Security-Aware Fog-based Efficient Home Monitoring for Elders
SAFE-HOME – Security-Aware Fog-based Efficient Home Monitoring for Elders
CENTRO-01-0247-FEDER-072082 / LISBOA-01-0247-FEDER-072082
Reinforce research, technological development, and innovation
Centro e Lisboa
- LVS – UNIVERSAL, LDA, Project Leader
- Instituto de Telecomunicações
- Universidade de Aveiro
- Altice Labs, S.A.
- CLYNXIO, LDA
Total eligible costs
European Union funding
FEDER – CENTRO 2020: 563 038,44€ / FEDER – LISBOA 2020: 75 339,33 €
SAFE-HOME is an innovative international multi-disciplinary project, which aims at designing a monitoring system for elders to understand their activity level and with the ability to identify emergency situations. SAFE-HOME targets a non-wearable non-invasive and not dependent on users monitoring system, while preserving the privacy of its users. SAFE-HOME targets one of the 2030 sustainable development goals of the UN, namely “Good Health and Well-being”.
SAFE-HOME is foreseen to deliver innovative solutions for providing a non-invasive privacy/security-aware system for home-monitoring of elders, without jeopardizing their independence, autonomy, and without putting too much dependence on the users themselves. Some of SAFE-HOME main innovations can be listed as follows:
- A new line of low-cost high-durability optical fiber sensors for measuring pressure and vibration on the floor, which can be used for monitoring users’ motion in enclosed areas;
- An efficient privacy/security-aware delay-sensitive high-computational fog-cloud network enabling smart-home and eHealth application within buildings;
- A security aware architecture, where the solution works on the security of the transmitted data, while preserving the privacy and identity of the users. The fog-cloud solution targets processing sensitive private data on user’s own fog, while sending anonymous data to the cloud, for privacy reasons;
- The integration of highly non-invasive wearables to help with the monitoring of elderly with low dependence on the user, using advanced technologies, such as wireless charging to avoid the frequent need to charge;
- A suite of artificial intelligence and learning algorithms, capable of classifying variations in perceived regular patterns, e.g., to identify different gait patterns, and different individuals, which can be used in home-security applications;
- A full non-invasive home-monitoring system, tailored for elderly and vulnerable citizens, enabling them to live a fulfilling life, without jeopardizing their autonomy or lifestyle.