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Spatial Big Data, BIM and GIS Visualization: Sustainable, Resilience and Smart Cities

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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Urban and Rural Development".

Deadline for manuscript submissions: closed (30 June 2022) | Viewed by 50225

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Special Issue Editors

Dr. Sara Shirowzhan

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Guest Editor

City Futures Research Centre, School of Built Environment, University of New South Wales, Sydney, Kensington, NSW 2052, Australia
Interests: sensing technologies; AI; machine learning; advanced GIS; BIM; digital twins; city analytics methods; digital construction; smart cities; smart construction
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Willie Tan

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Guest Editor

Department of the Built Environment, College of Design and Engineering, National University of Singapore, Singapore 117566, Singapore
Interests: megaprojects; project finance; geomatic engineering; urban management
Special Issues, Collections and Topics in MDPI journals

Dr. Samad Sepasgozar

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Guest Editor

School of Built Environment, UNSW Sydney, Sydney, NSW 1466, Australia
Interests: sustainability; energy efficiency; artificial intelligence; smart city; digital twin; applications of the internet of things; advanced GIS; LiDAR; BIM; digital technology in infrastructure; mixed reality applications; information and communication technology; spatial analysis and visualization; authentic education
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

There are many initiatives of smart cities and advocators for automation and robotics in construction and mining (https://www.iaarc.org/) across the world.

Since digital technology is rapidly advancing, applications are not fully identified in different fields, and many sustainability challenges are not adequately addressed. This Special Issue welcomes all technical endeavors, technology developments, case studies, empirical investigations and experimentations related to advanced information modeling and systems, automation and robotics and other compatible technologies carried out to address the many challenges in smart cities, smart construction and mining, infrastructure maintenance, and disaster management.

While technical development is advancing, the sustainability aspects of the technology, including its side effects and socioeconomic issues, have not been fully developed. This Special Issue invites all researchers to share their scholarly work concerning the development of advanced technologies and sustainability concerns, social issues, and economic benefits of the relevant technologies in smart cities, transportation, construction, mining and civil engineering.

The scope of the work includes but is not limited to the following:

Innovations and sustainability;
Digital technologies and lean construction;
Sensing technologies and quality control;
Green infrastructure and construction;
Automation and robotics;
Use of Geo-ICT for planning sustainable smart cities;
Geospatial data acquisition for sustainable smart cities;
Geospatial database management;
Big data analytics for smart cities;
Real-time location intelligence;
Use of geospatial data for smart urban management, particularly infrastructure planning, construction, and maintenance;
Real-time monitoring of urban environment including air, water, and noise; and
Use of geospatial data for planning and building resilient cities, including security and disaster responses.

Dr. Sara Shirowzhan
Prof. Willie Tan
Dr. Samad M. Sepasgozar
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

green technologies
lean construction
automation and robotics
cloud GIS
big data GIS applications
lidar
geospatial artificial intelligence
deep and machine learning
spatiotemporal data analysis
imaging and scanning data in GIS
location tracking
global positioning system
smart city
infrastructure and construction
disaster management
building information systems
emergency responses
socioeconomic issues

Published Papers (7 papers)

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Research

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36 pages, 6439 KiB

Open AccessEditor’s ChoiceArticle

The SDGs, Ecosystem Services and Cities: A Network Analysis of Current Research Innovation for Implementing Urban Sustainability

by Scott Hawken, Homa Rahmat, Samad M. E. Sepasgozar and Kefeng Zhang

Sustainability 2021, 13(24), 14057; https://doi.org/10.3390/su132414057 - 20 Dec 2021

