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Abstract and Figures

A worldwide movement in advanced manufacturing countries is seeking to reinvigorate (and revolutionize) the industrial and manufacturing core competencies with the use of the latest advances in information and communications technology. Visual computing plays an important role as the "glue factor" in complete solutions. This article positions visual computing in its intrinsic crucial role for Industrie 4.0 and provides a general, broad overview and points out specific directions and scenarios for future research.
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Jorge Posada, Carlos Toro, Iñigo Barandiaran, David Oyarzun
Vicomtech-IK4 Foundation (Spain)
Didier Stricker DFKI – German Research Center for
Artificial Intelligence (Germany)
Raffaele de Amicis Fondazione Graphitech (Italy)
Eduardo B. Pinto Centro de Computação Grafica (Portugal)
Peter Eisert Fraunhofer HHI (Germany)
Jürgen Döllner Hasso Plattner Institut (Germany)
Ivan Vallarino Mivtech (Panama)
*Members of
Abstract—We present in this paper a comprehensive view of
the important role of Visual Computing as Key Enabling
Technology in the materialization of the different global visions
of new generation of ICT solutions in Manufacturing and
Industry in general. A worldwide trend in advanced
manufacturing countries is defining Industrie 4.0, Industrial
Internet and Factories of the Future as a new wave that can
revolutionize the production and its associated services, based on
the emergence of the Internet of Things and Services in the
factory, allowing the configuration of Cyber-Physical Systems in
combination with other key technologies. Visual Computing
plays an important role as “glue factor” in complete solutions.
Index Terms— Advanced Manufacturing, Digital
Manufacturing, Industrial Internet, Industrie 4.0, Computer
Graphics, Computer Vision, Visual Computing
here is a clear, worldwide trend in some of the most
advanced worldwide economies in reinvigorating (and
revolutionize) the industrial and manufacturing core
competencies with the use of the latest advances in ICT. A
tacit recognition in the fact that ICT could open completely
new possibilities to improve productivity and efficiency in
manufacturing is leading much of the actual efforts. The
aforesaid trend states that the relative weight of ICT in the
new competitive approaches to manufacturing will be growing
in the years to come. Local and regional governments are
aware of the importance of ICT in industry and for such
reason, novel initiatives and programmes are being developed
and launched. Initiatives such as the Industrial Internet and the
Advanced Manufacturing Partnership in USA, the Industry 4.0
(Industrie 4.0 in German), la Nouvelle France Industrielle, etc.
are just a few of different examples of this vision. Even
smaller regions with a long tradition in manufacturing (and not
only countries) are following the trend from their own local
perspective (e.g. the Basque Country intelligent specialization
policy RIS3 in Advanced Manufacturing).
Fully complementary with the fields of Internet of Things and
Industrial Internet but more focused in aspects close to
Automation, Connectivity and Ubiquitous Information, Cyber-
security, Intelligent Robotics, Product Lifecycle Management,
Semantic Technologies and Industrial Big Data, the
technologies comprised in Visual Computing provide a
feasible support for the new aforementioned initiatives and are
explicitly considered for example in the German vision of
Industrie 4.0 [6], which will be used as the context initiative of
this paper.
Some of the key aspects addressed by Industrie 4.0 are: (i) the
IT-enabled mass customization of manufactured products, in
which production must adapt to very short batches or even
individual needs, (ii) the automatic and flexible adaptation of
the production chain to changing requirements (iii) the
tracking and self-awareness of parts and products and their
communication with the machines and with other products,
(iv) the improved human machine interaction paradigms,
including the coexistence with robots or radically new ways to
interact and operate in the factory, (v) the optimization of
production due to IoT-enabled communication in the Smart
Factory, and (vi) the emergence of radically new types of
services and business models contributing to new ways of
interaction in the value chain. As explained in [6], with the
introduction of the Internet of Things and Services, the Cyber-
Physical Systems –CPS- are central to this vision, and include
smart machines, storage systems and production facilities that
are able to exchange information with autonomy and
intelligence, are able to decide and trigger actions, and can
control each other independently.
To achieve this vision, as stated in [11], it is necessary to
capture, analyze and interact with both the real -physical- and
the virtual –digital/cyber- production world, with high level of
precision in all dimensions (spacial, temporal, etc.). From this
perspective, the application of Computer Graphics and
Computer Vision (Visual Computing) technologies play an
important role in achieving Industrie 4.0 solutions, as for
instance in HMI aspects, in visual monitoring of the real and
the physical worlds, to name just two aspects. This article will
analyze in detail how Visual Computing technologies are key
enablers for Industrie 4.0 and Industrial Internet.
Visual Computing is understood as the entire field of
acquiring, analysing and synthesising visual data by means of
computers which provide relevant-to-the-field tools [29].
Among the most recognizable technologies advantaged by
Visual Computing, Computer Graphics and Computer Vision
(including Human-Machine Interaction), are proving to be
In this article we introduce a conceptualization of the main
technologies of Visual Computing for Industrie 4.0. We show
some concrete examples of applied research projects (in
different international scenarios) and their alignment with
aforesaid view. Furthermore, we identify key technologies and
challenges to be addressed by the scientific community
approaching the realization of Industrie 4.0. We intent to
Industrie4.0& Industrial
provide an integrated view and an international perspective of
the current trends and challenges of Visual Computing for
Industrie 4.0. Our discourse is based on the common view and
aggregated experiences of relevant applied research centres in
Europe and America).
We argue that Visual Computing could play and important
role in the development of Industrial Internet and Industrie 4.0
This paper is structured as follows: in section II we present an
illustration of concepts focusing in the topics of Industrial
Internet and Industrie 4.0 and showing the need of Visual
Computing technologies. In section III we illustrate the
relevance of Visual Computing as Key Enabling Technology
with an arguably central role in both visions, detailing the
most relevant technologies for the related industrial priorities.
Section IV proposes specific application and research
challenges in the field, and lastly, in section V we show some
examples of projects where Visual Computing plays a relevant
role for Industrie 4.0.
Advanced Manufacturing is defined as the kind of
manufacturing that entails rapid transfer of new knowledge
into industrial processes and products [15]. It is widely
accepted that ICT technologies are Key Enabling
Technologies to accelerate and improve productivity in
manufacturing. The deployment of ICT in the late 60s into
production was actually an Industrial Revolution. The
competitive factories of today cannot be conceived without
today´s Industrial Automation pyramid (including PLC, MES,
ERP and other key technologies) in production, or without the
Product Lifecycle Management supported by advanced
CAD/CAM/CAE tools, just to mention a few evident cases.
