Energy intelligence for supporting seniors at home
With built-in machine learning-based data analytics, CLEVERGUARD brings insights into seniors' habit changes in a non-intrusive way, supporting them to stay longer at home independently.
Supporting senior people living alone at home, thanks to pattern recognition when using electrical appliances.
To ensure this, the market needs non-invasive, non-stigmatising solutions that respect the privacy of single baby boomers in need of care, while being cost-effective and low maintenance.
Current solutions like home surveillance camera systems or ambient sensor systems invoke concerns and expressions like: “I don’t want Big Brother in my own house” and inflicts the elderly dignity.
Family members are missing solutions that respect the privacy of their loved ones, but also keep track of changes in activity and can inform them with a simple but efficient alert system.
The CleverGuard system is a novel smart-home-monitoring solution for seniors and their caregivers. By measuring and analysing the electric energy consumption of the household, the activities of daily living of the residents are derived, using an easily retrofitable low cost smart meter. Short and long term deviations from the daily/weekly routine are detected. Depending on the urgency a notification or alert to relatives and/or formal caregivers is issued in an user friendly and secure way. Due its non-visible character, the solution is non-stigmatizing, and fosters security, and peace of mind for all stakeholders.
During all project stages, the involvement of the end-users is actively sought and their feedback is used for design and implementation of CleverGuard. The process used, follows the UCD methodology, involving seniors living home alone, their informal and formal caregivers. Three iterations are planned to sharpen the final system:
Acceptance testing of interface mockups and the already available business partner components
1st field trial with a MVP;
2nd field trial with the final envisaged product.
Adding smart ADL detection and classification – by means of self learning big data algorithms – allows detection and analysis of pattern and pattern shift of the user behavior. The activity status recognition is visualized in a secure dashboard for formal and informal carers. Additionally alert notifications can be pushed in potential critical situations.
CleverGuard starts with the commercially available, CLEMAP One smart meter and the corresponding IOT-cloud infrastructure, allowing advanced NILM detection and load disaggregation monitoring.
Expected results and impact
CleverGuard supports the ubiquitous desire of most elderly persons to live as long as possible self-determined and independent. It targets this desire through three main aspects: safety, prevention, and data. It provides:
of appliance usage and related activities of residents, using electric energy consumption low maintenance smart meter in combination with sophisticated data analytics;
of appliance usage, activity patterns and their variations.
and early prevention of potential upcoming risks;
Notification of abnormal situations
Activity status information