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检索条件"任意字段=2012 ASCE International Conference on Computing in Civil Engineering"

共 2005 条记录，以下是61-70 订阅

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Human-Sensitive Quantification of City-Scale Human Activity Changes during Natural Disasters

Human-Sensitive Quantification of City-Scale Human Activity ...

引用

asce international conference on computing in civil engineering (I3CE)

作者： Liu, Yang Liu, Kaijian Stevens Inst Technol Dept Civil Environm & Ocean Engn Hoboken NJ 07030 USA

ISBN: (数字)9780784485248

ISBN: (纸本)9780784485248

In this pressing time of climate change, the nation's civil infrastructure systems are challenged by more frequent and intensifying natural disasters. Natural disasters have a disruptive impact on human activities. In coping with ever-increasing disasters, research studies have strived to develop resilience strategies to build physically resilient infrastructure systems. However, there is a lack of research investigating the impact of disasters on human activities across different population groups. To address this limitation, this paper proposes a clustering-based method to analyze the changes in human activities during disasters in a human-sensitive way. The proposed method includes two components: (1) population group discovery to cluster atomic population units into distinctive population groups and (2) activity change quantification to quantify the changes in activity frequency for each identified population group. As a preliminary study, this paper focuses on presenting the proposed method and its implementation in analyzing the impact of Hurricane Ida on different population groups in Manhattan, NYC.

关键词： Disasters

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Using Computer Vision and Parametric Design Software to Quantify Nature Dose in Indoor Built Environments

Using Computer Vision and Parametric Design Software to Quan...

引用

asce international conference on computing in civil engineering (I3CE)

作者： Bianchi, Eva Tavakoli, Arash Billington, Sarah L. Stanford Univ Dept Civil & Environm Engn Stanford CA 94305 USA

ISBN: (数字)9780784485248

ISBN: (纸本)9780784485248

Humans have an innate need to connect with nature, and designing built environments that promote this connection can support well-being. While research has shown that natural materials, views of nature through windows, and presence of indoor plants, are design features that promote well-being, there is a lack of understanding of how much connection to nature inside buildings is needed to achieve desired well-being outcomes. To answer the question of "how much," we first need tools to quantify indoor doses of nature. In this study, we compare two methods of measuring nature indoors to a baseline pixel analysis. We use a semantic segmentation computer vision technique and a parametric method. These methods are applied to photographs and 3D models of a conference room. While both methods face limitations relating to quantifying views of nature through windows, they perform well overall compared to our baseline. We discuss the advantages and limitations of each method to support studies of the role of connection to nature indoors on well-being.

关键词： Semantics

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Debris Management with Vulnerability Heatmapping and Indexing

Debris Management with Vulnerability Heatmapping and Indexin...

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asce international conference on computing in civil engineering (I3CE)

作者： Walker, Richard Yoon, Soojin Oklahoma State Univ Sch Civil & Environm Engn Div Civil Engn Stillwater OK 74078 USA Oklahoma State Univ Div Engn & Technol Stillwater OK 74078 USA

ISBN: (数字)9780784485248

ISBN: (纸本)9780784485248

Debris generated and left in the wake of a disaster is one of a community's greatest obstacles in the ability to restore function. The objectives of this paper are (1) to provide systematic procedures to develop and visualize the debris vulnerability index based on the four dimensions and (2) to develop to prioritize debris removal by integrating all dimensions into GIS mapping. The proposed methodology for Social. Unmanned aerial vehicle was applied to collect the 3D volumetric information, and 11 metrics were selected and evaluated to establish vulnerability of a location. The proposed process incorporates all systems into a process giving decision makers the ability to quickly determine scope, complexity, potential impact, and recovery needs. Therefore, the outcome of this research will ensure maximum utilization of the limited resources to reach a larger number of people who might be facing life-threatening situations in a timely manner, which will enhance resilience of the community.