Recent developments in ICT are arguably opening
revolutionary possibilities for manufacturing and production,
being the most important one the implementation of the latest
internet-related technologies in the industry. Due to several
technical, market and cultural reasons, industry is
paradoxically one of the last niches to be conquered by the
pervasive and ubiquitous developments associated with the
Internet of Things and Services.
In the USA, the so called “Industrial Internet - the Third
Wave” –term coined by General Electric in their visionary
paper [1] already widely accepted in many American
academic organizations such as NSF I/URCC Center for
Intelligence Maintenance Systems (IMS) and other relevant
industrial actors, has a strong focus on a higher degree of
intelligence with the power of advanced computing, analytics,
low-cost sensing and new levels of connectivity permitted by
the Internet [23]. Three elements characterize this vision:
(i) intelligent machines,
(ii) advanced analytics, and
(iii) people at work.
In Figure 1 the data loop of Industrial Internet points out very
relevant aspects for which Visual Computing could be a Key
Enabling Technology, such as remote and centralized data
visualization, or big data analytics.
Figure 1. Industrial Internet data loop (General Electric) [1]
On the other side, the strategic initiative Industrie 4.0 (whose
leitmotiv is as ambitious as “Securing the future of German
Manufacturing Industry”) [6] has created not only a German-
wide but an international landmark in terms of setting the
vision, technological opportunities and scientific challenges,
related with the entrance of the new generation of ICT
technologies, including the Internet of Things and Services
and the Cyber-Physical Systems (or CPS) [10,16], in industrial
production systems. The basic idea is that we are facing a
fourth industrial revolution (see Figure 2), with disruptive
applications of new generations of ICT in manufacturing..
Interestingly enough, the CPS concept was actually coined by
US in 2006-2008 by Lee et al. [7]. This concept has been
readily adopted in Europe by Germany in the Industrie 4.0
initiative and later by the European Union in their H2020
research framework program [5]. CPS refers to the
convergence of the physical world and the digital world
(cyberspace). When applied to production, CPS is specialized
in CPPS or Cyber-Physical Production Systems. Even
considering that there is some criticism regarding certain
vagueness in the term and sometimes excessive marketing [4],
it is now widely accepted that the vision and the related
technologies of Industrie 4.0 have set already a real impact in
current and future industrial manufacturing systems.Reputed
independent studies [22] show that the potential of Industry
4.0 is already on its way, and that its international scope is
clear, especially for Europe. This study shows specific
examples of European companies (such a Trumpf –smart
social machines-, Siemens –customized knee implants-, Bosch
and many others in Germany, but also Rolls-Royce -3D
printing of jet engine components- in UK, and Dassault –cloud
based collaborative 3D CAD- in France, for instance) are
pioneering this trend
In both USA and European visions a strong industrial
commitment with long term associations is backed up by
research institutions: The Industrial Internet Consortium was
constituted in 2014 and the Industrie 4.0 Plattform in 2013.
Figure 2. Industrie 4.0–The 4th Industrial Revolution with CPS [6]
In Figure 3, a conceptualization of Industrie 4.0 and implied
interaction technologies by a leading machine tool producer
(Trumpf) [9] is shown. The coexistence and mutual interaction
of the physical world and the virtual (cyber) world, with the
use of emerging ICT, opens possibilities such as:
(i) the concept of social machines following paradigms of
Internet connectivity and Social Networks,
(ii) the seamless interconnection of global facilities,
(iii) the advantaging of augmented operators with extended
perception and action possibilities and
(iv) last but not least, the use of Smart Products able to know
and update their status providing services in a virtual
production context.
As it will be shown in the next section, the detailed
technological concepts behind Industrie 4.0 are somewhat
lacking of cohesion. Diverse technologies such as Big Data,
Advanced HMI, 3D Models and Simulations, Cloud
Computing, Cyber-Physical Systems, Internet of Things and
Services, Machine to Machine (M2M), and Smartization [8]
can be applied in Industrie 4.0 solutions. Isolated, they seem to
have no evident relation but when used together in an
industrial application context their added value brings new
Figure 3. Interaction possibilities in a Smart Factory scenario [9]
We argue that Visual Computing technologies are an
important Key Enabling Technology that could act as a “glue
factor” providing a cohesion element in many applications
related with Industrie 4.0 and Industrial Internet. Although in
several scenarios of Industry 4.0 there is no specific role for
Visual Computing (as for instance in pure IoT connectivity
applications between machines and parts), in many relevant
cases its role as facilitator and integrator of other technologies
enhances sensibly the final application. As a relevant example,
Visual Analytics solutions can link industrial Big Data
processing & mining, with Semantic Technologies and
Product Lifecycle Management technologies (each technology
separately would have a more limited impact).
One of the most successful application areas for Computer
Graphics has been industry and manufacturing. To point out a
very relevant example, the whole field of 3D CAD/CAM/CAE
is a very direct consequence of the key enabling capability of
Computer Graphics in the right industrial moment. 3D CAD
research that started in the late 60´s has been decisive for the
competitiveness of many industrial sectors, conspicuously the
automotive, aeronautic, industrial plants and machine-tool
sectors. In the case of Computer Vision, the industrial sector
has also a great importance, especially when applied to quality
control and inspection (Machine Vision) of manufactured
products, and more recently to robotic control, to name two
relevant fields. Almost every manufacturing industry has such
systems integrated. These evident examples complemented by
many others, showing how Visual Computing technologies
have a very strong position in modern digital manufacturing.
We consider that Visual Computing will be also a Key
Enabling Technology in the new generation of Industrial
Internet and Industrie 4.0, along with other technologies such
as Industrial Automation.
Looking at the future, in the strong global wave represented by
Industrie 4.0, Industrial Internet, and other similar initiatives, a
somewhat disperse collection of technologies is mentioned
recursively as necessary for achieving these visions. Surely the
Internet of Things and Services is the core technology, since
this is being revolutionized by the emergence of intelligence
(intelligent devices, intelligent networks, and intelligent
decisioning) [2], and complemented by fully cloud-based
systems, cost-effective Internet solutions for industrial set-ups,
secure and robust networks, mobile Internet possibilities, etc.
But it is also true that a few key additional technologies are
indeed necessary for complete solutions, such as Cyber
Security or Semantic Technologies [17]. A comprehensive
review of relevant technologies for Industry 4.0 from the point
of view of an authorized relevant standardization body can be
found in the chapter 4 of [27]. We simplify this
comprehensive view in Figure 4, pointing out the relevance of
Visual Computing technologies (explicitly quoted as computer
graphics, image processing. 3D, image representation,
visualization, user interfaces, etc.) in this context.
