There are currently thousands of people waiting for organ transplants, with their lives on hold while a successful donor match is sought. This post explores the potential use case on how edge computing could be applied to the issues of organ donation and related areas.

What is edge computing?

We are currently in an era of cloud computing, where the infrastructure, hosting, machine learning and compute power of cloud providers deliver hosted access to a wide range of centralized services to process and manage our data.

With edge computing, the processing and management of data happens closer to the actual source of the data, instead of the data first having to be sent to the cloud to be processed. A typical example would be for IoT devices to collect and transfer data to a local device that includes small-scale compute, storage and network connectivity for local processing of the data “at the edge” before being passed to the cloud.

Benefits of edge computing

There are potentially billions of edge (IoT) devices. Having them all constantly connected and feeding data to the cloud is inefficient and can cause latency concerns depending on the nature of the data. This process can be made more efficient by edge devices. Instead of feeding data to the cloud, it is fed to a local device—the edge—for processing. The device at the edge can then filter and process the incoming data before sending the outcome to the cloud. In turn, this change can reduce the amount of data traversing the network.

<<< Start >>>



<<< End >>>

Organ donation on the edge

How can this help with organ donation, particularly with finding a successful donor match?

In this use case, people themselves are the edge devices collecting data. More specifically, biohackers could have an IoT “edge” device inside them that continuously collects information about that person’s body: blood type, tissue antigens, organ structures, heart health etc.

The IoT device inside that person’s body uses device-to-device communication to talk to other devices it senses inside the bodies of other nearby people. Each respective IoT device collects data about the other person’s body. At the end of the day, the IoT device would have collected data from everyone who walked past during the day.

When arriving home at night, the person’s internal IoT device transmits the data to a local device in the house—the edge. That device analyzes and processes all the data collected during the day with the aim of finding people who have bodies that “match” and would be a suitable organ donor. This data is then transmitted to the cloud from the edge, perhaps forming a subset of a person’s digital twin profile monitoring overall general health. Over time a substantial list of exact donor matches would be collected and stored centrally, with the matched people uniquely identified by the internal IoT device.

Organ matching

Should a person at some point need an organ transplant, blood transfusion or similar procedure, he or she would have over time collected a ready-made list of perfectly matched donors who could provide the donation required.

Depending on the nature of the procedure required, all the matched donors could be contacted to request help in providing blood at their nearest clinic, or even altruistically donating an organ to help someone survive.

Conclusion

This is one possible use case of how edge computing could potentially change the normal ways of doing things, in this case regarding the opportunity to improve the organ donation process. We realize we’ve only scratched the surface and there are many areas such as security, privacy, ethical and cultural concerns to be considered, but maybe there is a kernel of idea here to explore further. There are no limits to the opportunities that advances in technology such as edge computing will provide to improve our future. 

David Wright

Tech Architect Delivery Senior Manager

Subscription Center
Subscribe to Software Engineering Blog Subscribe to Software Engineering Blog