The Cognitive Digital Twin

THE EMERGENCE OF COGNITIVE DIGITAL PHYSICAL TWINS
AS THE 21ST CENTURY ICONS AND BEACONS
AN IN-PROGRESS VISION, KEY CATEGORIES, APPLICATIONS
AND
A REFERENCE ARCHITECTURE FRAMEWORK
Dr. Ahmed El Adl
©Nov. 2016
Introduction
Being Digital (by Nicholas Negroponte, 1996) and When
Things Start to Think (by Neil Gershenfeld, 2000) as well as
many R&D efforts done by many teams around the globe
over the last decades introduced into the public psyche the
potential emergence and the rise of smart machines.
Recently, some companies adopted these ideas in their
marketing campaign claiming an imminent change to a
future where fully integrated and inherently intelligent self-
organizing systems, subsystems, and components shall
define the next generation of intelligent machines.
Additionally, the massive advances and major
breakthroughs that occurred in different areas of
technology and science gave us a lot of optimism. However,
this optimism is faced with the hurdles of removing the dead
weight of old technologies and changing our current way of
thinking to pave the path for new theories and concepts in
the engineering and design of the future systems, which may
lead to intelligent machines. An even greater challenge is
integrating cognition and evolution capabilities in the design
of such machines and systems.
Recently, the discussions about the IoT/IoE, smart machines,
and cognitive systems created a lot of motivation, hope, and
confusion. Therefore, some companies started different
initiatives to discover and understand the possible
implications and values of these new technologies to their
current and future business. However, without
breakthrough results.
Unfortunately, many of these companies are afraid to delve
deeper to be able to envision their future. Instead, they
started retrofitting existing machines to designate them as
“connected” and attach sensors to collect data to call them
“smart”. They run workflows on steroids to claim
“intelligence” in their analytics. Others are haphazardly
collecting and feeding big (volume) data sets to existing
software systems and voila – one has “cognitive software
systems” listed as an attribute to post their sales numbers
forgetting that the harsh reality will soon prove them wrong,
the customer experience and opinion.
One reason for the current confusion, perhaps, is our
general inability to ask correct questions. Let us step back
and pose a few key questions.
➢ What machines, devices, and systems could be built
with the tools and technologies at hand today and
without further inventions?
➢ How should we design, build, and use them?
➢ Do we really want to just connect everything and
haphazardly collect large volumes of data?
➢ Is it all about the data?
➢ How can we enable smart machines to achieve
specific tasks while learning to achieve even more
complex tasks over time?
Once we understood and answered those questions, we’ll
be able put a plan for relevant innovation and drive effective
transformation which will not only help us transform what
we’ve to where we want it to be but also, we'll be able to
envision and build the right systems, machines, and
businesses we need in the future.
PUBLISHED
NOV.
2016

The Cognitive Digital Twins Dr. Ahmed El Adl, Nov. 2016
“We should build smart systems and machines that
can collaborate with us to augment our current
physical and cognitive capabilities across and
beyond our lifetime and the space we can
physically exist in today”
We might agree about this ultimate goal. However, the
debate rages on about answers to these and other related
questions, which may be cryptic in bio-inspired designs and
how nature is evolving to adapt and enhance the physical
and cognitive capabilities of creators including humans.
The current breakthroughs in key areas such as “Digital
Biology” coupled with Bio-mimicry
(https://biomimicry.org/), cybernetics, and deep learning
are elements, which when converged may offer completely
new dimensions and approaches for real neuromorphic
computing and bio-inspired systems and machines that can
intelligently sense, learn, reason, act and evolve. This
approach may be the Holy Grail.
The current advocacy to advance the principles and
pervasive practice of digital twins calls for distributed
cognitive and communication capabilities by design where
systems can inherit, grow, and share intelligence across
different sub-systems as well as multiple generations of
systems and machines.
Designing, building, and managing such bio-inspired systems
and machines may require a new form of hardware-
software design, architecture, and integration paradigms we
haven’t yet encountered. To do so, we have to adopt
“Cognitive Digital First” way of thinking. This would require
us to first design and build cognitive digital twins, which will
digitally represent, augment, and accompany a new
generation of machines (The Physical Twins). Both the digital
and physical twins will work in tandem to achieve the
excepted tasks and functionalities.
“Cognitive Digital Physical Twins will continue
optimizing their cognitive, digital and physical
design and capabilities based on the data they’ll
collect and experience they'll gain over time, not
only based on models and data we gave them, or
they inherited”
In this article, while I’ll try to avoid going into deep
technical details and not to give you time-wasting
financial predictions, I’ll try to explain my in-progress
overall vision, definition, key categories as well as
provide an initial reference architecture framework for
the Cognitive Digital Twins (CDT) as I see today (Nov.
2016).