We suggest that Visual Computing could play a key role in
enhancing and enabling the realization of Industrial Systems
that follow the new paradigms of the next industrial
revolution. In many cases it is precisely the use of Visual
Computing technologies what allows a complete and
integrated solution (see Fig. 4), since acts as a “glue factor”.
This is not necessarily always the case (there are for instance
solutions purely based on Industrial Automation and IoT that
don´t require Visual Computing). However, when we see the
overall picture of the possibilities of this wave-revolution,
Visual Computing plays indeed an important role and will be
present in many solutions.
Figure 4. Visual Computing as part of the technologies in
Industrie 4.0
In order to achieve Cyber-Physical Systems for Industry, the
virtual simulation of products and processes, before and
during operation, are a key aspect for achieving critical goals
for product configuration and production flexibility. The
modeling and simulation of processes covering the full
product lifecycle (from design to disposal) is a very relevant
aspect, especially with the emergence of the Cyber-Physical
Equivalence (CPE) concept, coined by Lukas and Stork [11].
The aforementioned concept refers to the fact that virtual and
physical dimensions coexist synchronized in time. The
equivalence given in terms of digital twins provides very
interesting features as virtual simulation can be overlapped
with the physical object feeding real data being processed in
realtime and overlapping the simulation model in an
unobtrusive way. CPE is relevant in our approach because the
set of tools that will allow the inter equivalence between the
real object and its twin need advanced Computer Graphics
techniques for its implementation in a real world scenario. Not
only is the product level addressed but also the processes
level, the machines and the factories. Virtual simulations
should be ready to cope with self-organizing production and
control strategies [21]. This is a clear linking example of
Product Lifecycle Management, Industrial Automation and
Semantic Technologies [20], in which Visual Computing plays
a central role.
A new generation of Human Machine Interaction applied to
industry is needed for optimizing the configuration of
manufacturing jobs, including not only operation of machines
and production lines, but also aspects related to extended
training and qualification. These are intelligent and
multimodal assistance systems that put the person in the centre
of production. For instance, there are HMI related research
projects financed by the German Government in the program
Virtual Techniques for the Factory of the Future – A
Contribution to Industry 4.0", [3]. Many of those projects
address enhanced HMI development with a special focus in
involving the interaction using personal mobile devices with
scattered and heterogeneous CPS. The traditional and de-facto
standards for operation of machines can move towards
radically new forms of interaction, including gestures, mimics
and haptics, using new forms of “interaction primitives” in
analogy to the currently normalized functions and symbols
for machine operation. HMI by itself is a factual part of
today’s manufacturing systems and it is present in the
manufacturing lines more and more. New technologies related
to HMI like multi touch and contextual menus categorized by
user roles are new approaches in both the technical and
conceptual perspectives and they are now part of some of the
catalogues of machine-tool providers. It is a fact that HMI new
developments need to be aligned with CPS gathering of data
and being essentially oriented towards a user perspective.
Such systems will involucrate the user in the factory as a
consumer and producer of knowledge that can be advantaged
by the manufacturing processes.
A last example is related with the Industrial Big Data and the
need of new enabling capabilities for Intelligent Decisioning
emphasized in the Industrial Internet initiative. The potential
of Visual Analytics (an important scientific field in Visual
Computing) is serving as “glue factor” and enabling
technology for linking otherwise separated technologies such
as Industrial Big Data, IoT-Cloud, Intelligent Devices and
Semantic Technologies. Industry is one of the most
demanding and challenging scenarios for Visual Analytics: as
pointed out in [18] in many cases billions and even trillions of
individual products of certain industries are produced per year.
Also, the level of information provided by modern machines
and production lines can be of very high orders of magnitude
(a single complex machine can have a couple of thousand
sensors, that in some cases should be read in milliseconds
pulses, providing many billions readings per year). This
requires not only new ways of handling the sheer amount of
information, but also new forms of organizing the information
in a sensible way to be understood by humans and allow them
to take decisions. Visual Analytics can help to provide new
insights and hidden patterns, not evident by purely automatic
data mining.
There are many other examples that reinforce our claim, such
as the IntoSite project of Ford and Siemens using Geographic
Information Systems and VR Environments to navigate global
manufacturing sites and share best practice information; or the
SmartFactory Lab hosted by DFKI in Kaiserslautern
(Germany) demonstrating the use of Visual Computing
through the use of mobile devices and advanced visualization
techniques such as Augmented Reality for accessing and
analyzing the information generated in an integrated
Intelligent Factory;; or the Spanish applied research project
Thinking Factory led by the crankshaft manufacturing
company Etxe-Tar, where Visual Computing techniques are
applied for visualizing and analyzing Big Data, gathered by
CPSs installed in several manufacturing cells for the
generation of services such as preventive or predictive
In Figure 5 we have performed an analysis of the most
relevant Visual Computing technologies to determine the
significance for future applications in Industrie 4.0 and
Industrial Internet as it has been proposed for example by the
ARVIDA, SOPHIE, ProSense, SmarPro and similarprojects
in Germany [24]. This is a useful guide to identify critical
crossings between priorities of the next industrial revolution
based on ICT and the fundamental Visual Computing
technologies that can act as enablers. The criteria in the left
side of the figure will be explained in more detail in the next
chapter, where concrete examples will be introduced
developing the concepts of this matrix. This matrix is by no
means exhaustive, in the sense that other crossings are also
possible depending on the application scenario.
The figure shows interesting confirmation of the relevance of
Visual Computing in this context, and at the same time is a
way to align research priorities in the specific technologies
with regard to the different needs of the new generation of
industrial systems based on Industrie 4.0.
Figure 5. Visual Computing technologies relevant for Industrie 4.0
This section will focus on specific research challenges and
potential applications of Visual Computing for the next
industrial revolution proposed by Industrie 4.0 and Industrial
Internet. We order these proposals according to high-level
criteria that are at the core of these initiatives [1, 6], and that
are depicted at the left side of Figure 5. We will summarize
the relevance of these criteria and propose application
scenarios for the crossing with Visual Computing
technologies. The purpose is to suggest interesting research
lines in each of the priorities and show at the same time from a
global perspective the integrative and relevant role of Visual
In this context, we would like to recall the work by von Lukas
and Stork [11] (in German), that proposes that Visual
Computing can help in a bidirectional way to achieve Cyber-
Physical Equivalence in Industrie 4.0: the direction of
cyberizing the physical” (inluding different sensors/actuators
with physically-based simulation) and the opposite direction,
physicalizing the cyber” (realistic, real-time visualization
and interaction with digital models and also the 3D printing
area). They also point out a short summary of themes of
Visual Computing relevant for Industrie 4.0, related with
geometric data models adapted to CPS, real-time simulation
approaches, or image processing needs to reconstruct and
cyberize” the physical world. With a similar approach, our
work gives an enhanced and more comprehensive and global
overview, with concrete examples, and adds a direct and
explicit link with the strategic priorities of both the Industrie
4.0 and the Industrial Internet initiatives.
