Matching Items (17)
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- All Subjects: Civil Engineering
- Genre: Academic theses
- Creators: Parrish, Kristen
- Status: Published
Description
Ten regional climate models (RCMs) and atmosphere-ocean generalized model parings from the North America Regional Climate Change Assessment Program were used to estimate the shift of extreme precipitation due to climate change using present-day and future-day climate scenarios. RCMs emulate winter storms and one-day duration events at the sub-regional level. Annual maximum series were derived for each model pairing, each modeling period; and for annual and winter seasons. The reliability ensemble average (REA) method was used to qualify each RCM annual maximum series to reproduce historical records and approximate average predictions, because there are no future records. These series determined (a) shifts in extreme precipitation frequencies and magnitudes, and (b) shifts in parameters during modeling periods. The REA method demonstrated that the winter season had lower REA factors than the annual season. For the winter season the RCM pairing of the Hadley regional Model 3 and the Geophysical Fluid-Dynamics Laboratory atmospheric-land generalized model had the lowest REA factors. However, in replicating present-day climate, the pairing of the Abdus Salam International Center for Theoretical Physics' Regional Climate Model Version 3 with the Geophysical Fluid-Dynamics Laboratory atmospheric-land generalized model was superior. Shifts of extreme precipitation in the 24-hour event were measured using precipitation magnitude for each frequency in the annual maximum series, and the difference frequency curve in the generalized extreme-value-function parameters. The average trend of all RCM pairings implied no significant shift in the winter annual maximum series, however the REA-selected models showed an increase in annual-season precipitation extremes: 0.37 inches for the 100-year return period and for the winter season suggested approximately 0.57 inches for the same return period. Shifts of extreme precipitation were estimated using predictions 70 years into the future based on RCMs. Although these models do not provide climate information for the intervening 70 year period, the models provide an assertion on the behavior of future climate. The shift in extreme precipitation may be significant in the frequency distribution function, and will vary depending on each model-pairing condition. The proposed methodology addresses the many uncertainties associated with the current methodologies dealing with extreme precipitation.
ContributorsRiaño, Alejandro (Author) / Mays, Larry W. (Thesis advisor) / Vivoni, Enrique (Committee member) / Huang, Huei-Ping (Committee member) / Arizona State University (Publisher)
Created2013
Description
Engineering education can provide students with the tools to address complex, multidisciplinary grand challenge problems in sustainable and global contexts. However, engineering education faces several challenges, including low diversity percentages, high attrition rates, and the need to better engage and prepare students for the role of a modern engineer. These challenges can be addressed by integrating sustainability grand challenges into engineering curriculum.
Two main strategies have emerged for integrating sustainability grand challenges. In the stand-alone course method, engineering programs establish one or two distinct courses that address sustainability grand challenges in depth. In the module method, engineering programs integrate sustainability grand challenges throughout existing courses. Neither method has been assessed in the literature.
This thesis aimed to develop sustainability modules, to create methods for evaluating the modules’ effectiveness on student cognitive and affective outcomes, to create methods for evaluating students’ cumulative sustainability knowledge, and to evaluate the stand-alone course method to integrate sustainability grand challenges into engineering curricula via active and experiential learning.
The Sustainable Metrics Module for teaching sustainability concepts and engaging and motivating diverse sets of students revealed that the activity portion of the module had the greatest impact on learning outcome retention.
The Game Design Module addressed methods for assessing student mastery of course content with student-developed games indicated that using board game design improved student performance and increased student satisfaction.
Evaluation of senior design capstone projects via novel comprehensive rubric to assess sustainability learned over students’ curriculum revealed that students’ performance is primarily driven by their instructor’s expectations. The rubric provided a universal tool for assessing students’ sustainability knowledge and could also be applied to sustainability-focused projects.
With this in mind, engineering educators should pursue modules that connect sustainability grand challenges to engineering concepts, because student performance improves and students report higher satisfaction. Instructors should utilize pedagogies that engage diverse students and impact concept retention, such as active and experiential learning. When evaluating the impact of sustainability in the curriculum, innovative assessment methods should be employed to understand student mastery and application of course concepts and the impacts that topics and experiences have on student satisfaction.
Two main strategies have emerged for integrating sustainability grand challenges. In the stand-alone course method, engineering programs establish one or two distinct courses that address sustainability grand challenges in depth. In the module method, engineering programs integrate sustainability grand challenges throughout existing courses. Neither method has been assessed in the literature.
