Considering the reality of the iOT–generating a heat-map of bandwidth…

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I’ve spent a lot of time on my iOT concepts of stayable, wearable and portable. Systems that operate to provide you with information that you can leverage.

Yesterday I saw a presentation that discussed the concepts of stayable sensors that collect data on a variety of things that people (hobbyists) want to know about. From earthquakes to pending weather the information we gather on our portable devices has changed radically in the past ten years.

This made me think for a bit and I began to realize that my bandwidth question remains valid. But I also realized that the bandwidth issue extends further than I had previously thought.

As I consider the iOT concepts around where the device is (stays at home, something I wear, something I put in my pocket or attach to me in some way) requires bandwidth. Smart systems don’t require much bandwidth unless they are moving video. Weather systems and other types of sensors you leave in your home don’t stretch your bandwidth. Video does but in the end that really isn’t the problem.

There are sensors by the USGS on rivers. These sensors are designed to notify the state government where they are located, municipalities and of course the USGS if the stream, lake or river rises to a flood stage. That information has to be available real time which is a different modality than the can be delayed broadcast of my personal weather station. In fact it changes the modalities and provides an information stratus requirement.

  • Information that is required now. Delay causes people to die. There are any number of sensors that fit into this category and they need access to a real time network.
  • Information that is predictive and helps figure out when the next issue (see previous bullet) is going to happen. This needs to be provided real time as well. If we can via this data predict the next earth quake, then we reduce the number of deaths or eliminate fatalities completely – that’s a really good thing.
  • Useful information that will reduce impact of an event (Hobbyists would use this for their daily or other activities. If the surf is running very high maybe you kayak on the river instead of the ocean etc.).
  • Fun information that is good to know but isn’t critical.

It’s interesting because in the end all of this generates a massive analytics and data movement problem. In the end I wonder if the iOT is missing the boat. It isn’t just the sensors and information provided in the internet of things. It is ultimately the information that drives the iOT. The DiOT. Data becomes the one thing that changes how the iOT interacts. The analysis of that data and the bandwidth to move that data around (from sensor to scientists, hobbyists and data stores) becomes critical. The other matrix to measure all of this against isn’t then just the criticality of the data. Given an old fashioned plot the criticality of the information is the x axis. The y axis then is the delivery modality of that information. Information that is needed right now (critical) has to have a real-time delivery modality. The other quadrants created then are near real time, as needed (push time) time and finally archive. You have to have an achieve to research historical trends. But a historical trend doesn’t have to be real time.

The reality of the iOT and the components that are personal to that stayable, wearable and portable then becomes not only the sensor data but the bandwidth and compute required. Mapping that against the criticality of the information and the delivery modality provides us with a heat map of bandwidth.

more to come…