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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 ...




Episode 53


With pundit projections in the billions of devices and trillions of dollars, these are heady times for IoT. But there are challenges – big challenges in our way. This keynote presents how we get from where we are today to an outcome-based economy, realizing the business promise of IoT.
Listen (or read the transcript) to Bruce Sinclair’s opening keynote address at Internet of Things World 2016 on IoT business and technology and the outcome-based economy ...




Episode 52

It’s a symbiotic relationship – the big corporation, in search for that innovative edge, and the small startup, in search for support to get their ideas off the ground. Both have what the other needs – desperately. Coming together they form one type of ecosystem. To be players, all IoT companies – big and small – must be part of one or more ecosystems.
Listen to this podcast (or read the transcript) where I speak with the folks at TechrIot about their approach of bringing IoT companies together ...




Episode 50

As the technology of IoT evolves the concept of a distributed computing environment is becoming increasingly relevant. A key component of this architecture is fog computing, blending the cloud to the edge. Being able to access computing, networking and storage resources locally makes sense for many classes of IoT deployments.
Listen to this podcast (or read the transcript) where I speak with the bigwigs of the newly formed, OpenFog Consortium ...


A solid route to take when developing a consumer Internet of Things product is concept -> ideation -> proof of concept -> prototype -> video -> crowdfunding -> MVP -> beta with early investors -> product. Harvesting your vested customers to become true fans is an incredibly powerful way to take a product to market and doesn’t necessary sidestep traditional funding sources. One of the reasons I like it most however is because it follows my launch philosophy of Design -> Sell -> Build - especially important in IoT.
Watch this video (or read the transcript) to see John Mein discuss the details of how to start with crowdfunding to launch a successful consumer IoT product and company ...




Episode 49

In this episode Bruce recounts recent meetings with clients and discussions with IoT design houses to discuss the current state of the art in data analytics in IoT deployments.
Listen to this analysis episode (or read the transcript) with Bruce Sinclair for the reasons why data analytics isn’t usually considered by clients and why that’s OK ...