The Internet Of Everything will be managed in a generalized fashion

Jon Bruner’s nice post The next industrial revolution: It’s all about software, but it’s a little harder than that suggests a generalized software solution it not a good idea for managing the IOE.

Actually, software is abundant, yet search results still have little context. What is lacking is context and organization.

I agree that doing things unilaterally won’t work. But, seems to me that a generalized approach is the only thing that will work. Stephan Wolfram proved that only 3 to 4 initial conditions are needed to create all the complexity required to manage anything. That’s how evolution works. People keep missing the IOE forest for the shiny trees. Everything has truckloads of info from sensors, and decision flow to actuators, but how are gazillions of interdependent decisions made in real time?

How about a system that mimics how the human body works? How biomes work? It’s already proven, and most repetitious decisions happen autonomously.

Evolution’s initial conditions are deceptively simple:

  • Nodes: private property, and imply local scope. Larger scope and data should be aggregated.
  • Connections: how things are differentiated and communicate. Infinite scope, so data winnowed at source, by source.
  • A classification system that gives everything a relationship and value.
  • Then, take a step forward (add value first): the process of iteration: Gather resources and feedback. Integrate. Add value.
  • Trade the value, broadcast winnowed info.
  • And what most don’t understand, excrete what no longer has value locally!

People regularly err at:

  • Private property. Symptoms are ad based revenue models, and privacy concerns. Connections define nodes. If they didn’t, things would just be a morass.
  • And they don’t excrete. Symptoms are info overwhelm. And older stuff should be aggregated unless there is a good reason.

In time, IOE’s fragments must simplify to this integrated model. There is no other proven way to robustly organize complex non linear systems. Artificial Intelligence, a misnomer, is not in competition with evolution, its a subset of evolution, which is always trying to maximize future options in a timeframe.

Everything seems to be a story. IOE’s beginning are sensors, the end filled with actuators. The middle hopefully makes valuable decisions.

Castpoints uses a generalized data framework so that any data can be input, within a context.

Classification tree

  • Tier 1 (anyone, kids, teens, grown-up, unoffensables)
    • Tier 2
      • Tier 3 (etc.)
        • Item’s (or role’s) short description
          • Birth
          • Status
          • Location
          • Value
          • Visibility scope (role, role classification, event, public)
          • News made here; scope managed by liaison
          • Tags or stipulations (describes the rest of item, if needed)
            • Labels (temp, density, etc.) so we know what we are talking about.
            • Value (can be summed, or averaged, up the event level). These can be numbers or text
            • Units (°F, °C, °K, etc.)
            • Value tally scope (role, event, public)

Another article about the emerging data standards. My response, “They are all going to fail! Google needs so much mining because their method of valuing items is indirect with little context. The shear mass of data will soon evolve to mimic the way nature organizes data: encoded via a self adapting classification system that provides context for the item label, value (numerical, or text), units, timestamp, location, prices, and ownership. Data is then aggregated up in larger scopes, preserving privacy. Decisions made by people and machines are then sent to actuators that will send feedback. Huge integration is what makes it all work at any scale.”


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