THE CASE FOR COGNITIVE DIGITAL TWINS
THE NOISE, CONFUSION AND PROMISE OF IOT AND
DIGITAL TRANSFORMATION
Today, you can’t go to a conference, a meeting or even have
a discussion with anybody without having to discuss or hear
about the IoT and Digital Transformation.
Both are important topics, however as you might have
already experienced yourself, most of the discussions end
nearly where it started; what is the IoT? Didn’t we already go
digital since decades?
This is distracting many people from the real issues and
exhausting valuable resources. Therefore, let us get things
clearly defined so that we could focus on real relevant
innovation and challenges.
Today, IoT is being defined as the next generation of digital
networking technologies and protocols, which are
essentially required to connect a massive number of digital
devices and transfer an unlimited amount of data in real
time. This is, by all means, not a complete definition.
“The IoT/IoE should provide the core technologies,
platforms, and services required to build the future
“Digital Ecology” where smart digital Things can be
created, live, smartly act and interact as well as
evolve in a manageable and a secure way.”
And what about Digital Transformation? Recently,
companies are asked to digitally transform their business
and finally start adopting digital technologies. Really? Didn’t
we start digitizing the enterprise tasks, processes and
functions many decades ago? And what about the large
population of CNC machines and robots adding real values
every day and everywhere in many industries?
“The current wave of technology-driven
transformation should not be just a technology
upgrade (app modernization) or adding more
software to what we already have”
Over the past few decades, we went through different waves
of technology-driven transformation as follows:

“The required transformation should not only be
digital, but it should also be a digital cognitive
transformation.”
To do that, we should understand what the concept of
“Cognitive Digital Enterprise” means. Cognitive Digital
Transformation is way more than adding more analytics
tools and gathering more data. Having this as the compass
and way of thinking while defining and building the new
cognitive enterprise around new smart products and digital
services will enable a non-destructive yet efficient
transformation to the next generation of smart digitally
enabled, represented, and augmented business.
THE CURRENT APPROACH
Some companies got it right and are able so far to avoid
getting stuck and sucked in the wrong and short- sighted
terms and discussions about IoT, Digital Transformation, app
modernization, Big Data ... etc. However, they’re starting to
understand that retrofitting the current physical world as it
is today by adding some sensors in and around existing
products and haphazardly collecting and analyzing big
amount of Data is just a temporary solution that didn’t prove
its commercial viability yet and possibly never.
Additionally, it is clear that the current approach of
transforming businesses and machines to digitally
connected, created major challenges to many organizations
without offering a viable proven solution. Some of these
challenges are:
• Strategy: What is the right strategy to define and
implement a technology-driven digital business without
disrupting the current business?
• Approach: Is the digital twin the right way to go? What
does digital twin mean? Is it all about collecting some
data?
• Platform: What are the required technology platforms,
standards, protocols, and architecture?
• Mist vs. Fog vs. Cloud computing: What about edgeless
distributed cognitive computing?
“Distributed Cognitive Architecture will soon end
the dilemma of cloud vs. edge vs. mist computing”
• Cognitive capabilities: Do we need to add more data
analytics tools or move to the new generation of real
cognitive systems that can understand, reason, and
learn.
• Cyber-physical security: How are we going to proactively
identify and prevent the cyber-physical security risks
during and after the transformation?
"The current approach of retrofitting machines
and tweaking processes is not a feasible and risky
approach especially as a long-term solution"
Therefore, many business and technology leaders are
looking for a completely new approach to transform their
current business and create new ones that they can stay
relevant and lead in the era of cognitive business and smart
machines.
THE COGNITIVE DIGITAL TWIN (CDT): BACKGROUND
Cyber-Physical Systems (CPS) are heterogeneous blends that
combine digital computation, communication, and physical
world dynamics. They form the foundation of embedded
systems (http://leeseshia.org/). The concept of digital twins
was first advocated by NASA and became a key engineering
concept of its space exploration programs. Advancing the
concept of cognitive digital twins in practice must draw
heavily from the advances in CPS reengineered using
cognitive computing architecture and capabilities.
While cyber-physical systems (CPS) added a lot of values,
they produced mainly digitally controlled machines with
some embedded software, which can control some
functions and collect and analyze a small amount of data.
“The current efforts to create “Digital Twins” for
existing machines have a very limited vision if any.
They're limited to a small set of functionalities with
the main focus on operational effectiveness and
predictive maintenance.”
“Digital Twins for enterprises should not be just a
couple of simple analytics cockpits applications.”
This is not what a Cognitive Digital Twin of a Physical Twin
should be. To get out of the current stagnation and confusing
situation, we should start building physical systems, which
will be by-design an integral part of intelligent Digital Twin
that will accompany and augment them. The physical twin
and the digital twin will construct the Cognitive Digital
Physical Twin (CDPT).

