Security-aware fog-based efficient Home monitoring for elders

Project Safe-Home
Project Key Information

Project Status: set-up

Start Date: July 2020

End Date: June 2023

Budget (total): 10972 K€

Effort:  184 PY

Project-ID: C2019/2-4

Project Coordinator

Name: Ayman Radwan

Company: Instituto de Telecomunicações

Country: Portugal

E-mail: aradwan(Replace this parenthesis with the @ sign)av.it.pt

Project Consortium

Instituto de Telecomunicações, Portugal

University of Aveiro, Portugal

Clynx.io, Portugal

LVS Universal,Lda, Portugal

CIP Technology, United Kingdom

Manchester Metropolitan University, United Kingdom

Swanmesh, United Kingdom

STARFLOW S.L. , Spain

HOP Ubiquitous, S.L. , Spain

Calboquer S.L. , Spain

Takosan Otomobil Gostergeleri San.ve.tic.a.s. , Turkey

Tiga, Turkey

TURKGEN YAZILIM SANAYI TICARET LIMITED SIKRETI, Turkey

Karel Elektronik San. ve Tic. A.S., Turkey

SBI Bilisim A.S., Turkey

Masaryk University, Czech Republic

Mediatrade, Czech Republic

Code Creator, Czech Republic

medCV.eu.sp.z.o.o, Poland

Poznań Supercomputing and Networking Center, Poland

Health Gauge, Canada

MedSoft Group, Canada

University of Alberta, Canada

IRM, Korea

Altice Labs, S.A, Portugal

Accuro technology S.L., Spain

SMART Health Solutions S.L., Spain

Hamk Smart, Finland

Elive Ecosystems Oy, Finland

Kuori Tech Oy, Finland

Seniortek Oy, Finland

Avarn Security Oy, Finland

Granlund Oy, Finland

Noatek Oy, Finland

Abstract

The continuous ageing of our population is increasing the burdens on already over-exhausted health-care systems. On the one hand, senior citizens in general would prefer to live at the comfort of their own home, with as much autonomy and independence as possible. Such situation would require close monitoring of their health conditions. Hiring home-carers would put high financial burdens on elders, who are usually retired and living on limited budget. On the other hand, this would require a high number of home-carers, which are probably more than the available. Addressing this topic, SAFE-HOME plans to design a home-based non-invasive monitoring system for elders, enabling them to live a fulfilling life at the comfort of their home, with complete autonomous and independence, yet with the needed continuous connection to the care takers, while invisible.

SAFE-HOME is a multi-disciplinary project, which exploits the intersection of a number of disruptive technologies, namely sensor design, artificial intelligence and machine learning algorithms, and recent advances in wireless networking, with emphasis on the interoperability of fog-cloud. The project aims at designing a system for monitoring the activity and movement of elders within a confined space (Home), in order to understand their activity level, with ability to identify emergency situations for alerting specific personnel, based on emergency type (e.g. medical staff, ambulance, or emergency contact). SAFE-HOME will also consider users surrounding information (e.g.: neighbourhood and city information) in order to enrich solution results. It is important to note, here, that the system is required to be non-invasive and not dependent on the user; hence, for instance, wearables, although can be integrated, are not main components of the system, since they depend on the user always remembering to wear and charge them (at the right times).

The project commits to create tangible outputs, which includes not only design, testing, and implementation, but also inputs to standardization, and regulation where relevant. SAFE-HOME is almost committed to the creation of commercially exploitable intellectual property, in the form of a Non-invasive Home Monitoring solution, specifically tailored for elder citizens’ requirements, including relevant information from the smart building and city. Although by definition SAFE-HOME is a research project, multiple independent modules are envisaged as potential products:

a) A suite of low-cost sensitive sensors, suitable for a wide range of usages;

b) Different combinations of sensors, able to infer diverse behaviour of humans, including activity/inactivity levels, unsocial behaviour, long periods of sleeping, etc.;

c) A smart security-aware, delay-sensitive fog-cloud networking;

d) Different machine learning modules, which can easily be tailored to different products and industry.

e) A smart building sensor network and application to interchange healthcare and other relevant social-care information with the smart city. This outcome will be aligned with current international standardization committees (UNE178108 and ITU L.1370) were consortium partners are already contributing.

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