Kanishka Atapattu
Chief Operations Officer CAMS
RMIT University
Check out the incredible speaker line-up to see who will be joining Kanishka.
Download The Latest AgendaConference Day Two: Wednesday, 10 April 2019
Wednesday, April 10th, 2019
2:00 PM CASE STUDY: Predicting Facility Deterioration and Costs Using Algorithms Leading to Improved Building Asset Management
With costly lifecycle management of buildings that can add up to 60% of an asset’s overall budget, RMIT Engineering Researchers found an opportunity levering a machine learning platform to collect and collate data on the utilisation of their buildings and facilities which enabled them to better predict the rate of deterioration. Using the information gathered, Kanishka and his team were able to reduce the time and costs invested in building maintenance and further extend the life cycle of RMIT buildings. In this session, hear insights into:
- Adopting a data-driven approach to improve building life cycle management
- Integrating the CAMS software across all RMIT buildings
- Using machine learning to eliminate costly and unnecessary maintenance and manual inspections