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The Era of Edgeless Computing - Part 4

Welcome to the fourth 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.


Elephant in the room

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

“The risk of a wrong decision is preferable to the terror of indecision” – Moisés Maimonides

Cities are busy places with lots of things happening in different spaces and at different times of the day. The data that expresses the built environment and the flow of people and things through the city is plentiful, but making sense of it quickly and surely is hard. In the world of data the elephant in the room is decision-making. It is about identifying the problem that needs to be solved, picturing a desirable outcome, assessing the impact and risk of potential interventions, and knowing when the trigger has to be pulled.

Decisions demand intellect, humility and courage. Hurrying decisions isn’t smart, because ill informed action is risky. Procrastinating is even worse, because opportunities can be squandered and situations can quickly deteriorate and lead to harm.

Consider a doctor treating an acutely ill patient in a hospital. The patient’s heart is beating unevenly; she is having trouble breathing and is feeling anxiety and pain. The doctor is considering whether her symptoms suggest a treatment of drugs, ventilation, surgery or just further observation, when the patient has a cardiac arrest. The doctor must now act, based upon best available knowledge. Most of us are not called upon to make life and death decisions, but the consequences of everyday action or inaction can still have far-reaching effects.

In the context of a city, or even a small neighborhood, the choices and potential consequences are many and varied. Consider mobility. Moving people from where they are to where they want to be is a problem with many dimensions. There are different transport options: planes, trains, automobiles, boats, buses, bikes and walking. There are different costs: fares, car ownership and parking, share schemes and each person’s time. And there is the impact on productivity and convenience, energy and land use. There are also different decision time windows: long-term planning, daily optimization and immediate response.

There are many moving parts and normally no single right or wrong answer. Decisions will depend upon such things as cost, journey time and environmental impact. And fewer options may remain after only a short time in a deteriorating situation, such as sudden congestion on a major road. Different people will have different preferences. Somebody travelling on business might select the quickest journey, such as a taxi, paying a premium for getting them to a meeting on time. A cash-strapped student, on the other hand, might sacrifice convenience and select a cheaper option, such as a bus. The bus operator will almost certainly offer a more frequent service during busy periods on popular routes, than in quieter times. And so on.

Data scientists describe this as a multi-variable optimization problem, characterized by a complex data landscape. It is a dynamic problem that changes continuously over time and space. You can visualize the data as a rather complicated graph drawn against multiple axes, looking somewhat like hilly terrain. And like a physical landscape, there will be peaks and valleys in the data when examined under the lens of the different decision criteria. Good solutions are the peaks. Poor solutions are the valleys. The best decision at any moment of time will be a compromise that considers all or most of the different criteria.

We tackle the decision-making problem using genetic algorithms, essentially trial and error involving a massive number of options. The algorithms look to see whether choices are better or worse than what has been considered before, pursuing things that look the most promising and killing off options that are going nowhere. Done well, this builds up a picture of the options that will survive and thrive. Done badly, the algorithms procrastinate and fail to converge towards an answer. Our algorithms exploit approaches that work in nature, powered by unique features of the PlanIT Urban Operating System™ (UOS). This allows:

Genetic algorithms aren’t for every problem that needs solving, but they certainly come into their own whenever there are more than a handful of choices and decision-makers. Used judiciously, they can tame problems relating to the use of land, energy, water, transportation and many other things affecting city life, all of which can be expressed by data.

Decision-making is not for the faint-hearted. But data, used well, can reduce the risk and stress tremendously. It helps frame good decisions when they are needed and assess the influence before the consequences are fully developed. Creighton Abrams, a US Army General in Vietnam, famously said, “When eating an elephant take one bite at a time”. It is pretty good advice when dealing with our elephant in the room.

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
Download the full series as a PDF


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.

www.living-planit.com or follow us on Twitter @Living_PlanIT