Cited by 17 | Viewed by 4547

Abstract

Ecosystem services are essential for cities and are key factors in achieving many of the Sustainable Development Goals (SDGs). Such services are best delivered through green infrastructure, which works in resourceful, multifunctional, synergistic, and environmentally sensitive ways to deliver ecosystem services and provide alternative cleaner pathways for the delivery of multiple urban services. It is unclear if current research supports the necessary linkages between ecosystem services, cities, and green infrastructure in order to achieve the SDGs. To answer this question, we conducted a systematic review analysing 3392 studies on the SDGs from the WoS database. The contents of 66 of those with relevance to ecosystem services and urban research were reviewed in depth. We applied network-analytic methods to map the relationships of different knowledge clusters of SDGs research (1) across time, (2) across disciplines, and (3) in relation to ecosystem services and cities. The results of our analysis show that research on the SDGs have developed stronger networks from 2010–2018, but this research has not been sustained. Further, whilst research on cities now occupies a central place in the SDGs literature, research on ecosystem services only shows tentative links to both green-infrastructure research and SDGs research. Such literature on urban green infrastructure remains peripheral to the central challenge of sustainable urban transitions. We conclude that when it comes to the SDGs, research articles typically consider urban services independently of green infrastructure. Further, it suggests that green infrastructure is not generally considered as a sustainable alternative to conventional urban infrastructures. To address this serious shortcoming, we recommend transdisciplinary approaches to link urban ecosystem and urban green infrastructure research to the 2030 global sustainability agenda. Full article

(This article belongs to the Special Issue Spatial Big Data, BIM and GIS Visualization: Sustainable, Resilience and Smart Cities)

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27 pages, 1015 KiB

Open AccessArticle

Investigating the Personalization–Privacy Paradox in Internet of Things (IoT) Based on Dual-Factor Theory: Moderating Effects of Type of IoT Service and User Value

by Ae-Ri Lee

Sustainability 2021, 13(19), 10679; https://doi.org/10.3390/su131910679 - 26 Sep 2021

Cited by 9 | Viewed by 3069

Abstract

Despite people’s concerns over privacy leakage in the Internet of Things (IoT), the needs for personalized IoT services are increasing, creating a conflicting phenomenon viewed as the personalization–privacy (P–P) paradox. This study proposes a research model that utilizes dual-factor theory to investigate the P–P paradox in IoT. It aims to analyze the impact of the dual factor—personalization and privacy concerns related to IoT services—on the intention to use IoT. Further, the model includes four-dimensional motivated innovativeness and previous privacy-invasion experience as key antecedents of the dual factor. Particularly, this study examines the moderating effects of the type of IoT service and user value on the relationship between dual factor and usage intention. Data were collected using a web-based survey. The results showed that personalization had a significant impact on the intention to use IoT, whereas privacy concerns did not. The effects of all antecedents except social innovativeness were significant. The P–P paradox phenomenon appeared differently depending on the type of IoT service and user value. This study contributes to gaining a better understanding of the factors that influence the increase in IoT usage in terms of both protecting and appropriately using personal information for IoT services. Full article

(This article belongs to the Special Issue Spatial Big Data, BIM and GIS Visualization: Sustainable, Resilience and Smart Cities)

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23 pages, 3101 KiB

Open AccessArticle

Analysis of Lightning-Induced Voltages Effect with SPD Placement for Sustainable Operation in Hybrid Solar PV-Battery Energy Storage System

by Nor Izzati Ahmad, Zaipatimah Ali, Mohd Zainal Abidin Ab. Kadir, Miszaina Osman, Nur Hazirah Zaini and Muhammad Hakirin Roslan

Sustainability 2021, 13(12), 6889; https://doi.org/10.3390/su13126889 - 18 Jun 2021

Cited by 6 | Viewed by 2605

Abstract

This paper discusses the lightning-induced voltage effect on a hybrid solar photovoltaic (PV)-battery energy storage system with the presence of surge protection devices (SPD). Solar PV functions by utilizing solar energy, in generating electricity, to supply to the customer. To ensure its consistency, battery energy storage is introduced to cater to the energy demand. For the countries located at the Equator, lightning has always become a major issue for the system to operate at maximum efficiency, due to its nature of installation in open space areas where the equipment may suffer serious damage that may stop the operation abruptly. To minimize the possible damages, insulation coordination on the lightning protection system is needed. Hence, three case studies, i.e., lightning current amplitude, lightning strike distance, and cable length are presented in this paper, which the quantified analysis is taking into account, to identify the performance of the system with the single installation of SPD Class II at DC and AC sides. The simulation results have contributed towards a better understanding of the importance of SPDs, and the need to properly coordinate according to the standard, taking into account the quantified information obtained from this work, hence providing the necessity of proper installation of SPD will provide better maintenance and prolong the lifespan of the equipment. Full article

