Advanced monitoring and assisted living management, aiming to improve everyday living and enhance the wellbeing of people belonging to vulnerable groups.
Scenario
A social care service provider, for example a care centre for elderly individuals or a nursing home, desires to exploit big data-driven insights, in order to provide added value services to vulnerable individuals. The services pertain proactive and reactive security and protection through smart notifications and personalised recommendations, as well as indoor comfort and quality preservation. Proactivity and reactivity of the aspired services aims at prolonging self-sufficiency and independence of the at-risk individuals, boosting inclusion, and facilitating informed decision making, either by the individuals themselves, or by their (in)formal carers.
Data Sources
The system will analyse and process domain specific data coming from various sources, including, yet not limited to, (anonymised) medical data, smart home sensor data, wearable devices, and other proprietary or external open sources (e.g. weather, social media, health or crime statistics).
Architecture and Operations summary
The demonstrator architecture is graphically illustrated in the following schematic. As per the illustration, the core module responsible for the aggregation of the information from the various sources is the AEGIS platform, which is fed data from the open sources as well as from the platform end users.
The AEGIS web application serves as the main interface for the interaction of the formal carers with the AEGIS platform. The AEGIS platform is assigned the role of the primary processing unit where data from various sources are gathered, evaluated and processed. Data analysis produces sets of general rules and conditions for safety, security, indoor comfort and environmental quality. The web interface provides a supervisory picture of the monitored individuals to the medical personnel so as to facilitate personalised, informed decision making. In particular, the aforementioned rules are fed to the web application, which acts as a server to the end-user’s mobile app, transmitting and receiving personalized data. The rules from the first step become tailored to each individual and/or its living environment, offering, on the one hand, personalized notifications and alerts, and, on the other hand, individualized control actions for the unobtrusive preservation of indoor health and well-being conditions.
Apart from the web interface, the services bundle includes dedicated mobile applications for informal carers and vulnerable or at-risk individuals. The apps are responsible for communicating the personalised notifications, alerts and ambient indoor conditions. In tandem, the apps undertake the job of aggregating personal information (e.g. information from wearable devices and sensory equipment), which is fed to the AEGIS platform and mapped to the extracted rules, leading, thus, to the identification of personalised service offerings. In this context, the web interface acts as a data monitoring system for the shareholders and other core actors, sending alerts and notifications when a high-risk incident is happening, or is predicted to happen with high confidence.
In order to achieve advanced monitoring and assisted living management, AEGIS will leverage a slew of data coming from different sources for improving everyday lives and enhancing the well-being of elderly people. AEGIS will implement a bundle of services and applications addressing the needs of both elderly people and social care services that indicatively enhance elderly’s cognition and strengthen their personal security, health and well-being through the delivery of personalised notifications, guidance and ambience (smart home).