- Effective, robust capture of the application requirements to dictate the specific technology solution sets for the embedded intelligence.
- Determination of the solution spaces for: sensor modalities (temperature, pressure, acceleration, orientation); communications technologies (wired/wireless, near field, far field, frequency, antenna design, communications network topology); power sources (scavenged, mains, battery); processor selection (with/without, I/O capabilities, clock frequency, memory capacity, power requirements, thermal management requirements, packaging solution);
- Multi-variable design trade-off techniques, balancing the cost, quality, time and effectiveness of embedded intelligence solutions;
- Design of standard platforms of hardware and software on an open-research basis.
design for EI
This theme addresses the challenges in creating the whole system form and function to ensure a fit for purpose solution (including cost, functionality, availability, reliability, resilience etc...)
PhD projects with a focus in design include:
- Dimitrios Pantazis co-sponsored by HSSMI "Machine-to-Machine (M2M) Wireless Intelligence"
- Samantha Gunn co-sponsored by Macphie "Microwave Sensor for the Food Industry"
- David Czerski co-sponsored by Renishaw "Remote sensing and positioning by using Galfenol on remotely powered surface wave acoustic devices"
- Gajarajan Sivayogan co-sponsored by AVL List GmBH "Tribo-dynamic analysis of bevel and hypoid gears"