This is the first article of a new series we will be producing to cover the complexities of this journey towards the full IT-OT convergence in industrial companies.
When implementing a data-based strategy, it all starts with the Data. One of the typical sources to extract data are IoT devices. Knowing which IoT communication protocols exist and how to use them for data communication is essential as they are the ones that make data gathering from them possible.
As organizations‘ appetite for seizing opportunities at the edge grow, scaling from a single use case in one facility to various uses cases in multiple locations poses a significant challenge. This article highlights the importance of implementing an Edge Management and Orchestration tool to efficiently and securely scale edge computing initiatives.
Most industrial companies (up to 77% according to a last-year study by IBM) are working or planning to work with AI and Machine Learning as a means to optimize their operations or enable new revenue streams. And Machine Learning Operations (MLOps) is becoming the paradigm as a work framework for the Data and Infrastructure teams involved.
In industrial manufacturing, the cement industry is notable for its considerable environmental impact and high energy usage. Amid increasing environmental concerns and a drive towards sustainability, edge computing presents innovative solutions to improve supply chain efficiency, sustainability, energy conservation, and product traceability.
According to Gartner, “The technology or service offering must be innovative, impactful and available for purchase for a Cool Vendor.” With Barbara, companies can deploy, run, and manage their models across distributed locations, as easily as in the cloud.