Intelligent Systems Research in the Construction Industry

YesWith the increasing complexity of problems in the construction industry, researchers are investigating computationally rigorous intelligent systems with the aim of seeking intelligent solutions. The purpose of this paper is therefore to analyse the research published on ‘intelligent systems in the construction industry’ over the past two decades. This is achieved to observe and understand the historical trends and current patterns in the use of different types of intelligent systems and to exhibit potential directions of further research. Thus, to trace the applications of intelligent systems to research in the construction industry, a profiling approach is employed to analyse 514 publications extracted from the Scopus database. The prime value and uniqueness of this paper lies in analysing and compiling the existing published material by examining variables (such as yearly publications, geographic location of each publication, etc.). This has been achieved by synthesising existing publications using 14 keywords2 ‘Intelligent Systems’, ‘Artificial Intelligence’, ‘Expert Systems’, ‘Fuzzy Systems’, ‘Genetic Algorithms’, ‘Knowledge-Based Systems’, ‘Neural Networks’, ‘Context Aware Applications’, ‘Embedded Systems’, ‘Human–Machine Interface’, ‘Sensing and Multiple Sensor Fusion’, ‘Ubiquitous and Physical Computing’, ‘Case-based Reasoning’ and ‘Construction Industry’. The prime contributions of this research are identified by associating (a) yearly publication and geographic location, (b) yearly publication and the type of intelligent systems employed/discussed, (c) geographic location and the type of research methods employed, and (d) geographic location and the types of intelligent systems employed. These contributions provide a comparison between the two decades and offer insights into the trends in using different intelligent systems types in the construction industry. The analysis presented in this paper has identified intelligent systems studies that have contributed to the development and accumulation of intellectual wealth to the intelligent systems area in the construction industry. This research has implications for researchers, journal editors, practitioners, universities and research institutions. Moreover, it is likely to form the basis and motivation for profiling other database resources and specific types of intelligent systems journals in this area

A framework for integrating syntax, semantics and pragmatics for computer-aided professional practice: With application of costing in construction industry

Producing a bill of quantity is a knowledge-based, dynamic and collaborative process, and evolves with variances and current evidence. However, within the context of information system practice in BIM, knowledge of cost estimation has not been represented, nor has it been integrated into the processes based on BIM. This paper intends to establish an innovative means of taking data from the BIM linked to a project, and using it to create the necessary items for a bill of quantity that will enable cost estimation to be undertaken for the project. Our framework is founded upon the belief that three components are necessary to gain a full awareness of the domain which is being computerised; the information type which is to be assessed for compatibility (syntax), the definition for the pricing domain (semantics), and the precise implementation environment for the standards being taken into account (pragmatics). In order to achieve this, a prototype is created that allows a cost item for the bill of quantity to be spontaneously generated, by means of the semantic web ontology and a forward chain algorithm. Within this paper, ‘cost items’ signify the elements included in a bill of quantity, including details of their description, quantity and price. As a means of authenticating the process being developed, the authors of this work effectively implemented it in the production of cost items. In addition, the items created were contrasted with those produced by specialists. For this reason, this innovative framework introduces the possibility of a new means of applying semantic web ontology and forward chain algorithm to construction professional practice resulting in automatic cost estimation. These key outcomes demonstrate that, decoupling the professional practice into three key components of syntax, semantics and pragmatics can provide tangible benefits to domain use

An Evaluation System for University-Industry Partnership Sustainability: Enhancing Options for Entrepreneurial Universities

The concept of university–industry partnership sustainability (UIPS) stands for well-adjusted progress among key players from universities and industry by sustaining their welfare, both in the present and in the future. This paper sought to develop an evaluation system for UIPS. The need for such a system is justified at three levels: the micro level (i.e., research and innovation performance, transfer and absorptive capability, and technology development), the meso level (i.e., institutional arrangements, communication networks, and local and indigenous rules) and the macro level (i.e., supply and demand, regulations, financing, taxes, culture, traditions, market, climate, politics, demographics, and technology). The UIPS evaluation system developed in this study offers the possibility of calculating a fair value of UIPS and providing recommendations for improving university–industry (U–I) partnerships. This can be of great importance for entrepreneurial universities that would like to strengthen their corporate links and/or reduce/reverse the “hollowing effect” of globalisation in disadvantaged regions. Additionally, this paper also contains discussions on the advantages, limitations, and managerial implications of this proposal.info:eu-repo/semantics/publishedVersio

A rule-based semantic approach for automated regulatory compliance in the construction sector

