.
对已建设施(如建筑物)的现实捕捉(RC)是开发可用于设施管理的可靠模型的重要一步。传统上,这些模型是基于设施的设计图纸和/或测量数据开发的。但是,由于设施的老化或由于没有记录的维修和翻新活动,现有设施的设计图纸可能会遗漏或不反映设施的实际状况。Pegasus Research & Technologies(PRT)为加拿大航空航天和国防部门提供研究和工程服务,例如使用人工智能进行无人机(UAV)实验的模拟试验台。最近,PRT的服务产品已经发展到包括使用安装在UAV上的激光扫描仪的建筑设施管理应用的RC。然而,将扫描仪收集的数据转换为有用的建筑信息模型(BIM)是一项具有挑战性的任务。本项目假设使用配备激光扫描仪的无人机来收集创建建筑物内部空间3D模型所需的数据。此外,它假设有一个算法forobject识别/分类的基础上收集的传感器数据的无人机。结果是建筑构件(如墙、窗、门等)。已经在语义图中定义了。然而,在这一领域的差距是,目前还没有直接的方式将这种语义地图与BIM联系起来。该项目旨在:(1)开发语义地图和标准BIM类之间的接口;(2)根据收集的数据自动创建BIM模型,以支持后续的建筑检查任务。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Hammad, Amin其他文献
Point Cloud-Based Concrete Surface Defect Semantic Segmentation
- DOI:
10.1061/jccee5.cpeng-5009 - 发表时间:
2023-03-01 - 期刊:
- 影响因子:6.9
- 作者:
Bolourian, Neshat;Nasrollahi, Majid;Hammad, Amin - 通讯作者:
Hammad, Amin
Optimizing energy consumption and occupants comfort in open-plan offices using local control based on occupancy dynamic data
- DOI:
10.1016/j.buildenv.2020.106818 - 发表时间:
2020-06-01 - 期刊:
- 影响因子:7.4
- 作者:
Salimi, Shide;Hammad, Amin - 通讯作者:
Hammad, Amin
Automated excavators activity recognition and productivity analysis from construction site surveillance videos
- DOI:
10.1016/j.autcon.2019.103045 - 发表时间:
2020-02-01 - 期刊:
- 影响因子:10.3
- 作者:
Chen, Chen;Zhu, Zhenhua;Hammad, Amin - 通讯作者:
Hammad, Amin
Enhancing Cluster-based RFID Tag Localization using artificial neural networks and virtual reference tags
- DOI:
10.1016/j.autcon.2015.03.009 - 发表时间:
2015-06-01 - 期刊:
- 影响因子:10.3
- 作者:
Soltani, Mohammad Mostafa;Motamedi, Ali;Hammad, Amin - 通讯作者:
Hammad, Amin
Simulation-Based Optimization of Surveillance Camera Types, Number, and Placement in Buildings Using BIM
- DOI:
10.1061/(asce)cp.1943-5487.0000704 - 发表时间:
2017-11-01 - 期刊:
- 影响因子:6.9
- 作者:
Albahri, Ameen Hamza;Hammad, Amin - 通讯作者:
Hammad, Amin
Hammad, Amin的其他文献
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{{ truncateString('Hammad, Amin', 18)}}的其他基金
Cyber-Physical System Approach for Improving Productivity and Safety of Construction Projects
提高建设项目生产力和安全性的网络物理系统方法
- 批准号:
RGPIN-2019-05508 - 财政年份:2022
- 资助金额:
$ 1.82万 - 项目类别:
Discovery Grants Program - Individual
Cyber-Physical System Approach for Improving Productivity and Safety of Construction Projects
提高建设项目生产力和安全性的网络物理系统方法
- 批准号:
RGPIN-2019-05508 - 财政年份:2021
- 资助金额:
$ 1.82万 - 项目类别:
Discovery Grants Program - Individual
Cyber-Physical System Approach for Improving Productivity and Safety of Construction Projects
提高建设项目生产力和安全性的网络物理系统方法
- 批准号:
RGPIN-2019-05508 - 财政年份:2020
- 资助金额:
$ 1.82万 - 项目类别:
Discovery Grants Program - Individual
Cyber-Physical System Approach for Improving Productivity and Safety of Construction Projects
提高建设项目生产力和安全性的网络物理系统方法
- 批准号:
RGPIN-2019-05508 - 财政年份:2019
- 资助金额:
$ 1.82万 - 项目类别:
Discovery Grants Program - Individual
Improving Productivity and Safety of Highway Construction Projects Using Near Real-Time Simulation
利用近实时仿真提高公路建设项目的生产力和安全性
- 批准号:
RGPIN-2014-04016 - 财政年份:2018
- 资助金额:
$ 1.82万 - 项目类别:
Discovery Grants Program - Individual
Improving Productivity and Safety of Highway Construction Projects Using Near Real-Time Simulation
利用近实时仿真提高公路建设项目的生产力和安全性
- 批准号:
RGPIN-2014-04016 - 财政年份:2017
- 资助金额:
$ 1.82万 - 项目类别:
Discovery Grants Program - Individual
Application of Computer Vision for Detecting Equipment on Construction Sites
计算机视觉在建筑工地检测设备中的应用
- 批准号:
499486-2016 - 财政年份:2016
- 资助金额:
$ 1.82万 - 项目类别:
Engage Grants Program
Improving Productivity and Safety of Highway Construction Projects Using Near Real-Time Simulation
利用近实时仿真提高公路建设项目的生产力和安全性
- 批准号:
RGPIN-2014-04016 - 财政年份:2016
- 资助金额:
$ 1.82万 - 项目类别:
Discovery Grants Program - Individual
Improving Productivity and Safety of Highway Construction Projects Using Near Real-Time Simulation
利用近实时仿真提高公路建设项目的生产力和安全性
- 批准号:
RGPIN-2014-04016 - 财政年份:2015
- 资助金额:
$ 1.82万 - 项目类别:
Discovery Grants Program - Individual
Improving Productivity and Safety of Highway Construction Projects Using Near Real-Time Simulation
利用近实时仿真提高公路建设项目的生产力和安全性
- 批准号:
RGPIN-2014-04016 - 财政年份:2014
- 资助金额:
$ 1.82万 - 项目类别:
Discovery Grants Program - Individual
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