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Live at IOT Summit Chicago: The Gap between Technology and Reality (or the problem of Data for the sake of it)

rscasny

Hi element14 Community!

 

I'm writing live at the IOT Summit in Chicago at the W Hotel (172 W. Adams). I just listened to a presentation called The Silent Intelligence: Connecting the Data.

 

The gist of the presentation (which every IOT engineer should listen to) is: we are drowning in data and there is a gap between technology and reality. In another words data for the sake of it.

 

Another way of saying it: the analog "real" world problems are not being addressed by the digital solutions because we may not understand the problem that technology is supposed to solve.

 

Eliminating this situation requires the following:

 

  • Understand the problem
  • Break it Down
  • Identify the Data
  • Get the Data

 

Something to ponder....

 

Is our understanding  of IOT too focused on building projects that generate data (i.e., website that market themselves as project libraries)  rather than starting with problem solving and letting the technology follow (e.g., element14 Design Challenges)?

 

Later,

 

Randall Scasny

--element14

  • Sounds like a very useful presentation!

    I get the feeling that in our lines of work and in this community, we're sometime way ahead of knowing what is possible, compared to the product teams who are dealing with understanding what customers want, and providing customers with the ideas with what is possible.

     

    In a way, despite being interested in the technology, maybe we almost need to do the role of a product team, in looking at identifying problems and the real business case for it. A few times I've seen patents not filed, since although it was a novel approach, there really wasn't any value in filing it if there is no strong commercial use.

     

    Also, I forget who originally said it, but there was the concept that when looking to create solutions, it is likely that information is possibly only useful in two ways - one is if it can be used quickly (for example in real-time) when that information could be valuable to solving the problem, otherwise it's usefulness drops, if you're collecting data but not solving anything useful, and may only increase much later if the information is available in a useful manner, e.g. big data and APIs, for solving some other problem. That I guess is far riskier, the information may again become useless if better technologies appear meanwhile, or if cloud services close down, since there are costs involved, or data gets abused, security concerns, etc.