Our proposed matrix is designed based on three main criteria:
1) the integration dimensions,
2) the product and production priorities, and
3) the human factors dimension.
The methodology that we use to present these challenges and
applications is to sketch them in the 3 tables of this section,.
The Computer Graphics and Visual Computing researcher
should be able to define and identify, from the context and the
proposed subject, specific research contributions in each line.
The tables focus more on providing a path (a roadmap of main
global challenges) than in detailing each challenge. To
illustrate this approach we present one scenerario for each
table category.
The first criterion in our proposed matrix is related with the
“integration dimensions. According to ACATECH [6], there
are three dimensions in the integration of manufacturing
- the Vertical integration and networked manufacturing
- the End-to-end digital integration of engineering across
the entire value chain
- the Horizontal integration through value networks
Vertical integration allows CPS be used to create flexible and
reconfigurable manufacturing systems. The setting for the
vertical integration is the Factory. It refers to the integration
of various Information Technology systems at different
hierarchical levels during a manufacturing process and that is
where CPS plays an important role as sensor/actuator duality
behavior elements. Visualization of the complex interaction
between these levels may help the user to improve the factory
ICT systems in end-to-end digital integration refers to a
holistic digital engineering view, and proposes to close the gap
between product design and manufacturing and the customer
(Product Lifecycle Management), from the product design and
development, through production planning, production
engineering, production and associated services. This is one of
the central aspects where Visual Computing has an influence,
since CAx systems are highly visual.
Finally, horizontal integration refers to the use of these
technologies for exchanging and managing information across
different agents around a manufacturing process such as
resources management system, logistics, marketing, or inter-
company value chains. As an example, Augmented Reality
based maintenance, with the newest advances in devices and
processing, can be an excellent case for Visual Computing
contribution to horizontal integration
Table 1 shows how Visual Computing enabling technologies
are related with aforementioned integration dimensions.
Vertical Integration requires a level of communication and
interaction between different production layers, towards a
Smart Factory vision. Visual Computing technologies such as
as real-time 3D representation of data-flow during product
manufacturing are important enablers in this dimension
Table 1. Industrie 4.0-Future Factories – Visual Computing Challenges in the 3 Integration Dimensions
Industrie 4.0–Integration
Dimension Visual Computing Enabling Technologies and Challenges
Vertical Integration, networked
manufactured systems:
Autonomous CPPS that
exchange information, trigger
actions and control each other
-Virtual Environments: Visually empowered 3D Simulation scenarios for new ways of planning production, especially
suitable for dynamic & fast changes. Scenarios for testing different configurations.
-Real time representation of production: Visualization of flows of information/material/knowledge in the factory, not only
physical representation.
-3D Scanning / 3D Reconstruction of factories: real need and big challenge to adapt old factories to new paradigms.
-End User Interfaces to edit configurations in demanding work conditions (in production lines).
End-to-end digital Engineering
Holistic Lifecycle Management
-Natural flow of the persistent and interactive digital model in Product Lifecycle Management in Full 3D Web: Real
industrial large 3D CAD/CAM models with full access to semantic/product dynamic data in Web3D.
-3D real-time simulations for a cyber-physical equivalence of production.
-New paradigms of 3D Geometric representation of new processes (e.g. laser based manufacturing, fast-speed material
removal, micro and nanomanufacturing, etc.) and new materials (biomaterials, metallic powders for 3D metal printing,
-Computer Vision “Closing the loop” of 3D production planning, giving real-time coupling of production process and 3D
models. Geometry adaptation to physical conditions.
Horizontal integration through
value networks:
Value chain integration
-Augmented Reality for service-based actions with providers and clients. Maintenance and installation are the main
drivers. Main Challenges are in the ergonomic aspects of the solutions going from the lab to the real factory and in the
integration with the information systems. Intelligent Media streaming/search is also a key technology to improve service
(as in teleoperation).
-3D Model automatic simplification preserving critical features for service tasks and at the same time allowing
interaction/visualization in mobile low-power devices in the client.
The end-to-end integration dimension can benefit from Visual
Computing techniques such as 3D visualization techniques
for realistic product representation and simulation.Also
Computer Vision related techniques for product quality
management, both offline and online, are relevant. Online
real-time Computer Vision techniques allow closing the loop
from product design and product manufacturing, i.e.,
providing immediate feedback from the real part to be
compared with the digital 3D model. In an Industrie 4.0
scenario, this can be a dynamic feedback as the part is being
manufactured, not a comparison between the final part and the
static 3D model
Finally, horizontal integration is also enhanced by Visual
Computing through the using of, for example, Augmented
Reality techniques for added-value services, such as functional
or installation augmented manuals (AR manuals).
Also, techniques related with 3D compression, model
simplification or model adaptation by using semantic
information can be fundamental when big amounts of 3D data
need to be interchanged or transferred to different entities
through value networks. This problem existed also before, but
with Industrie 4.0 it becomes more relevant.
To illustrate some specific challenges that stem from Table 1,
let´s look into “new paradigms of 3D Geometric
representation of new processes” in more detail. For the
Computer Graphics researcher, there is a challenge in devising
new ways to represent 3D Geometry for CAD/CAM, since
radically new fabrication processes emerge and require new
3D representations and algorithms (for instance slicing). Take
as example 3D Printing: computational aspects of this type of
fabrication are posing research challenges such as appropriate
orthogonal slicing [25][26]. Other challenges here include
volumetric representations, to cope with multiple materials
and a sheer number of voxels.
The second criterion in the matrix, described in Table 2, is
related with product and production priorities in Industrie 4.0.
We have taken as basis the priorities explained in [6] (pages
15-18 and 20-25) and have conceptualized, reorganized and
summarized them in such a way that the applicability of
Visual Computing technologies is more evident for a meta-
category of product and production, leaving all priorities
related with human factors in a separated category. This
classification also helps to bridge more clearly with the
Industrial Internet priorities.
