Category: Technical How-to

Introduction Machine learning (ML) at the edge requires powerful edge requires powerful edge devices with a unique set of requirements. The availability, safety, and security requirements for the edge differ from cloud since they are located at the customer site, outside the data center, and interface directly with operational technology (OT) and the internet. Since […]

Introduction AWS IoT TwinMaker makes it easier for developers to create digital twins of real-world systems such as buildings and factories with the ability to use existing data from multiple sources. AWS IoT TwinMaker uses a connector-based architecture that you can connect data from your own data source to AWS IoT TwinMaker without needing to […]

Introduction Many modern industrial operations require extensive monitoring and real-time decision making for efficiency and safety reasons. To reduce the unexpected network interruption and delay in IoT data processing, edge computing becomes a desirable option for real-time IoT data processing and monitoring. Edge computing is a system of micro computing/storage devices that are installed at […]

Introduction In this second-series blog post, we will continue to showcase a user interface (UI) application at the edge with AWS IoT Greengrass V2, a jointly developed solution by AWS Partner, TensorIoT, and AWS Professional Services. This UI application at the edge contains multiple custom AWS IoT Greengrass V2 components to achieve flexible IoT data […]

Introduction Automakers, fleet operators, and automotive suppliers are recognizing the potential of vehicle data to transform their business models and optimize their operations. However, implementing data-driven use cases is often challenging. Proprietary vehicle data formats, high costs of data ingestion and implementation complexity can slow down innovation. AWS IoT FleetWise is a service that makes […]

Introduction Widely adopted Internet of Things (IoT) communication standards for device-to-cloud and cloud-to-device are typically asynchronous, enabling event-driven patterns to ensure resilience, cost savings, and failure tolerance. However, customers across industries need to enable synchronous communication patterns to ensure time-critical logic in their edge devices. Automotive manufacturers, for example, want their connected vehicles to be […]

Introduction In the first part of this blog series Create insights by contextualizing industrial equipment data using AWS IoT SiteWise (Part 1) we focused on asset modelling and real-time analytics in AWS IoT SiteWise. We created a dashboard in AWS IoT SiteWise Monitor to get a real-time overview of our furnace heating cycles. But we […]

Introduction More and more customers in the manufacturing industry want to collect data from machines and robots located in different facilities into a centralized AWS cloud-based IoT data lake. But the data produced by industrial equipment is often raw data points like temperature and pressure time series. Feeding those raw data streams directly into your […]

Introduction Trying to get started with AWS IoT TwinMaker and need to convert your OBJ file to glTF? Perhaps you have performed a point cloud scan of your environment with Matterport and it’s not clear how you can import the Matterpak bundle into AWS IoT TwinMaker. In this blog, you will apply a model conversion […]

Introduction Industrial digital transformation is driving changes to the Operational Technology (OT) landscape, making it more connected to the internet and IT systems and solutions. With OT/IT convergence, OT environments are leveraging more IT solutions to improve productivity and efficiency of production operations. Industrial customers can use AWS edge and cloud services to securely access […]