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TOWARD A DESIGN APPROACH FOR INDUSTRIAL INDOOR LOCATION-BASED SERVICES (I²LBS)

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INTERNATIONAL DESIGN CONFERENCE - DESIGN 2018
https://doi.org/10.21278/idc.2018.0149
TOWARD A DESIGN APPROACH FOR
INDUSTRIAL INDOOR LOCATION-BASED
SERVICES (I²LBS)
T. Falkowski, M. Günther, C. Jürgenhake, H. Anacker and R. Dumitrescu
Abstract
In the context of the ongoing industrial digitization, location-based services (LBS) can play a key role
in improving internal company workflows and processes and the associated supporting activities. A lack
of standardized indoor-positioning technologies and complex integration with the existing infrastructure
are two of the main barriers for the implementation of LBS. In this paper, we present an approach for
the design of industrial indoor LBS or (I²LBS), which supports companies during the early design and
planning phase, taking into account their unique prerequisites.
Keywords: location-based services, indoor positioning, design methods, features, internet of
things (IoT)
1. Introduction
The evolution of information and communication technology (ICT) is the main driver behind the digital
transformation of the corporate and the private world. In this context, paradigms such as the Internet
of Things (IoT) and Industrie 4.0 have emerged and been subject to substantial scientific and
commercial exploitation. Although these paradigms stem from different backgrounds, they share some
of the same core principles. IoT is a term that is closely related to the advent of Radio-Frequency
Identification (RFID) in the late 1990s (Xu et al., 2014; Perera et al., 2014). Nowadays, the term is
used to describe the vision of a worldwide network of globally interconnected devices that are uniquely
addressable (Fortino and Trunfio, 2014). Industrie 4.0, a term coined in Germany in 2011, aims at the
incorporation of digital technologies into industrial processes such as manufacturing to achieve an
interconnection of machines, tools, work pieces as well as storage and transport systems to improve
processes both internally and along the value chain. This is made possible through advanced
processing, sensor and communication technology (Bauernhansl, 2014). At their core, both paradigms
aim at the amalgamation of the physical and the digital world, the resulting systems of which are
referred to as cyber physical systems (Broy, 2010). In the private space, the digitization of every-day
life is visibly evolving. Communication devices and digital services have become an essential part in
most of our lives. Context-awareness plays an important role in providing convenient modes of
interaction and delivering relevant information for a given situation (Perera et al., 2014). Context can
be broken down into primary context and secondary context, where primary context refers to time,
location, identity and activity and secondary context refers to personal context, technical context,
spatial context, social context and physical context, which are derived or deducted from the primary
context information (Küpper, 2007).
Mobile services that put the location in the focus are referred to as Location-based services (LBS) and
can be considered a sub-group of context-based services. The availability of mobile devices and
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accessibility of GPS (and similar satellite-based positioning technologies) have led to a widespread use
of these location-based services in the B2C space. Due to technical limitations, the use of LBS was
limited to outside areas in the past (Gu et al., 2009; Zhu et al., 2014). The recent emergence of accessible
indoor positioning solutions, however, makes the implementation of indoor location based services
feasible. Example application spaces include shopping malls, hospitals or warehouses. One area where
LBS have not yet reached a solid foothold, are industrial applications. In the context of Industrie 4.0,
however, Indoor Positioning Systems and Location-Based Services become a key enabling technology
(Uckelmann and Wendeberg, 2015). With the exception of intra logistics, most companies do not use
indoor positioning systems and location based services to improve their internal value added activities
due to factors such as unclear potential benefits and lack of standards (Conti et al., 2016). In this paper,
we present an approach for the design of industrial indoor location-based services (I²LBS) that are
tailored to the needs of manufacturing companies. The presented approach aims at supporting companies
during the early planning and implementation phase. As part of our research, we have conducted an
extensive literature review, identified and analysed existing LBS applications (B2C, B2B and current
research projects) and interviewed industry representatives about the potential uses of indoor positioning
systems and the resulting location-based services. Within our research, we address the following
research questions:
How can the unique potentials of Location-based service be captured in industrial applications?