According to this classification, the product self-awareness is
a requirement for the so called “Smart Products”. In this
context, the use of technologies such as 3D Cyber-Physical
Equivalence, to make the physical and virtual representations
of parts, machines and lines fully synchronized, are essential.
Optimized decision-making is one of the most critical
requirements where Visual Analytics applied to Industrial Big
Data can give new insights to decision-makers. The feedback
given by production data to 3D digital engineering in real-time
can be a key factor to model the deviation between the
theoretical model and actual product. Specially adapted User
Interfaces are also necessary, adapted to user profile and
context. Web3D can provide new possibilities for the
Emergence of new services and business models, which is a
very important motivation in Industrie 4.0, technologies such
as the ”in” or “digital alter-ego” of the product [19]. Resource
and Energy Efficiency is another field of high interest, where
virtual environments, GIS, simulation & visualization, open
new ways to improve these aspects in Industrie 4.0. As an
example, the interactive study of different logistic paths to
transport parts from one factory to another can lead to energy
efficiency measures
Let´s analyze in more detail one of the challenges of Table 2:
Visual Analytics for Production Big Data. As presented in
[18], a typical real-life scenario in the manufacturing industry
of personal care products can produce 152.000 data samples a
second (in millisecond cycles), 13 billion of samples a day,
and 4 trillion of samples per year. Visually inspecting clusters
of sample data in time may give a hint for a specific
production bias due to, for instance, machine deterioration.
Visual Analytics opens in this context new ways to handle this
complexity and get insights from this overwhelming amount
of data, but only due to newest advances in Big Data and
visualization (such as presented in several articles of IEEE Big
Data 2014) such challenges can start to be addressed today.
Table 2. Industrie 4.0-Future Factories – Visual Computing Challenges in Product & Production
Industrie 4.0– Product &
Production Visual Computing Enabling Technologies and Challenges
Product self-awareness (history,
status, location, delivery strategy,
-Integration of GIS (outdoor) with in-factory (indoor) localization-visualization systems, for individualized product
tracking and as underlying connection layer between factories and products when delivered.
-Cyber-Physical 3D equivalence at all times linking product digital model and situational status.
Personalization / flexibility –
flexible adaptation to Individual
customer requirements
- 3D interactive tools to empower of the end user in the final configuration of his/her own product.
- Automatic generation of options catalogue according to production parameters and user preferences.
- 3D Shape automatic adaptation that fits production and manufacturing restrictions.
- Linking of 3D changes with resource impacts (in time and cost).
Optimized decision-making with
access to real-time production
and design data
-Visual Analytics of Production Big Data: Trillions (or more) samples per year (e.g. GE Industrial Big Data [18]).
-Real-time mixing of production Big Data with 3D digital engineering design data
-User Interface dynamic adaptation of information to user-profile, devices and context. Visual Analytics system for the
engineer and the worker.
Emergence of new services and
business models -Digital coexistence or “alter-ego” of the physical product, enabled by Web3D, localization and mobile interaction
technologies, allowing new services (e.g. social networks of users of the same product line).
Resource and energy efficiency
& Sustainable production -Dynamic resource visualization at the factory level, including sustainability footprint (e.g. CO2 consumption), energy
distribution in the plant, material waste, etc. Can be mixed with VR and in some cases Augmented Reality.
The third criterion, described in Table 3, is related with the
human factors dimension. Industrie 4.0 and Industrial Internet
visions, and also the visions of EFFRA/EU (EFFRA roadmap
for the Factories of the Future) [5], recognize the strategic
importance of skilled workers and engineers for a competitive
Smart Factory vision. For work organization and design where
novel multimodal HMI and new interfaces can change the
current operation of machines and factories by workers.
Fostering the creativity of skilled workers by means of virtual
simulation of production, and training and knowledge capture
[17] can also be achieved with new multimedia and
Augmented Reality techniques. For safety and security,
cognitive vision and virtual simulation of emergencies are
enabling technologies. Finally the socio-technical interaction
with robots and intelligent machines is a promising area
enhanced by Visual Computing technologies such as 3D
reconstruction, virtual environments and visual programming
of robots.
Let´s analyze as an example for Table 3 the challenge of “New
Human Machine Interface modalities” in an Industry 4.0
perspective. A very good and detailed study on this subject,
where the challenges are explained in detail, can be found in
[28]. To mention a few of th 26 identified tools and challenges
in this work: separation of display and interaction logic,
integration of multimedia, real-time data from different
perspectives, support for different HMI variants, self learning
context recognition, dynamic user profile, interfaces to MES
for a preview of simulation results, HMI design and
communication interfaces for mobile devices, support for
multi-touch and gestures, social (chat/wiki/blog), and open to
new input possibilities.
As a summary of this section, the researcher interested in
computer graphics and Visual Computing can identifyrelevant
research lines and challenges for Industry 4.0 and Industrial
Internet. We provide hints to main topics of interest and open
challenges, researchers can follow to detect more specific and
detailed challenges in each of them.
Table 3. Industrie 4.0-Future Factories – Visual Computing Challenges in Human Factors
Industrie 4.0– Relation with
Human Factors Visual Computing Enabling Technologies and Challenges
Work organization and design,
productivity enhancement though
improved human intervention
-New Human Machine Interface modalities allowing new modes of interaction adapted to workers job restrictions: voice-
based interaction, gesture recognition, etc.
- Need of Post-WIMP interfaces adapted to the future trend of mobile devices in the factory.
-Advanced Manufacturing and Production Planning visualization: linking SCADA systems with Virtual Reality
paradigms for interaction in the planning and understanding of the production plan.
-Interfaces with Manufacturing Execution Systems (MES) allowing different configuration capabilities.
Foster creativity in skilled
workers instead of routine -End user tools for visualization of flexible production plans including the location of different machines and persons
(with complementary skills) in alternative production scenarios. Tools for discussions between engineers and workers.
Training and continuing
professional development.
capture and systematic reuse of
the knowledge of the worker
-Multimedia capture and intelligent retrieval of the knowledge of the worker, as a Key Enabling Technology to capture
and transfer knowledge between the workers.
-3D Authoring tools and end-user UI for operational training of complex machines, and in some cases in Virtual and
Augmented Reality set-ups.
Safety and Security -Cognitive Computer Vision systems able to detect and contextualize the events occurring in the factory with the goal of
improving safety and security. Focus on hazardous area exposition, collision detection with massive objects.
