Dr Andrew Markham
Governing Body Fellow, Kellogg College
+44 1865 (6) 10729
Wolfson Building, Parks Road, Oxford OX1 3QD
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"!
Jan 2014: Our paper looking at the effect of climatic variations on animal behaviour (with data captured by our ultra-low power wireless sensors) has been published in PloS One!
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)
Accuracy Estimation For Sensor Systems
Hongkai Wen‚ Zhuoling Xiao‚ Andrew Markham and Niki Trigoni
In IEEE Transaction on Mobile Computing. 2014.
Demo: IMU−Aided Magneto−Inductive Localization
T. E. Abrudan‚ Zhuoling Xiao‚ A. Markham and N. Trigoni
In Microsoft Indoor Localization Competition‚ at the 13th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN 2014). Berlin‚ Germany. 2014.
Fusion of Radio and Camera Sensor Data for Accurate Indoor Positioning
A. Markham S. Papaioannou H. Wen and N. Trigoni