Category: Amazon EMR

How can technology leaders rapidly deliver responsible artificial intelligence-based innovation while aligning with the broad spectrum of strict regulatory requirements? The answer is simple: Amazon Web Services (AWS) GovCloud (US) provides the technology that underpins a solid foundation for securely and compliantly building and deploying AI capabilities. Read this post to learn more.

Rideshare demand prediction is a well-explored topic in academia and industry, with abundant online resources offering diverse modeling frameworks tailored to different geographic contexts. A challenge with rideshare demand prediction, however, is that the trip data required to calibrate or train models can be exceptionally large. In this post, we explore the challenges of big data analytics and showcase how ArcGIS GeoAnalytics Engine, a spatial analytics library for the Apache Spark environment, can be used on Amazon EMR to effectively address these problems.

In alignment with Singapore’s ambitious sustainability objectives, the Land Transport Authority (LTA) of Singapore is intensifying its efforts to spur the adoption of electric vehicles. This contributes to the nation’s goal of achieving 100 percent cleaner energy vehicles by 2040, and the effort leverages Amazon Web Services (AWS). LTA has set up EV-Electric Charging Pte Ltd (EVe) to manage the deployment of up to 12,000 electric vehicle (EV) charging points distributed across 2,000 Housing Development Board (HDB) carparks.

The research team at SLU’s Sinquefield Center for Applied Economic Research (SCAER) required vast quantities of anonymized cell phone data in order to study the impacts of large-scale social problems. SCAER needed to store, clean, and process 450 terabytes of data, so it worked with Amazon Web Services (AWS) to create a fast, cost-effective solution for managing its growing quantities of data.

In this blog post, learn how companies operating in AWS can design architectures that maximize flexibility so they can support both cloud and on-premises deployment use cases for their satellite imagery processing workloads with minimal modifications. 

In this blog post, learn a high-level architecture, built on AWS, that uses a graph database to analyze unstructured and structured educational data that can, for example, help inform a recommendation to a student for the appropriate courses to take in their next semester based on multiple personalized data factors.

Maryland Transportation Institute (MTI), an interdisciplinary research and education organization based out of the University of Maryland, focuses on solving complex transportation problems. When COVID-19 hit, MTI was presented with an urgent new problem: the organization was tasked with gathering, processing, and reporting daily transportation data from nearly 65% of the US population. To keep the public safe, they needed more computing power—quickly. They used the AWS Cloud.

Predictive maintenance solutions involve using artificial intelligence (AI) algorithms and data analytics tools to monitor operations, detect anomalies, and predict possible defects or breakdowns in equipment before they happen. To help keep aircraft mission ready, the Air Force turned to PavCon, LLC, (PavCon), a woman-owned small business, to create an actionable predictive maintenance solution powered by Amazon Web Services (AWS).