-Visual Simulation for Emergency Response in the factories.
Socio-technical interaction, co-
working with configurable robots -Visual programming of robot interactions: imitation of human motion based on Computer Vision for anthropomorphic
robots. Ease of use and control of the robot by the worker, not necessarily the engineer.
-Virtual Environments simulations for human-robot coexistence in production, different configuration and parameters.
In this chapter we present 3 selected examples of research
projects directly related with Visual Computing applications
for Industrie 4.0, covering a broad spectrum of the criteria
presented in last chapters.
MACHS: Virtual platform for professional training of complex
machine operation scenarios based on Serious Games
The main goal of the R&D project MACHS is the
development of a game-like 3D environment to accelerate and
improve the training process (previous to actual operation of
the machine) of specialized machine-tool maintenance staff. It
is promoted by the industrial group Danobat –(part of
Mondragon Corporation, one of Europe’s largest industrial
groups). Target user of the system are professional workers
who have to apply their knowledge to new and different
specialized machines, that in some cases are not even
produced yet. Therefore, it is important to generate high
quality interactive 3D environments, with a pedagogical focus,
to enhance the immersivity and user experience, but it is even
more important to provide appropriate authoring tools and
graphical interfaces for non-ICT specialists to construct the
learning experience, and to follow the maintenance tasks
performance during the execution in the system [12]. Serious
games environments can support different configuration
scenarios that may come as a result from machine adaptation
to flexible production, in contrast with static manuals (in the
form of written manuals or videos showing specific
sequences) where everything is predefined in advance. In the
future, this kind of environments should be, if possible,
automatically generated even in changing conditions, although
in current versions of the project this is still not possible, and
require a preliminary definition that can evolve according to
programmed rules in the game.
The preliminary definition of the interaction of the worker and
the machine in MACHS is a basis for the planning of new
generation of Cyber-Physical Systems in which in many cases
the proper interaction between the workers and machines
and/or robots have to be carefully monitored, more especially
if we consider and flexible configuration scenarios. By
providing different training experiences (such as the point-of-
view vs. external observer perspectives), and allowing
multiple trial-error actions with appropriate feedback,
MACHS allow a natural way to expose the worker to the
unknown environment of these new machines scenarios.
This links with the Human Factors requirements in Industrie
4.0 [6], described in Table 3, related to training and continuing
professional development for supporting future demands of
having even more production flexibility.
The interaction with the module is intuitive and visual, giving
the user the possibility to include 3D virtual models of specific
machines and to define actions directly by interacting with the
3D model of the machine. The module also provides custom
functions to enhance the commitment of the target user of the
course, such as the inclusion of the 3D virtual tutor, and
gaming and motivational features. XML-compliant forms are
automatically generated by the authoring module, which is
based on an intuitive state diagram graph editor linking
machine parts and worker actions (Figure 6), and they include
the virtual machine specifications (describing the main
functional parts of the machine, and the degrees of freedom
and constraints for their relative movement) and all the
information that is required to build the actions that compose a
training course. The concrete specification of these XML
compliant forms can be found in [12]. A sequence of actions
is then defined where the user can simulate the operation of
the machine in different conditions.
The animation engine is able to automatically generate a 3D
interactive environment from the information stored. It
interactively reproduces the graph that has been created with
the authoring module, reacting to the user actions in the way
the author of the course has specified, and following the rules
that allow possible different configuration of the actions
The project has been evaluated by machine-tool companies
from Danobat Group and is under prototype test with their
new machines for two main purposes: training and marketing.
Figure 6. Immersive 3D & Authoring Tools for training of workers,
relevant for Industrie 4.0
COGNITO: Capturing of manipulative workflows with
Augmented Reality
The main objective of COGNITO is to develop technologies,
which allow the capturing of manipulative workflows in
industrial production scenarios in such a manner that it can be
then used as training material for adaptive Augmented Reality
training set-ups.
COGNITO is an EU-funded collaborative research project
related with Industrie 4.0 –the SmartFactory KL is the laeding
partner for the Industrie 4.0 demonstrator [19].
The relationship with the priorities presented in human factors
is related with the capture and systematic reuse of the
knowledge of the worker, as shown in Table 3. It is also
related with the vertical, horizontal and end-to-end
dimensions of integration in Table 1, regarding the use of
Augmented Reality techniques for implementing advanced
HMI, applied to training and maintenance. Although capturing
systems already exist on the market, they focus primarily on
capturing raw motion data, matched to a coarse model of the
human body. Moreover, the recorded data is organised as a
single kinematic sequence, with little or no reference to the
underlying task activity or workflow patterns exhibited by the
human subject. The result is data that is difficult to use
requiring extensive editing and user manipulation, especially
when cognitive understanding of human action is a key
concern, such as in virtual manuals or training simulators in
industrial scenarios.
COGNITO technology addresses these issues by advancing
both the scope and the capability of human activity capturing
and rendering. Specifically, it developes novel techniques that
allow cognitive workflow patterns to be analysed, learnt,
recorded and subsequently rendered in a user-adaptive manner
[13, 14]. Our concern is to map and closely couple both the
afferent and efferent channels of the human subject, enabling
activity data to be linked directly to workflow patterns and
task completion. Focus has been put particularly on tasks
involving the hand manipulation of objects and tools due to
their importance in many industrial applications. The key
elements of the developed technology is a novel on-body
sensor network consisting of miniature inertial and vision
sensors, estimation of an osteo-articular model of the human
body, recovering the workflow digitally, and developing novel
rendering mechanisms for effective and user-adaptive
visualization. The work has been evaluated within the context
of designing effective user assistance systems based around
Augmented Reality techniques for specialised industrial
manufacture and has been carried out in close collaboration
with industrial and end user partners with promising results.
Figure 7: Created visual workflow using video observation
(upper images); Augmented Reality support, using previous
digitalized visual workflow
Figure 8: Visual workflow using AR Manuals. The user sees
his/her own hand overlapped with the hand of an expert who
recoded the sequence previously. Green color means that
movements are correct in order and tolerance.
SLOPE: Integrated Processing and Control Systems for
Sustainable Exploitation of Forests
This is rather unconventionalexample of how Industrie 4.0 and
Industrial Internet can affect not only the factories themselves,
but can affect also important production scenarios closely
related with logistics and industrial exploitation of raw
materials (in this case, wood from forests) – considering the
horizontal integration dimension introduced in Table 1,.
