Edge Computing & 5G for Digital Transformation in the Industry4.0 era

| December 15, 2018

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Fourth Industrial Revolution (Industrie 4.0) – Role of IoT & Cyber-Physical Systems (CPS) Source: Recommendations for implementing the strategic initiative INDUSTRIE 4.0 by The Industry-Science Research Alliance & Sponsored by the German Federal Ministry of Education and Research.

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RunSafe Security Inc.

RunSafe Security is the pioneer of a patented cyberhardening transformation process designed to disrupt attackers and protect vulnerable embedded systems and devices. With the ability to make each device functionally identical but logically unique, RunSafe Security renders threats inert by eliminating attack vectors, significantly reducing vulnerabilities and denying malware the uniformity required to propagate. Headquartered in McLean, Virginia, with an office in Huntsville, Alabama, RunSafe Security’s customers span the critical infrastructure, IIoT, automotive, medical, and national security industries.

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How AI and IoT Provide Value in Construction

Article | March 24, 2020

Internet of Things (IoT) sensors predominantly provide visibility to an operating stack – enabling access to real-time and accurate operational data. Laying analysis on top of that data produces dashboards and other visual representations but artificial intelligence (AI) extends this further by harnessing the data streams to train models and identify patterns. Observations can then be made by a computer much like a human analyst could but at tremendous speed and scale. AI makes it possible to anticipate and predict events in a robust and scalable way. This can create huge business advantages. In this article, we’ll look at applications of AI and IoT in construction.

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How Will the Emergence of 5G Affect Federated Learning?

Article | March 24, 2020

As development teams race to build out AI tools, it is becoming increasingly common to train algorithms on edge devices. Federated learning, a subset of distributed machine learning, is a relatively new approach that allows companies to improve their AI tools without explicitly accessing raw user data. Conceived by Google in 2017, federated learning is a decentralized learning model through which algorithms are trained on edge devices. In regard to Google’s “on-device machine learning” approach, the search giant pushed their predictive text algorithm to Android devices, aggregated the data and sent a summary of the new knowledge back to a central server. To protect the integrity of the user data, this data was either delivered via homomorphic encryption or differential privacy, which is the practice of adding noise to the data in order to obfuscate the results.

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How Big Data and IoT Are Connected

Article | March 24, 2020

Big data as a term and a field, has been around for some time. It relates to the ways in which we study, analyze and process data sets that are too large to be handled by traditional data-processing software. Data can be described as ‘big’ when it demonstrates the four ‘V’ qualities: veracity (accuracy), velocity (speed), volume (size) and variety (both structured and unstructured). IoT, on the other hand, came much later and relates to devices, data and marrying them together. This area looks at making devices ‘smart’ (anything from watches to kettles) and collecting data about their performance or usage to influence consumer behavior.

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Driving Rapid and Continuous Value for IoT Through an Ecosystem Approach

Article | March 24, 2020

In the wake of the COVID-19 pandemic, manufacturing is roaring back to life, and with it comes a renewed focus on Digital Transformation initiatives. The industry stands on the doorstep of its much-anticipated renaissance, and it’s clear that manufacturing leaders need to not only embrace but accelerate innovation while managing critical processes like increasing capacity while maintaining product quality. Effective collaboration will be key to doing both well, but it’s even more critical as workforces have gone and are still largely remote. As the virus swept the globe, it became apparent quickly that there would be winners and losers. Many manufacturers were caught off-guard, so to speak. Before manufacturing’s aforementioned reckoning, the industry had already been notorious for its slow adoption of the digital, data-centric mindset that has transformed other industries.

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Spotlight

RunSafe Security Inc.

RunSafe Security is the pioneer of a patented cyberhardening transformation process designed to disrupt attackers and protect vulnerable embedded systems and devices. With the ability to make each device functionally identical but logically unique, RunSafe Security renders threats inert by eliminating attack vectors, significantly reducing vulnerabilities and denying malware the uniformity required to propagate. Headquartered in McLean, Virginia, with an office in Huntsville, Alabama, RunSafe Security’s customers span the critical infrastructure, IIoT, automotive, medical, and national security industries.

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