Jan 2015: Our paper on novel magneto-inductive localization of underground animals has been published in Methods in Ecology and Evolution!
Apr 2014: We received the best paper award at IPSN 2014 for the paper "Lightweight map matching for indoor localisation using conditional random fields"!
Feb 2014: We received the best poster award at EWSN 2014 for the poster "A Case for Magneto-Inductive Indoor Localization"!
I am a University Lecturer (Associate Professor) in Software Engineering, looking at sensing and communication in extreme and challenging application. Previously I was an EPSRC Postdoctoral Research Fellow, working on the UnderTracker project. I am investigating how to localize people, animals and objects in environments where technologies like GPS fail, such as underground or indoors. Key to this is the use of magneto-inductive tracking and communication. This has been applied to monitoring animals in their underground habitats, allowing for the first time detailed reconstruction of animal trajectories in their underground burrows.
I also worked on the WildSensing project, which used wireless sensor nodes to monitor badger behaviour. My work is typically cross-disciplinary, and one interesting avenue of research was automatically evolving code for distributed computing. This used a computational analog of a biological process, termed a discrete Gene Regulatory Network (dGRN). I obtained my PhD from the University of Cape Town, South Africa in 2008 researching the design and implementation of a wildlife tracking system, using heterogeneous wireless sensor networks.
PhD in Electrical Engineering, University of Cape Town, South Africa (2008):
"On a wildlife tracking and telemetry system: a wireless network approach"
BSc in Electrical Engineering, First Class Honours, University of Cape Town, South Africa (2004)
VINet: Visual Inertial Odometry as a Sequence to Sequence Learning Problem
N. Trigoni R. Clark S. Wang H. Wen and A. Markham
In AAAI Conference on Artificial Intelligence (AAAI). 2017.
Magneto−Inductive Underground Tracking: Principles and Systems
A. Markham‚ N. Trigoni‚ T. Abrudan and O. Kypris
In Elsevier, editor, Underground Sensing: Monitoring and hazard detection for environment and infrastructure − 1st edition. Chapter 8.2. 2016.
Tracking People in Highly Dynamic Industrial Environments
N. Trigoni S. Papaioannou A. Markham