This mindset and engineering approach are not only about
implementing solutions around existing machines or
processes to increase productivity or revenue. It is all about
building a completely new generation of smart machines,
cognitive software systems, as well as digitally connected
services, which can be consumed by machines and humans.
THE COGNITIVE DIGITAL TWIN: DEFINITION
KEY CHARACTERISTICS AND ARCHITECTURAL PRINCIPALS OF CDTS ARE:
Some of the key characteristics and architectural principles
of CDTs are:
• CDTs are highly interconnected distributed cognitive
systems and, in some cases, are very large complex
systems of systems (SoSs).
• CDTs exist in the digital space and will evolve over time
as their physical Twins evolve.
• CDTs will span physical and digital systems and soon us,
the humans.
• They’ll be able to act, interact and collaborate across
domains, physical and virtual worlds
• CDTs will continuously evolve to be able to
autonomously take contextual decisions and execute
more complex tasks in the digital as well as physical
worlds (experience-driven behavior)
• CDTs and their physical twins will learn over time to
identify, create, and provide new services, which their
early immature versions couldn’t offer.
• Cognitive digital twins may or may not have physical
twins:
• Cognitive Digital Twins will have the abilities of physical
and digital self-diagnostic and healing.
“CDTs will use manufacturing and engineering
techniques such as additive manufacturing and
similar future technologies to autonomously

manufacture and install some parts of its own
physical twin.”
• CDTs will create a massive new economy around semi or
fully automated digital smart services defined and
offered by the CDTs themselves in collaboration with the
physical twin(s) and possibly humans’ partners.
• The early generations of cognitive digital twins will be
designed to make no mistakes. Therefore, they’ll have
less intelligence and make a lot of mistakes. However,
the following generations will be smarter by allowing
them to try new things, make mistakes and
autonomously learn out of it. Aren’t we so?
“Cognitive Digital Twin will possess valuable
knowledge and experiences gained and optimized
over its lifetime. Therefore, it shall not vanish nor
be destroyed once the life of the physical twin
ended – The power of Mind Transfer and Evolution
THE COGNITIVE DIGITAL TWIN: ARCHITECTURAL FRAMEWORK
THE NEW DESIGN AND ARCHITECTURE MINDSET
CDTs are massive smart modular yet highly integrated and
collaborative systems, where biologically inspired
architectures, autonomous cognition, and controlled
evolution will be fundamental characteristics and
capabilities.
“Inspired by the 11 billion years long brain and
the neocortex evolution, Distributed Cognitive
Architecture (DCA) is the future of smart
systems and machines.”
The design, implementation, and operation of cognitive
digital twins will not be an easy task, at least over the next
few years. Nevertheless, the current systems and system-of-
systems (SoSs) engineering theories and frameworks will fail
short and can’t efficiently help us in building such systems.
"Model-based Systems Engineering (MBSE)
techniques and tools should gain cognitive and
evaluation capabilities that they can support
the semi or, in some cases, full autonomous
evolution of the digital and physical twins
design and functionalities."
The advances in neuromorphic computing, which replaces
the older emphasis on separate modules for input, output,
instruction-processing, and memory, showed us that
machine intelligence should be addressed by both the
physical as well as the digital design and architecture.
“A combination of traditional and neuromorphic
computing would soon be the dominating
computing architecture until a fully biologically-
inspired computing architecture, hardware and
software is mature enough.”
Keeping this concept in mind while designing the physical
and digital systems and machines will solve many problems
we currently have in AI / ML. It’ll also accelerate the patchy
progress we’ve had for decades. You can’t write a couple of
algorithms that you think are capable of doing smart things,
train them with large set of data then upload them to a
machine and expect that this machine will suddenly be
smart. Therefore, a major shift in how we envision,
architect, and build systems and machines is required.
“We should abandon the Von Neumann’s
model and principles of designing and building
binary machines that can just compute. We
should also free up ourselves from the mentality
of Isaac Asimov of building robots that can do
repetitive tasks for us (slaves). Instead, we
should start building biologically inspired smart
machines that will be our future counterparts,
colleagues and possibly our adversaries”
However, over the next few years, some will be trying to
stitch existing technologies together, extend protocols and
standards that they can quickly implement workarounds and
get the first generation of cognitive digital Twins designed
and implemented. That is fine as a temporary approach as
long as it doesn’t distract us from shifting toward the new
approach of building such cognitive digital physical twins.

