Category: AWS IoT Core

To remain competitive in a marketplace that increasingly views transportation as a service emphasizing customer experience, vehicle capabilities and mobility applications need to improve and increase value over time, much like the internet of things and smart phones have done. Vehicle manufacturers and fleet operators are responding to this change by using data to inform […]

Designing a scalable, global, real-time, distributed system to process millions of messages from a variety of critical devices can complicate architectures. Collecting large data streams or image recognition from the edge also requires scalable solutions. AWS IoT Core is designed to handle large numbers of Internet of things (IoT) devices sending a few messages per […]

The Internet of Things (IoT) brings sensors, cloud computing, analytics, and people together to improve productivity and efficiency. It empowers customers with the intelligence they need to build new services and business models, improve products and services over time, understand their customers’ needs to provide better services, and improve customer experiences. Business operations become more […]

To become more environmentally sustainable, customers commonly introduce Internet of Things (IoT) devices. These connected devices collect and analyze data from commercial buildings, factories, homes, cars, and other locations to measure, understand, and improve operational efficiency. (There will be an estimated 24.1 billion active IoT devices by 2030 according to Transforma Insights.) IoT devices offer […]

This post was co-authored with Michael Brown, Sr. Manufacturing Specialist Architect, AWS; Dr. Rajesh Gomatam, Sr. Partner Solutions Architect, Industrial Software Specialist, AWS; Scott Robertson, Sr. Partner Solutions Architect, Manufacturing, AWS; John Harrington, Chief Business Officer, HighByte; and Aron Semie, Chief Technology Officer, HighByte Merging industrial and enterprise data across multiple on-premises deployments and industrial […]

The ability to analyze your Internet of Things (IoT) data can help you prevent loss, improve safety, boost productivity, and even develop an entirely new business model. This data is even more valuable, with the ever-increasing number of connected devices. Companies use Amazon Web Services (AWS) IoT services to build innovative solutions, including secure edge […]

Federated Learning (FL) is an emerging approach to machine learning (ML) where model training data is not stored in a central location. During ML training, we typically need to access the entire training dataset on a single machine. For purposes of performance scaling, we divide the training data between multiple CPUs, multiple GPUs, or a […]

The IoT (Internet of Things) has accelerated digital transformation for many industries. Companies can now offer smarter home devices, remote patient monitoring, connected and autonomous vehicles, smart consumer devices, and many more products. The enormous volume of data emitted from IoT devices can be used to improve performance, efficiency, and develop new service and business […]

In process manufacturing, it’s important to fetch real-time data from data historians to support decisions-based analytics. Most manufacturing use cases require real-time data for early identification and mitigation of manufacturing issues. A limited set of commercial off-the-shelf (COTS) tools integrate with OSIsoft’s PI Historian for real-time data. However, each integration requires months of development effort, […]

As a manufacturing enterprise, maximizing your operational efficiency and optimizing output are critical factors in this competitive global market. However, many manufacturers are unable to frequently collect data, link data together, and generate insights to help them optimize performance. Furthermore, decades of competing standards for connectivity have resulted in the lack of universal protocols to […]