关键词： Debris

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Forecasting Construction Labor Productivity Metrics

Forecasting Construction Labor Productivity Metrics

引用

asce international conference on computing in civil engineering (I3CE)

作者： Jacobsen, Emil L. Teizer, Jochen Wandahl, Soren Aarhus Univ Dept Civil & Architectural Engn Aarhus Denmark Tech Univ Dept Civil & Mech Engn Lyngby Denmark

ISBN: (数字)9780784485248

ISBN: (纸本)9780784485248

This study presents an autoregressive method for forecasting construction labor productivity metrics. Productivity is an essential parameter to monitor progress in construction projects as it can determine whether the project succeeds or fails in terms of cost and time. However, collecting productivity data, or data correlating with productivity, takes time and effort. Furthermore, the collected productivity data offers limited insights into the current and past performance of the construction activities, which can be valuable to project managers but are often too late to act on due to the transitory nature of construction projects. To increase the amount of information available for decision-makers and analyses, this paper investigates the possibility of using forecasting methods to estimate future values of direct work, indirect work, and waste. Four models are developed and evaluated on a dataset collected on Danish construction sites. Being able to forecast these metrics will add value for decision makers.

关键词： Forecasting

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Enhancing the Time Efficiency of Personal Protective Equipment (PPE) Detection in Real Implementations Using Edge computing

Enhancing the Time Efficiency of Personal Protective Equipme...

引用

asce international conference on computing in civil engineering (I3CE)

作者： Gugssa, Mikias Li, Long Pu, Lina Gurbuz, Ali Luo, Yu Wang, Jun Mississippi State Univ Richard A Rule Sch Civil & Environm Engn Mississippi State MS 39762 USA Univ Alabama Dept Comp Sci Tuscaloosa AL USA Mississippi State Univ Elect & Comp Engn Mississippi State MS USA

ISBN: (数字)9780784485248

ISBN: (纸本)9780784485248

Multiple studies have investigated the use of computer vision to enhance construction workers' safety by detecting personal protective equipment (PPE). However, implementing smart and automated PPE detection in near real time in real practices is still a significant challenge. The performance of PPE detection (e.g., accuracy) in near real-time implementations (i.e., time efficiency) has not been adequately studied to date. Thus, this study proposed an edge computing-based method for detecting PPE gloves in near real time, which can enhance workers' safety and protect data privacy. This study used transfer learning methods to monitor PPE compliance and edge computing to improve time efficiency and protect data privacy. Both edge computing-based and cloud computing-based methods were examined and compared pertaining to time efficiency. The results demonstrated how the developed edge computing-based method can improve safety glove detection in a more time-efficient manner while also maintaining data privacy.

关键词： Efficiency

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Simulating Structural Motions of Floating Cities in an Immersive Virtual Reality Environment

Simulating Structural Motions of Floating Cities in an Immer...

引用

asce international conference on computing in civil engineering (I3CE)

作者： Wang, Shengzhe Han, Bing Univ Colorado Dept Civil Engn Denver CO 80202 USA

ISBN: (数字)9780784485231

ISBN: (纸本)9780784485231

Modular floating structures (MFS) offer an attractive solution for the expansion of coastal cities in adaptation to flooding and sea level rise driven by climate change. Yet, large-scale floating structures for human habitation are unprecedented with no guidelines to inform their practical design. For such projects to succeed, it is essential to investigate how prospective residents will experience life on a floating city from the perspective of comfort and habitability. In response, this paper leverages immersive virtual reality (VR) to establish a framework replicating the motions of a floating structure within any given sea state. The test bed successfully reproduced the motions of an MFS excited by waves corresponding to 1, 50, and 100-year storm events with 96.1%-98.2% accuracy. This validated the feasibility of exploring MFS user experience, decision making, and communication in a completely virtual environment. Ultimately, we establish VR as an invaluable tool for the exploration of immersive visual stimuli to response perception in the context of a floating city.

关键词： Virtual reality

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Potential of Vision-Based 6-DoF Pose Estimation for Cuboid-Shape Objects from Construction Jobsites

Potential of Vision-Based 6-DoF Pose Estimation for Cuboid-S...

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asce international conference on computing in civil engineering (I3CE)

作者： Miao, Quan Liu, Meiyin Rutgers State Univ Dept Civil & Environm Engn New Brunswick NJ 08901 USA

ISBN: (数字)9780784485224

ISBN: (纸本)9780784485224

Technological advancement transforms construction jobsites into more intelligent systems. Among the technologies, robotics relies on environmental perception, such as the motion and dynamics of interacting objects;a digital twin expands its capabilities by collecting real-time data of the physical twin, including spatial and physical properties. Given booming attention and efforts in such technologies, there lacks a non-invasive approach to collect jobsite objects' 3D location and orientation, which is a required step for physically based modeling. As an initial effort, this paper proposes a vision-based approach to estimate the 6-DoF object pose of construction jobsite objects from a single image while leveraging deep learning. Tests are performed on a brick and a concrete block of cuboid shape. The evaluation against ground truth data, collected by an RGB-D camera, presents a certain potential for utilizing a non-invasive perception approach to collect jobsite objects' advanced kinematic data for extended capabilities of intelligent systems.