KEY ARCHITECTURAL BUILDING BLOCKS
For the first wave of Cognitive Digital Twins, key architectural building blocks will be required as follows:
COGNITIVE DIGITAL TWIN CORE (CDTC) –
THE CORE:
The digital core would be the initial digital representation of
the “Physical Twin” including its main initial states “as-
designed”, “as-built”, “as-sold” and “as-configured”. Also,
it’ll contain the initial states and core capabilities of the
digital twin itself including the required systems and tools.
Additionally, the CDTC will have different metadata, core
self-defense mechanisms as well as governing rules to
guarantee that the whole CDPT will function, evolve, and
used as intended. The initial core will usually be kept
unchanged over time. However, to enable continuous
evolution of both physical and digital twins, minor additions
or updates will be required and allowed based on specific
sets of predefined rules.
COGNITIVE DIGITAL TWIN ANCHORS (CDTA) –
THE DATA WORKERS:
Real-time, historical, and extrapolated data will drive the
actions and the evolution of the CDPTs. Anchors will
continually monitor and collect specific parameters,
statuses, and contents of interest from different local as well
as external distributed data sources. They'll use data mining
techniques to initially prepare the collected data. CDTA will
use different cognitive capabilities (AI/ML …) and techniques
to dynamically define the data structures and detect suitable
sources.
“CDTA will use different techniques to
extrapolate and generate its own version of the
reality based on varieties of parameters and
rules such as time, experience, context,
The Cognitive Digital Twin (CDT): Reference Architectural
Framework

situation, and self and/or environmental
awareness - machine perception”
CDTA will be able to adapt over time so that they
can effectively deal with changes which might happen to
data structure, contents as well as the sources. They should
use local and cross-systems capabilities to evolve their data
models in a non-destructive way over time so that the right
data will be collected, structured, enriched, possibly
converted to useful information, and made available for
usage.
CDTA are required for neuromorphic computing. Our
current computing systems collect, and store data based on
predefined formats and rules. This data will be made
available to different processes and tools on request. On the
other hand, CDTA will collect data either based on
predefined rules, dynamically defined rules, or triggered by
specific events. Usually, data will be sent directly to the
destination(s) in a format that will enable faster reasoning
and if needed immediate actions. This key architecture
principle is a dominating architecture in the biological
species. It is essential for cognitive smart systems and
machines and will be made possible by CDTA.
COGNITIVE DIGITAL TWIN SURROGATES (CDTS) –
THE KNOWLEDGE WORKERS:
Smart “Things” will have functions to be performed,
characteristics to be maintained and interactions with digital
and physical worlds to be made.
“Based on situational & context-aware
cognitive rules, CDT surrogates are experts in a
specific domain and will continuously create
and update their knowledge to keep up with the
evolution of the overall CDPT and its
environment.”
To do so, they’ll apply different knowledge discover and
machine learning techniques on the data and information
available to the CDPT from different sources. This up-to-date
knowledge will enable the CDT to take more complex
decisions and evolve the cognitive capabilities of the overall
CDPT over time.
Additionally, CDTS will communicate their knowledge with
different systems and subsystems of the CDT, its physical
twin as well as other CDTs (e.g., within its digital Swarm).
Complex sets of cognitive rules and skills will determine
what, when and how to share knowledge and with whom.
CDTS will continuously work with other CDT’s subsystems to
update the rules used to gather, create, and share
knowledge across the lifetime of the CDPT.
COGNITIVE DIGITAL TWIN BOTS (CDTB) – THE
MAKERS:
CDTBs are creative highly specialized digital workers that can
carry out complex and hybrid tasks either in the digital space
(e.g., software algorithms) or in the physical space (e.g. to
control a Humanoid on another planet or a machine on a
smart factory floor).
“CDTBs are smart digital or digital-physical sub-
systems designed and continuously learning to
do specific tasks repetitively and intelligently.
They will leverage the knowledge they gained to
get smarter and share it back with their
Cognitive Digital Twin.”
Those CDTBs will evolve over time through learning by doing
as well as the knowledge made available by the surrogates
(CDTS). CDPTs will be able to autonomously define, create
and train new CDTBs as needed.
COGNITIVE DIGITAL TWIN PERSPECTIVES (CDTP) –
THE INTERFACES:
CDT perspectives will be responsible for multi-directional
multi-channel communications and interfaces including
communications with the physical Twin, other Digital Twins
as well as Humans or non-human subjects and objects. A
fundamental redesign of some of the current software
engineering concepts such as APIs is needed.
“The current APIs have to be redesigned and
extended to be able to support Cognitive Digital
Physical Twin Programming Interface (CDPTPI
or simply TPI).”
TPIs will create one of the major new economies of the 21st
century. They'll be the main interface to smart digital and
physical systems and machines. To do so, we’ll also have to
redefine M2M and M2H interfaces. This is mainly to
compensate for the weakest point in such new smart digital