This thesis aimed to develop sustainability modules, to create methods for evaluating the modules’ effectiveness on student cognitive and affective outcomes, to create methods for evaluating students’ cumulative sustainability knowledge, and to evaluate the stand-alone course method to integrate sustainability grand challenges into engineering curricula via active and experiential learning.
The Sustainable Metrics Module for teaching sustainability concepts and engaging and motivating diverse sets of students revealed that the activity portion of the module had the greatest impact on learning outcome retention.
The Game Design Module addressed methods for assessing student mastery of course content with student-developed games indicated that using board game design improved student performance and increased student satisfaction.
Evaluation of senior design capstone projects via novel comprehensive rubric to assess sustainability learned over students’ curriculum revealed that students’ performance is primarily driven by their instructor’s expectations. The rubric provided a universal tool for assessing students’ sustainability knowledge and could also be applied to sustainability-focused projects.
With this in mind, engineering educators should pursue modules that connect sustainability grand challenges to engineering concepts, because student performance improves and students report higher satisfaction. Instructors should utilize pedagogies that engage diverse students and impact concept retention, such as active and experiential learning. When evaluating the impact of sustainability in the curriculum, innovative assessment methods should be employed to understand student mastery and application of course concepts and the impacts that topics and experiences have on student satisfaction.
ContributorsAntaya, Claire Louise (Author) / Landis, Amy E. (Thesis advisor) / Parrish, Kristen (Thesis advisor) / Bilec, Melissa M (Committee member) / Besterfield-Sacre, Mary E (Committee member) / Allenby, Braden R. (Committee member) / Arizona State University (Publisher)
Created2015
Description
Given the importance of buildings as major consumers of resources worldwide, several organizations are working avidly to ensure the negative impacts of buildings are minimized. The U.S. Green Building Council's (USGBC) Leadership in Energy and Environmental Design (LEED) rating system is one such effort to recognize buildings that are designed to achieve a superior performance in several areas including energy consumption and indoor environmental quality (IEQ). The primary objectives of this study are to investigate the performance of LEED certified facilities in terms of energy consumption and occupant satisfaction with IEQ, and introduce a framework to assess the performance of LEED certified buildings.
This thesis attempts to achieve the research objectives by examining the LEED certified buildings on the Arizona State University (ASU) campus in Tempe, AZ, from two complementary perspectives: the Macro-level and the Micro-level. Heating, cooling, and electricity data were collected from the LEED-certified buildings on campus, and their energy use intensity was calculated in order to investigate the buildings' actual energy performance. Additionally, IEQ occupant satisfaction surveys were used to investigate users' satisfaction with the space layout, space furniture, thermal comfort, indoor air quality, lighting level, acoustic quality, water efficiency, cleanliness and maintenance of the facilities they occupy.
From a Macro-level perspective, the results suggest ASU LEED buildings consume less energy than regional counterparts, and exhibit higher occupant satisfaction than national counterparts. The occupant satisfaction results are in line with the literature on LEED buildings, whereas the energy results contribute to the inconclusive body of knowledge on energy performance improvements linked to LEED certification. From a Micro-level perspective, data analysis suggest an inconsistency between the LEED points earned for the Energy & Atmosphere and IEQ categories, on one hand, and the respective levels of energy consumption and occupant satisfaction on the other hand. Accordingly, this study showcases the variation in the performance results when approached from different perspectives. This contribution highlights the need to consider the Macro-level and Micro-level assessments in tandem, and assess LEED building performance from these two distinct but complementary perspectives in order to develop a more comprehensive understanding of the actual building performance.
This thesis attempts to achieve the research objectives by examining the LEED certified buildings on the Arizona State University (ASU) campus in Tempe, AZ, from two complementary perspectives: the Macro-level and the Micro-level. Heating, cooling, and electricity data were collected from the LEED-certified buildings on campus, and their energy use intensity was calculated in order to investigate the buildings' actual energy performance. Additionally, IEQ occupant satisfaction surveys were used to investigate users' satisfaction with the space layout, space furniture, thermal comfort, indoor air quality, lighting level, acoustic quality, water efficiency, cleanliness and maintenance of the facilities they occupy.
