Smart Batteries Using Predictive Data Analytics at Cloud

Project Member(s): Kong, X., Lu, H.

Funding or Partner Organisation: Energywise Pty Ltd (Energywise)
Energywise Pty Ltd (Energywise)
Department of Industry, Innovation and Science (Innovation Connections)
Department of Industry, Innovation and Science (Innovation Connections)

Start year: 2020

Summary: In this project, we design and develop smart battery solution that is driven by Machine Learning(ML) and advanced data analytics for predictive diagnosis and maintenance, IoT enable smart asset tracking, and better support of battery aware applications. The targets of this project include: 1) Extending the lifetime battery through smart battery management; 2) Ensuring smooth operation through predictive and planned maintenance; 3) Improving safety of battery as asset through streaming data analytics; 4) Supporting smart battery-aware applications through uniform interface

FOR Codes: Telemetry Equipment, Pattern Recognition and Data Mining, Machine learning not elsewhere classified

Acknowledgement of Country

UTS acknowledges the Gadigal people of the Eora Nation, the Boorooberongal people of the Dharug Nation, the Bidiagal people and the Gamaygal people, upon whose ancestral lands our university stands. We would also like to pay respect to the Elders both past and present, acknowledging them as the traditional custodians of knowledge for these lands.