The idea of where data may be kept and processed has changed over time. Cloud computing was first used to augment or replace a typical core data center, and now the network edge has joined the club. For storing, analyzing, and processing data, health systems providers have primarily depended on the cloud in recent years. But now every organization including healthcare, and a variety of other industries are figuring out how to effectively evaluate and profit from their data. These organizations are producing huge silos of data and want immediate processing on the data like running analytics to find out the patterns . For now, edge computing and cloud coexists and collaborate; however, due to the rapid spread of the IoT network, the cloud suffers from latency and bandwidth issues, which can become a bottleneck in processing the data in an efficient manner. Hence, in the near future, a major shift in trend is inevitable, and edge computing is undeniably important and the growing trend. With the help of edge computing, the data will be processed near the point where it is being generated. The biggest advantage of edge computing is the ability of computers to compute, process, analyze, and interpret data with the same degree of accuracy but without latency. This would decrease cost, increase productivity, and enhance the patient experience, moving us a step closer to autonomous treatment instead of merely automatic. There are five benefits over cloud computing that are provided by edge computing and fog computing: faster speed of data transmission; less reliance on restricted bandwidth; greater privacy and security; better control over generated data.
Edge computing is keen to revolutionize the healthcare industry through its unparalleled features. It can capitulate the workload of medical professionals by eliminating less important work, such as collecting and managing patient data . Additionally, for rural regions where medical care is behind, it will make health care more sustainable and accessible. Edge computing is most beneficial for systems whose information must be operated on instantly and there is little time for it to be uploaded to the cloud. For example, intensive care device sensors that need instantaneous data processing and order execution, such as closed-loop devices that preserve physiological homeostasis. As sensors grow more precise and intelligent, there is a comparable closed-loop regulation of systems controlling respiration, neurological activity, insulin levels, heart rhythms, and GI functions. Further, a potential example that could exploit onsite edge computing is emergency medical services. By allowing edge computing, critical information can be transmitted in real-time from the ambulance to the hospital, saving time for emergency departments to prepare with expertise to save lives. Moreover, edge computing can be leveraged efficiently in multicampus healthcare systems.
As far as costs are concerned, analysts estimate that the mass adoption of IoT edge technologies will help healthcare organizations save up to 25% of their company expenses. Some of these savings would come from day-to-day technologies like security and surveillance or intelligent building controls, but patient monitoring and participation may be the true breakthrough. Among the edge computing use cases are wearable IoT medical equipment, implantable sensors, and streamlined IoT healthcare systems that rely on big data analytics that could dramatically minimize per patient costs across the spectrum of treatment.
As the Edge computing paradigm is a new idea, there aren’t many lightweight solutions available. Though many studies execute this notion primarily by developing their own edge application that is hardware-specific, they lack the open source component, ease of customization, and adaptability . Further, there is one more technology, blockchain that might be connected with the future edge-IoT ecosystem. It can assist the current edge-IoT ecosystem in processing decentralized end-user requests autonomously and transparently.
- Rong, G., Xu, Y., Tong, X., & Fan, H. (2021). An edge-cloud collaborative computing platform for building AIoT applications efficiently.
- Haseeb, K., Din, I. U., Almogren, A., Ahmed, I., & Guizani, M. (2021). Intelligent and secure edge-enabled computing model for sustainable cities using green internet of things. Sustainable Cities and Society, 68, 102779.
- Ray, P. P., Dash, D., & De, D. (2019). Edge computing for Internet of Things: A survey, e-healthcare case study and future direction. Journal of Network and Computer Applications, 140, 1-22.
Cite this article as:
Mamta (2021) Quick Medical Data Access Using Edge Computing, Insights2Techinfo, pp.1
- Internet-of-Medical-Things (IoMT): An Unexplored Dimension in Healthcare
- Technological Advancements in Healthcare Industry
- AI and Federated Machine Learning for Smart Healthcare