Which elements need to be considered when designing industrial location-based services?
How can the conceptualization process for industrial location-based services be supported?
We discuss the foundations of location-based services including a technical overview, the
characteristics of indoor positioning as well as the challenges associated with the industrial
implementation of LBS in Section 2 of this paper. Additionally, we present a categorization of I²LBS
and provide application examples for each category. We present our 4-phase design approach in
Section 3, describing each phase along with the associated tools and methods. We subsequently
present a case study for the validation of our approach in Sections 4 and conclude the paper with a
summary and outlook.
2. Location-based services
Location-based services emerged with the increasing availability of mobile phone services and the
subsequent usage of cell-ID for emergency services. Since then, the concept of LBS has evolved into an
essential part of mobile services in the B2C-sector (Küpper, 2007; Ryschka et al., 2014). Prominent
examples of commercial location-based services include Google maps for navigation, the check-in
service Foursquare but also Facebook friend finder. There exist many different definitions and
synonyms for location-based services with most of the early definitions originating in the
telecommunication sector. Service, in the context of LBS, refers to an IT service as opposed to
traditional service offerings of companies (Küpper, 2007; Werner, 2014). The common ground for all
definitions is the location, which is the core element of LBS. According to Junglas and Watson, LBS
are services that take into account the position of an entity (Junglas and Watson, 2008). This very broad
definition does not consider additional features or details of the LBS. Many authors focus on the
consumer market where the user plays a central role. In this context, Gärtner et al. define LBS as a
service that uses the knowledge of where a user of an information device is located (Gärtner et al., 2007).
For our research purpose, we use the following definition:
A location-based service is defined to be a service relying on the following three aspects: the ability to
infer the location of one or more mobile entities, the ability to communicate information, and the ability
to use location data in order to provide the service. (Werner, 2014, p. 5)
In his definition, Werner takes into account the possibility of using LBS for individual entities as well
as for the interaction of multiple entities. He not only pays attention to the communication that has to
take place to enable the service, but also the central importance of the position for the provision of the
service. In doing so, he generally uses the term position information without restricting it further and
possibly excluding individual position determination methods or position dimensions.
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2.1. Components of location-based services
From a technical point of view, location-based services can further be broken down into several
components that fall under one of three aforementioned categories: localization, communication and
service provision. Figure 1 shows the high-level components that make up LBS.
Figure 1. Components of location-based services, expanded from
(Falkowski et al., 2016)
Localization comprises the positioning technology (e.g. GPS satellites) or a combination of multiple
positioning technologies and a reference system, which maps the input signal to a formalized position.
Examples for reference systems include 2D-maps (e.g. building plan), 3D-maps (e.g. virtual model of a
shop floor) or a database (e.g. list of available conference rooms). Service provision is achieved by an
IT service, i.e. a software application along with all the data required for the service. Communication
requires an adequate communication network (e.g. LTE or WiFi) and a user interface (e.g. smart phone
or computer). The implementation of location-based service requires the specification of each
component along with a close consideration of the existing infrastructure and other requirements for a
specific use case.
2.2. Indoor positioning and LBS
The availability of Global Navigation Satellite Systems (GNSS) is a driving factor for the success of
location-based services. With the incorporation of GNSS receivers into computing devices such as
navigation systems and smart phones, a reliable and accurate method for position determination became
available to the general population. The major drawback of satellite-based positioning systems,
however, is the fact that they do not reliably work inside enclosed spaces such as tunnels or buildings
due to the requirement of line-of-sight (Werner, 2014; Brena et al., 2017). As a result, extending the
reach of location-based services to indoor environments requires the use of alternative positioning
technologies. Unlike GNSS, which has become the standard technology for outdoor localization, there
exist many different positioning technologies intended for indoor use (Basiri et al., 2017; Brena et al.,
2017). Torres-Solis et al., for example, classify the available indoor positioning systems by their
underlying physical operating principle: Radio frequency, photonic, sonic waves, mechanical and other
(Torres-Solis et al., 2010). Examples for radio-frequency-based systems include RFID, WiFi-based
positioning systems, Ultra-wide band (UWB) or Bluetooth beacons, that all have specific advantages
and limitations. There exist many surveys on available indoor positioning systems and their specific
characteristics and limitations (Liu et al., 2007; Gu et al., 2009; Mautz, 2009; Zhu et al., 2014; Brena et
al., 2017). What is missing, however, is a structured approach that helps with the selection of an
appropriate technology for a specific use case, which we address in our current research.
