« Descartes was killed by IoT » by Francois Hamon at GreenCityZen

For more than 400 years, since the French

mathematician Rene Descartes came on the

scene, scientists and engineers have been

guided by his approach to problem-solving.

The Cartesian method, also referred to as

rationalism, uses a systematic process to

reduce concepts to their most basic

elements. It’s a top-down method of

analysis, creating a series of what can be

viewed as series of black boxes, each

embedded with a fixed mathematical

function or algorithm. This deterministic approach created the success of the western technology.

Modern mechanics, electronics, and software designs are mostly

inspired by this reductionism or simplification paradigm.

Nevertheless, in the era of the Internet Of Things the Cartesian

models seems to have reached the limit.

Why does Descartes fail to model the natural world?

Cartesian model considers the physical world as the sum of static and unchanging closed systems. It is an

accurate model when talking about things like tables, chairs, or even a truck. But the model doesn’t work

as well when we talk about open systems cohabitating, exchanging with their environment.

As pointed out by Edgar Morin in [1], most of the systems in the natural world are unstable and continuously

compensating to reach a steady state. As example of this complexity, he points to the flame of a candle, the

circular motion of a whirlpool, a growing organism, thermal regulation. All these phenomena are open

systems, because they exchange energy or material with their environment. These natural systems are in a

constant state of change, triggered by external events, and have the ability to adapt themselves to new

conditions. The Cartesian method struggles to account for these types of open systems.

In the 50’s with the cybernetic theory the American mathematician Norbert Wiener[2] really put Cartesian

thinking to the test. Cybernetics is the cornerstone of

modern-day robotics, and a discipline filled with the

complexity of open systems. In presenting his theory

of cybernetics, Wiener addresses the short-comings

of Descartes, and the Cartesian focus on closed-

system models. Wiener emphasizes the importance of

open-system models, and introduces a major

innovation: the feedback link. When a system

generates some change in its environment, that change is reflected with the feedback link that triggers back

a system change. Feedback loops let systems adapt on a continual basis, and give systems the ability to

regulate their own behavior to reach optimal performance.

Cartesian model or “the blind’s margin”

Up to now, when modeling a system in its natural environment the feedback link was rarely available because

it often needs to probe and sense continuously the environment; most of the time in hard to reach locations.

"Wiener emphasizes the

importance of open-system

models, and introduces a major

innovation: the feedback link”

"Modern industry design

is mostly inspired by

Descartes approach”

Not being able to implement feedback loops in

cybernetic systems has given rise to a

workaround, with built-in margins designed to

accommodate variations in operating

conditions. For example, in gas pipelines, the

system typically includes a 30 percent pressure

margin to ensure delivery to the final node. The pressure margin increases the system’s reliability but,

because the margin is often higher than needed, it ends up wasting resources and reducing overall

performance.

Using margins to make up for the lack of a feedback loop has become common practice, especially in system

engineering, because it lets the operator offset any errors in the system model by using kind of insurance to

protect against the unexpected. The waste produced by these margins is seen as a necessary cost, required

to keep the system in balance over time.

Most of systems in the industry or the city, use that kind of margin, leading to waste of resources and

performance reduction. This is the case for irrigation systems, gas and water distribution, lighting

infrastructure monitoring …

The actual Internet of Thing revolution is here

The arrival of the Internet of Things (IoT), brings the Wiener’s theory of cybernetics in a new phase and

gives scientists and engineers a very good reason to stop using the Cartesian model and wasted margins.

The billions of environment-sensing probes, capable of operating in difficult conditions, are ideally suited

to creating feedback loops in cybernetic systems, even

on a very large scale, and enables dramatic

improvements in how we optimize system performance

and manage resources.

The actual IoT revolution is here: our cities and

industries infrastructures can all take advantage of the

cybernetic models and converge to the optimal

environmental performance and resource delivery.

What if the pipe leaks?

To see the advantage of the cybernetic model over the Cartesian one, let’s consider a watering system for a

greenspace. Using the Cartesian method, we take into account the plant’s watering needs throughout the

year, along with historical weather patterns, which help predict seasonal rain amounts. As shown in Figure

1, the model creates a watering plan, identifying delivery frequency and volume, which is then fed to the

pipe model.

Figure 1: Simple Cartesian model

But what if something unexpected happens? Maybe the pipe leaks, or there’s unusual weather. What then?

Best case, the watering plan’s built-in margin compensates for the unexpected and the greenspace survives,

even though there’s water wasted, due the margin, the rest of the time. Worst case, the greenspace dies.

With the cybernetic model, though, we can introduce a feedback loop. We’ll do so by using a sensor,

connected to the IoT, for soil moisture. The resulting system, shown in Figure 2, can automatically adjust

“The IoT, with its billions of

environment-sensing probes,

spells the end of Descartes and

makes cybernetics a reality on a

large scale.”

“Eliminating the blind margin used in

most industrial and urban systems saves

resources and improves performance.”

the watering instructions in response to unanticipated changes in soil moisture, due to heavy rain, drought,

or even a leaky pipe.

Figure 2: Cybernetic model

The IoT sensor adds bottom-up data to the model, and thereby reduces waste and makes it easier to

highlight and react to unanticipated events. Having the system use an interoperable connection to an

external data source, through the IoT, also creates an efficient way to track external effects on the system.

Each element in the overall system can have the ability to operate autonomously and, over time, the model

becomes dynamic, since it has the ability to auto-correct.

The Death of Descartes

Internet of thing is essentially a way to connect the traditional internet with the physical world.

The IoT puts an end to the reductionist paradigm put forward by Descartes. The IoT lets us move beyond

an object-centric model that uses linear causality with a top-down approach, so we can adopt a holistic

model that is relation-centric and uses recursive causality with a bottom-up approach.

The real world is unpredictable, and the systems we develop to operate in the real world need to cope with

that unpredictability. The IoT provides a better match between models and reality, and as a result does a

better job of dealing with unpredictability, while also saving resources and increasing performance.

[1] Edgar Morin « Introduction to complex thought»

[2] Norbert Wiener « Cybernetics: or Control and Communication in the Animal and the Machine »

Author: Francois Hamon CEO at GreenCityZen

The internet of thing technology offers the opportunity to operate the

systematic or cybernetic transition. It could make the models fitting much

better to reality allowing to save resources, increase performance and

anticipate emergences/emergencies.

About Greencityzen:

GreenCityZen is a greentech pioneer in the industrial Internet of things (IoT) for

industry and smart city. The HummBox is a continuous measurement solution

for the monitoring of environmental data : from the sensor to the dashboard.

Low energy devices, fast deployment and interoperabilty are strong assets to

bring immediate benefits such as reduced costs of field trips, improved process

performance and help to enrich service offerings.