Artificial Intelligence Applications in Civil/Construction/Architectural Engineering Education

It is increasingly important to go beyond traditional departmental course curriculum boundaries for some areas of science and engineering education. Artificial Intelligence (AI) is one such field; its applications are very extensive and interdisciplinary. The graduate students should especially be encouraged to learn various applications of contemporary computing techniques including artificial neural network (ANN), genetic algorithm (GA), etc. Civil/construction/ architectural Engineering has exercised a rapidly growing interest in the application of neurally inspired computing techniques. The motive for this interest was the promises of certain information processing characteristics similar to those of the human brain. Soft computing (SC) is an emerging approach to computing, which parallels to remarkable ability of the human mind to reason and learn in an environment of certainty and precision. This paper highlights various applications of AI in civil/construction/architectural engineering especially in SC areas. As an example of a graduate project, this paper demonstrated an ANN and GA based knowledge model where the customer’s preferences regarding comfort and safety issues in a large residential multistory flat housing scheme was studied. Architecture/engineering is an applied science where many lessons can be learned from existing structures, their successes and failures, and incorporating them to find out new techniques for a better structure. This implies that the designer should be able to derive from each previous design some qualitative values, especially on user’s approval regarding building’s safety and comfort quality as to assure a successful design. Architects/design engineers are quite often challenged with soft data, which are linguistic qualitative in nature, and needed to interpret and integrate into their design decision making processes. They should know much about their customer’s desires and requirements, and especially customer’s preferences when it comes to specific design issues. Hence, post-Proceedings This paper highlights various applications of AI through an example and referring other research papers. As an example of a graduate project, this paper demonstrated an ANN and GA based knowledge model regarding comfort and safety issues in a large residential multistory flat housing complex. Through post occupancy of building evaluation, the builders/designers able to assess what elements exceed customers’ expectations and are important in repeating in future projects, as well as the elements that fall short of expectations and may require modification for the next projects. During this process, designers are challenged with soft data, which are linguistic qualitative in nature, and needed to interpret and integrate into their design decision making processes. This paper demonstrated an Artificial Neural Network (ANN) and Genetic Algorithm (GA) based knowledge model of customer’s preferences regarding comfort and safety issues in a large residential multi-story flat housing scheme. The data in the form of a structured questionnaire regarding comfort and safety issues was collected. A five-point scale was used to depict the range of importance from least to most for each issue. A General Regression Neural Networks (GRNN) model was trained and evaluated in order to determine the best representative response for each question. The questionnaire dealing with various issues related to the safety and comfort were grouped into various grouping for GA optimization, and created various scenarios to improve safety and comfort for the studied housing complex one of which was discussed in this paper. It was observed that ANN and GA have exceptional ability to process the qualitative data, analyze, interpret and finally integrate it into a sound knowledge model for architectural design.