Uncertainty in IoT for Smart Healthcare : Challenges, and Opportunities
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– Quality of Services (QoS): the quality of services is an important parameter
used in the healthcare services which is a highly time-sensitive system. Numerous challenges exist to meet the quality requirements of IoT-based applications in terms of energy efficiency, sensing data quality, network resource consumption, and latency. The quality of body sensors determines the accuracy
and sensitivity measurements provided by a sensor.
3.4 Causes of Uncertainty in IoT Systems
Uncertainty is one of the key problems for most IoT systems based on RFID
(Radio Frequency IDentification) technology. Listed below are causes of uncertainty relating to the following fields [20]:
– Inconsistent data (unbounded data, data conflict): RFID tags can be read
using various readers at the same time therefore it is possible to get inconsistent data about the exact location of tags;
– Incomplete data (Noisy data, data loss): tagged objects might be stolen or
forged and generate fake data.
– Ambiguity Data (plausibility, imprecision): sometimes radio frequencies might
cause data to be reflected in reading areas, so RFID readers might read those
reflections;
– Missing readings: tag collisions, tag detuning, metal/liquid effect, tag misalignment;
– Redundant data: captured data may contain significant amounts of additional
information;
4 Findings and Recommendations
4.1 Research Challenges
a) How to guarantee connectivity of massive IoT devices in a wide range during
high mobility?
b) How to guarantee resource management in highly dense network?
c) How to utilize power/energy of IoT devices?
d) How to extend IoT devices battery life?
e) Incorporating devices for retailer locked-in services.
f) Secure integration and deployment of services (cloud-based) at both device
and network levels.
g) Early detection of both outsider and insider threats.
h) Standardized security solutions without delaying data integrity.
4.2 Major Requirements
– adaptation of trust management mechanisms, similarly to what was already
adopted for P2P and grid systems and technical security policies;
237
– Quality of Services (QoS): the quality of services is an important parameter
used in the healthcare services which is a highly time-sensitive system. Numerous challenges exist to meet the quality requirements of IoT-based applications in terms of energy efficiency, sensing data quality, network resource consumption, and latency. The quality of body sensors determines the accuracy
and sensitivity measurements provided by a sensor.
3.4 Causes of Uncertainty in IoT Systems
Uncertainty is one of the key problems for most IoT systems based on RFID
(Radio Frequency IDentification) technology. Listed below are causes of uncertainty relating to the following fields [20]:
– Inconsistent data (unbounded data, data conflict): RFID tags can be read
using various readers at the same time therefore it is possible to get inconsistent data about the exact location of tags;
– Incomplete data (Noisy data, data loss): tagged objects might be stolen or
forged and generate fake data.
– Ambiguity Data (plausibility, imprecision): sometimes radio frequencies might
cause data to be reflected in reading areas, so RFID readers might read those
reflections;
– Missing readings: tag collisions, tag detuning, metal/liquid effect, tag misalignment;
– Redundant data: captured data may contain significant amounts of additional
information;
4 Findings and Recommendations
4.1 Research Challenges
a) How to guarantee connectivity of massive IoT devices in a wide range during
high mobility?
b) How to guarantee resource management in highly dense network?
c) How to utilize power/energy of IoT devices?
d) How to extend IoT devices battery life?
e) Incorporating devices for retailer locked-in services.
f) Secure integration and deployment of services (cloud-based) at both device
and network levels.
g) Early detection of both outsider and insider threats.
h) Standardized security solutions without delaying data integrity.
4.2 Major Requirements
– adaptation of trust management mechanisms, similarly to what was already
adopted for P2P and grid systems and technical security policies;