From a Macro-level perspective, the results suggest ASU LEED buildings consume less energy than regional counterparts, and exhibit higher occupant satisfaction than national counterparts. The occupant satisfaction results are in line with the literature on LEED buildings, whereas the energy results contribute to the inconclusive body of knowledge on energy performance improvements linked to LEED certification. From a Micro-level perspective, data analysis suggest an inconsistency between the LEED points earned for the Energy & Atmosphere and IEQ categories, on one hand, and the respective levels of energy consumption and occupant satisfaction on the other hand. Accordingly, this study showcases the variation in the performance results when approached from different perspectives. This contribution highlights the need to consider the Macro-level and Micro-level assessments in tandem, and assess LEED building performance from these two distinct but complementary perspectives in order to develop a more comprehensive understanding of the actual building performance.
ContributorsChokor, Abbas (Author) / El Asmar, Mounir (Thesis advisor) / Chong, Oswald (Committee member) / Parrish, Kristen (Committee member) / Arizona State University (Publisher)
Created2015
Description
High performing and sustainable building certification bodies continue to update their requirements, leading to scope modification of certifications, and an increasing number of viable sources of environmental information for building materials. In conjunction, the Architecture, Engineering, and Construction (AEC) industry is seeing increasing demand for such environmental product information. The industry and certifications are moving from using single attribute environmental information about building materials to lifecycle based information to inform their design decisions.
This dissertation seeks to understand the current practices, and then focus on strategies to effectively utilize newer sources of environmental product information in high performance building design. The first phase of research used a survey of 119 U.S.-based AEC practitioners experienced in certified sustainable building projects to understand how the numerous sources of environmental information are currently used in the building design process. The second phase asked two focus groups of experienced AEC professionals to develop a Message Sequence Chart (MSC) that documents the conceptual design process for a recently designed building. Then, the focus group participants integrated a new sustainability requirement for building materials, Environmental Product Declarations (EPDs), into their project, and documented the adjustments to their specific design process in a second, modified MSC highlighting potential drivers for inclusion of EPDs. Finally, the author examines the broader applicability of these drivers through case studies. Specifically, 19 certified high-performance building (HPB) case studies, for reviewing the impact of three different potential drivers on the design team’s approach to considering environmental product information during conceptual design of a HPB, as well as the projects certification level.
LEED certification has changed the design of buildings, and the new information sources for building materials will inform the way the industry selects building materials. Meanwhile, these information sources will need to expand to include a growing number of products, and potentially more data as the industry’s understanding of the impacts of building materials develops. This research expands upon previous research on LEED certification to illustrates that owner engagement and commitment to the HPB process is a critical success factor for the use of environmental product information about building materials.
This dissertation seeks to understand the current practices, and then focus on strategies to effectively utilize newer sources of environmental product information in high performance building design. The first phase of research used a survey of 119 U.S.-based AEC practitioners experienced in certified sustainable building projects to understand how the numerous sources of environmental information are currently used in the building design process. The second phase asked two focus groups of experienced AEC professionals to develop a Message Sequence Chart (MSC) that documents the conceptual design process for a recently designed building. Then, the focus group participants integrated a new sustainability requirement for building materials, Environmental Product Declarations (EPDs), into their project, and documented the adjustments to their specific design process in a second, modified MSC highlighting potential drivers for inclusion of EPDs. Finally, the author examines the broader applicability of these drivers through case studies. Specifically, 19 certified high-performance building (HPB) case studies, for reviewing the impact of three different potential drivers on the design team’s approach to considering environmental product information during conceptual design of a HPB, as well as the projects certification level.
LEED certification has changed the design of buildings, and the new information sources for building materials will inform the way the industry selects building materials. Meanwhile, these information sources will need to expand to include a growing number of products, and potentially more data as the industry’s understanding of the impacts of building materials develops. This research expands upon previous research on LEED certification to illustrates that owner engagement and commitment to the HPB process is a critical success factor for the use of environmental product information about building materials.
