Category: Amazon Machine Learning

Introduction McKinsey research shows that a remarkable 70% of top tech executives are investing in digital twins, highlighting the growing momentum for this technology. Their goal is to achieve more agile and resilient operations, as digital twins offer a wide range of applications, from remote control and monitoring to complex system simulations, enabling a new […]

Introduction Building a resilient path to post-pandemic recovery requires adaptability to dynamic trends. Therefore, many logistics leaders use predictive analytics to drive supply chain decisions, improve internal operational processes, meet regulatory compliance, and reduce transportation maintenance costs. Use cases for advanced predictive analytics in logistics include transportation management, fleet management, last-mile delivery, and visibility into […]

Introduction Customers in manufacturing, logistics, and energy sectors often have stringent requirements for needing to run machine learning (ML) models at the edge. Some of these requirements include low-latency processing, poor or no connectivity to the internet, and data security. For these customers, running ML processes at the edge offers many advantages over running them […]

In this post we discuss how AWS IoT for Defense and National Security (IoT4D) increases readiness by driving operational excellence for manufacturing and supply chains, improving sustainability for buildings and bases, improving equipment maintenance and uptime, and providing situational awareness at the tactical edge. IoT workloads securely collect, aggregate, and store data from fleets of […]

Introduction Our homes contain everything from dust, cooking fumes, and chemicals released from paint, furniture, and cleaning agents. Add to that polluted outdoor air making its way into our homes through ventilation, and you’ve got a cocktail of toxins floating around between your four walls. Clean air has proven positive health benefits. It can provide […]