- Edge Computing Uses IoT Devices for Fast Health IT Analytics
“IoMT is well-suited to meet the needs of the transforming healthcare industry, by supporting the transition from disjointed care to coordinated care and reactive to proactive care-delivery approaches, for example,” report authors stated.
Healthcare organizations are seeking to integrate more categories of IoT devices into their health IT ecosystems.
The report outlines five application areas where IoT devices will benefit clinicians and patients.
- On body: wearable devices, peripherals, and implants.
- In home: digital and virtual assistants, activity monitors, and home medical devices.
- Within the community: automated kiosks, emergency response intelligence, and mobility.
- In the clinic: handheld medical devices, care coordination technologies, and administrative support tools.
- In hospital: real-time location services, patient/personnel flow tools, and smart, connected equipment.
An estimated 4.5 billion IoMT devices accounted for 30 percent of all IoT devices, according to report authors. The immediate response and real-time potential of IoT devices in healthcare make it the leading industry for connected tools and devices.
The report predicted that 20 to 30 billion IoMT devices will be connected by 2020.
The IoT impacts the future of patient monitoring because the devices provide additional information and monitors patients in real-time. Clinicians are able to interact with patients in real-time using the data collected by IoT devices, improving patient care.
Real-time data allows clinicians to collect, analyze, and decide on a patient’s condition during the initial interaction. Real-time environments also lower costs because they avoid bulk processing and overnight loading into data warehouses.
Organizations interesting in using IoMT devices are looking for better and more efficient ways to analyze the influx of data produced by the devices.
The IEEE finds that cloud computing is no longer an efficient enough way to process data produced on the edge of the network by IoT devices.
An IoT device is the edge between the data source, which is the patient, and the cloud. Analytics need to be performed on the edge of the network for real-time analytics to be fully realized.
The IEEE defines edge computing as “enabling technologies allowing computation to be performed at the edge of the network, on downstream data on behalf of cloud services and upstream data on behalf of IoT services. The ‘edge’ is as any computing and network resources along the path between data sources and cloud data centers.”
The IEEE cited the change of connected devices from data consumers to producers as a driving factor behind edge computing. Users are now producing and consuming data on their smart devices. This paradigm shift means that more functionality is needed at the edge.
The number of IoT devices, along with the volume of data they constantly produce, causes bottlenecking for centralized cloud-based computing. Cloud-based computing is more robust and efficient than edge computing on a broad infrastructure scale, but bandwidth restrictions make edge computing the better choice for near real-time analytics.
IoMT devices allow clinicians and patients to actively record data and share it with the network. Organizations implementing broad IoT strategies can take advantage of the number of devices by embracing edge computing, which provides an easier way to take advantage of real-time analytics to improve patient care.
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