Four leading healthcare shows under one roof

25 - 26 September 2018

ExCeL London

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Four leading healthcare shows under one roof

25 - 26 September 2018
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Using IoT for Enhanced Glucose Monitoring

Medilync was founded with the goal of revolutionising the way diabetes is managed and treated in a value-based care landscape. In the value-based landscape, a deep understanding of the patient and the ability to make recommendations about lifestyle choices are crucial to long-term success.

The Problem

Medilync creates an all-in-one telehealth device, called Insulync. Composed of a glucose meter and insulin pen reader, Insulync enables doctors with the ability to interact with patients in a more impactful way, leveraging near-real time analysis of data feeds on blood sugar levels, insulin dosage, pulse, and blood pressure. With the sensitivity of the personal data that is captured with the Medilync smart glucometer, there are a number of challenges.

  1. How to register and identify the devices as known devices and belonging to a given patient.
  2. How to securely and reliably send data to the cloud at scale.
  3. How to send commands and configuration to the device itself in a secure way.

Overview of the Solution

In January 2015, Medilync developers spent several days on site at Microsoft with developers from the Technology Evangelism and Development (TED) team working to find a solution to these challenges. The solution to these three challenges comes in the form an open source project called Nitrogen (nitrogen.io). Nitrogen is a set of IoT components that leverage Azure and its premium services such as Azure Event Hubs, while providing security, scale and reliability, similar to the Azure IoT suite.

Azure Event Hubs are very high scale queues and buffers for the ingestion of telemetry data. Each Azure Event Hub is capable of handling up to one gigabyte of data per second and can then optionally hold that data up to 30 days while the consumers of that data process it.

By default, Azure Stream Analytics can consume data directly from Azure Event Hubs. Azure Stream Analytics processes data in near real-time and can perform actions based on pre-defined rules. This allows a SQL like query language over the top of real time streams and join that with existing data to look for clustering and anomalies.

In addition, Medilync uses HDInsights to do processing of historical data for additional insights. Azure Event Hub can handle up to 30 consumers at one time, so an additional consumer was used to pull data and store it in HDFS so that HDInsights could get to it. HDInsights is a PaaS (Platform as a Service) implementation of Hadoop. The output from the HDInsights processing is stored in MongoDB database which feeds dashboards and long-term reports since. Additionally, Medilync uses Azure Mobile Services to notify mobile apps that changes, or updates are available based on this data processing.

 

Come and visit Medilync at stand J78 to find out more.

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