In this project, a spectrum monitoring system will be developed to ensure the electromagnetic health along the train lines and to aid with future electromagnetic system integration. It also allows for early detection of electromagnetic interference to resolve any potential issues before it happens. Another application of this project is to ensure the smooth integration of any future wireless systems. Therefore, it is important that the wireless channel within the tunnel system of the SMRT line is well understood. In this project, we perform channel modelling along the SMRT tunnels. Channel modelling allows for future electromagnetic system integration by providing information on optimal location for installation. In order to visualise the electromagnetic spectrum along the SMRT train tracks environment, a software will be developed to visualize the electromagnetic health and provide an early warning system for potential electromagnetic interference.
In this research project, we perform spectrum monitoring along the SMRT lines and use machine learning to identify unwanted electromagnetic signals within the electromagnetic spectrum that can potentially cause interference to the wireless signal system of the SMRT system. Feature extraction in machine learning can be very useful for the identification of undesired transmission and location identification of these signals. We also aim to achieve a channel model for the complex underground environment in the SMRT system through measurements and analysis. These information will eventually be visualised on mobile devices or though web pages. Therefore, a user friendly graphical user interface will be developed for this project.