Category: Amazon Kinesis

The University of Pittsburgh, the University of Illinois Urbana-Champaign (UIUC), the University of California Davis Health Cloud Innovation Center (UCDH CIC)—powered by Amazon Web Services (AWS)—and the AWS Digital Innovation (DI) team have built a prototype that uses machine learning (ML) and generative artificial intelligence (AI) to transform the public health communications landscape by giving officials the tools they need to fight medical misinformation, disinformation, and malinformation.

Fleet managers can use Amazon Web Services (AWS) to ingest and analyze fleet driver data. In this post, we share how a large public transit agency in the United States worked with AWS to create a proof-of-concept (POC) to analyze operator behavior and improve its visibility of sudden acceleration-based events.

As the amount of health data increases, different healthcare, life sciences, population health, and public health organizations are working to modernize their data infrastructure, unify their data, and innovate faster with technologies like artificial intelligence and machine learning (AI/ML). In this blog post, we dive deep on architecture guidance that enables healthcare providers to improve patient care.

Education technology (EdTech) company GoGuardian announces the availability of a Go Client library for Amazon Kinesis Data Streams via open source. Go is a widely used language among developers for streaming applications that was previously not available for Amazon Kinesis Data Streams (Amazon KDS).

During the COVID-19 pandemic, educational institutions that operated on in-person model shifted many of their traditionally in-person operations and activities—including grading, assessments and testing, and admissions—to a virtual format, where many had never been before. Educational technology (EdTech) companies around the world used the cloud to help quickly create and scale to meet the needs of these academic institutions while maintaining a consistent and smooth student experience.

The College of Liberal Arts at University of Texas at Austin wanted to make it simple for students, faculty, and staff to contact support agents. This is how they built and scaled a contact center solution on AWS with Amazon Connect that reduced call wait time, cut costs, and more easily resolved technical issues — all while call volume more than quadrupled.

Prodigy Game (Prodigy) has a mission to help every child in the world love learning and make education freely available to students globally. Prodigy’s math game – geared toward learners in the first to eighth grade – allows students to hone their math skills with questions delivered according to their individual needs. As their user base grew, so did the strain on their ability to handle the increasing demands. They turned to AWS.