ContributorsBurke, Rebekah (Author) / Parrish, Kristen (Thesis advisor) / Gibson, G. Edward (Committee member) / Allenby, Braden (Committee member) / Arizona State University (Publisher)
Created2018
Description
The Colorado River Basin (CRB) is the primary source of water in the
southwestern United States. A key step to reduce the uncertainty of future streamflow
projections in the CRB is to evaluate the performance of historical simulations of General
Circulation Models (GCMs). In this study, this challenge is addressed by evaluating the
ability of nineteen GCMs from the Coupled Model Intercomparison Project Phase Five
(CMIP5) and four nested Regional Climate Models (RCMs) in reproducing the statistical
properties of the hydrologic cycle and temperature in the CRB. To capture the transition
from snow-dominated to semiarid regions, analyses are conducted by spatially averaging
the climate variables in four nested sub-basins. Most models overestimate the mean
annual precipitation (P) and underestimate the mean annual temperature (T) at all
locations. While a group of models capture the mean annual runoff at all sub-basins with
different strengths of the hydrological cycle, another set of models overestimate the mean
annual runoff, due to a weak cycle in the evaporation channel. An abrupt increase in the
mean annual T in observed and most of the simulated time series (~0.8 °C) is detected at
all locations despite the lack of any statistically significant monotonic trends for both P
and T. While all models simulate the seasonality of T quite well, the phasing of the
seasonal cycle of P is fairly reproduced in just the upper, snow-dominated sub-basin.
Model performances degrade in the larger sub-basins that include semiarid areas, because
several GCMs are not able to capture the effect of the North American monsoon. Finally,
the relative performances of the climate models in reproducing the climatologies of P and
T are quantified to support future impact studies in the basin.
southwestern United States. A key step to reduce the uncertainty of future streamflow
projections in the CRB is to evaluate the performance of historical simulations of General
Circulation Models (GCMs). In this study, this challenge is addressed by evaluating the
ability of nineteen GCMs from the Coupled Model Intercomparison Project Phase Five
(CMIP5) and four nested Regional Climate Models (RCMs) in reproducing the statistical
properties of the hydrologic cycle and temperature in the CRB. To capture the transition
from snow-dominated to semiarid regions, analyses are conducted by spatially averaging
the climate variables in four nested sub-basins. Most models overestimate the mean
annual precipitation (P) and underestimate the mean annual temperature (T) at all
locations. While a group of models capture the mean annual runoff at all sub-basins with
different strengths of the hydrological cycle, another set of models overestimate the mean
annual runoff, due to a weak cycle in the evaporation channel. An abrupt increase in the
mean annual T in observed and most of the simulated time series (~0.8 °C) is detected at
all locations despite the lack of any statistically significant monotonic trends for both P
and T. While all models simulate the seasonality of T quite well, the phasing of the
seasonal cycle of P is fairly reproduced in just the upper, snow-dominated sub-basin.
Model performances degrade in the larger sub-basins that include semiarid areas, because
several GCMs are not able to capture the effect of the North American monsoon. Finally,
the relative performances of the climate models in reproducing the climatologies of P and
T are quantified to support future impact studies in the basin.
ContributorsGautam, Jenita (Author) / Mascaro, Giuseppe (Thesis advisor) / Vivoni, Enrique (Committee member) / Wang, Zhihua (Committee member) / Arizona State University (Publisher)
Created2018
Description
The increasingly recurrent extraordinary flood events in the metropolitan area of Monterrey, Mexico have led to significant stakeholder interest in understanding the hydrologic response of the Santa Catarina watershed to extreme events. This study analyzes a flood mitigation strategy proposed by stakeholders through a participatory workshop and are assessed using two hydrological models: The Hydrological Modeling System (HEC-HMS) and the Triangulated Irregular Network (TIN)-based Real-time Integrated Basin Simulator (tRIBS).
The stakeholder-derived flood mitigation strategy consists of placing new hydraulic infrastructure in addition to the current flood controls in the basin. This is done by simulating three scenarios: (1) evaluate the impact of the current structure, (2) implementing a large dam similar to the Rompepicos dam and (3) the inclusion of three small detention dams. These mitigation strategies are assessed in the context of a major flood event caused by the landfall of Hurricane Alex in July 2010 through a consistent application of the two modeling tools. To do so, spatial information on topography, soil, land cover and meteorological forcing were assembled, quality-controlled and input into each model. Calibration was performed for each model based on streamflow observations and maximum observed reservoir levels from the National Water Commission in Mexico.
Simulation analyses focuses on the differential capability of the two models in capturing the spatial variability in rainfall, topographic conditions, soil hydraulic properties and its effect on the flood response in the presence of the different flood mitigation structures. The implementation of new hydraulic infrastructure is shown to have a positive impact on mitigating the flood peak with a more favorable reduction in the peak at the outlet from the larger dam (16.5% in tRIBS and 23% in HEC-HMS) than the collective effect from the small structures (12% in tRIBS and 10% in HEC-HMS). Furthermore, flood peak mitigation depends strongly on the number and locations of the new dam sites in relation to the spatial distribution of rainfall and flood generation. Comparison of the two modeling approaches complements the analysis of available observations for the flood event and provides a framework within which to derive a multi-model approach for stakeholder-driven solutions.