关键词： Intelligent systems

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Trust in Construction AI-Powered Collaborative Robots: A Qualitative Empirical Analysis

Trust in Construction AI-Powered Collaborative Robots: A Qua...

引用

asce international conference on computing in civil engineering (I3CE)

作者： Emaminejad, Newsha Akhavian, Reza San Diego State Univ Dept Civil Construct & Environm Engn San Diego CA 92182 USA

ISBN: (数字)9780784485224

ISBN: (纸本)9780784485224

Construction technology researchers and forward-thinking companies are experimenting with collaborative robots (aka cobots), powered by artificial intelligence (AI), to explore various automation scenarios as part of the digital transformation of the industry. Intelligent cobots are expected to be the dominant type of robots in the future of work in construction. However, the black-box nature of AI-powered cobots and unknown technical and psychological aspects of introducing them to job sites are precursors to trust challenges. By analyzing the results of semi-structured interviews with construction practitioners using grounded theory, this paper investigates the characteristics of trustworthy AI-powered cobots in construction. The study found that while the key trust factors identified in a systematic literature review-conducted previously by the authors-resonated with the field experts and end users, other factors such as financial considerations and the uncertainty associated with change were also significant barriers against trusting AI-powered cobots in construction.

关键词： Intelligent robots

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Using Eye-Tracking to Examine the Cognitive Process of Hazard Recognition in Construction VR Scenarios

Using Eye-Tracking to Examine the Cognitive Process of Hazar...

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asce international conference on computing in civil engineering (I3CE)

作者： Luo, Yanfang Seo, JoonOh Hasanzadeh, Sogand Hong Kong Polytech Univ Dept Bldg & Real Estate Hong Kong Peoples R China Purdue Univ Lyles Sch Civil Engn W Lafayette IN USA

ISBN: (数字)9780784485248

ISBN: (纸本)9780784485248

The construction industry is a high-risk environment with numerous potential hazards, emphasizing the need for effective hazard recognition to prevent accidents and injuries. However, the cognitive processes underlying hazard recognition ability are not well understood. Eye-tracking technology can offer valuable insights into the cognitive process, and this study investigates differences in higher and lower hazard recognition ability using eye-tracking technology in virtual reality scenarios. Participants were instructed to report hazards immediately when identified. Results indicate that individuals with lower hazard recognition ability had longer perception or comprehension times in the case of successful identification. These findings underscore the importance of understanding eye movement data to develop effective hazard recognition training programs to improve workers' ability to identify and respond to potential hazards at jobsites.

关键词： Hazards

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Expert Demonstration Collection of Long-Horizon Construction Tasks in Virtual Reality

Expert Demonstration Collection of Long-Horizon Construction...

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asce international conference on computing in civil engineering (I3CE)

作者： Li, Rui Zou, Zhengbo Univ British Columbia Dept Civil & Environm Engn Vancouver BC Canada

ISBN: (数字)9780784485231

ISBN: (纸本)9780784485231

With the shortage of skilled labors in recent years, there is a pressing need for utilizing robots to perform repetitive and heavy construction tasks. Reinforcement learning (RL)-based robots become a promising solution because of their robustness and adaptability to unseen scenarios. However, long training time and complex reward design for these robots remain challenging. An effective solution is to collect expert demonstrations as inputs to better initialize policies of RL agents, or directly train inverse reinforcement learning (IRL) agents to recover reward functions. Therefore, this paper proposes a comprehensive virtual reality (VR)-based platform for expert demonstration collection. To show the effectiveness of our platform, a collaborative long-horizon construction task is implemented. We gathered 20 expert demonstrations as input to train a behavior cloning (BC) model. Results showed that the learned policy achieved reasonable success rates in completing the task, indicating the effectiveness of our demonstration collection platform.

关键词： Demonstrations

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