Emergency guide system for the elderly

According to EC Eurostat between 2013 and 2080 the working population is projected to decline steadily. As a result, the share of those aged 80 years or above in the EU-28’s population is projected to more than double between 2013 and 2080. Similarly, US CDC (Centers for Disease Control and Prevention) reports show that by 2050, Americans aged 65 or older will mount to 89 million people; this is more than double the number of older adults in the United States in 2010. Based on these projections and bearing in mind the financial burden of hospices and retirement, more and more elderly people with aging problems likely will try to survive in their own domiciles. Even thought this might seem to be a less costly option, on the contrary to the controlled environments such as retirement homes, in the case of emergency there will be no one to guide or help them evacuate their house or building.

Our aim is to implement, deploy and evaluate an emergency guide system, which will navigate elderly people out of the endangered area. This will be achieved by installing off-the-shelf low-cost sensors and beacons to the residency and round the minute tracking of the elderly user. The sensors will be triggered in the event of emergency – such as fire and earthquake – and user will be guided by one of multimodal interaction methods – heat, vibration, sound – that is specifically tailored according to his/her needs. Conducting this research activity as part of the programme will enable the researchers to collaborate in an international level and would be a stepping-stone for creating a larger scale project with partners from other European countries.

Meet the Principal Investigator(s) for the project

Professor George Ghinea - I am a Professor in the Department of Computer Science at Brunel University London. I obtained my BSc. Degree with Computer Science and Mathematics majors from the University of the Witwatersrand, South Africa. I later went on to obtain BSc. (Hons.) and MSc. Degrees, both in Computer Science, from the same university. I was awarded my PhD – Quality of Perception: An Essential Facet of Multimedia Communications - from the University of Reading, UK, in 2000. In it, I proposed the Quality of Perception metric, a precursor of the Quality of Experience (QoE) concept now widely known. However, whilst QoE is still a concept, QoP is a concrete metric. Thus, recognising the infotainment duality of multimedia, QoP not only characterises the subjective enjoyment associated with experiencing multimedia presentations, but also how such presentations aid a person\'s ability to assimilate informational content. My research activities lie at the confluence of Computer Science, Media and Psychology. In particular, my work focuses on the area of perceptual multimedia quality and how one builds end-to-end communication systems incorporating user perceptual requirements. I have applied my expertise in areas such as eye-tracking, telemedicine, multi-modal interaction, and ubiquitous and mobile computing. I am particularly interested in building human-centred e-systems, particularly integrating human perceptual requirements. My work has been funded by both national and international funding bodies – all of it being collaborative work with other teams and stakeholders I have been privileged to be involved with. I have also been honoured to supervise 33 PhD students to completion and to have published over 350 high-quality research articles with them and other research collaborators. Currently, my research pursuits are centered on extending the notion of multimedia with that of mulsemedia – a term which I have put forward to denote multiple sensorial media, ie. media applications that go beyond engaging the by now traditional auditory and visual senses, engaging three of our other human in a realistic manner akin to our experiences of everyday life.

Related Research Group(s)

Interactive Multimedia Systems - Building sensor and media-rich, cross-layer, inclusive e-systems, with an interest in human-machine interaction, sensorial-based interfaces, data visualisation and multimedia.

Smart Technology Advancements in Health and Rehabilitation - Data science/wearable technology and Rehabilitation; Haptic feedback, multi-sensory interfacing and Robotics in Health; Immersion and Engagement in Virtual Rehabilitation; TeleHealth/TeleRehab; Data: using AI and Machine learning to improve health.

Partnering with confidence

Organisations interested in our research can partner with us with confidence backed by an external and independent benchmark: The Knowledge Exchange Framework. Read more.

Project last modified 13/10/2023