BIM-based smart compliance checking to enhance environmental sustainability

The construction industry has been facing immense challenges to move towards more- sustainable buildings with minimum harm to the environment. The building design and construction process is conditioned by numerous sustainability regulations and assessment measures, to promote sustainable construction. These regulations are continuously expanding in their requirements, and incorporating a huge amount of data that needs to be rigorously dealt with, in order to check compliance and asses the performance Building Information Modelling (BIM) promotes the effective information and process integration across the building life-cycle and supply chain. This integration should comply with an increasingly-complex regulatory environment and statutory requirements. The aim of this thesis is to improve and facilitate the sustainability compliance checking process, by focusing on inter-operability between existing methods of compliance checking and building information modelling. This thesis presents a generic approach for BIM based compliance checking against standards and regulations, with a particular focus on sustainable design and procurement. To achieve this, a methodology has been developed to enable automated sustainability compliance checking. This involves (a) extracting regulatory requirements from sustainability-related regulations available in textual format; (b) converting these into BIM- compatible rules; (c) processing these rules through a dedicated rule-based service; and (d) performing regulatory compliance analysis underpinned by the concept of BIM. A semantic extension of the IFC (Industrial Foundation Classes) for sustainability compliance checking has been developed. The outcome of the research was implemented in the RegBIM project and is in the process of being exploited as an online service by industrial organization, the Building Research Establishment (BRE) in the UK

Towards automated compliance checking in the construction industry

The Construction industry has a complex structure of regulatory compliance, consisting of statutory requirements and performance based regulations. The increasing importance of sustainability has further intensified this, with a new building’s compliance against sustainability assessment methodologies now often an important contractual requirement. Automatic compliance checking against these requirements has been long sought after within this industry and several approaches have attempted to achieve this goal. The key improvement that can be made to many existing approaches is enabling the development and maintenance of the regulations by those who are most qualified to do this the domain experts. This is illustrated by the fact that in many cases regulatory compliance systems are closed and when modifications are needed they must be made by software’s developers. This process is simply not viable in this industries rapidly changing environment. In this paper we describe our framework for compliance checking, showing the potential for utilising an integrated process to enable domain experts to create and maintain their own regulations that can then be executed by an open source rule engine. We will describe our process, the methodology and software developed to support it. We will present our initial results in the form of two case studies illustrating progress towards automation of commonly used regulations. Finally, we will also discuss how our approach could be generalised to other related sectors to enable the adoption of a similar approach towards automatic regulatory compliance

ARTIFICIAL INTELLIGENCE IN CLOUD COMPUTING TECHNOLOGY IN THE CONSTRUCTION INDUSTRY: A BIBLIOMETRIC AND SYSTEMATIC REVIEW

The integration and impact of artificial intelligence (AI) and cloud computing (CC) technology in the construction industry (CI) would support their implementation process and adoption. However, there is a lack of research in the extant literature, and recent advances in this field have not been explored. As such, the key research question focuses on the extent of existing literature, main research hotspots, and recent advances (i.e., research gaps and future directions) in AI in CC in the CI. To address this research question, this study aims to conduct a state-of-the-art review of AI in CC in the CI by providing a qualitative discussion of the main research hotspots, research gaps, and future research directions. This review study used a four-step bibliometric-systematic review approach consisting of literature search, literature screening, science mapping analysis, and qualitative discussion. The results found four main research hotspots, namely (1) construction project performance indicators, (2) data analysis and visualization, (3) construction quality control and safety, and (4) construction energy efficiency. These findings would provide valuable insights for scholars and practitioners seeking to understand and integrate AI and CC technology applications in the CI. This review study will lay a better foundation for future developments in construction project management processes, data-sharing protocols, real-time safety monitoring, and ethical implications of AI and CC technologies