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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 62

Repeat this mantra: Privacy by Design, Privacy by Design. Although, Security by Design is a best practice followed by IoT companies in the know, its business counterpart, related to risk, isn’t chanted nearly as often as it should be. Privacy by Design should be repeated with every second breath. In this episode of the IoT Business Show
Listen to this podcast (or read the transcript) where I speak with Paul Plofchan about Privacy by Design and other privacy best practices ...


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 ...




Episode 56

Black hat, white hat… gray hat? What does it all mean? In this context, the different colored hats refer to the different approaches to testing the cyber security of your IT, or in our case, IoT infrastructure.
Listen to this podcast (or read the transcript) where I speak with Paul Jauregui about pen testing and other things you need to know about when working with an external security assessment firm ...


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 ...