The stakeholder-derived flood mitigation strategy consists of placing new hydraulic infrastructure in addition to the current flood controls in the basin. This is done by simulating three scenarios: (1) evaluate the impact of the current structure, (2) implementing a large dam similar to the Rompepicos dam and (3) the inclusion of three small detention dams. These mitigation strategies are assessed in the context of a major flood event caused by the landfall of Hurricane Alex in July 2010 through a consistent application of the two modeling tools. To do so, spatial information on topography, soil, land cover and meteorological forcing were assembled, quality-controlled and input into each model. Calibration was performed for each model based on streamflow observations and maximum observed reservoir levels from the National Water Commission in Mexico.
Simulation analyses focuses on the differential capability of the two models in capturing the spatial variability in rainfall, topographic conditions, soil hydraulic properties and its effect on the flood response in the presence of the different flood mitigation structures. The implementation of new hydraulic infrastructure is shown to have a positive impact on mitigating the flood peak with a more favorable reduction in the peak at the outlet from the larger dam (16.5% in tRIBS and 23% in HEC-HMS) than the collective effect from the small structures (12% in tRIBS and 10% in HEC-HMS). Furthermore, flood peak mitigation depends strongly on the number and locations of the new dam sites in relation to the spatial distribution of rainfall and flood generation. Comparison of the two modeling approaches complements the analysis of available observations for the flood event and provides a framework within which to derive a multi-model approach for stakeholder-driven solutions.
ContributorsCázares Rodríguez, Jorge E (Author) / Vivoni, Enrique (Thesis advisor) / Wang, Zhihua (Committee member) / Mays, Larry W. (Committee member) / Arizona State University (Publisher)
Created2016
Description
In the burgeoning field of sustainability, there is a pressing need for healthcare to understand the increased environmental and economic impact of healthcare products and services. The overall aim of this dissertation is to assess the sustainability of commonly used medical products, devices, and services as well as to identify strategies for making easy, low cost changes that result in environmental and economic savings for healthcare systems. Life cycle environmental assessments (LCAs) and life cycle costing assessments (LCCAs) will be used to quantitatively evaluate life-cycle scenarios for commonly utilized products, devices, and services. This dissertation will focus on several strategic and high impact areas that have potential for significant life-cycle environmental and economic improvements: 1) increased deployment of reprocessed medical devices in favor of disposable medical devices, 2) innovations to expand the use of biopolymers in healthcare materials and devices, and 3) assess the environmental and economic impacts of various medical devices and services in order to give healthcare administrators and employees the ability to make more informed decisions about the sustainability of their utilized materials, devices, and services.
ContributorsUnger, Scott (Author) / Landis, Amy E. (Thesis advisor) / Bilec, Melissa (Committee member) / Parrish, Kristen (Committee member) / Arizona State University (Publisher)
Created2015
Description
In this era of high-tech computer advancements and tremendous programmable computer capabilities, construction cost estimation still remains a knowledge-intensive and experience driven task. High reliance on human expertise, and less accuracy in the decision support tools render cost estimation error prone. Arriving at accurate cost estimates is of paramount importance because it forms the basis of most of the financial, design, and executive decisions concerning the project at subsequent stages. As its unique contribution to the body of knowledge, this paper analyzes the deviations and behavior of costs associated with different construction activities involved in commercial office tenant improvement (TI) projects. The aim of this study is to obtain useful micro-level cost information of various construction activities that make up for the total construction cost of projects. Standardization and classification of construction activities have been carried out based on Construction Specifications Institute’s (CSI) MasterFormat® division items. Construction costs from 51 office TI projects completed during 2015 and 2016 are analyzed statistically to understand the trends among various construction activities involved. It was found that the interior finishes activities showed a much higher cost of construction, and a comparatively higher variation than the mechanical, electrical, and plumbing (MEP) trades. The statistical analysis also revealed a huge scope of energy saving measures that could be achieved in such TI projects because of the absence of energy management systems (EMS) found in 66% of the projects.
