Urban sensing and smart home energy optimisations: A machine learning approach

Md Sumon Shahriar, M. Sabbir Rahman

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

    8 Citations (Scopus)


    Energy effciency for smart home applications is proposed using urban sensing data with machine learning techniques. We exploit Internet of Things (IoTs) enabled environmental and energy panel sensor data, smart home sensing data and opportunistic crowd-sourced data for energy effcient applications in a smart urban home. We present some applications where data from the IoT enabled sensors can be utilised using machine learning techniques. Prediction of small scale renewable energy using solar photovoltaic panels and environmental sensor data is used in energy management such as water heating system. Smart meter data and motion sensor data are used in household appliance monitoring applications with machine learning techniques towards energy savings. Further event detection from environmental and traffc sensor data is proposed in planning and optimising energy usage of smart electric vehicles for a smart urban home. Initial experimental results show the applicability of developing energy effcient applications using machine learning techniques with IoT enabled sensor data.

    Original languageEnglish
    Title of host publicationIoT-App 2015 - Proceedings of the 2015 International Workshop on Internet of Things Towards Applications, co-located with SenSys 2015
    Number of pages4
    ISBN (Electronic)9781450338387
    Publication statusPublished - 1 Nov 2015
    Publication typeA4 Article in conference proceedings
    EventInternational Workshop on Internet of Things towards Applications -
    Duration: 1 Jan 2000 → …


    ConferenceInternational Workshop on Internet of Things towards Applications
    Period1/01/00 → …


    • Energy efficiency
    • Machine learning
    • Urban sensing

    Publication forum classification

    • Publication forum level 1

    ASJC Scopus subject areas

    • Computer Networks and Communications
    • Computer Science Applications


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