Machine learning for estimation of building energy consumption and performance:a review

Ever growing population and progressive municipal business demands for constructing new buildings are known as the foremost contributor to greenhouse gasses. Therefore, improvement of energy eciency of the building sector has become an essential target to reduce the amount of gas emission as well as fossil fuel consumption. One most eective approach to reducing CO2 emission and energy consumption with regards to new buildings is to consider energy eciency at a very early design stage. On the other hand, ecient energy management and smart refurbishments can enhance energy performance of the existing stock. All these solutions entail accurate energy prediction for optimal decision making. In recent years, articial intelligence (AI) in general and machine learning (ML) techniques in specic terms have been proposed for forecasting of building energy consumption and performance. This paperprovides a substantial review on the four main ML approaches including articial neural network, support vector machine, Gaussian-based regressions and clustering, which have commonly been applied in forecasting and improving building energy performance

Proceedings of the 29th EG-ICE International Workshop on Intelligent Computing in Engineering

This publication is the Proceedings of the 29th EG-ICE International Workshop on Intelligent Computing in Engineering from July 6-8, 2022. The EG-ICE International Workshop on Intelligent Computing in Engineering brings together international experts working on the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolution of challenges such as supporting multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways. &nbsp

Proceedings of the 29th EG-ICE International Workshop on Intelligent Computing in Engineering

This publication is the Proceedings of the 29th EG-ICE International Workshop on Intelligent Computing in Engineering from July 6-8, 2022. The EG-ICE International Workshop on Intelligent Computing in Engineering brings together international experts working on the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolution of challenges such as supporting multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways. &nbsp

Using IT/ICT as a new medium toward implementation of interactive architectural communication cultures

Design is a multi-aspect, iterative, and complicated exclusive human activity and a critical aspect of many modern industries. The early phases of design are drastically affected by quality of communications among process stakeholders. Communication culture within every society depends on the tools people use for their communicational transactions. Today globalization and advanced IT/ICT technologies revolutionized communication culture in every society. We can see extreme changes in product design in the architectural design process. So understanding the situation of design culture dealing with IT/ICT seems vital. This paper contributes with an overview of the current situation of IT/ICT related benefits and challenges due to several aspects of the design process and culture. Explored key points here, establish the background for the introduction of an IT/ICT impact on the design collaboration culture. Conclusions outline the new design interaction culture and the IT/ICT related impacts on different phases of the architectural design process

Alignment problems of timber production in Architecture-Engineering-Construction Projects in Malaysia

Due to the negative effects of the carbon-dioxide on the ecosystem, the Architecture-Engineering-Construction industries are looking for the new materials with lower carbon-footprint. One of the best natural materials that can be used in AEC industries is wood and its derivatives. However, due to the physical and chemical properties of timber, the application of it in AEC industries, especially in the process of manufacturing and production, encounter with some difficulties and obstacles; and they are causes of decreasing the speed and increasing the cost of production in AEC industry. The most important problem in the process of off-site manufacturing of the wooden pieces is caused by the differences between dimensions of pieces in drawings with the dimensions of it that need to be set for the workshop machinery. These changes are not only necessary in the process of sawing pieces, but also in the other processes such as assembling and making the details. Therefore, during the process of manufacturing and production of the wooden pieces, there are a lot of changes on the dimensions of a component in the production drawings and they negatively affect the manufacturing process and, hence increasing the cost and delaying in production. The aim of this research was to find and identify the reasons of these changes in order to mitigate the risks. The research adapted a desktop study followed by direct observations in order to identify the major problems and obstacles. The results showed the problems are mostly due to the tacit nature of design knowledge and lack of proper knowledge of the designers about the actual process of timber production. This research is a novice attempt for expediting timber production process in order to leverage sustainable and modern methods of offsite manufacturing oriented construction

Advanced intelligent agents for optimised dynamic process monitoring and defect inspection in construction projects

Defects and errors in new or recently completed work continually pervade the construction industry. Whilst inspection and monitoring processes are established vehicles for their 'control', the procedures involved are often process driven, time consuming, and resource intensive. Paradoxically therefore, they can negatively impinge upon the broader aspects of project time, cost, and quality outcomes. Acknowledging this means appreciating concatenation effects such as the potential for litigation, impact on other processes and influence on stakeholders' perceptions – that in turn, can impede progress and stifle opportunities for process optimisation and innovation. That is, opportunities relating to for example, logistics, carbon reduction, health and safety, efficiency, asset underutilisation, and efficient labour distribution. This study evaluates these kinds of challenge from a time, cost, and quality perspective, with a focus on identifying opportunities for process innovation and optimisation. It reviews – within the construction domain – state of the art technologies that support optimal use of artificial intelligence, cybernetics, and complex adaptive systems. From this, a conceptual framework for development of a real-time intelligent observational platform (RtIOP) supported by advanced intelligent agents, is presented and discussed. RtIOP actively, autonomously, and seamlessly manages intelligent agents (cameras, RFID scanners, remote sensors, etc.) in order to identify, report, and document 'high risk' defects. Findings underpin a new ontological model that supports ongoing development of a dynamic, self-organised sensor (agent) network, for capturing and reporting real-time construction site data. The RtIOP model is a 'stepping stone' towards advancement of independent intelligent agents, embracing sensory and computational support, able to perform complicated (previously manual) tasks that provide optimal, dynamic, and autonomous management functions

New offsite production and business models in construction: priorities for the future research agenda

Despite the benefits offered by offsite construction, as a percentage, the offsite market is still relatively small. This phenomena is complex; but for brevity, includes a myriad of factors, not least: lack of awareness; supply chain challenges (capacity and knowledge); cultural perception; lack of viable business process models/solutions; and paucity of skills (design/manufacturing/construction). However, many governments are still promoting the offsite agenda through various conduits. Given this, a CIB Task Group (TG74) developed a research roadmap for new production and business models for the construction industry uptake. This paper summarises the work of TG74, where people, process and technology drivers were investigated for construction, manufacturing and design and mapped against three levels of priority and three timeframes. Results indicate that for people drivers, new skills are urgently needed in the design field within a 0–5 year timeframe (compared to a timeframe of 6–10 years for the manufacturing sector). Regarding process drivers, construction process was classed as high priority, followed by design process and manufacturing process. Finally, for technology drivers, construction technology was identified as being high priority, followed by design technology and manufacturing technology, all of which need to be addressed in the medium term. This study presents a roadmap for future uptake