This is My Architecture Special Episode Video Series
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Sleep apnea impacts more than 936 million people worldwide. Join AWS builder Karen Hildebrand, PhD as she works backwards from what sleep apnea feels like to a patient to how ResMed CPAP devices and myAir app empowers patients to own their health and finally get a good nights sleep. If you have restless nights due to sleep apnea or know someone who does learn more about how reinforcement learning and cloud connected experiences enable patients to wake up to results. Visit https://www.resmed.com/en-us/sleep-apnea/ for more information.
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Scuderia Ferrari has launched a new fan app that innovates fan engagement through personalization. Utilizing AWS analytics and event-driven architecture, the app provides a unique look behind the scenes of the most successful Formula 1 team. Join builder Adrian De Luca in Maranello, Italy to learn about the app's architecture and meet with Ferrari leadership to understand the future of fan engagement in the sport. Learn how personalization and machine learning based AWS services are delighting fans (the 'tifosi') around the globe.
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Having won 9 gold, 3 silver, and 8 bronze medals along with setting a new world record in the woman's 4x100 freestyle relay in Tokyo 2021, the Australian Olympic Swim team delivered their most successful Olympic games ever.
Join builder Gerardo Estaba on this special episode of This is My Architecture as he explores how Swimming Australia use machine learning in the AWS cloud to assist swimming coaches with their relay order decisions. We explore how historical swimming results and other swimming data are ingested in the cloud, transformed and then used to train a machine learning algorithm that's queried by coaches using a custom app to help them predict swimming times and the best possible relay order.
We dive into Swimming Australia's event-driven architecture for their relay order prediction system, to understand how they ingest, transform and orchestrate data using AWS Glue, AWS Step Functions and Amazon Simple Storage Service (S3). We also learn how they leverage Amazon Athena and Amazon SageMaker to build, train, and deploy the relay order machine learning models, and how they leverage Amazon Aurora, AWS Lambda and Amazon API Gateway to process requests from the coaches application.
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Autonomous flight is just around the corner. The aviation industry projects more than 10,000 un-manned cargo vehicles to maneuver busy airspaces at any given time before the decade is out. In this episode of This is My Prototype we meet AWS customers who, together with the AWS Prototyping team are standing on the leading edge of enabling autonomous flight with the Cloud.
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The Emirates Mars Mission made history as the first Arabic nation to reach Mars in an unprecedented short amount of time. The Hope Probe will now spend two years gathering data from the red planet’s atmosphere, all of which will be ingested into the AWS cloud. Join builder Adrian De Luca on this special episode of This is My Architecture as he learns about the international collaboration between the UAE's Mohammed Bin Rashid Space Centre and the University of Colorado’s Laboratory for Atmospheric and Space Physics. We explore how the probe's imaging instruments were built, the challenges of sending signals in space and processing vast amounts of data. We dive deep into the event-driven solutions architecture to understand how they collect images and telemetry data with Amazon S3, AWS Lambda and Amazon Simple Queue Service (SQS). We also learn how they process it all with using serverless services like AWS Step Functions and AWS Batch, and distribute it to the scientific community through a secure web application built using Amazon Cloudfront, Amazon Cognito and Amazon API Gateway.
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30MHz has built a smart agriculture solution which provides growers with real-time remote crop monitoring solutions to help them optimise irrigation and ventilation, prevent disease or sunscald, improve pest management or predict shelf life. 30MHz and AWS Prototyping team co-developed a prototype to modernise this solution on a serverless architecture with AWS IoT Core and AWS Greengrass to process greenhouse data from the sensors on a local gateway device and continue the operations even offline with intermittent connectivity. In the next step, a machine learning pipeline was built with Amazon SageMaker, to help growers take decisions on climate and irrigation in order to provide optimal growing conditions for their crops.
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