11 Healthcare IoT
535
11.6 Major Challenges of IoT Healthcare
IoT e-Health seamlessly connects patients, clinics, and hospitals across a vast
variety of locations to coordinate and orchestrate healthcare. There are, however,
many research issues that must be carefully addressed before it can become viable
for mainstream deployment [1, 9].
11.6.1 Interoperability, Standardization, and Regulation
IoT has generated concerns when it comes to standardization. Manufacturers, end
users, and service providers all require operating standards within and among IoT
focus areas. The issue of standardization is complex because IoT seeks to capture a
diverse range of disciplines that are monitored and regulated by different regulatory
agencies. The issue is further complicated by the stringent guidelines mandated
by guiding medical authorities. For example, in the United States standardizing
wireless medical devices requires a multi-agency regulatory collaboration including
the food and drug administration (FDA), centers for medicare and medicaid services
(CMS), and the federal communications commission (FCC). This means that
companies must carefully evaluate the policies and procedures required by all three
agencies. IoT e-Health will also need to maneuver through a complicated structure
comprised of multiple agencies before IoT e-Health products will become readily
available in the market. These issues are not unique to the United States; e-Health
will come up against similar issues in other areas of the world [1, 9].
11.6.2 Heterogeneity
IoT healthcare applications require a broad range of contextual data obtained
using both different and heterogeneous health sources. Heterogeneity is generally
perceived in two forms [18]:
• Data heterogeneity – Multimodal sensors that are different in structure, format,
and semantics result in significant heterogeneity in data. These data sets can be
inconvenient to share or reuse because they lack formal descriptions.
• Sensor heterogeneity – Integrating several sensors that function at differing
frequencies and require differing network protocols creates issues around interoperability. In addition, combining devices and sensors can create increased
levels of interference. When interference and the ranges as well as the working
frequencies of coexisting wireless networks overlap, the healthcare network
system can be substantially affected, hindering the availability of important data.
535
11.6 Major Challenges of IoT Healthcare
IoT e-Health seamlessly connects patients, clinics, and hospitals across a vast
variety of locations to coordinate and orchestrate healthcare. There are, however,
many research issues that must be carefully addressed before it can become viable
for mainstream deployment [1, 9].
11.6.1 Interoperability, Standardization, and Regulation
IoT has generated concerns when it comes to standardization. Manufacturers, end
users, and service providers all require operating standards within and among IoT
focus areas. The issue of standardization is complex because IoT seeks to capture a
diverse range of disciplines that are monitored and regulated by different regulatory
agencies. The issue is further complicated by the stringent guidelines mandated
by guiding medical authorities. For example, in the United States standardizing
wireless medical devices requires a multi-agency regulatory collaboration including
the food and drug administration (FDA), centers for medicare and medicaid services
(CMS), and the federal communications commission (FCC). This means that
companies must carefully evaluate the policies and procedures required by all three
agencies. IoT e-Health will also need to maneuver through a complicated structure
comprised of multiple agencies before IoT e-Health products will become readily
available in the market. These issues are not unique to the United States; e-Health
will come up against similar issues in other areas of the world [1, 9].
11.6.2 Heterogeneity
IoT healthcare applications require a broad range of contextual data obtained
using both different and heterogeneous health sources. Heterogeneity is generally
perceived in two forms [18]:
• Data heterogeneity – Multimodal sensors that are different in structure, format,
and semantics result in significant heterogeneity in data. These data sets can be
inconvenient to share or reuse because they lack formal descriptions.
• Sensor heterogeneity – Integrating several sensors that function at differing
frequencies and require differing network protocols creates issues around interoperability. In addition, combining devices and sensors can create increased
levels of interference. When interference and the ranges as well as the working
frequencies of coexisting wireless networks overlap, the healthcare network
system can be substantially affected, hindering the availability of important data.