Analytics on Compressed IoT Data

The Internet of Things (IoT) refers to a paradigm in which internet connectivity is ubiquitous among all kinds of devices everywhere. Associated with this is a massive increase in data collection and use, which has the potential to deliver huge long-term value to people and society. For example, reducing downtime and maintenance costs for production systems, improving autonomous vehicle safety and reducing environmental impact through efficiency improvements.

However, current technology is not prepared to deal with so many devices transmitting and using data simultaneously. To realise the benefits of IoT, an end-to-end framework that considers data compressing and data analysis wholistically is critical.

The goal of this project is to investigate the synergies and trade-offs between data compression and analysis. Specifically, this will involve developing algorithms for doing analytics directly on compressed data and optimising compression for both storage and analytics concurrently.