world, the Humans, who can lack attention or mental clarity
or just bored or biased for example.
“CDPTs will learn to adapt and evolve their
communications capabilities, techniques, and
styles with humans, machines, as well as
processes.”
COGNITIVE DIGITAL TWIN SELF-MANAGEMENT
(CDTSM) – THE ADMINSTRATOR:
Cognitive digital physical twins will usually be large complex
and distributed systems. Some digital components will be
embedded in the physical twins and some physical
components will be controlled by the digital twin. Managing
the life cycle of such systems will be too complex and near
impossible to do for humans. Therefore, a smart self-
management system should be in place to manage the
digital physical twins.
Managing the lifecycle phases of CDPTs will require a
combination of advanced sets of software systems and
cyber-physical management capabilities. In addition, they’ll
at least partially manage the physical Twin as well. CDTSM
will apply its cognitive capabilities to develop sophisticated
project and program management skills similar to what
humans possess today. Self-monitoring, proactive and
event-driven self-diagnostic as well as robust digital and if
possible, physical self-healing should be key capabilities of
these systems.
“CDTSM will manage the functions and
evolution of both digital and physical twins to
guarantee compliant actions and “purposeful
evolution”
CDTSM systems will evolve and be able to define, implement
and enforce new self-management rules and tasks. The
metadata and core functions embedded in the core of the
CDT would define some fixed boundaries and rules for self-
management as well as self-evolution.
COGNITIVE DIGITAL TWIN DEFENSE SYSTEM
(CDTDS) – THE GUARDIANS:
Every Digital twin will introduce unprecedented vulnerability
and risks to both Digital as well as physical worlds. Because
of such possible devastating consequences, the current
cyber security techniques such as intrusions detection and
response are not enough to secure Cognitive Digital and
Physical Twins.
Therefore, CDPTs should be designed so that danger and
even serious intents of intrusions will be proactively
detected and blocked through a bottom-up digitally and
physically secure design. It should be able to use intelligent
digital and physical techniques and tools to define and
implement self-defense plans aiming to protect itself against
any kind of harm, misuse, or unauthorized use.
Context and environmental awareness will play crucial roles
as well. Therefore, CDTDS will be able to override any
external control including human control if needed,
especially in massive digital or physical attacks situation with
high-risk consequences where humans could be slow to
comprehend and react appropriately on time.
“CDPTs will use advanced cognitive techniques
to develop and evolve their self-defense plans
and capabilities including reasonable
preemptive actions against other CDPT(s) if
needed”

COGNITIVE DIGITAL SWARM (CDS)
DEFINITION:
CDTs would socialize, collaborate, and partner with another
CDTs, which for example share the same interest or provide
specific services they need. Such relationships and interests
will make it beneficial for the CDTs to create Digital Swarms
using specific rules and requirements defined by each
individual CDT. Such rules will help the CDTs to identify, find,
join, and as needed leave digital swarm(s) on-time safely and
efficiently. This should be part of the CDT’s core capabilities
and be refined over time through continuous learning and
balanced evolution.
“Cognitive Digital Twins will be like humans,
they’re smarter, safer and more efficient when
they communicate, share and collaborate with
others”
Cognitive Digital Swarms will be able to create and share
their collective intelligence and capabilities based on specific
rules defined by every individual member as well as by the
swarm collectively. “Swarm Intelligence” will make every
swarm member capable of taking smarter decisions and
carrying out more sophisticated tasks efficiently and in a
more secure way.
“The cognitive digital swarms will use their
collective cognitive and situational awareness
capabilities to define own rules and identify new
swarm members across the whole accessible IoE
digital ecosystem and possibly invite them to
join the swarm as needed.”
Once created, the digital swarms will have their own sets of
governance and collaboration rules, which will manage their
joint activities together. The accessibility to the physical
twins of digital swarm members will be in many cases
exposed to more strict rules than the rules used to access
the joint digital resources.
CDTs will be allowed to have simultaneous relationships
with different digital swarms. However, rules should exist to
guarantee that conflict of interests will be avoided and risks
to the members will be minimized or preferably eliminated.
In some situations, digital swarms will need to join
capabilities and abilities with other swarms to achieve larger
common goals. Therefore, swarms will create “Digital
Clusters” under specific circumstances. Imagine different
digital swarms within a smart city joining capabilities and
resources to enable the expected higher quality of life for its
residents and visitors.
KEY CATEGORIES OF COGNITIVE DIGITAL SWARMS
For the first waves of digital swarms, I’m proposing 4 major
categories, which will be helpful in increasing the values,
stability, resilience as well as the security of Cognitive Digital
Physical Twins and their Swarms as follows:
STRATEGIC DIGITAL SWARMS
The participating CDTs will dynamically share the relevant
digital and physical resources, take over tasks on behalf of
the swarm or each other. They’ll make specific experiences
available to each other so that they can jointly achieve their
individual and collective goals.
“Strategic digital swarms will not have detailed
predefined specific goals. However, they’ll have
common causes such as keeping the traffic
flowing in a city or protecting the airports of a
country or even running a company.”
They’ll potentially define specific goals over time and be
driven by the current situation they're dealing with. The
collective cognitive and physical capabilities, as well as the
requirements of the swarm, will play a major role in defining
and implementing the short- and long-term common goals.
For example, all the safety-related Cognitive Digital Twins of
some or even all the US Airports will be by default and
continuously a member of the national aviation safety
strategic digital swarm. While every member will do its
individual tasks of monitoring and securing its own airport,
they’ll share security and safety relevant information