Communication
network
Service/
application
User
interfac e
Data and
content
Positioning
technology
Refer en ce
system
Service provision
Localization
Communication
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2.3. Challenges for industrial LBS
There are various reasons why location-based services have not yet found a solid foothold in industrial
applications. Many researchers have published surveys on indoor positioning technologies that compare
their capabilities (Brena et al., 2017). Few researchers, however, consider these technologies together
with the potential applications for an industrial context. The majority of existing LBS research focuses
on commercial and not on industrial applications (Peng and Nguyen, 2010). Healthcare is one important
application area where real time locating systems (RTLS) are actively investigated (Fisher and
Monahan, 2012; Kamel Boulos and Berry, 2012; van Haute et al., 2016). The work that does consider
industrial applications seems to be mostly limited to the area of logistics. According to a study conducted
by the EU-fun ded i-locate project in 2016, the top three barriers for using indoor locations based services
for the questioned organisations were privacy, the lack of standardized indoor positioning systems and
the integration with the IT infrastructure (Conti et al., 2016). Privacy in LBS is the subject of ongoing
research and needs to be addressed on various levels (legislation, regulation, policy, implementation
etc.) (Chow and Mokbel, 2009; Shin et al., 2012; Abbas et al., 2014). In order to overcome the latter
two barriers, however, we see a clear need for a systematic design approach for industrial location-based
services that help companies find the appropriate solution for their unique situation.
2.4. Industrial indoor LBS examples
We differentiate between two distinctive application areas for industrial location-based services, the
shop floor and the office. At the shop floor level, LBS can support value-creation processes and
supporting processes such as logistics, maintenance or quality control. At the office level, the integration
of LBS can improve interaction and information processes. Although the prerequisites and
characteristics of the two areas can differ substantially, our approach considers both of these areas. The
main reason is the aspect of scalability.
Table 1. LBS categories mentioned by different authors
The objective of our approach is specifying the optimal LBS solution for a given situation while also
considering additional use cases, without limiting oneself to a single scenario. In order to structure the
potential scenarios, however, we researched possible classifications for industrial location-based
services. Table 1 presents the comparison of the different categories for location-based services from
different authors. Based on this literature review, we have identified five distinctive categories for the
characterization of industrial location based services. Table 2 lists some example applications for each
category, taking into account the industrial background.
Asset
management
Information
provision
Security
Author
LBS categories
Wayfinding
Process
Analytics
Werner, 2014
Peng and Nguyen, 2010
Schiller and Voisard, 2004
Steiniger et al., 2008
Ryschka et al., 2014
Küpper, 2007
Basiri et al., 2017
Industrial LBS Non-industrial LBS
Liard, 2012
Seitz, 2013
Conti et al., 2016
Bernardos et al., 2007
Entertainment/
Gaming
Marketing/
Commerce
Social
networking
Location-Sen-
sitive Billing
Other
Mentioned by author
Not mentioned by autho
r
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Table 2. Industrial location-based services categories
Industrial LBS category Shop floor examples applications Office example applications
Asset management Location based tool configuration Automatic resource check out and
tracking system
Information provision Automatically provide maintenance
instructions for the closest machine Virtual sticky notes: Providing key
information (e.g. meeting notes)
based on the current location
Security Lone worker monitoring Access control based on physical
location of personnel
Wayfinding Guiding maintenance personnel to a
specified destinations Guiding clients/guests to a meeting
room
Process Analytics Monitoring the usage of storage areas
and traffic routes Monitoring the occupancy rate of
meeting rooms
For the purpose of this article, we describe two use cases that can be implemented in an industrial
environment. The first example is location-based tool configuration, falling under the asset management
category. On a manufacturing shop floor with an assembly line production, workers need to use specific
tools for reoccurring assembly tasks. Depending on the product and the assembly step, the tool needs to
be configured in a specific way. One example is the automotive assembly process, where a torque
wrench is set to different torque levels depending on the component that needs to be tightened. Since
the assembly process is highly standardized, the location of the assembly step and the location of the
component is predefined. As part of the proposed I²LBS, the tool is equipped with an indoor positioning
receiver and additional computational hardware that allows for an automatic reconfiguration depending
on the current location of the tool, thereby reducing the potential of errors and facilitating the traceability
