Ever shorter response times, increasing volatility and almost unmanageable complexity are bringing production challenges into sharp focus. But the IIoT is providing a new architecture for factory automation which enables an ultra-flexible production concept for companies – for greater adaptivity and resilience.

The Otosense SMS technology solution consists of an edge device called Smart Motor Sensor (SMS), Android and iOS mobile applications to provision the device, web dashboards to visualize the data, and AI based analytics and REST API services hosted in the cloud.

IoT-connected sensors with cloud-based geolocation capabilities allow organizations to monitor assets over large geographic regions. With this technology in place, retailers can work directly with their manufacturers and logistics partners to mitigate potential delays in the supply chain while managing customer expectations.

The OPC Foundation continues to forge ahead with technology advancements. Recent highlights include the launch of the UA Cloud Library developed in conjunction with CESMII and completion of the second release candidate for the OPC UA FX (Field eXchange) specifications that is part of the FLC initiative.

New automation and machine control networking solutions include direct integration of OPC UA Pub/Sub for real-time communication, a server inference engine for increasing machine learning requirements and a TwinCAT/BSD Hypervisor that increases availability through integrated virtual machine environments.

Looking at industry and the need for fully Ethernet-based networks, Single Pair Ethernet (SPE) offers a promising solution. SPE only requires two wires to transfer data and power and is designed in a way that, over an entire network, all machines can talk in the same language.

Top predictions for edge computing are related to technology advancements, hybrid edge-cloud architectures and impact to industries. The effect of edge computing on blockchain, and other digital ledger technologies, will become clearer in a few years. Similarly, 5G’s impact on edge computing is still too early to predict.

Enabling AI capabilities at the edge can improve operational efficiency and reduce risks and costs for industrial applications. Choose the right computing platform for your industrial AIoT application by addressing specific processing requirements during implementation.

Industrial edge computing can mean data are processed locally and never leave the site, or data can be forwarded for processing to a central platform. Hybrid systems with a mix of local and centralized data processing are the most common model used in practice but the key is potential advantages…

Wireless and cellular networks offer an array of solutions for IoT deployments. Identifying the parameters of the use case, and the nature of the deployment, is very important as companies optimize their communications networks for IIoT applications.