This is a joint project of Edinburgh Strategic Alliance.
Care homes are energy intensive units as they provide continuous environmental service over an extended period time in a year. This is intensified by high set-points for heating due to a common perception that elderlies prefer a warm room due to their low active and metabolic rate. However, our recently studies have shown care homes are often overheated undesirably. On the other hand there is no clearly defined thermal comfort standard for older occupants in care homes.
The aim of this study is to develop a personal comfort model APP for older residents in care homes based on a previous collaboration project between ESALA and EGIS. The model will collect and analyse the data, both environmental and personal, and produces a personal comfort report and the information is transmitted to the duty manager’s PC/Smart-Phone. Such information would reveal individual needs to enable a responsive individual support and care and it could also become an add-on module to a current smart personal care system.
The model development includes assessing data size or subject numbers needed for a significance test and reviewing the algorithms of machine learning tested in our previous project will be used and optimised to achieve the best predict results and the cross-validation method will be conducted to test the prediction performance.
The study consists of three other major tasks: 1 developing a special designed questionnaire survey to collect personal thermal responses to various indoor conditions in their bedrooms, canteens, lounge and living rooms. 2 developing a method that applies the “peripheral temperature” as the objective indicator of thermal comfort, as there are great portion of dementia residents in care homes. 3 revising the existing APP interface to meet the older occupants’ needs. 4 developing the mobile application.
EdenApp will be reviewed and used to develop the Model APP as it is an open-source data collection platform for its low hardware cost and diversity data collection, including the environmental and personal data for this project. The collected data includes the air temperature, relative humidity, globe temperature, windows opening condition, peripheral temperature and other individual inputs by the use themselves. By applying the technology of Internet of Things, EdenApp sensor synchronize the data with the cloud server in real-time and feed the data flow with the mobile application and it is possible to conduct personalized field study. As an easy-to-use data collection tool, EdenApp is the idea tool to collect subjective data with its functions of Human Interface Guide, colour management method and adding functions such as notifications and cloud account. Compared with conventional paper-based or digital questionnaire, it is easier to use for old occupants and more likely to represent subject’s actual comfort votes which potentially reduce the subjective sampling error.
To make an application please visit the website.
The scholarship will cover tuition fees and provide an annual stipend of approximately £15,009 for the 36 month duration of the project and is available to applicants from the UK, EU and overseas.