Prognosis of actions due to analysis of personal movements and actions in massive multi-user (3D) environments

During analysis of movements of individuals in public places, there are only two dimensions that can represent movement of an individual, shown via data saved between starting and end point, even incorporating elevators and stairs to different (shop) levels). That is a multi-linear way of looking at movements of individuals in crowds in a specific environment. Most big shopping corporates use these kinds of analysis methods.

But what if (like in 3D environments) movement can be up and down as well, or even immediate? Or the environment can change from one moment to the other? This gives us a literally new dimension in data about individual movements, meaning person 'X' in environment 'A' at a certain time will react in a certain way. If that environment is different the next day, the individual has to readjust and react accordingly, as will his contacts.

Going a step further:

If an individual is allowed immediate entry to a certain location or product without having to move physically ("teleporting to a location"), be it 2 or 3 dimensional, how can you analyse the decisions a person will make? If I need three products, but need to walk through the whole shop (IKEA setup) to get them, that is not efficient for me as an individual, even if their statistics are showing that the majority may buy more that way. I do not like shopping in Ikea, I prefer walking 5 streets to visit three shops with humans who can advice me. But that is not analysable?

I think big data should be brought back to what they are valuable for: the individual.

Looking forward to reactions,


PS: Another aspect of big data is future prognosis:

In the 80's, when I worked at Wang education, we had 15 years of data showing which users from which companies had followed which courses (a staggering amount of 500 MB of data ;o) They wanted to destroy that data as it was obsolete (courses we don't organise anymore).

Playing with it, I found out a certain customer had his staff trained on average every three years on new versions and/or platforms. The data implied the customer was ready for a new upgrade. When I asked the sales representative to contact them, two weeks later we had a new deal. Sounds fab, it is true, but sadly Wang doesn't exist anymore.

What does exist is how big data can predict, and using data on how people move around and communicate together in changing 3D environments is fascinating. I'd wish our servers could handle such big data.


Kind regards,









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Tags: Multi-user, analysis, choices, individual


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