(This article belongs to the Special Issue Spatial Big Data, BIM and GIS Visualization: Sustainable, Resilience and Smart Cities)

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29 pages, 4351 KiB

Open AccessArticle

Machine Learning for the Improvement of Deep Renovation Building Projects Using As-Built BIM Models

by Sofía Mulero-Palencia, Sonia Álvarez-Díaz and Manuel Andrés-Chicote

Sustainability 2021, 13(12), 6576; https://doi.org/10.3390/su13126576 - 09 Jun 2021

Cited by 20 | Viewed by 4515

Abstract

In recent years, new technologies, such as Artificial Intelligence, are emerging to improve decision making based on learning. Their use applied to the Architectural, Engineering and Construction (AEC) sector, together with the increased use of Building Information Modeling (BIM) methodology in all phases [...] Read more.

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emissions in cities is focusing on the energy renovation of existing buildings, thus tackling one of the main causes of these emissions. This paper shows the potentials, constraints and viable solutions of the use of Machine Learning/Artificial Intelligence approaches at the design stage of deep renovation building projects using As-Built BIM models as input to improve the decision-making process towards the uptake of energy efficiency measures. First, existing databases on buildings pathologies have been studied. Second, a Machine Learning based algorithm has been designed as a prototype diagnosis tool. It determines the critical areas to be solved through deep renovation projects by analysing BIM data according to the Industry Foundation Classes (IFC4) standard and proposing the most convenient renovation alternative (based on a catalogue of Energy Conservation Measures). Finally, the proposed diagnosis tool has been applied to a reference test building for different locations. The comparison shows how significant differences appear in the results depending on the situation of the building and the regulatory requirements to which it must be subjected. Full article

(This article belongs to the Special Issue Spatial Big Data, BIM and GIS Visualization: Sustainable, Resilience and Smart Cities)

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17 pages, 11165 KiB

Open AccessArticle

Assessment of the Local and Global Stability of the Luzzone Arch Dam Including Visualisation of the Data Analysis

by Faham Tahmasebinia, Rowan Doskey, Omar Elrich, David Kelly, Samad Sepasgozar and Fernando Alonso Marroquin

Sustainability 2021, 13(7), 4062; https://doi.org/10.3390/su13074062 - 06 Apr 2021

Cited by 1 | Viewed by 1896

Abstract

This study investigates the local and global stability of the Luzzone Dam. Two finite element models were built; one with foundation rock, the other without. The purpose of this was to demonstrate a potential gulf between rigid connection modelling, and rock–structure interaction (RSI). Strand7 is not a traditional geotechnical finite element model (FEM) program, though performed well when modelling radial displacement on the Luzzone Dam. Generally, the percentage between a rigid base and RSI model displacement was 10%. This result was validated against previous numerical models on the structure. Static loads produced a radial displacement on the crown structure of 9.01 cm. Uneven stress distributions at the base of the structure were shown to be the most unpredictable result. With rigid base connections, these loads produced peak tensile stresses of 10.7 MPa. This was greater than its dynamic counterpart, asking questions about fully fixed restraints. It is noted that this is above yield and should be investigated further. Special attention will be devoted to determining the failure criteria in the simulated dams to suggest better practical guide lines for the practical engineers on site. Full article

(This article belongs to the Special Issue Spatial Big Data, BIM and GIS Visualization: Sustainable, Resilience and Smart Cities)

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40 pages, 1599 KiB

Open AccessFeature PaperArticle

Smart Digital Marketing Capabilities for Sustainable Property Development: A Case of Malaysia

by Sheen Low, Fahim Ullah, Sara Shirowzhan, Samad M. E. Sepasgozar and Chyi Lin Lee

Sustainability 2020, 12(13), 5402; https://doi.org/10.3390/su12135402 - 03 Jul 2020

