Advanced Technologies for Construction and Smart Societies

A special issue of Societies (ISSN 2075-4698).

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 4774

Special Issue Editors


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Guest Editor
School of Surveying and Built Environment, University of Southern Queensland, Springfield Central, QLD 4300, Australia
Interests: construction and project management; building information modelling (bim) application in the construction industry; construction technologies

Special Issue Information

Dear Colleagues,

The construction industry, which has historically lagged behind in technology adoption, is facing adoption challenges with the introduction of modern digital disruptive technologies. Advanced technologies such as artificial intelligence, machine learning, computer vision, big data, Internet of Things, unmanned aerial vehicles, virtual reality, augmented reality, mixed reality, cloud computing, 3D scanning, wearable technologies, robotics, blockchain, software as a service (SaaS), 3D printing, digital twins, building information modelling, ubiquitous computing, renewable energy, autonomous vehicles, 5G communications, and geospatial and scanning technologies are disrupting the construction industry. These advanced technologies have expanded the possibilities for finding solutions to persistent construction problems and have enabled more successful projects that can be objectively measured. However, the adoption of these technologies necessitates the acquisition of modern digital skills and the upgrading of traditional systems and processes involved in construction projects to align with the initiatives of modern smart cities and societies.

The target contributors include academics and practitioners in the fields of construction and project management, urban planning, civil engineering, geographical information systems (GIS), surveying, and the wider built environment. Potential contributors include higher-degree research students in construction management, university professors, researchers, construction managers, construction engineers, civil engineers, project managers, city management teams, real estate and property managers, urban planners, council and regional management teams, architects, IT managers, data scientists, software developers, computer systems analysts, web developers, governance management specialists, and others.

The Guest Editors invite high-quality contributions on a range of topics related to advanced technologies for the construction and smart societies, including:

  • Advanced construction technologies;
  • Construction innovation;
  • Disruptive technologies for smart societies;
  • Building information modelling (BIM) for the construction and societies;
  • Sustainable smart cities, societies, construction, property, and real estate;
  • Industry 4.0 and Industry 5.0 technologies in the construction and societies;
  • Advanced construction technologies for developing smart decision support systems;
  • The big 9 disruptive technologies in construction and societies;
  • Artificial intelligence (AI), machine learning (ML), and natural language processing for use by the construction industry and societies;
  • Unmanned aerial vehicles (UAVs) in the construction and societies;
  • Internet of Things (IoT) in the construction and societies;
  • Big data in the construction and societies;
  • 3D scanning and wearable technologies in the construction and societies;
  • Virtual reality (VR), augmented reality (AR), and mixed reality (MR) in the construction and societies;
  • Blockchains and 3D printing in the construction and societies;
  • Digital Twins in the construction and societies;
  • Autonomous vehicles and 5G communications in the construction and societies.
  • Advanced remote sensing and GIS for the construction and smart societies;
  • Other technologies for the construction and smart societies.

Contributions on other relevant topics are also welcome.

In this Special Issue, contributions have to follow one of the three categories of papers, article, conceptual paper, or review, and must address the topic of the Special Issue.

Dr. Amirhossein Heravi
Dr. Fahim Ullah
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 conceptual papers 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 double-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Societies is an international peer-reviewed open access monthly 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 1400 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

  • construction technologies
  • construction management
  • disruptive technologies
  • digital technologies
  • smart societies

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Published Papers (1 paper)

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Research

15 pages, 1834 KiB  
Article
Forecasting Construction Cost Index through Artificial Intelligence
by Bilal Aslam, Ahsen Maqsoom, Hina Inam, Mubeen ul Basharat and Fahim Ullah
Societies 2023, 13(10), 219; https://doi.org/10.3390/soc13100219 - 11 Oct 2023
Cited by 4 | Viewed by 4122
Abstract
This study presents a novel approach for forecasting the construction cost index (CCI) of building materials in developing countries. Such estimations are challenging due to the need for a longer time, the influence of inflation, and fluctuating project prices in developing countries. This [...] Read more.
This study presents a novel approach for forecasting the construction cost index (CCI) of building materials in developing countries. Such estimations are challenging due to the need for a longer time, the influence of inflation, and fluctuating project prices in developing countries. This study used three techniques—a modified Artificial Neural Network (ANN), time series, and linear regression—to predict and forecast the local building material CCI in Pakistan. The predicted CCI is based on materials, including bricks, steel, cement, sand, and gravel. In addition, the swish activation function was introduced to increase the accuracy of the associated algorithms. The results suggest that the ANN model has superior prediction results, with the lowest Mean Error (ME), Mean Absolute Error (MAE), and Theil’s U statistic (U-Stat) values of 0.04, 28.3, and 0.62, respectively. The time series and regression models have ME values of 0.22 and 0.3, MAE values of 30.07 and 28.3, and U-Stat values of 0.65 and 0.64, respectively. The proposed models can assist contractors, project managers, and owners through an accurately estimated cost index. Such accurate CCIs help correctly estimate project budgets based on building material prices to mitigate project risks, delays, and failures. Full article
(This article belongs to the Special Issue Advanced Technologies for Construction and Smart Societies)
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