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Episode 54

IoT consumer products are more expensive than their traditional counterparts, often by order of magnitude. Not good but makes sense - the tech needs to be financed. But however innovative the products are, higher pricing will cause a headwind. Part of the problem is consumer IoT products are still being sold with traditional product business models.
Listen to this podcast (or read the transcript) where I speak with Nate Williams about the opportunity to innovate consumer IoT business models ...


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 ...


In the data science of IoT there’s no one size fits all data model. Each situation needs to be analysed separately by your data scientist. Then the output too, needs to be custom tailored to your customer - internal or external. This output, often in the form of a dashboard, is critical in aiding the identification of value with your data. Therefore, iterate on its design as often as you do on the design of the IoT product.
Watch this video (or read the transcript) to see Christian Mastrodonato discuss standing up an Internet of Things Pilot from a Data Scientist’s perspective ...

This IoT Inc Business Meetup features John C. Mein, Vice President of Sales, Business Development and Fundraising at Petzila. Join to meet the Silicon Valley ecosystem in person or watch the stream ...


Creating the local intelligence for an Internet of Things product requires special programming skills and knowhow to work within constrained environments. Environments possibly constrained by computing, networking, memory, power or all of the above. The effort to reduce manufacturing costs produces these constraints but sometimes the biggest costs are the ones you didn’t plan for.
Watch this video (or read the transcript) to see Peter Hoddie share his deep experience in programming constrained devices and the (business) issues to consider when planning development ...


The digital twin, as GE refers to it, or the software-defined product (SDP) as I teach it, is the critical component of incremental value generation in the Internet of Things. It’s always overlooked at the expense of the shiny things… and that’s a mistake. The digital twin or SDP is central to the IoT product/system/environment – interrogated by the product app and worked on and improved by analytics – it is the place to start when defining your IoT product requirements.
Watch this video (or read the transcript) to see Hima Mukkamala explain the importance of the digital twin and to put it into the perspective of the IoT platform ...

This IoT Inc Business Meetup features Hima Mukkamala, Head of Engineering at Predix, GE Digital. Join to meet the Silicon Valley ecosystem in person or watch the stream ...




Episode 34

I’m sold. In fact I’ve been sold since early 2014 when I first started digging into the emerging Low Power Wide Area (LPWA) market. I’m sold not because it’s cool tech – I’m sold because its affordable. The price makes business sense for a wide range of IoT use cases – some we’re familiar with and others we haven’t even considered yet due to current cost structures.
Listen to this podcast (or read the transcript) with Hardy Schmidbauer of the LoRa Alliance and Thomas Nicholls of Sigfox about what LPWA is and the different ways it’s sold ...