instantaneously and in a smart way so that the unexpected
security situations will be dealt with appropriately and
proactively.
The DS members will also be able to carry out tasks on behalf
of the whole DS or specific member such as accessing the
physical twin, taking over control over specific equipment,
whole building or soon commanding Robotic Security
Guards (RSG), which are in fact CDTs themselves, to deal
with a security situation in an airport or a school.
JOINT VENTURE DIGITAL SWARMS
Under some conditions, two or more cognitive digital twins
will collaborate to achieve a common predefined goal(s).
They will work together to put a plan together as they go.
For example, several smart factories are assembling the
components and systems required to build a specific aircraft
model based on the conditions specified in suppliers’
contracts. The different interdependencies between those
factories such as What? When? Where and how? will dictate
a temporary joint venture relationship between the CDTs of
those involved factories across different vendors and
geographies. They will work together to fulfill the contract
conditions and deliver on time, budget, quantity, and
quality. A swarm of the involved supply chain management
systems will assist this manufacturing swarm.
“JV swarms would extremely streamline the
manufacturing processes and lead to
unprecedented levels of manufacturing
automation, quality of products and cost
reduction.”
Once goals are achieved, JV swarms will not be needed
anymore. However, the collective experience should be
shared and possibly used for another joint venture to
produce the same product or even other products by the
same JV swarm or the CDTs themselves within another
swarm.
“CDTs will evolve through doing that they can
provide higher efficiency, learn to do smarter
and more complex tasks in smarter ways over
time (continues unsupervised machine
learning).”
OUTSOURCING DIGITAL SWARMS
Every Cognitive Digital Twin and its physical Twin will have
its strengths, weaknesses, and limitations by
design. However, to guarantee focus and optimal use of the
digital and physical resources, some limitations will continue
to persist, or new ones might occur temporarily or even
permanently due to different circumstances.
“CDTs will be able to learn by doing and even
get rid of some of the design weaknesses and
limitations.”
To make Digital Twins as efficient as possible; outsourcing or
crowdsourcing of some tasks will be essential capabilities for
the digital twins as well as digital swarms. The relationship
between the members of this type of digital swarm will be
weak and temporary. Sharing information as well as physical
resources will be limited to the bare- minimum required to
do the common tasks.
SPATIAL DIGITAL SWARMS
The spatial locations of some or all elements of Cognitive
Digital Physical Twins will make it beneficial in specific cases
to establish a spontaneous or planned digital swarm based
on current location or spatial requirements. In some cases,
the spatial locations of the physical twins will not have to be
near to each other for them to be part of a spatial swarm.
For instance, the CDT of my car will be continuously in a
strategic alliance with my Human Cognitive Digital Twin and
my smart Home Cognitive Digital Twin. Those Twins will
construct my Personal Cognitive Digital Swarm. My PCDS will
be the foundation for my Personal Cognitive Digital
Assistant - CDA. My CDA will dynamically join spatial swarms
with the relevant Public Cognitive Digital Twins and swarms
to deliver the best and safest experience to me on the road,
at home, at work or anywhere else all the time.
ANONYMOUS DIGITAL SWARMS
Like humans, some CDTs will anonymously be a part of a
digital swarm for a limited time until they achieve specific
short-term goal(s). In this case, not much information nor
physical resources will be shared or at least it should be
optional.

For example, the Cognitive Digital Twins of all cars at a
specific traffic light will temporarily and anonymously join a
spatial DS including the CDT of the traffic lights controller
itself as well as other related smart city public CDTs. They
will work together to control the traffic flow optimally and
instantly around this specific spatial location. This will be
done within the larger context of optimal traffic
management of the nearby areas as well as the whole smart
city.
“Anonymous Digital Swarms will play a major
role in the era of Cognitive Digital Physical
Twins (CDPTs) especially because of the much-
needed extra safety and security layers they
provide by design”
The short-term goal(s) will be achieved without future
commitments or sharing knowledge and experience. Also,
access to the Physical Twins should be limited or completely
avoided. However, for instance, in the above example, in
some situations it would make sense that the swarm
controller will be granted access to the braking systems of
one or more cars to avoid collisions or guarantee compliance
with current traffic rules.
KEY CATEGORIES OF COGNITIVE DIGITAL TWINS
To effectively design cognitive digital twins, which will
digitally represent and augment the physical world, we’ve to
start with defining the “purpose of Life” of a cognitive digital
twin in the context of the "purpose of life" of its physical
twin and the environment in which the CDPT will have to
fulfill its purpose of life. This will help us get a clear
understanding of not only the initial roles and functions of
the CDT but also define and enable the evaluation process
for this specific CDPT which will enable it to achieve the
expected purposes of life within its new digital ecological
system while adding values to our life.
To make the first generation of CDTs as successful as
possible, we should identify and define the major categories
of cognitive digital twins based on mainly the categories of
their physical twins. This approach will help us precisely
identify the required existing and future technologies we
need, focus the next innovation cycles on filling the gaps and
accelerate the creation of the right CDTs.
Currently, I’m recommending starting with the following
main categories for Cognitive Digital Twins:
MACHINES COGNITIVE DIGITAL TWINS (MCDT) –
THE DIGITAL PHYSICAL TWIN
This category of CDTs will be the most dominant category
over the next years and will have a great impact on
everything around us. MCDTs will help us rethink the way we
design, build, use, maintain and operate machines,
appliances, and devices.
“Creating MCDTs for existing machines will be
our first exercise to better understand what
smart machines are and how to design and
build them”
MCDTs are not just an add-on or add-in. They go beyond IoT,
Big Data Analytics, AI/ML … It is a completely new way of
design thinking and engineering approaches in designing,
building, and using machines and systems.
“Soon, our buying decisions as individuals and
enterprises will be greatly influenced by the
availability and the quality of a cognitive digital
Twin for the specific machines, devices, or
appliances we would like to buy at home and
work. “
We can see this happening today in different industries such
as aviation, industrial machinery, and some consumer
devices. Even offering simple data collection and predictive
analytics capabilities around the operation of an aircraft or
locomotive engine decides winners and losers today.
HUMAN COGNITIVE DIGITAL TWIN (HCDT) – THE
DIGITAL AVATAR
The Human Cognitive Digital Twin will completely change us,
our life, and the way we live it. Imagine that our digital brain
replica, medical record, education, social and work

