Edge Mining for Energy Efficient IoT

Ross Wilkins, James Brusey, Elena Gaura, Michael Allen, John Kemp

    Research output: Contribution to conferencePaper

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    Abstract

    Cogent Labs is a world-leading applied research centre at Coventry University, dedicated to analysis and development of sensing-based socio-technical systems. It has a dual focus: robust, deployable pervasive IoT sensing systems for real-life applications at scale; and effective packages for empowering users to maximise the benefits of those systems. Since its inception in 2006, Cogent has quickly become an established world centre of excellence in Internet of Things (IoT). It has attracted several million pounds worth of funding across a wide range of high- impact projects, from sources including The EU, EPSRC, TSB, and a portfolio of direct industrial funding. High- profile partners have included Cambridge University, MIT, Meggitt PLC, Jaguar Land Rover and Orbit Heart of England Housing Association. The group has world-leading expertise in application areas such as physiological measurement (posture; health stress risk prediction), buildings monitoring, and assistive technology (AT). It has made two important world first innovations: real-time on-body posture monitoring and movement analytics; and low-power, robust, unobtrusive home monitoring solutions at industrial scale (over 100 homes within 8 separate projects, with monitoring periods up to 3 years). Both applications are based on the underlying edge mining technology described below.
    Original languageEnglish
    Publication statusPublished - 2014
    EventWorkshop on Internet of Things - a Deeper Dive 2014 - Brussels, Belgium
    Duration: 16 Dec 201416 Dec 2014

    Workshop

    WorkshopWorkshop on Internet of Things - a Deeper Dive 2014
    CountryBelgium
    CityBrussels
    Period16/12/1416/12/14

    Bibliographical note

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    Keywords

    • edge mining
    • internet of things

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  • Cite this

    Wilkins, R., Brusey, J., Gaura, E., Allen, M., & Kemp, J. (2014). Edge Mining for Energy Efficient IoT. Paper presented at Workshop on Internet of Things - a Deeper Dive 2014, Brussels, Belgium.