
Mohamed Mohamed Ahmed
About
My research project
Monitoring data analytics for smart infrastructure using advanced machine learning algorithmDigital 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. 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, pipelines, and offshore wind turbines. 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 and life extension.
Experimental works in the laboratory will be conducted for the validation of the proposed algorithm. In addition, further investigation of real structures will be conducted, through the collaboration with industry/asset owners.
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. 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, pipelines, and offshore wind turbines. 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 and life extension.
Experimental works in the laboratory will be conducted for the validation of the proposed algorithm. In addition, further investigation of real structures will be conducted, through the collaboration with industry/asset owners.