Embedded systems used in sensing, internet of things, wearables and robotics are typically resource constrained. Constraints can include computational power and memory, but typically, the key constraint is power. This is especially the case in battery powered or energy-harvesting devices, where the aim is to provide intelligent signal processing whilst respecting these constraints. In this activity, we investigate how to optimize algorithms and data processing to use fewer resources, without adversely affecting performance. Applications include health, environmental sensing and continuous positioning.

Selected Publications

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• Distilling Knowledge From a Deep Pose Regressor Network

  Muhamad Risqi U. Saputra Pedro P. B. de Gusmao Yasin Almalioglu Andrew Markham and Niki Trigoni

  In IEEE/CVF International Conference on Computer Vision (ICCV). 2019.

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• The Cougar Project: A Work−In−Progress Report

  Alan Demers‚ Johannes Gehrke‚ Rajmohan Rajaraman‚ Niki Trigoni and Yong Yao.

  In ACM SIGMOD Record. Vol. 34. No. 4. December, 2003.

  Details about The Cougar Project: A Work−In−Progress Report | BibTeX data for The Cougar Project: A Work−In−Progress Report | Download of The Cougar Project: A Work−In−Progress Report

• Energy−Efficient Data Management for Sensor Networks: A Work−In−Progress Report

  Alan Demers‚ Johannes Gehrke‚ Rajmohan Rajaraman‚ Niki Trigoni and Yong Yao

  In 2nd IEEE Upstate New York Workshop on Sensor Networks. 2003.

  Details about Energy−Efficient Data Management for Sensor Networks: A Work−In−Progress Report | BibTeX data for Energy−Efficient Data Management for Sensor Networks: A Work−In−Progress Report | Download of Energy−Efficient Data Management for Sensor Networks: A Work−In−Progress Report