Cited by 58 | Viewed by 19957

Abstract

Digital tools and marketing have been widely adopted in various industries throughout the world. These tools have enabled companies to obtain real-time customer insights and create and communicate value to customers more effectively. This study aims at understanding the principles and practices of sustainable digital marketing in the Malaysian property development industry by investigating the extent to which digital marketing has been adopted, the impediments to its adoption, and the strategies to improve digital capabilities for the local context. Digital marketing theories, practices, and models from other industries are adopted and applied to the local property development industry to lay the foundation for making it smart and sustainable. This paper proposes a marketing technology acceptance model (MTAM) for digital marketing strategy and capability development. The key factors used in the model are ease of use, perceived usefulness, perceived cost, higher return, efficiency, digital service quality, digital information quality, digital system quality, attitude towards use, and actual use. The model and hypothetical relationships of critical factors are tested using structural modeling, reliability, and validity techniques using a sample of 279 Malaysian property development sector representatives. A quantitative approach is adopted, using an online questionnaire tool to investigate the behavior of respondents on the current digital marketing practices and capabilities of Malaysian property development companies. The results show that the sample property development companies are driven by the benefit of easily obtaining real-time customer information for creating and communicating value to customers more effectively through the company brand. Further strategies, such as creating real-time interactions, creating key performance indicators to measure digital marketing, personalization, and encouraging innovation in digital marketing are most preferred by local professionals. An adoption framework is provided based on the reviewed models and results of the current study to help transform the Malaysian property development sector into a smart and sustainable property development sector by facilitating the adoption of digital technologies. The results, based on real-time data and pertinent strategies for improvement of the local property sector, are expected to pave the way for inducing sustainable digital marketing trends, enhancing capabilities, and uplifting the state of the property development sector in developing countries. Full article

(This article belongs to the Special Issue Spatial Big Data, BIM and GIS Visualization: Sustainable, Resilience and Smart Cities)

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Review

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22 pages, 5860 KiB

Open AccessReview

Lean Practices Using Building Information Modeling (BIM) and Digital Twinning for Sustainable Construction

by Samad M. E. Sepasgozar, Felix Kin Peng Hui, Sara Shirowzhan, Mona Foroozanfar, Liming Yang and Lu Aye

Sustainability 2021, 13(1), 161; https://doi.org/10.3390/su13010161 - 25 Dec 2020

Cited by 65 | Viewed by 12028

Abstract

There is a need to apply lean approaches in construction projects. Both BIM and IoT are increasingly being used in the construction industry. However, using BIM in conjunction with IoT for sustainability purposes has not received enough attention in construction. In particular, the capability created from the combination of both technologies has not been exploited. There is a growing consensus that the future of construction operation tends to be smart and intelligent, which would be possible by a combination of both information systems and sensors. This investigation aims to find out the recent efforts of utilizing BIM for lean purposes in the last decade by critically reviewing the published literature and identifying dominant clusters of research topics. More specifically, the investigation is further developed by identifying the gaps in the literature to utilize IoT in conjunction with BIM in construction projects to facilitate applying lean techniques in a more efficient way in construction projects. A systematic review method was designed to identify scholarly papers covering both concepts “lean” and “BIM” in construction and possibilities of using IoT. A total of 48 scholarly articles selected from 26 construction journals were carefully reviewed thorough perusal. The key findings were discussed with industry practitioners. The transcriptions were analyzed employing two coding and cluster analysis techniques. The results of the cluster analysis show two main directions, including the recent practice of lean and BIM interactions and issues of lean and BIM adoption. Findings revealed a large synergy between lean and BIM in control interactions and reduction in variations, and surprisingly there are many uncovered areas in this field. The results also show that the capability of IoT is also largely not considered in recent developments. The number of papers covering both lean and BIM is very limited, and there is a large clear gap in understanding synergetic interactions of lean concepts applying in BIM and IoT in specific fields of construction such as sustainable infrastructure projects. Full article

(This article belongs to the Special Issue Spatial Big Data, BIM and GIS Visualization: Sustainable, Resilience and Smart Cities)

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