Cost-effectiveness analysis and evaluation of a ‘three-old’ reconstruction project based on smart system

Wang, Dong; Liu, Jingkuang; Wang, Xuetong; Chen, Yujing

doi:10.1007/s10586-017-1490-3

Cited by 12 publications

(3 citation statements)

References 18 publications

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“… A third of the studies categorised under estimation and cost control examine the application of AI to cost prediction and estimation (Shin, 2015;Juszczyk, 2017;Elmousalami, 2019;Yaqubi and Salhotra, 2019;Juszczyk, 2020). Other applications in the category include tender price evaluations (Zhang et al, 2015;Bilal and Oyedele, 2020a;Mehrabani et al, 2020), cash flow prediction and mapping (Cheng et al, 2015;Cheng et al, 2020a), and cost-effectiveness analysis (Wang et al, 2019). Furthermore, publications categorised as estimation and cost control include assessment of profitability (Oyedele et al, 2019), profit margin estimation (Bilal and Oyedele, 2020b), and prediction of project award price (Chou et al, 2015).…”

Section: Areas Of Applicationmentioning

confidence: 99%

Artificial Intelligence in Construction Projects: A Systematic Scoping Review

2022

EPPM-Journal

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The use of artificial intelligence (AI) in construction projects has surged in recent years and is believed to represent a significant potential for increasing productivity and efficiency in the industry. The purpose of this paper is to present a state-of-the-art view of the field by conducting a review of publications concerning the topic of AI in construction and comparing the findings to previously conducted reviews. This paper provides an overview of the recent and current uses of AI in construction projects, through a descriptive analysis of the characteristics and contents of 86 peer-reviewed articles from 2015 to 2020. Although the application of AI in the industry is not entirely new, construction appears to currently be behind other industries in terms of adopting and adapting to AI. The results show that a wide range of research is conducted on AI in construction projects. A limited number of publication channels and authors stand behind a significant part of the reviewed publications. Most studies are conceptual or use a mixed-methods research design. The research addresses several areas of application, but there is a predominance of quantitatively based subfields of construction, such as estimation and cost control, logistics, planning, and scheduling. Future research should focus on developing holistic and process-oriented frameworks for projects to move from ambition to practice. Findings can inform the future development and implementation of AI in the construction industry context. For researchers, this study identifies areas in need of further attention and examines possibilities for future exploration of multidisciplinary approaches that combine construction engineering, project management, AI, and social science. For practitioners, the study highlights current trends and work within the field, providing an overview of the potential for pilot studies, tests, and innovations.

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Section: Areas Of Applicationmentioning

confidence: 99%

Artificial Intelligence in Construction Projects: A Systematic Scoping Review

2022

EPPM-Journal

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“…More than assessing construction costs for new buildings, in [77] is studied and analyzed the cost of reconstruction of urban buildings. Here, the authors developed an intelligent system capable of monitoring all the reconstruction processes, using AI based on fuzzy logic to assess the influence that the reconstruction will have on the environment and is identified as a solution for cost reduction at the time of monitoring.…”

Section: Building Cost Forecastmentioning

confidence: 99%

Applications, Opportunities and Challenges of AI in the Real Estate Sector

Antão,

Ribeiro,

Pereira

2024

Preprint

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The article presents a Multivocal Literature Review (MLR) on the use of Artificial Intelligence (AI) in the real estate sector, aiming to analyze existing applications, literature gaps, and current challenges. The methodology involved defining keywords, searching online repositories, and applying inclusion/exclusion criteria. In total, 185 documents were selected and reviewed. Findings underscore the significance of areas such as personalized strategies for clients, real estate recommendation systems, and process automation. A literature gap was identified regarding the analysis of performance and accuracy of these applications, indicating the need for further research and technological development to meet the demands of the real estate sector.

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“…From the perspective of urban renewal, the process of transforming stock housing into affordable housing is the same as the urban village micro-renovation model, and the comprehensive benefits of the renovation project are evaluated using the epi-material element model, and its good economic, cultural and social benefits help guide the participation of all social parties (Liu and Li, 2019). From the perspective of construction cost control, the use of a system with intelligent sensors to monitor all the renovation procedures in the process of converting stock housing into affordable housing can optimize the comprehensive benefits for all stakeholders (Wang et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Study on micro-mechanism of the affordable housing community in urban renewal the case of Zunyi city, Guizhou province

Yang

Gong

2023

Front. Environ. Sci.

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Introduction: Affordable housing in China refers to housing with social security for low and middle income people under the unified planning and coordination of the government. In the process of urbanization, the construction of affordable housing and commercial housing should be developed in parallel, but under the role of the real estate market economy, the development of the two is unbalanced, resulting in a disparity in quantity, a large gap in quality, unreasonable management, and even residential segregation. The construction and development of China's affordable housing community is a huge and complex systemic project. This study focuses on a series of problems in the relationship between supply and demand of affordable housing based only on the development context of urban renewal at this stage.Methods: Based on existing literature and official data, combined with field visits and research, this study uses Vensim PLE software to build a system model for converting various types of stock into affordable housing, and to investigate the effect of various policies on solving the problem of supply and demand of affordable housing.Results: The research results show that 1) the policies stimulate the increase of urban population and help promote the supply cycle of affordable housing; 2) under the stimulation of the supply policy of converting stock housing into affordable housing, social investment will improve by 33%–64% and the gap of affordable housing will decrease by 29%–58%; 3) under the stimulation of the policy of optimizing the management of affordable housing, the coverage rate of affordable population will improve by 3%–5% and the middle and low income households’ per capita housing floor area will increase by 9%–18% l; 4) under the comprehensive influence of the combined policies, the urban population will grow healthily, the per capita income and per capita housing floor area of low- and middle- income people will be improved, the stock of housing will be reduced, the number of affordable housing will increase, the affordable housing gap will be reduced, and the affordable housing community will be developed sustainably and healthily.Meaning: The research results and recommendations will provide references for the government and competent authorities to enact or update the policies on affordable housing.

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Cost-effectiveness analysis and evaluation of a ‘three-old’ reconstruction project based on smart system

Cited by 12 publications

References 18 publications

Artificial Intelligence in Construction Projects: A Systematic Scoping Review

Artificial Intelligence in Construction Projects: A Systematic Scoping Review

Applications, Opportunities and Challenges of AI in the Real Estate Sector

Study on micro-mechanism of the affordable housing community in urban renewal the case of Zunyi city, Guizhou province

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