Mountains in Europe occupy ~35% of the land area and are
mostly covered by forests. Forestry operations in mountain
areas are seldom performed by the harvester/forwarder
system, being the sector still characterized by manual felling
and extraction of timber by cable cranes. Due to the limits
posed by steep terrain conditions, poor road network of
mountain areas, limited storage and operational room,
harvesting and extracting systems are more expensive and less
flexible compared to the cut-to-length systems based on
wheeled machines, commonly found in flatland forests of EU
Nordic Countries. Powerful and more intelligent machines
must be developed for forest works in steep terrain. This is the
gap that the European project SLOPE is trying to fill, by
developing an integrated system (CPS), supported by
information technologies such as GIS-based 3D visualization,
tracking technologies, covering the cycle from forest
information system to logistic transportation, and allowing
optimization of the forest production in mountain areas.
Information about material origin, quality and availability will
be integrated in a unique system, accessible online using
Web3D and GIS technologies, and available in real time to a
series of operators.
The historical series and up-to-date remote sensing data, and
other relevant information related to the area (i.e. local land-
use plans, cadastral maps, and other thematic maps) will be
loaded into the system. Remote sensing analysis of multi-
spectral images will be performed in order to extract macro
information of the forest (biomass volume, spectral vegetation
indices –SVIs-, growth rate). Furthermore a combination of
UAV or Vehicle Mounted LIDAR (Light Detection and
Ranging) and Terrestrial Laser Scanner –TLS- surveys will be
planned and carried out some weeks before the scheduled
harvesting operations (point 1 in Fig.9). The processing of the
acquired data generates the Digital Forest Model (DFM),
where each tree is a single object in a 3D Geodatabase
providing greater product knowledge (point 2 in Fig.9).
The DFM will support the forest planners for multiple criteria
decision analysis (MCDA), to plan and simulate the harvesting
operation, taking into account all possible constraints (e.g.
infrastructural, geomorphological, etc.) and optimization
procedures (e.g. joint forest management and coordination of
harvesting of adjacent parcels owned by different landowners)
(point 3 in Fig.9). The DFM will also support specific logistic
decisions, such as the selection of the optimal cable crane
positioning and set-up. As an added application, the DFM
could be used as a tool for pre-selling procedures, where one
or more customers commit to buy the whole lot upon
estimation of the volume and the timber assortments
potentially available.
Figure 9: SLOPE project – full cycle
In this example, we may say that the “smart factory” location
is actually the forest: the actual industrial activity happens in
the forest and not in man-made physical premises. Also the
“products” are not manufactured goods, but trees cut.
However, many of the possibilities and concerns of Industrie
4.0 are also present in this case, as explained before: logistic
chains, virtual models, flexible/adaptive production, etc.
We have presented in this work a comprehensive view of how
Visual Computing can contribute as a Key Enabling
Technology to Industrie 4.0 and Industrial Internet. This new
wave (or revolution) is now opening new fields for
productivity, the emergence of new business possibilities and
opportunities for securing the future of Manufacturing in
advanced economies with a high industrial value added. There
are four compelling reasons to consider Computer Graphics,
Computer Vision and in general Visual Computing
technologies essential to these visions:
(i) the deep roots of 3D CAD/CAM modeling as Key Enabling
Technology for digital manufacturing
(ii) the “glue factor” capability that makes possible to
integrate other key technologies together (iii) the “virtual
component in the Cyber-Physical Systems of Industrie 4.0 and
the visualization component in Industrial Internet address core
Computer Graphics and Visual Computing concepts, and
(iv) the human factor and HMI are recognized in all these
vision as one of the main enablers (people at work in
Industrial Internet, people at the forefront in EFFRA/EU
roadmaps, and all human factors-related priorities in Industrie
4.0) Despite this central role, the current strategic vision
documents and research literature provide a somewhat
scattered view of Visual Computing technologies in this
context. This article positions Visual Computing in its intrinsic
crucial role for Industrie 4.0 and provides a general and broad
overview pointing out specific directions and scenarios for
future research. The scientific community in Visual
Computing will have new exciting fields of research linked to
the challenges of the next industrial revolution.
We would like to thank the European Commission for the
cofinancing of the COGNITO and SLOPE projects. We would
also like to acknowledge IK4-IDEKO and the company
VirtualWare for providing interesting scenarios for the
MACHS project, and in general to all project partners of the
presented projects. We also thank ETXE-TAR for their strong
support in promoting real applications of Industrie 4.0
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Dr. Jorge Posada is Associate Director of Vicomtech-IK4 Foundation
(Spain), and President of He is guest member from IK4
Research Alliance in the subgroup “Industry 4.0” of Acatech (German
National Academy of Science and Engineering). He has published over 60
articles in Computer Graphics, virtual engineering and multimedia.
Dr. Carlos Toro is Senior Researcher at Vicomtech-IK4. He is expert in
semantic technologies for virtual engineering and has chaired international
conferences in the field.
Dr. Iñigo Barandiaran is Head of Department of Industry and Advanced
Manufacturing in Vicomtech-IK4. His main research topics in Visual
Computing are Computer Vision and machine learning for feature extraction
and recognition.
Dr. David Oyarzun is Head of Department of 3D Animation and Interactive
Virtual Environments in Vicomtech-IK4. His main research interests are
Virtual and Augmented Reality.
Dr. Didier Stricker is Scientific Director of “Augmented Vision” at the
German Research Center for Artificial Intelligence (DFKI) and CEO of the
international organization of Computer Graphics institutes
Dr. Eng. Raffaele De Amicis is Managing Director of Graphitech. His
interests are in CAD, virtual reality, virtual engineering, and geoVisual
Eduardo Pinto is Senior Advisor of Universidad do Minho, and was during 8
years Executive Director of Centro de Computação Grafica in Portugal.
Dr. Peter Eisert is head of Computer Vision & Graphics at Fraunhofer HHI
and is Chair on Visual Computing at Humboldt University. His research
topics are 3D scene and surface reconstruction, object tracking and
Dr. Jürgen Döllner is full professor of computer science at the Hasso-
Plattner-Institute. His research fields are Computer Graphics systems and
Ivan Vallarino Jr. is CEO from Mivtech, Panama.
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... Unnecessary motion is uneven movements of human and machines on shop floors. CPSs coupled with machine learning and smart sensors can easily identify and control unnecessary motion during operation and servicing (Posada et al., 2015;Jazdi, 2014). Accurate mapping of production streams is possible by getting real time feedback from sensors and actuators. ...