of the assembly tasks. The second example is what we call virtual sticky notes and can be classified into
the information provision category. In a typical office environment, e.g. a research and development
department, collaboration between experts is essential. Due to the high mobility of the personnel,
however, inquiring or passing on relevant information can be cumbersome and most people stick to
using email as the main means of communication. This can result in a loss of information or an untimely
reaction because people cannot handle the amount of incoming emails. To address this problem, we
propose using an indoor location-based service that enables the provision of information based on the
current whereabouts of the addressee. Similar to leaving physical notes (i.e. stick y notes) for a co-worker
to remind them of something important or ask for specific piece of information, the proposed I²LBS can
leave digital notes at designated spots. Once the addressee enters the designated area, they receive a
notification containing the information on their smart phone. The advantage to email or other forms of
messaging is the restriction to a physical location, which acts as an information filter. By placing the
virtual note at a location were the addressee can directly react to it, e.g. in front of one's own office
asking them to come in, we facilitate collaboration and communication. These two use cases
demonstrate the different characteristics that I²LBS can have, which also results in substantially different
requirements. Our approach enables a structured design of such use cases with the aim of deriving
technical requirements and selecting the appropriate technologies.
3. I²LBS design approach
With the previously described challenges in mind, we developed an approach for specifying indoor
LBS applications, focusing on the early conception phase. Our first step was an analysis and
classification of existing LBS use cases that are relevant for industrial scenarios. In addition to
identifying relevant applications, we compared existing classifications for location-based service use
cases and derived the five previously mentioned categories for industrial location-based services (see
Section 2.4). Based on these categories, we identified common features and created a feature model
for each category, taking into account the possible combination of different features relevant for each
category, based on the approach by Kühn et al. (2014). The overall approach for specifying industrial
location-based services covers four phases: Weak point identification, LBS use case selection,
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requirement specification and technology selection. Figure 2 shows a phase/milestone diagram for the
developed approach.
Figure 2. Phase/Milestone diagram for the design of industrial LBS
The result of our approach is an LBS concept design that can serve as the basis for an implementation
contract. This facilitates the selection of potential contractors since the essential boundary conditions
are determined in the course of applying our design approach. In the following paragraphs, we describe
the different phases, along with the necessary tasks and methods, in detail.
3.1. Phase 1 - weak point identification
In the first phase of our design approach, we consider the current situation of the company, focusing
on a selected area of interest, such as the manufacturing shop floor. We assume that existing processes
have already been modelled and can now be analyzed with regard to possible LBS implementations.
Following a systematic procedure, we consider non-value added activities to uncover problematic
tasks or weak points within the overall process. Our method does not rely on a specific process
notation but depending on the notation used and the level of detail of the process model, additional
information might be required for the identification of possible weak points. We have created a
questionnaire to acquire this additional information, which can be used for interviewing personnel
involved in the process. The goal is to uncover the real-life process flow and not just an optimal
reference process. It is therefore crucial to analyze certain process steps with the help of specific set
of questions that target the non-value adding aspects of the activity. Figure 3 shows an excerpt from
the questionnaire.
The questions aim at further detailing an activity/ a process step. If a question applies to a certain activity,
the respective answer will help with identifying weak points. Some answers directly point out weak
points (e.g. no designated storage for key resources) whereas others need to be processed further to
pinpoint a specific weak point. It is important to note that the possibility for a problem to occur (e.g. a
potential time delay) can in itself already be a weak point. Along with the process analysis, we document
the existing IT-infrastructure for the area of interest, which covers both hardware and software solutions
already in use at the site. The documentation uses a standard checklist covering all relevant aspects of
the infrastructure. Using a severity assessment, we rate the identified weak points based on the likelihood
of occurrence and its impact and describe the weak point in a standardized template. At the end of the
first phase, we have a list of all the identified weak points and a documentation of the current
infrastructure.