A key concern for professionals in any industry is ensuring regulatory compliance. Regulations are often complex and require in depth technical knowledge of the domain in which they operate. The level of technical detail and complexity in regulations is a barrier to their automation due to extensive software development time and costs that are involved. In this paper we present a rule-based semantic approach formulated as a methodology to overcome these issues by allowing domain experts to specify their own regulatory compliance systems without the need for extensive software development. Our methodology is based on the key idea that three semantic contexts are needed to fully understand the regulations being automated: the semantics of the target domain, the specific semantics of regulations being considered, and the semantics of the data format that is to be checked for compliance. This approach allows domain experts to create and maintain their own regulatory compliance systems, within a semantic domain that is familiar to them. At the same time, our approach allows for the often diverse nature of semantics within a particular domain by decoupling the specific semantics of regulations from the semantics of the domain itself. This paper demonstrates how our methodology has been validated using a series of regulations automated by professionals within the construction domain. The regulations that have been developed are then in turn validated on real building data stored in an industry specific format (the IFCs). The adoption of this methodology has greatly advanced the process of automating these complex sets of construction regulations, allowing the full automation of the regulation scheme within 18 months. We believe that these positive results show that, by adopting our methodology, the barriers to the building of regulatory compliance systems will be greatly lowered and the adoption of three semantic domains proposed by our methodology provides tangible benefits

Big data analytics system for costing power transmission projects

© 2019 American Society of Civil Engineers. Inaccurate cost estimates have significant impacts on the final cost of power transmission projects and erode profits. Methods for cost estimation have been investigated thoroughly, but they are not used widely in practice. The purpose of this study is to leverage a big data architecture, to manage the large and diverse data required for predictive analytics. This paper presents a predictive analytics and modeling system (PAMS) that facilitates the use of different data-driven cost prediction methods. A 2.75-million-point dataset of power transmission projects has been used as a case study. The proposed big data architecture fits this purpose. It can handle the diverse datasets used in the construction sector. The three most prevalent cost estimation models were implemented (linear regression, support vector regression, and artificial neural networks). All models performed better than the estimated human-level performance. The primary contribution of this study to the body of knowledge is an empirical indication that data-driven methods analysed in this study are on average 13.5% better than manual methods for cost estimation of power transmission projects. Additionally, the paper presents a big data architecture that can manage and process large varied datasets and seamless scalability

A framework for collaborative planning, forecasting and replenishment (CPFR): state of the art

Purpose– Although many papers purport the significant value attributable to supply chain performance from the use of Collaborative Planning, Forecasting and Replenishment (CPFR), the question of ‘what are the main constructs and efficient framework for successful implementation of CPFR?’ remains largely unanswered. This question will be addressed by identifying and analysing the main constructs for successful implementation of CPFR. This paper attempts first to seek answers to this question. Second, to review the scope and value of CPFR using a devised state-of-the-art taxonomy for the classification of selected bibliographical references and third, to develop a conceptual framework by identifying areas which need more research. Design/methodology/approach– The method underlying this paper followed the steps of a systematic literature review process outlined by Soni and Kodali (2011). The review is based on a total of 93 papers published from 1998 to 2013 on CPFR. Findings– Four main constructs for successful implementation of CPFR have been identified: CPFR enablers, CPFR barriers, trading partner selection and incentive alignment. The findings indicate that there is a need for better understanding of the amount and level of information sharing as an important function of CPFR implementation. The paper also illustrates a number of shortcomings in the current literature and provides suggestions to guide future research on implementing CPFR in different industries. Practical implications– This paper is of interest to both academicians and practitioners as it helps to better understand the concept and role of CPFR in supply chain integration and its implementation results, enablers and inhibitors. The proposed framework in this paper can be used to give insight for future research and practice. Originality/value– The paper offers a framework for the review of previous research on CPFR and identifies the most important shortcomings that need to be addressed in future research. In addition, this review is both greater in scope than previous reviews and is broader in its subject focus

Exploring Leadership Strategies to Maximize Profitability in the Nigerian Housing Sector

The collapse of construction companies in the Nigerian housing sector continues unabated, even in the face of 17 million housing deficits. Many construction company leaders believe that lack of business opportunities and the recent world economic decline have been responsible for the collapse. This situation has resulted in limited business activities for 80% of the Nigerian construction companies. This multiple case study explored the strategies used by leaders to maximize profitability in the Nigerian housing sector. The RBV and Porter\u27s model of competition provided the conceptual framework for the study. Findings were based on detailed reviews of the policies and procedures of the companies, coupled with semi-structured face-to-face interviews with 5 leaders of construction companies that have successfully completed and currently involved in several housing projects in 2 southwestern states in Nigeria. The research question examined the strategies construction company leaders used to maximize profitability in the Nigerian housing sector. Four themes representing strategy categories emerged from thematic analysis: planning, human capital development, leadership factor, and organizational location. The key outcomes from the findings include the need to plan with the available resources, employ and invest in competent staff, increase leadership influence, and improve knowledge of the business environment. The implication for social change includes a potential reduction in unemployment in Nigeria. Profitable organizations will construct more affordable housing through collaboration with public authority, and more low-income earners will be able to afford to live in a decent environment, thus reducing the populations of slum dwellers in the country