experience, as well as other information are combined
together and stored in a Cognitive Digital Twin. This could
create a limitless number of opportunities for us
“Soon, we'll be able to use our HCDT to control
our Robotic Avatar(s) not only on earth but also
virtually anywhere in the universe. Are we
Avatars of other creators?”
HCDTs will make it possible to finally create the Bio-digital
species, where our physical and cognitive capabilities will be
truly augmented and freed up from many biological
weaknesses and limitations. Our biological evolution will be
accelerated and extended by cognitive digital evolution.
Even the early versions of HCDTs would immediately have a
tremendous positive impact on the quality of our life. For
example, they’ll help us solve many health problems in cost
effective and highly personalized ways adding great values
to our daily work and private life instantly.
HCDTs will help integrate us even more and efficiently with
each other as well as into the physical world around us. A
seamless collaboration between different CDTs of machines
and objects at home, at work and everywhere in between
will extremely increase our capabilities and enhance every
aspect of our life.
“Human Cognitive Digital Twins are going to
accelerate the rise of Cognitive Digital Assistants
(CDA), which I do believe will be one of the major
technological breakthroughs over the next years
and decades to come”
Additionally, HCDTs will be able to socialize, act and
collaborate on our behalf. For instance, the HCDTs of a group
of people who have the same disease would be able to
collaborate and share the right information in real time
within a digital swarm of themselves, their doctors,
scientists, and other medical services providers that the
whole group can get the best medical care and highly
personalized life assistance.
OBJECTS COGNITIVE DIGITAL TWIN (OCDT) –
SMART THINGS
The Objects Cognitive Digital Twins will enable and
accelerate the digitization, digital representation, and
augmentation of a large number of objects in the physical
space. Those objects are not humans nor individual smart
machines.
“The size and the level of complexity of OCDTs
will vary dramatically based on the nature of
the physical object they represent.”
In many cases, machines, devices, or other complex physical
objects will be built out of a digital swarm of a very large
number of OCDTs rather than having just one MCDT.
For example, OCDTs of smart streets sensors within a smart
City would dynamically join many other OCDTs and MCDTs
of cars, traffic management systems, sensors, parking areas
identifiers … to create a Digital Swarm representing a smart
city. OCDTs might soon be the largest population of
cognitive digital twins.
ENTERPRISE COGNITIVE DIGITAL TWIN (ECDT) –
THE COGNITIVE ENTERPRISE
Companies of different sizes and industries should
understand that rethinking and integrating their current IT
and OT landscape as well as their business models is NOT
enough to survive and stay relevant in the era of Cognitive
Digital Twins.
“Companies should rethink the very nature of
their business models, the products they build
as well as the services they provide to be
relevant in the era of "Smart Everything"
Today, creating an overarching Cognitive Digital Twin
representing the new digital core of the enterprise is
partially possible. Soon, building a complete ECDT for the
whole enterprise will be possible.
“ECDT-focused transformation would help
define, guide and accelerate the creation of its
future cognitive digital business, where
products, solutions, services, processes, and
people are intelligently connected and digitally
represented and augmented.”
Doing so will require a new organizational structure and
business models, where automated cognitive business
decisions will be taken by different CDTs and DSs and most
probably in collaboration with counterparts of limited
intelligence and data processing capacity and speed, the
humans.