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Figure 3. Questionnaire excerpt
3.2. Phase 2 - LBS use cases selection
The goal of the second phase is the selection of suitable LBS solutions that address some or all of the
previously identified weak points. The first step is the prioritization of weak points, in order to narrow
down the problem space. We propose conducting workshops with all relevant stakeholders to enable a
mostly objective view on the list of weak points when considering all opinions. As part of the workshops,
the experts can go through the severity rating and discuss possible solutions. If a weak point can be
addressed through a simple non-technical solution (e.g. reorganizing certain tasks, splitting-up
responsibilities) they should be eliminated from the list. At the end, only the critical weak points remain
for further consideration. The experts then classify the weak points into one or more predefined types:
Long search times, long waiting time, high error rate, insufficient transparency, ineffective
collaboration, waste of resources/ high resource redundancy, safety risks. This classification
supports the identification of possible LBS solutions. We have created profiles for common LBS use
cases for the different industrial LBS categories that also list the type of weak points that it addresses
taking into account the RTLS-MUDA concept by Uckelmann and Wendeberg (2015). Figure 4 shows
the profile for location-based tool configuration.
Figure 4. I²LBS profile for the use case: Tool configuration
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At this stage, the LBS use cases describe the general goal and working mode without going into a
technical specification. This allows for a solution-neutral selection of use cases. Since a single LBS use
case can address multiple weak points, it is possible to rank the selected use cases based on their
effectiveness, i.e. the use cases that addresses the most critical weak points gets attributed the highest
effectiveness. Since the use cases are not directly linked to specific technologies, the implementation
effort can only be estimated at this point.
3.3. Phase 3 - requirement specification
Phase 3 aims at fleshing out the selected use case selected in the previous phase and specifying the
requirements. For the first step, we use a feature model of the selected use case category, which
comprises all the possible feature options, in the form of a feature tree. Together with the company, we
can now specify the LBS use case by selecting the required features. Figure 5 shows the excerpt of a
feature tree for the asset management category.
Figure 5. Extract of the feature model for the asset management category
By selecting a use case profile, we have already narrowed down the features for the use case but there
is still further refinement necessary. By going through the list of mandatory and optional features, we
can fully specify the functionality for the individual use case. Based on the selection, we can derive
functional requirements.
3.4. Phase 4 - technology selection
In the last phase, we select suitable technologies that match our requirements and fit the existing
infrastructure. The technology comprises positioning and communication technologies as well as front
and back end hard- and software. For the technology selection, we are developing a technology
morphology, which is linked to the use case feature models. This enables us to narrow down the
technology options based on the use case specification and the infrastructure restrictions. The final LBS
concept design comprises all service features along with the appropriate technologies. With this final
specification, it is also possible to go through another reiteration of the use case selection to identify
other use cases that can be implemented with the currently specified system.
4. Case study
As an example application for the presented I²LBS design approach, we consider a repair process based
on case study, which we conducted with one of our industry partners. Figure 6 shows an excerpt form
the process model created for the case study.
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Figure 6. Excerpt from the process model of the exemplary repair process
The excerpt from the process model for the repair process shows the process steps from receiving the
defective product to the disassembly of product. The process has been visualized using the OMEGA
modelling method (Gausemeier and Plass, 2014) and provides a starting point for validating our design
approach. In phase 1, we identified the weak points and potentials for the integration of LBS within the
repair process and analysed the existing infrastructure. With the help of the questionnaire, we identified
nine weak points in the process that could be remedied by an LBS implementation. We marked the
occurrence of media disruption in the process model and added them to the list of identified weak points.
In the course of workshops with relevant stakeholder from the company, we ranked all weak points and
identified the two most severe weak points:
Insufficient transparency: Workers involved in the repair process need to gather information on
a defective work piece at various points in the repair process. The information includes the
damage report, bill of materials and list of replacement parts required, among other things.
