This project aims to consolidate the foundation technology for the sensing and perception functions of a system that is able to monitor passenger behaviour, operational characteristics of passenger trains as they arrive at crowded stations and the condition of key features of trains using the same low cost sensor sets.
Following this, the project aims to integrate this information and uncover means for exploiting it holistically with devised perception algorithms to provide means for sensing and perceiving behaviour, and the subsequent systematic, controlled and predictable influence of passenger behaviour to target larger system objectives and optimistation.
The specific potential outcomes from this project include devising, implementing, and empirically validating and demonstrating:
1. A monitoring system to collect raw data
- Multi-sensor automated, online passenger behaviour, train operations diagnostics, and vehicle condition monitoring real-time during operations raw data sensing and perception system.
2. Algorithms for extracting valued information in real time during operations, specifically:
- Advanced detection technologies and algorithms for passenger behaviours for perceiving behaviours such as passenger flow/movements through the station and predicting future events/situations.
- Downer EDI