Instrumentation & Measurement Magazine 24-6 - 59

to adapt living environments
to deal with this type
of emergency, ensuring the
measurement of health,
socialization, well-being,
comfort, and hygiene of inhabitants
[7]. Alongside, it
is paramount to implement
the remote monitoring of
people at home, through
tele-assistance and measured
data shared via cloud,
thus ensuring timely health
assistance, while maintaining
social distancing and,
therefore, reducing the risk
of contagion.
Fig. 1. Fundamental proprieties of a smart housing.
living environments " smart " : sensors and monitoring tools
undoubtedly play a key role in this (digital solutions can support
health, well-being, social connectedness, and fun across
the life course [6]). Moreover, it is also important to introduce
these technologies following widely accepted certification
schemes, to regularize these environments and have standard
systems that can be managed according to shared procedures.
In this way, a big amount of data, particularly coming from
ageing people, would be available and could be analyzed
(thoroughly taking into account privacy, data protection and
management matters, in compliance to the " General Data Protection
Regulation - GDPR, Regulation (EU)2016/679 " ). This
would lead to the development of data-driven healthcare and
digital health services that could be extremely useful for the
whole healthcare system, also allowing the delivery of personalized
medicine. AFH should become a key public policy,
and a certification scheme could help the stakeholders become
aware of the issues in the present buildings. Moreover, this
strategy would help to define proper tools and policy frameworks
to support healthy and independent living.
SLEs: Benefits for Ageing People, Also
During Pandemic Emergency
The measurement of well-being, which includes personal,
physical, social, mental, and health parameters, has become a
need in the last several months, during the lockdown period
due to COVID-19 emergency. As a matter of fact, fragile people
should be protected, and smart technologies can limit the risk of
contagion, also supporting the social relations of at-home people.
Indeed, the COVID-19 pandemic has increased the interest
of government, authorities, and public and private healthcare
systems in SLEs for ageing people. There is an urgency
September 2021
The final objective of
AFH is the delivery of
total care in the home environment
(being more
cost-efficient and effective
in terms of health outcome),
especially when
real world social and physical interactions are not possible
for prolonged periods. This includes the cases of COVID-19
quarantine and people requiring particular protection from
a potentially harmful infection (e.g., people with co-morbidities
like cancer or diabetes), who constantly need proper care
assistance. SLEs can provide significant contributions to the
management of an emergency, not only for healthcare delivery,
but also from a social point of view, as described in Table 1.
Role of Measurements and Sensors in
SLEs for Ageing People
Once the housing needs of ageing people are understood, it is
necessary to identify the measurement process, to extract the
parameters of interest using sensors suitable for their measurement
and the appropriate data analysis that will allow
remote monitoring (Fig. 2). Analyzing the (big) data gathered
by these measurement systems (which could be also
merged to clinical data contained in the patient's Electronic
Health Record (EHR)), it is possible to derive indicators of the
inhabitant's health and well-being status. This can help to understand
the proper way to adapt the environment conditions
to the dweller's needs, improving well-being perception and
QoL. In particular, the SLE offers remote monitoring and social
connection opportunities, providing data to be processed
through AI algorithms, deriving useful parameters to support
decision-making (which we can also refer to as " Data-Driven
Decision making, " D3
M [9]) by healthcare providers and caregivers.
The confidence of the decision will surely depend on
the quality of the input information, which in turns depends
on the measurement accuracy of the data provided to the AI
algorithms (whose accuracy contribute to the provided output)
and, hence, on the sensors uncertainties. Indeed, poor
IEEE Instrumentation & Measurement Magazine
59

Instrumentation & Measurement Magazine 24-6

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