12th March 2018


The goal of this project is to develop a novel integrated decision support mechanism embedding intelligent sensing, communications and data processing methodology for improving sustainability of smart buildings through new insights, approaches and technologies for acquisition, communications, and extraction of useful information from the sheer volume of sensed data in the built environment. To reach this goal, the following research and innovation objectives and sub-objectives will be pursued:

Sensors & Instrumentation : Advancing sensor designs and signal processing for smart buildings.

  • Developing advanced application-specific sensor platforms based on low-power hardware implementation and novel battery-preserving sensing approaches, including ambient, structural sensing, and wearable electronics, for reliable and secure signal acquisition and pre-processing;
  • Developing connectivity for sensors via machine-to-machine (M2M) communication protocols;
  • Developing low-power sensor-level signal processing.

Sensor Acquisition & Communications :

  • Designing energy-efficient Internet of Things (IoT)- and Network of Things (NoT)-based architecture for seamlessly acquiring signals from smart objects.
  • Developing advanced NoT-based protocols enabling intelligent data fusion from smart objects, including static sensors, wearable electronics, vehicle sensors and virtual sensors;
  • Designing communication interface to the cloud.

Data processing & Interpretation :

  • Developing novel near real-time data analytics approaches for extracting meaningful information from the acquired data.
  • Designing new data representation and transform methods for dimensionality reduction including decentralised learning and iterative methods;
  • Designing computationally-efficient, decentralised data mining algorithms for large, distributed and heterogeneous datasets.

Decision Support for Smart Buildings :

  • Ensuring relevance, validity, accuracy and scalability through the application to smart buildings via cross-sectoral utilization of findings and demonstrating the effectiveness of the proposed solutions with close collaboration with end-users.
  • Integrating design findings into a holistic decision support system;
  • Assessing the viability of an integrated system using two testbeds;
  • Developing a data management plan and an open access database of raw and pre-processed data and ensuring semantic interoperability.


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