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A. Tissaoui and M. Saidi
Structural uncertainty refers to uncertainty surrounding the structure of a
decision model. Variability relates to the fact that individuals are unique and
therefore vary in their outcomes, which may partly be explained by individual characteristics [19]. Parameter uncertainty relates to the fact that the true
value of a parameter is not known [18]. In practice, it mostly refers to imprecise
estimates and standard errors surrounding a mean value, which corresponds to
measurement error. Decision uncertainty is the umbrella term for all uncertainty
surrounding a decision, and can be caused by any other type of uncertainty [12].
Methodological uncertainty can be defined as disparities in the choice of analytic
methods that underpin an assessment [18].
3.3 Sources of Uncertainty in IoT Systems
Several of other factors could influence the occurrence of uncertainty in IoT. Key
characteristics of IoT which influence uncertainty include:
– heterogeneity of devices or Interoperability: Interoperability plays an important role in smart healthcare, providing connectivity between different devices
using different communication technologies. Interoperability between different devices in different domains is a key limitation for IoT success due to lack
of universal standards. the large number of devices used means high diversity
in their calculation and communication capabilities.
– Resources constraints (energy and computational and storage capabilities): the
issue of power use is crucial. IoT devices used for healthcare are connected
with a collection of sensors. A continuous source of energy is required to
drive these devices, which presents a severe challenge in term of cost and battery life. Their computational and storage capabilities do not allow complex
operations support (e.g. cryptographic operations, etc.).
– privacy protection: The security protection is not about encrypting/decrypting user data, but about how a user in a heath community can
use trust information to filter out untrustworthy input when gathering health
information to enhance IoT health security. Due to constrained nature of IoT
device (limited processing and battery life) it is difficult to implement complex security protocols and algorithms. This leads to numerous attacks and
threats in term of security and privacy.
– scalability (connectivity in IoT): connectivity of a growing number of devices
being used every day. A smart healthcare network consists of billions of
devices. can succeed only if it can provide capabilities of sensing to produce
important information.
– data management: In smart healthcare, billions of devices are connected,
which can produce a huge amount of data and information for analysis. in IoT
it will be crucial to utilize appropriate data models and semantic descriptions
of their content, appropriate language and format.
– Network : Intermittent loss of connection in the IoT is fairly frequent. In
fact, IoT is seen as an IP network with more constraints and a higher ratio
of packet loss problems connected with overcoming this issue are related to
transfer speeds and delays in delivery of data;
A. Tissaoui and M. Saidi
Structural uncertainty refers to uncertainty surrounding the structure of a
decision model. Variability relates to the fact that individuals are unique and
therefore vary in their outcomes, which may partly be explained by individual characteristics [19]. Parameter uncertainty relates to the fact that the true
value of a parameter is not known [18]. In practice, it mostly refers to imprecise
estimates and standard errors surrounding a mean value, which corresponds to
measurement error. Decision uncertainty is the umbrella term for all uncertainty
surrounding a decision, and can be caused by any other type of uncertainty [12].
Methodological uncertainty can be defined as disparities in the choice of analytic
methods that underpin an assessment [18].
3.3 Sources of Uncertainty in IoT Systems
Several of other factors could influence the occurrence of uncertainty in IoT. Key
characteristics of IoT which influence uncertainty include:
– heterogeneity of devices or Interoperability: Interoperability plays an important role in smart healthcare, providing connectivity between different devices
using different communication technologies. Interoperability between different devices in different domains is a key limitation for IoT success due to lack
of universal standards. the large number of devices used means high diversity
in their calculation and communication capabilities.
– Resources constraints (energy and computational and storage capabilities): the
issue of power use is crucial. IoT devices used for healthcare are connected
with a collection of sensors. A continuous source of energy is required to
drive these devices, which presents a severe challenge in term of cost and battery life. Their computational and storage capabilities do not allow complex
operations support (e.g. cryptographic operations, etc.).
– privacy protection: The security protection is not about encrypting/decrypting user data, but about how a user in a heath community can
use trust information to filter out untrustworthy input when gathering health
information to enhance IoT health security. Due to constrained nature of IoT
device (limited processing and battery life) it is difficult to implement complex security protocols and algorithms. This leads to numerous attacks and
threats in term of security and privacy.
– scalability (connectivity in IoT): connectivity of a growing number of devices
being used every day. A smart healthcare network consists of billions of
devices. can succeed only if it can provide capabilities of sensing to produce
important information.
– data management: In smart healthcare, billions of devices are connected,
which can produce a huge amount of data and information for analysis. in IoT
it will be crucial to utilize appropriate data models and semantic descriptions
of their content, appropriate language and format.
– Network : Intermittent loss of connection in the IoT is fairly frequent. In
fact, IoT is seen as an IP network with more constraints and a higher ratio
of packet loss problems connected with overcoming this issue are related to
transfer speeds and delays in delivery of data;