Supply chain risk and its impact on performance: A structured literature review

Purpose: In the supply chain risk management literature, many reviews have been conducted to provide a full understanding of various aspects such as role of simulation and optimization methods in risk management, classification of risks, classification of risk mitigation strategies, and supply chain risk definitions. However, a structured review of risk impact on performance in supply chains is still lacking. Such a review is useful since the literature implies that maintaining and improving performance in risk environments are critically important to the business survival of firms in supply chains. Design/methodology/approach: This review synthesizes and analyses 48 papers published in journals from 2006 to 2020 based on the following criteria: risk type, impact mechanisms of risk (i.e., direct and indirect), performance, research method, research setting, and risk mitigation strategy. Findings: The findings conclude that the impact of risk on performance is complicated and influenced by many factors namely antecedents, mediators, and moderators. Originality/value: This review contributes to the theoretical development of SCRM research through the analysis of SCR impact mechanisms, and indicate gaps of knowledge and future research opportunities. Moreover, it helps managers to devise appropriate risk mitigation strategies thanks to a full understanding of risk impact mechanisms

Project management information system implementation framework for building construction

Project Management Information System (PMIS) today embraces numerous advanced technologies including context awareness, wireless communication technologies, Global Positioning System (GPS), cloud computing, quantum technology, and robotics. These technologies enhance the efficiency of a PMIS and its effectiveness in information communication (improve the information transfer and improve collaboration). PMIS has existed in the Malaysian construction industry for quite a while. However, PMIS has not been fully utilised where construction management (CM) teams are unable to take advantage of the benefits of PMIS as they are still trying to discover the right way to implement PMIS into current practices. Most construction managers do not know how and when to adopt PMIS in the construction management lifecycle due to a lack of guidelines in the form of detailed processes and steps involved in the implementation of PMIS. These guidelines are expected to be able to assist the construction management team in implementing a PMIS effectively in their project. Therefore, this research aims to develop a PMIS implementation framework for building construction management in Malaysia that would be able to assist construction management teams in implementing PMIS in a structured manner. A semi-structured interview was carried out with respondents that have experience and currently involved in managing building projects using PMIS in Malaysia. Findings from a thematic analysis of the interview data show that the CM team is lacking in knowledge, experience, and proper guideline in adopting the PMIS in their construction management process. Consequently, they were unable to fully benefit from the existing PMIS. The implementation framework was developed and validated with construction managers in the industry as a strategic approach for PMIS implementation in the Malaysian building construction management. The framework is also expected to be able to fill the gap in PMIS implementation by enhancing the capabilities of the CM team in implementing PMIS with the right process and the benefit of PMIS implementation could be fully obtained in improving the construction project management, specifically for beginners to PMIS either in Malaysia or other countries. In addition, the framework supports the increased productivity in construction projects by using new technology and building a solid base towards Construction 4.0

Determining uncertainties in AI applications in AEC sector and their corresponding mitigation strategies

The Artificial Intelligence (AI) methodologies and techniques have been used to solve a wide spectrum of engineering problems in Architectural, Engineering and Construction (AEC) industry with the aim of improving overall productivity and optimized decision throughout full project life cycle (planning, design, construction and maintenance). However, many AI applications are facing different limitations and constrains due to the lack of comprehensive understanding about the inherent uncertainty fundamentally and mathematically, hence the use of AI has not achieved a satisfactory level. It requires different actions to tackle different types of uncertainties which varies according to different types of applications. This paper therefore reviews 5 type of popular AI algorithms, including Primary Component Analysis, Multilayer Perceptron, Fuzzy Logic, Support Vector Machine and Genetic Algorithm; then examines how these artificial intelligence techniques can assist the decision-making process by mitigating uncertainty meanwhile achieving the expected high efficiency. The paper reviews each germane technique, mathematical explanation, analysis of reasons causing uncertainty, and concludes a set of guidelines and an application framework for optimizing their informed uncertainty for AEC applications. This work will pave the way for the fundamental understanding and in turn to provide a valuable reference for applying AI techniques in AEC sector properly to achieve better overall performance