ContributorsGhosh, Arunabho (Author) / Grau, David (Thesis advisor) / Ayer, Steven (Committee member) / Parrish, Kristen (Committee member) / Arizona State University (Publisher)
Created2016
Description
The fast pace of global urbanization makes cities the hotspots of population density and anthropogenic activities, leading to intensive emissions of heat and carbon dioxide (CO2), a primary greenhouse gas. Urban climate scientists have been actively seeking effective mitigation strategies over the past decades, aiming to improve the environmental quality for urban dwellers. Prior studies have identified the role of urban green spaces in the relief of urban heat stress. Yet little effort was devoted to quantify their contribution to local and regional CO2 budget. In fact, urban biogenic CO2 fluxes from photosynthesis and respiration are influenced by the microclimate in the built environment and are sensitive to anthropogenic disturbance. The high complexity of the urban ecosystem leads to an outstanding challenge for numerical urban models to disentangling and quantifying the interplay between heat and carbon dynamics.This dissertation aims to advance the simulation of thermal and carbon dynamics in urban land surface models, and to investigate the role of urban greening practices and urban system design in mitigating heat and CO2 emissions. The biogenic CO2 exchange in cities is parameterized by incorporating plant physiological functions into an advanced single-layer urban canopy model in the built environment. The simulation result replicates the microclimate and CO2 flux patterns measured from an eddy covariance system over a residential neighborhood in Phoenix, Arizona with satisfactory accuracy. Moreover, the model decomposes the total CO2 flux from observation and identifies the significant CO2 efflux from soil respiration. The model is then applied to quantify the impact of urban greening practices on heat and biogenic CO2 exchange over designed scenarios. The result shows the use of urban greenery is effective in mitigating both urban heat and carbon emissions, providing environmental co-benefit in cities. Furthermore, to seek the optimal urban system design in terms of thermal comfort and CO2 reduction, a multi-objective optimization algorithm is applied to the machine learning surrogates of the physical urban land surface model. There are manifest trade-offs among ameliorating diverse urban environmental indicators despite the co-benefit from urban greening. The findings of this dissertation, along with its implications on urban planning and landscaping management, would promote sustainable urban development strategies for achieving optimal environmental quality for policy makers, urban residents, and practitioners.
ContributorsLi, Peiyuan (Author) / Wang, Zhihua (Thesis advisor) / Vivoni, Enrique (Committee member) / Huang, Huei-Ping (Committee member) / Myint, Soe (Committee member) / Xu, Tianfang (Committee member) / Arizona State University (Publisher)
Created2021
Description
There are relatively few available construction equipment detectors models thatuse deep learning architectures; many of these use old object detection architectures
like CNN (Convolutional Neural Networks), RCNN (Region-Based Convolutional
Neural Network), and early versions of You Only Look Once (YOLO) V1. It can be
challenging to deploy these models in practice for tracking construction equipment
while working on site.
This thesis aims to provide a clear guide on how to train and evaluate the
performance of different deep learning architecture models to detect different kinds of
construction equipment on-site using two You Only Look Once (YOLO) architecturesYOLO v5s and YOLO R to detect three classes of different construction equipment onsite, including Excavators, Dump Trucks, and Loaders. The thesis also provides a
simple solution to deploy the trained models. Additionally, this thesis describes a
specialized, high-quality dataset with three thousand pictures created to train these
models on real data by considering a typical worksite scene, various motions, varying
perspectives, and angles of construction equipment on the site.
The results presented herein show that after 150 epochs of training, the YOLORP6 has the best mAP at 0.981, while the YOLO v5s mAP is 0.936. However, YOLO v5s
had the fastest and the shortest training time on Tesla P100 GPU as a processing
unit on the Google Colab notebook. The YOLOv5s needed 4 hours and 52 minutes, but
the YOLOR-P6 needed 14 hours and 35 minutes to finish the training.ii
The final findings of this study show that the YOLOv5s model is the most efficient
model to use when building an artificial intelligence model to detect construction
equipment because of the size of its weights file relative to other versions of YOLO
models- 14.4 MB for YOLOV5s vs. 288 MB for YOLOR-P6.
This hugely impacts the processing unit’s performance, which is used to predict
the construction equipment on site. In addition, the constructed database is published
on a public dataset on the Roboflow platform, which can be used later as a foundation
for future research and improvement for the newer deep learning architectures.
Contributorssabek, mohamed mamdooh (Author) / Parrish, Kristen (Thesis advisor) / Czerniawski, Thomas (Committee member) / Ayer, Steven K (Committee member) / Arizona State University (Publisher)
Created2022