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Episode 65

If you’ve been listening to my show for a while you know I’m a lover of IoT platforms. It just doesn’t make sense to create your own plumbing from scratch – especially since there are so many beauties to choose from that sport business models that are so agreeable early on. But what about open source platforms – are they ready yet for primetime?
Listen to this podcast (or read the transcript) where I speak with Hans Scharler about where open source platforms are today, and when it makes most sense to use them ...




Episode 64

It’s no secret that the IIoT is enabling manufacturing to go through its next revolution. Some call it Industrie 4.0, but it goes further than the shop floor. The Industrial Internet (of Things) is virtualizing the entire manufacturing industry from supply chain to factory to distribution and along the way is having a profound effect on the workforce and the equipment used.
Listen to this podcast (or read the transcript) where I speak with Tanja Rueckert about the hot topics of connected manufacturing and asset intelligence ...


Until recently we could perform Internet of Things computations in four general areas: We could compute in an external cloud, which means on one or more servers in a data center somewhere remote. We could compute “on prem”, which means on one or more servers in the enterprises’ local network. We could compute in the fog, which means on a gateway in the OT (Operational Technology) network or on a router or switch or some other network node in the IT (Information Technology) network. Or we could compute within in the IoT device or product, which means on an on-board embedded device.
Watch this video (or read this transcript) to see Jurgo Preden discuss the state of the art in Mist computing ...




Episode 57

Driverless cars, or autonomous vehicles, are the ultimate consumer IoT product. They represent the state of the art in sensors, apps and analytics but they share the same DNA as say, a smart lock. Whatever’s under the hood, driverless cars will save lives, save time and save fuel.
Listen to this analysis episode with Bruce Sinclair where he discusses why driverless cars are coming so fast and the IoT technology under the hood ...


Traditional System Integrators (SIs) are setting their sights on integrating the systems of the Internet of Things. And why not; due to networking inoperability and the immature state of IoT platforms and their corresponding ecosystems, for the foreseeable future most enterprises deploying IoT are going to need a helping hand.
Watch this video (or read the transcript) video to see Jayraj Nair discuss the ins and outs of working with a System Integrator (SI) on your Internet of Things project ...


The key to value creation in the Internet of Things is the model. The model is used by both the app and analytics. It quantifies the value proposition, so the better the model, the higher the value. Developing these models in traditional markets is time consuming enough but given the volume, velocity and variety of IoT data, the load on the IoT data scientist can be overwhelming. Enter machine learning or ML for short. Machine learning can augment the skills of the data scientist by helping to select the algorithms or weighted ensemble of algorithms that provide the underlying structure for the model.
Watch this video (or read the transcript) video to see Rob Patterson discuss how machine learning is being used to help create and maintain Internet of Things models ...