Dr Kagiso Magowe and his team at Telecommunication and Civil Engineering Departments of RMIT University are engaged in Smart Cities projects that aim at developing IoT infrastructure solutions to maximise the usage and efficiency of public resources (mainly local government assets) using smart sensors.

Such technological solutions comprise end-to-end IoT ecosystems that will enable integration of different types of sensors to collect data for a wide variety of use-case scenarios. The design and implementation of such solutions leverages on the technologies that offers, but not limited to, low-cost, low-power consumption and scalable capabilities. Noting the need to improve the functionality of many local governments, the real time data hosted in the cloud interactive platform, CAMS (Central Asset Management System) developed by RMIT University, will enable Councils to proactively and efficiently manage their assets and resources. Thus, leading to many benefits including but not limited to:

  • Enabling sustainable asset management of facilities and resources
  • Improving decision making, quality of services and delivery provided to the community
  • Using real-time information to bring intelligence into the customer experience and user satisfaction

This new disruptive technology of; connected things, connected systems and connected way of life seeks to shift the old paradigm of processes and procedures by harnessing invaluable data collected from smart sensors.


Dr Kagiso Magowe received the B.Eng. (Hons.) and M.Eng. degrees in telecommunications engineering from the University of South Australia, Adelaide, Australia, in 2010 and 2012, respectively, and the Ph.D. degree in electronics and telecommunications engineering from RMIT University, Melbourne, Australia, in 2017, where he is currently a Research Fellow with the School of Engineering. His research interests include communication theory, information theory, statistical signal processing, application of linear algebra, cognitive radios, localization, Internet of things (IoT) and application of machine learning.