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The Era of Edgeless Computing - Part 3

Welcome to the third of a series of articles to introduce some of the most cutting edge thinking about new computing and network architectures, bringing new forms of machine intelligence to where both digital and biological events occur.

Back to the future

By Peter van Manen, EVP, Research & Development of Living PlanIT

“Prediction is very difficult, particularly if it’s about the future” – Neils Bohr

In our modern world, we look at data to help understand what is working well and what might be done better. The data is often muddled and incomplete, sometimes current and sometimes a little old. Knowing what to do and when to bring about change requires observation, perception, intellect and courage. Change introduces risk as well as rewards.

It is hard enough collecting real data that can be relied upon. Life gets even more precarious when we embark on simulation. Models of complex things are, by definition, only approximations and so are unable to predict many of the subtle nuances of behavior, particularly when things are subjected to sudden changes. Though the endeavor is complicated, understanding our world through simulation is a valuable pursuit. Providing a glimpse of the future, through judicious use of simulation, can provide insight about potential consequences of interventions we are considering. Predicting consequences can reduce the stress and risk of decision-making.

There are some essential ingredients for a meaningful simulation:

The last point is important and easy to overlook. The farther ahead that you want to look, the harder the problem becomes. As we all know, deciding whether it might rain in the next hour is an easier and much less risky prediction than forecasting the weather coming in three days. The good news is that, in the context of operational decisions and interventions in a city, providing foresight of likely events within the next hour can be incredibly useful.

I cannot emphasize too highly the importance of having access to real data, both in setting up and continually verifying and fine-tuning simulations. After all, if we are serious about forecasting events expected in the next hour, we should be aware of what has been happening around us during the previous hour (and what normally happened at this particular time and place on previous days). However, simply replaying the past is not enough. Many small differences, along with the occasional sudden shock, can always create surprises – a great reason not to overextend our prediction horizon!

As far as the model is concerned, Norbert Weiner summed it up with his observation, “The best material model of a cat is another, or preferably the same, cat”. Models are imperfect representations of the truth. Empirical models allow the mathematics to detect patterns in the data, relying heavily upon history and probability. Physical models use the laws of physics to predict how things behave when subjected to external influences. Financial models use theories of economics and the markets to frame decisions and outcomes relating to the movement of money.

The PlanIT Urban Operating System™ (UOS) collects and curates time-series and other data in real-time. It makes this data accessible to higher-level applications, such as business rules, analytics and simulation models.

The UOS exploits distributed processing to allow scale, performance and resilience. It is perhaps unsurprising that a federated modelling approach is also favored. This opens the way for two very different styles of simulation, namely:

The first approach suits modelling of infrastructure, such as traffic and water, in which waves of activity happen across a city, but detailed behavior at troublesome hotspots is important. It can provide a detailed look at a building, street or neighborhood in the context of what is happening across the city and surrounding areas.

The second approach can provide a way of making urgent decisions quickly, by keeping a relatively unsophisticated model tuned and primed, ready to act quickly to assess the likely outcomes of potential interventions.

Maintaining the right level of consistency and coherency across the federation is vital. The prize is better intervention with less risk. This is where Edgeless Computing, enabled by the UOS, comes into play – helping to make cities better, safer and more vibrant places to live.

See more of this series of articles here...
Part 1 – Turtles all the way down
Part 2 – Living in real time
Part 3 – Back to the future
Part 4 – Elephant in the room
Part 5 – Needle in a haystack
Part 6 – Tale of two cities
Part 7 – Need to know
Part 8 – Gut feeling
Part 9 – Welcoming strangers

About Living PlanIT

Living PlanIT is a technology company that created the world’s first Urban Operating System (UOS) which, in combination with the products it supports, unlocks the full potential of data to make cities better, safer and more vibrant places to live.

Living PlanIT has built an extensive partner network around the concept of a shared, unified approach to smart urban technology architecture in which machine intelligence moves ever closer to originating sources of data and control. We call this architecture PlanIT Edgeless Computing™ and it is implemented throughout the PlanIT Urban Operating System™, providing a framework for resilient and secure computer and systems architecture for digital and biological sensing, control, analytics, machine learning, applications and visualization techniques.

Living PlanIT asserts its rights to the following Trademarks: Living PlanIT™, PlanIT Edgeless Computing™, Edgeless Computing™, PlanIT Urban Operating System™, PlanIT UOS™, PlanIT OS™, PlanIT Crumbs™, PlanIT PlaceApps™, PlanIT Valley™, PlanIT Assurance™, PlanIT Labs™, PlanIT Retail™, PlanIT Life™. Any reference to these names in this content shall be considered as an assertion of these Trademarks. or follow us on Twitter @Living_PlanIT