“Imagine a day, where the CEO, CFO or even the
board of a company would be just a bunch of
HCDTs, ECDTs, and MCDTs leading the new
cognitive digital businesses”
The first generation ECDTs will mainly represent and
augment their own company core business.
However, soon enterprise cognitive digital swarms will be
created out of different CDTs (e.g.):
• ECDTs of partners, suppliers, and customers,
• MCDTs of own machines in their own factories or sold
on customer's sites,
• HCDTs of own employees and in many cases their
customers.
This category of CDTs represents the way I understand the
“Cognitive Digital Enterprise” and how we should define and
implement “Cognitive Digital Transformation”.
SPECIAL CATEGORY: THE COGNITIVE DIGITAL
ASSISTANT (CDA)
“Cognitive Digital Assistants are a special
category of CDT. CDAs are highly specialized
digital experts that can learn and evolve to
carry out complex cognitive tasks in the digital
world. They’re digital twins without physical
twins associated directly to them.”
They would be able to help other categories of CDTs as well.
For example, they would collaborate with HCDT to augment
the mental and physical capabilities of a human. Also, they
would be able to provide different cognitive digital services
to CDTs as well as their associated physical Twins.
Soon, CDA will span and affect every aspect of our life and
reshape every industry we’ve today. They’ve the potential
to create a massive new economy, the economy of
intelligent digital assistants.
“Like many new major technologies, CDAs will
have even more serious social impacts and legal
liability than other categories of cognitive
digital twins. CDAs could be easily used to
mislead people and even nations even before
they realized that they exist.”
CDAs started to create new categories of economy and jobs.
However, they’ll take many white-collar jobs away, possibly
in a very short time, while not being able to create
alternative jobs for the same group of people.

CONCLUSION
Some of us would think that creating Cognitive Digital Twins
for machines or humans is a kind of science fiction. Partially,
it is. However, I do believe that the innovations,
technologies, and knowledge we’ve today would be
sufficient to get the first generation of real cognitive digital
twins designed and built.
“If at first, the idea is not absurd, then there is
no hope for it.” Albert Einstein.
However, to be able to create real and reliable CDTs,
fundamental changes must happen such as creating new
engineering paradigms and architecture concepts to be used
for envisioning and designing smart businesses, systems,
and machines. Over the next few years, we’re going to build
digital twins for some of the existing machines and
businesses.
However, the ultimate goal should be to first design and
build the cognitive digital twin then augment it with the
required physical twins, not vice versa (Cognitive-Digital-
First). Many of the machines and devices we’ve today will be
replaced by bodiless virtual digital yet smarter machines
sooner than many of us would have expected.
Another major change would be shifting our approach from
building computing machines to building cognitive smart
systems and machines, which can autonomously evolve,
learn, reason with and without purpose and interact in a
natural yet smart way.
“Cognitive Digital Twins and systems will have
profound positive economic and societal
impact on our life. However, they’ll spur
disruption and raise major issues including
moral and ethical issues. Therefore, the
underlying architectures and designs of such
systems and machines should address that and
give us smart tools to deal with such issues and
their consequences even before they happen.”
However, we shouldn’t forget that dumb machines have
proven to be more dangerous to us and our physical
environment than smart ones. Therefore, for us to be able
to envision and build such smart systems and machines, we
should stop being frightened by the thoughts that smart
machines will someday take away our jobs, have control
over us and possibly eliminate us. This is given that yes; they
did already take away a lot of jobs. At the same time, they
created a lot of new jobs, but different jobs for different
people. This is the main reason for justified fears and
rejection from some groups of people, who felt the real
impact.
Nevertheless, some of us will continue inventing and
building such cognitive digital physical twins (CDPTs)
whether the rest of us will agree or not. The engine of
innovation will never stop. It is just a matter of time, and the
machine’s cognitive capabilities will outmaneuver ours. This
will happen sooner than most of us would think. Didn’t many
devices and machines do that already today?
This major opportunity would help us to transform ourselves
and be capable of doing more tasks beyond our current
physical and cognitive capabilities as well as even beyond
the time and space, where we traditionally existed and lived
so far.
Therefore, either we approach smart machines and machine
intelligence with an open mind and less fear that we can
seize this opportunity, or we’ll have to deal with the
profound consequences of being outsmarted, outdated or
even irrelevant. Now, the choice is ours!

Disclaimer: This is an ongoing and partially published work aiming to understand the overall concept of Cognitive Digital Twins (CDT) as the foundation for
the next true-smart generation of machines, systems, and businesses. It introduces the first definition of CDT and the required system-level cognitive
computing architecture. It also summarizes the key categories and relationships of the cognitive digital twins and swarms.
I'm sharing this work here for your own education and hopefully inspiration. Most importantly, as you'll figure out after reading this "long" article, CDTs are a
multidiscipline and very complex topic yet very inspiring and promising. Therefore, once you read the article in its entirety, please share it, share
your comments, and share whatever opinion you might have either online or with me directly.

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