Construction IT from 1975 to 2019

In the construction industry, there are four major key performance indicators: safety, time, costs and quality. The application of information and computational technologies allow the construction practitioners to select the economically viaable solutions that can reduce time, improve safety performance or quality. For example, an additive manufacturing system which utilises many mobile robots print a large building structure. Wavelet neural network-based approach compresses data into low- and high-resolution surfaces to detect concrete cracks and other damages. That successfully overcomes the problems of labour inspection such as labour intensive, personal judgment and experience that’s prone to error. Convolution Neural Network performs feature extraction and predicts crack in a fully automated manner. In this research, we aim to compare and contrast the innovative construction informatics that achieve at least one of the four KPI in the construction industry and academic research:

 

1) artificial intelligence and natural intelligence

2) additive manufacturing,

3), knowledge and information sharing,

4) automated tools outside categories 1-3. We apply the abovementioned keyword search to study all the publications published academic databases Web of Science and Scopus from 1975 to 2019’s abstract. We then utilise the Social Network Analysis (SNA) method to study the major research that is studied in the construction industry research in all year long and evolution overtime. This approach not only allows us to see the major types of the research that the universities and research institutions have done, but also provide a research agenda to the latest research. After that, we also study the innovation that received patent according to those indexed in the Google database. A patent is an exclusive right granted for an invention and those who awarded patent must show new innovative idea exists in the invention. Apart from that, we use the abovementioned keywords in Google database to search for the 1) artificial intelligence and natural intelligence 2) additive manufacturing, 3), knowledge and information sharing, 4) automated tools to identify the construction companies’ research and development (R&D) in recent three decades. Evolution of the changes in R&D is also studied. Comparison between academic research, patent and general website information provided by the search engine Google allow us to understand the differences in the development of the informatics. Our research results show that many of the academic research sheds light on modelling, data, decision making and construction operation. On the other hand, many of the patents’ products are developed by using artificial neural network to predict the performance or construction device for building process. Keywords : artificial intelligence, patent, construction industry