Uncertainty in IoT for Smart Healthcare : Challenges, and Opportunities
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effective healthcare monitoring. Elderly, children or chronically ill people needed
to be examined almost daily. Remote monitoring is an important paradigm for
many real- world applications.
Context-awareness is a major criterion in the healthcare IoT applications.
As it has the ability to find the patient’s condition and the environment where
the patient was located it will greatly assist the healthcare professionals to
understand the variations that can influence the health status of these patients.
In addition to, the change of physical state of the patient may increase the
percentage of its vulnerabilities to diseases and be a cause for his/her health
deterioration [10].
Mahmoud et al. [11] focused on different IoT-based healthcare systems for
Wireless Body Area Network (WBAN) that can enable smart healthcare data
reception and data transmission. the author presented a detailed of resource
management, power, energy, security and privacy related to IoT-based smart
healthcare.
3 Characteristics of the Phenomenon of Uncertainty
3.1 Defining Uncertainty
The concept of uncertainty encompasses multiple aspects and meanings. The
widely spread use of the concept of uncertainty throughout various scientific
disciplines, as well as in everyday language, has caused it to acquire many
definitions.
According to F.H. Knight, uncertainty signifies deviations from the expected
states, which prevent us from the use of any probability for the determination of
a result for a given action or decision [1]. E. Ostrowska follows F. Knight with
the measurable and immeasurable uncertainty theory which defines the former
as risk and the latter as immeasurable uncertainty in its strict sense.
According to A.H. Willet uncertainty concerns changes which are difficult to
estimate, or events whose probability cannot be predicted because the amount of
available information is too limited [16]. A. Jøsang [17] proves that uncertainty
in its strict sense can be measured using subjective logic. Subjective logic is
a type of probabilistic logic that allows probability values to be expressed with
degrees of uncertainty. The idea of subjective logic is to extend probabilistic logic
by also expressing uncertainty about the probability values themselves, meaning
that it is possible to reason with argument models in the presence of uncertain
or incomplete evidence.
3.2 Types of Uncertainty in the Field of Healthcare
Depending on the contexts being studied in the field of healthcare, various types
of uncertainty are distinguished in the assessment of innovative programmes:
parameter uncertainty, structural uncertainty, methodological uncertainty, variability, heterogeneity and decision uncertainty [12].
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effective healthcare monitoring. Elderly, children or chronically ill people needed
to be examined almost daily. Remote monitoring is an important paradigm for
many real- world applications.
Context-awareness is a major criterion in the healthcare IoT applications.
As it has the ability to find the patient’s condition and the environment where
the patient was located it will greatly assist the healthcare professionals to
understand the variations that can influence the health status of these patients.
In addition to, the change of physical state of the patient may increase the
percentage of its vulnerabilities to diseases and be a cause for his/her health
deterioration [10].
Mahmoud et al. [11] focused on different IoT-based healthcare systems for
Wireless Body Area Network (WBAN) that can enable smart healthcare data
reception and data transmission. the author presented a detailed of resource
management, power, energy, security and privacy related to IoT-based smart
healthcare.
3 Characteristics of the Phenomenon of Uncertainty
3.1 Defining Uncertainty
The concept of uncertainty encompasses multiple aspects and meanings. The
widely spread use of the concept of uncertainty throughout various scientific
disciplines, as well as in everyday language, has caused it to acquire many
definitions.
According to F.H. Knight, uncertainty signifies deviations from the expected
states, which prevent us from the use of any probability for the determination of
a result for a given action or decision [1]. E. Ostrowska follows F. Knight with
the measurable and immeasurable uncertainty theory which defines the former
as risk and the latter as immeasurable uncertainty in its strict sense.
According to A.H. Willet uncertainty concerns changes which are difficult to
estimate, or events whose probability cannot be predicted because the amount of
available information is too limited [16]. A. Jøsang [17] proves that uncertainty
in its strict sense can be measured using subjective logic. Subjective logic is
a type of probabilistic logic that allows probability values to be expressed with
degrees of uncertainty. The idea of subjective logic is to extend probabilistic logic
by also expressing uncertainty about the probability values themselves, meaning
that it is possible to reason with argument models in the presence of uncertain
or incomplete evidence.
3.2 Types of Uncertainty in the Field of Healthcare
Depending on the contexts being studied in the field of healthcare, various types
of uncertainty are distinguished in the assessment of innovative programmes:
parameter uncertainty, structural uncertainty, methodological uncertainty, variability, heterogeneity and decision uncertainty [12].