An intelligent healthcare system based on the Internet of Things (IoT) is a collection of smart medical equipment and applications connected to health information technology systems through advanced communication. On a large scale, the Internet of Medical Things (IoMT) consists of billions of devices and sensors transmitting a continuous data stream. It has attracted much attention from researchers due to its wide applications in smart healthcare systems (SHS). It reduces costs by eliminating unnecessary visits, medication management, equipment control, and constructive interaction between doctor and patient. It also enables doctors to make sound evidence-based decisions, accelerating disease diagnosis and preventive treatment. This way, the IoMT benefits doctors, families, hospitals, and insurance companies.
This research topic covers the applications of AI in the scope of IoMT, which mainly include:
a) Body applications: Research in this area includes consumer health and medical/clinical wearables. Popular consumer health wearables include fitness devices, activity trackers, wristbands, sports watches, and smart clothing. On the other hand, clinical wearables are mainly devices that are used according to the doctor's prescription. Some examples are protective smart belts, hip protectors, brain stimulation headsets, etc.
b) In-home applications: The home segment includes Personal Emergency Response Systems (PERS), Remote Patient Monitoring (RPM), and remote virtual visits.
c) Social applications: The most important communities are vehicle health services, emergency response intelligence, kiosk services, point-of-care diagnostic medical devices, and logistics.
Topics of interest include, but are not limited to, the following two major categories:
a) Opportunities:
• Data gathering and pre-processing, and knowledge extraction in IoMT
• Methods of processing/transmitting health data in edge/fog/cloud
• Intelligent techniques to design serious games in public health
• Ambient-assisted living using VR, AR, MR, and Metaverse for public health
• Intelligent monitoring and controlling infectious diseases (such as Covid-19, Zika virus, etc.)
• Intelligent early warning systems to prevent infectious diseases (such as Covid-19, Zika virus, plague, etc.)
• Using IoT for intervention and treatment in public health
• Intelligent systems to prevent Neglected tropical diseases (NTDs), parasitic diseases, and Malaria
b) Challenges:
• Various aspects of trust, privacy, and data security in IoMT
• Examining the reasons for the lack of adoption of IoT technology (for example, not being affordable, etc.)
• Autonomic and reliable methods for IoT-based applications
• State-of-the-art reviews related to the IoT in public health
An intelligent healthcare system based on the Internet of Things (IoT) is a collection of smart medical equipment and applications connected to health information technology systems through advanced communication. On a large scale, the Internet of Medical Things (IoMT) consists of billions of devices and sensors transmitting a continuous data stream. It has attracted much attention from researchers due to its wide applications in smart healthcare systems (SHS). It reduces costs by eliminating unnecessary visits, medication management, equipment control, and constructive interaction between doctor and patient. It also enables doctors to make sound evidence-based decisions, accelerating disease diagnosis and preventive treatment. This way, the IoMT benefits doctors, families, hospitals, and insurance companies.
This research topic covers the applications of AI in the scope of IoMT, which mainly include:
a) Body applications: Research in this area includes consumer health and medical/clinical wearables. Popular consumer health wearables include fitness devices, activity trackers, wristbands, sports watches, and smart clothing. On the other hand, clinical wearables are mainly devices that are used according to the doctor's prescription. Some examples are protective smart belts, hip protectors, brain stimulation headsets, etc.
b) In-home applications: The home segment includes Personal Emergency Response Systems (PERS), Remote Patient Monitoring (RPM), and remote virtual visits.
c) Social applications: The most important communities are vehicle health services, emergency response intelligence, kiosk services, point-of-care diagnostic medical devices, and logistics.
Topics of interest include, but are not limited to, the following two major categories:
a) Opportunities:
• Data gathering and pre-processing, and knowledge extraction in IoMT
• Methods of processing/transmitting health data in edge/fog/cloud
• Intelligent techniques to design serious games in public health
• Ambient-assisted living using VR, AR, MR, and Metaverse for public health
• Intelligent monitoring and controlling infectious diseases (such as Covid-19, Zika virus, etc.)
• Intelligent early warning systems to prevent infectious diseases (such as Covid-19, Zika virus, plague, etc.)
• Using IoT for intervention and treatment in public health
• Intelligent systems to prevent Neglected tropical diseases (NTDs), parasitic diseases, and Malaria
b) Challenges:
• Various aspects of trust, privacy, and data security in IoMT
• Examining the reasons for the lack of adoption of IoT technology (for example, not being affordable, etc.)
• Autonomic and reliable methods for IoT-based applications
• State-of-the-art reviews related to the IoT in public health