Although most of this information is stored digitally at some steps of the repair process, most
documentation handling is still paper-based resulting in media disruption.
Long search times: The mechanics responsible for the repair work pick the defective products
from a first-in, first-out storage area. The repair process comprises multiple steps involving
different mechanics at various work areas. Once the repair process has started, the shop floor
managers have no way of knowing at which process step a given product is currently located,
since there is no registration system in place.
With the help of the infrastructure checklist, we assessed the current availability of information
processing equipment, software tools as well as restrictions concerning the building, use of
radiofrequency etc. Some of the main takeaways were the availability of WLAN access with sufficient
coverage of the shop floor, the use of an ERP software suite for order processing and an overall static
shop floor layout with only minor changes over time. These aspects need to be taken into consideration
for the requirement specification in the later phase. Based on the weak points from phase 1, we identified
two appropriate LBS profiles from our solution catalogue in phase 2:
Discrete asset localization: The position of an asset is recorded at discrete intervals (e.g.
designated process steps) and the information transferred to an information storage system (e.g.
central server)
Proximity asset information: Information about an asset can be accessed through a mobile
computing device (e.g. tablet) when brought into the proximity of the asset.
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Based on this selection, we derived the relevant feature tree elements in phase 3. As part of a workshop
with company stakeholders, we selected the most suitable feature options. Figure 7 shows an excerpt
from the feature selection.
Figure 7. Excerpt from the feature tree for the case study
The feature selection along with the results from the infrastructure checklist serve as the basis for the
use case requirements. As an example, the features sub-room level spatial reference and discrete
position update imply a gate-based localization, which requires the distribution of terminal devices
across the shop floor. This can be achieved with various technologies, which are selected in the
subsequent phase with the help of the technology morphology. For the use case, we have designed an
I²LBS concept build around distributed Bluetooth beacons NFC tags, which can be attached to the
product to be repaired, and tablets used as NFC readers and as the user interface. Although some WLAN
access point are already available on the shop floor, there are insufficient devices to be used for indoor
positioning. To stay within the budgetary restriction, we chose Bluetooth beacons to achieve a discrete
position update. The beacons are attached to the assembly stations and the signal emitted by the beacons
is read by the tablets which identify the position from the beacon ID. The workers use the tablets to scan
the attached NFC tag containing the identification information for the work piece. The current location
(i.e. repair station) is then send to a central database. Depending on the location and the required task,
additional information (e.g. spare parts list and location) will be displayed on the tablet. As a result of
the I²LBS, the repair process can be streamlined and the overall transparency improved.
5. Summary and outlook
The design of LBS is no trivial task due to the complexity of the use case configuration and the vast
selection of possible technologies for the implementation. We have developed a structured design
approach for which supports the planning of industrial location-based services, consisting of a
procedure model and supporting methods for the individual steps. Starting with the identification of
weak points in existing company work flows with the support of a questionnaire and an infrastructure
check list, we select suitable LBS application cases from our solution catalogue. The selected
applications are further detailed using a feature model, which facilitated the specification of
requirements. In the last step of our approach, we select suitable positioning and supporting
technologies based on the requirements and the infrastructure constraints. Our approach helps capture
the potentials of LBS for industrial application by considering weak points in existing work flows and
matching them with possible LBS solutions. The approach addresses not only the technological aspects
of LBS but also the features that need to be implemented, thus ensuring that only suitable technologies
are considered subsequently. The procedure model serves supports the designer throughout the
conceptualization and design of an I²LBS. Our exemplary case study shows the applicability of our
design approach for the area of industrial production. In further work, we will focus on developing a
tailor made process modelling and analysis method that directly incorporates the identification of non-
value added activities and allows an application of our approach even without any pre-existing process
analysis. In addition, we will continue the development of the LBS technology morphology, which we
Person Object
Located entity
Location based repair
process support
Localization
Spatial
reference
Position
update
Sub-room
level
Room
level B uilding leve l Discret e Conti nuous
Information
provi sion
Uni-
direc tio nal
Bi-
direc tional Push Pull
Information
dist ributi on Tr ig ge r
Ass embly
stations
At ass embly
stations
User can add
information
User triggers
action
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will integrate together with our LBS feature model into a software tool that can support the design
process.