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Our work explores the blend of science, art, and technology in chaos physicalization, translating complex mathematical models into tangible designs. It is closely aligned with research on data physicalization, drawing from design creativity and innovation models. Through interdisciplinary collaboration and innovative tools, we bridge theory and practice, fostering a culture of creativity. Industry 4.0 technologies and education enhance practicality and inspiration, blurring boundaries between art, science, and technology. Our methodology follows a comprehensive six-step process: Selection of the Chaotic Model, Computational Manipulation of forms to be physicalized, Material Choice, Manufacturing, Post-Processing, and Quality Control. This systematic approach has successfully resulted in an exhibition, showcasing tangible objects that serve as representations of various chaotic systems. Demonstrated through this art museum exhibition, we prove that chaos generates artistic and scientific novelty, transforming data into a source of creativity and design innovation. Furthermore, our project emphasizes the significance of cross-disciplinary synergy, demonstrating how the physicalization of chaos can act as a catalyst for new educational and professional perspectives, opening avenues for future collaborations among artists, scientists, and technologists.
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The global supply chain has been growing strongly in recent years. This development brings many benefits to the economy, society, and human resources in each country but also causes a large number of concerns related to the environment since traditional logistics activities in the supply chain have been releasing a significant amount of emissions. For that reason, many solutions have been proposed to deal with these environmental pollution problems. Among these, three promising solutions are expected to completely solve environmental problems in every supply chain: (i) Application of blockchain in the supply chain, (ii) Use of renewable energy and alternative fuels, and (iii) Design of a closed supply chain. However, it seems to lack a comprehensive study of these solutions aiming to overcome the drawbacks of traditional logistics. Indeed, this work focuses on analyzing and evaluating the three above-mentioned solutions and the impacts of each solution on solving problems related to traditional logistics. More importantly, this work also identifies critical factors and challenges such as policies, laws, awareness, and risks that are found to be remarkable difficulties in the shifting progress of traditional logistics to green logistics. Finally, directions for developing and deploying green solutions to the logistics, supply chain, and shipping sectors toward decarbonization strategies and net-zero goals are discussed in detail.
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In this study, requirements and guidelines for the design of high-quality HMIs and the corresponding engineering tools are formulated. They can serve as orientation in future HMI projects, both for the design and development of attractive HMIs and efficient engineering tools, as well as for the selection of a suitable and future-proof HMI engineering environment.
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In Germany, the term ?Industrie 4.0 [1] is currently prevalent in almost every industry-related fair, conference, or call for public-funded projects. First used at the Hanover Fair in 2011, the term, raised numerous discussions, and the major question is: is it a hit or hype? Even in politics, this term is used frequently with respect to German industry, and research efforts relating to it are currently supported by ?200 million from government-funding bodies?the German Federal Ministry of Education and Research and the German Federal Ministry of Economic Affairs and Energy. The term Industrie 4.0 refers to the fourth industrial revolution and is often understood as the application of the generic concept of cyberphysical systems (CPSs) [5]?[7] to industrial production systems (cyberphysical production systems). In North America, similar ideas have been brought up under the name Industrial Internet [3], [4] by General Electric. The technical basis is very similar to Industrie 4.0, but the application is broader than industrial production and also includes, e.g., smart electrical grids. The various definitions have caused confusion rather than increasing transparency. Overambitious marketing reinforced the confusion (Industrie 4.0 is already being done). This obscures the real and sound future visions behind Industrie 4.0. This column is intended to provide easy-to-understand access to the core ideas of Industrie 4.0 and describes the basic industrial requirements that need to be fulfilled for its success.
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The globalization of the world’s economies is a major challenge to local industry and it is pushing the manufacturing sector to its next transformation – predictive manufacturing. In order to become more competitive, manufacturers need to embrace emerging technologies, such as advanced analytics and cyber-physical system-based approaches, to improve their efficiency and productivity. With an aggressive push towards “Internet of Things”, data has become more accessible and ubiquitous, contributing to the big data environment. This phenomenon necessitates the right approach and tools to convert data into useful, actionable information.
Conference Paper
The success of Linked Data (LD) [1] has enabled an environment in which application data can easily be enriched by the abundance of available information on the Web. Many recent approaches of the Linked Data community go beyond the mere exposure of static data and propose the combination of Linked Data and Representational State Transfer (REST) [3, 5, 7] to enable dynamic systems. However, in highly dynamic environments, where near real-time data integration and processing with high update frequencies are required, the perceived overhead of Linked Data query processing and stateless communication pattern often prevents the adoption of resource state exchange-oriented systems. Nevertheless, in our demonstration, we show a Virtual Reality (VR) information system that leverages the REST principles and the integration capabilities of LD. We specifically chose a VR setting, because it requires very low latency [2] in order to enable a natural interaction of the user with the system. Our system consists of loosely coupled components [4] as implicated by REST, and provides an interactive experience by seamlessly integrating existing LD sources from the Web as well as high dynamic body tracking data in a VR environment. We show how sensor data exposed as LD, can be processed with high update frequencies and be rendered in a VR environment. Constantly evaluated queries are employed to realise both gesture recognition and collision detection of objects in the VR. Derived actions like data retrieval from the Web and the subsequent integration of the retrieved data with the sensor data are performed on-the-fly.
The aim of the latest issue of the Cybernetics and Systems journal is to provide guidelines to develop tools for smart processing of knowledge and information. It gives ideas and case studies to explore and the complexities and challenges of modern knowledge management issues. It also encourages the reader to become aware of the multifaceted interdisciplinary character of such issues. The preview of this issue is that the reader will leave it with a heightened ability to think about developing, evaluating implementing, and supporting intelligent knowledge- and information-based management systems in real-life environments in different ways. This Guest Edition is based on some significant contributions provided by one of the most dynamic and innovative conference series in the area, held in Spain in 2012. A paper entitled 'A Hybrid Method for Fuzzy Ontology Integration', introduces a novel concept of combining heuristics and consensus-based conflict resolution for fuzzy ontology integration.
A new method fabricates custom surface reflectance and spatially varying bidirectional reflectance distribution functions (svBRDFs). Researchers optimize a microgeometry for a range of normal distribution functions and simulate the resulting surface's effective reflectance. Using the simulation's results, they reproduce an input svBRDF's appearance by distributing the microgeometry on the printed material's surface. This method lets people print svBRDFs on planar samples with current 3D printing technology, even with a limited set of printing materials. It extends naturally to printing svBRDFs on arbitrary shapes.
3D printing is considered a disruptive technology with a potentially tremendous socioeconomic impact. The three articles in this special issue illustrate how novel computer graphics approaches are advancing such digital fabrication.