Expertise

Research topic:

Monitoring data analytics for smart infrastructure using an advanced machine learning algorithm


Description:

Digital technologies, including sensing technologies, data transmission technologies, and data science, have enormous potential to transform the construction industry. Monitoring data analytics can help to improve the maintenance efficiency and optimise asset life.


New machine learning algorithms will be investigated in order to find a suitable algorithm that will help in analysing the data obtained from civil infrastructure assets. The main objective of the project will be the interpretation of the sensing data acquired from the structural health monitoring system installed on civil infrastructure systems such as metallic bridges, offshore wind turbines, etc.. Machine learning algorithm will help to provide an assessment on the condition of the infrastructure and assist in the decision-making for several aspects, for example, predictive maintenance.

Organizational Affiliations

Past Affiliations

Research Student, School of Engineering, Faculty of Engineering and Physical Sciences, University of Surrey

Education

Electronics Engineering
24/09/201210/06/2016, Bachelor of Engineering(BEng, BE, BSE, BESc, BSEng, BASc, BTech, BSc(Eng), AMIE, GradIETE), University of Sheffield (United Kingdom, Sheffield)
Advanced Control and Systems Engineering
10/10/201609/2017, Master of Science(MSc, MSc, MSci, MSi, ScM, MS, MSHS, MS, Mag, Mg, Mgr, SM, or SM), University of Sheffield (United Kingdom, Sheffield)
Civil and Environmental Engineering
04/02/201918/03/2022, Master of Philosophy(MPhil), University of Surrey (United Kingdom, Guildford)