From Conventional to Sustainable SHM: Implementation of Artificial Intelligence in The Department of Civil Engineering, University of Malaya

Computer-based technologies and their applications pervade everywhere in real life, especially in different fields of civil engineering. For example, conventional structural health monitoring (SHM) has been rapidly upgraded to sustainable SHM using artificial intelligence. It is because conventional approaches are challenged by real-time, low-cost, and quality-guaranteed SHM. In this direction, a number of innovative researches have been carried out in the Department of Civil Engineering, University of Malaya. This paper attempts to present the latest developments of SHM-based artificial intelligence in Structural Health Monitoring Research Group (StrucHMRSGroup) and Advance Shock and Vibration Research Group (ASVR). To this end, the applications of artificial neural networks, fuzzy logic, genetic algorithm, data mining, and regression analysis in SHM are presented with the aim of showing the efficiency of these methods.