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Episode 86

The IoT platform is generally thought of as networking tech – middleware to connect all the IoT components together – and often it is, but a certain class of platforms, the so-called, application enablement platforms, or AEPs, also provide the development and execution environment for the digital twin.
Listen to this podcast (or read the transcript), the third in a series on the digital twin, where I speak with Jason Schern and Jeff Miller about the dt and its relationship to the AEP ...




Episode 85

The reason the digital twin, or software-defined product, as I prefer to call it, is the most important IoT tech, is because it’s the basis for the unique functionality possible from using the Internet of Things. Going beyond smarts or connectivity, it is this unique functionality that creates value, enough value that results in a profitable IoT product.
Listen to this podcast (or read the transcript), the second in a series on the digital twin, where I speak with Arnulf Hagen about the underlying models of the digital twin, and the high-level ways you can use them to create value ...




Episode 84

The digital twin, or software-defined product as I prefer to call it, is the most important tech in IoT, yet you hardly hear anything about it, when compared to other IoT tech such as sensing, networking and analytics. Maybe it’s because it’s such a new and abstract concept for most people. Well, that’s about to change.
Listen to this podcast (or read the transcript) with Dimitri Volkmann about producing the digital twin for the Industrial Internet of Things ...




Episode 81

There’s no denying it, robots are cool, even more cool when you call them cyber-physical systems, which is what they are, but they’re also IoT systems. And applying the thinking of IoT to robots makes them even cooler and more valuable because instead of being discrete systems, they can be integrated as a component of an IoT environment, working together with other components, to deliver outcomes.
Listen to this podcast (or read the transcript) with Chris Jones of iRobot about the Roomba and its place in the IoT world ...




Episode 74

Let’s face it, deploying IoT within a company, especially a large one, is an exercise in change management. To be successful on this multi-year journey takes a lot of planning, getting your priorities straight, some politicking and a bit of luck. There’s no need to reinvent the wheel, learn from your peers.
Listen to this podcast (or read the transcript) with Maciej Kranz who shares his experience in what works and what fails miserably ...




Episode 73

It seems like predictive analytics gets all the attention these days but generally speaking, it requires either a Data Scientist or a machine learning algorithm operating on lots of event data, in order to predict the all-important dimension of time, at least to any degree of useful certainty. Enter prognostic analytics. In a closed system of uniform conditions, prognostic analytics can make better predictions about the “when”.
Listen to this podcast (or read the transcript) with Moritz von Plate about how the characteristics of this older-school stats make it very well suited for predictive maintenance in Industrial IoT ...


Using the Internet of Things in retail virtualizes the shopping environment so it can be analysed to increase the store’s efficiency in converting foot traffic into sales.
Watch this video (or read this transcript) to see Benoit Cousin discuss how IoT is improving the physical shopping experience and the store’s relationship with its customer ...


Whether the Internet product is a discrete product, a system or infrastructure, more often than not, its end nodes are sitting in the wild – just waiting for a bad actor to get their hands on them. This physical accessibility introduces a new category of attack surfaces that need to be protected against.
Watch this video (or read this transcript) to see Vera Sell discuss edge device vulnerabilities in the Internet of Things and the best practices to follow to secure them ...


Big data analytics is generally answering questions about the past, whereas streaming analytics answers questions about the present. But what if you could bring the two together and answer questions about the present based on what happened in the past?
Watch this video (or read this transcript) to see Eric Tran-Le discuss a state of the art analytics ...