Human behaviour model combining multiple sensors

Panel: 5. Energy use in buildings: projects, technologies and innovation

This is a peer-reviewed paper.

Authors:
Liao Zhining, London South Bank University, United Kingdom
Kathryn Buchanan, Department of Psychology, University of Essex, United Kingdom
Mounir Adjrad, University College London, United Kingdom
Nikolaos Vastardis, University of Essex, United Kingdom
Christian Koch, London South Bank University, United Kingdom
Mohammad Ghavami, London South Bank University, United Kingdom
Riccardo Russo, University of Essex, United Kingdom
Kun Yang, University of Essex, United Kingdom
Sandra Dudley, London South Bank University
Ben Anderson, University of Southampton
Navid Ghavami, London South Bank University

Abstract

Occupant behaviour accounts for a considerable proportion of variation in the energy efficiency profile of domestic buildings. As such it is vital that any “smart system” that is designed to reduce energy consumption takes into consideration human behaviour. In the proposed paper we introduce an innovative system currently under development known as DANCER (Digital Agent Networking for Customer Energy Reduction), which aims to reduce energy consumption in domestic dwellings while still retaining desirable levels of occupants’ comfort. One of the ways in which the system aspires to achieve this is by inferring a model of human behaviour from multiple channels of information obtained from different wireless sensors: ultra wideband (UWB) radar and energy consumption sensors – all time stamped to a reference clock (the wireless gateway clock). In the proposed paper we illustrate how information from these multiple channels can be drawn together to infer human behaviour and generate policies that if desired by the end-user can be implemented to reduce consumption via automation. We consider the next steps for DANCER and what success might look like for a smart system from a multidisciplinary perspective.