Acknowledgement
Part of this research and development work was carried out in the research project "Lichtsensor-basierte Ortungs-
und Navigationsdienste für autonome Systeme" (LiONS) [Light sensor based localization and navigation services
for autonomous systems]. The project is funded by the German Federal Ministry of Education and Research
(BMBF). The authors would like to thank the project committee for their advice.
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Tommy Falkowski, M.Sc.
Fraunhofer IEM, Product development
Zukunftsmeile 1, 33102 Paderborn, Germany
Email: tommy.falkowski@iem.fraunhofer.de
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Führende Wissenschaftler und Technologen beantworten in dem neuen Standardwerk zum Thema Industrie 4.0 die Fragestellung: Was genau ist Industrie 4.0? Wie wird sie Produktion, Automatisierung und Logistik verändern? Was sind die Erfolgsfaktoren bei der Einführung? Welche Technologien werden das Rennen machen und wie sieht die IT der Zukunft aus? Ausgehend von ersten Anwendungen diskutieren die Autoren die wichtigsten Fragen aus Sicht der Wirtschaft und stellen einen Fahrplan für eine erfolgreiche Einführung von Industrie 4.0 vor. Ein zentraler Bestandteil des Werkes und Voraussetzung für jede Investition ist die detaillierte Beschreibung der Herausforderungen und Anforderungen an die IT anhand anschaulicher Praxisbeispiele. Die Themen reichen dabei von Basistechnologien über die vertikale und horizontale Integration bis hin zu cyber-physischen Systemen und zur Mensch-Maschine-Interaktion. Aber auch Aspekte der Datensicherheit werden behandelt. Abgerundet wird der 360-Grad-Rundumblick zum Thema Industrie 4.0 durch einen Ausblick auf die Zukunft. Ein Standardwerk zu Industrie 4.0, das in keinem Unternehmen fehlen darf. Der Inhalt · Einführung · Anwendungsszenarien · Basistechnologien · Migration · Ausblick Die Zielgruppen · Entscheider in der Industrie · Produktentwickler aus der Verfahrens- und Fertigungstechnik Die Herausgeber Prof. Dr.-Ing. Thomas Bauernhansl leitet das Institut für Industrielle Fertigung und Fabrikbetrieb (IFF) der Universität Stuttgart, das Fraunhofer-Institut für Produktionstechnik und Automatisierung IPA in Stuttgart sowie das Institut für Energieeffizienz in der Produktion (EEP) der Universität Stuttgart. Prof. Bauernhansl ist wissenschaftlicher Beirat der nationalen Plattform Industrie 4.0. Prof. Dr. Michael ten Hompel ist geschäftsführender Leiter des Fraunhofer-Institutes für Materialfluss und Logistik und Ordinarius der TU Dortmund. Zuvor gründete er das Software-Unternehmen GamBit, das er bis zum Jahr führte. Er gilt als einer der Väter des Internet der Dinge, ist Mitglied der „Logistik Hall of Fame“ und wissenschaftlicher Beirat der nationalen Plattform Industrie 4.0. Prof. Dr.-Ing. Birgit Vogel-Heuser leitet den Lehrstuhl für Automatisierung und Informationssysteme der TU München. Sie verfügt über langjährige Industrie- und Hochschulerfahrung im Bereich der System- und Softwareentwicklung verteilter, intelligenter, eingebetteter Systeme für Industrie 4.0.
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This paper presents the state-of-the-art of the leading indoor positioning technologies and systems. The positioning technology is classified into the active positioning system and the passive positioning system, which are presented respectively in detail, including wireless local area network, radio frequency identification, Bluetooth, inertial navigation, and magnetic field positioning. Additionally, the advantages and disadvantages of various indoor positioning technologies and systems are analyzed, as well as the positioning accuracy, applicability, and working principle. Particularly, in order to better understand them, the key performance parameters of the mentioned technologies and systems are finally compared using a table.
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