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Action Research Investigating the Technical and Use Case Determinants of Success for the Application of Mobile Augmented Reality (MAR) for Increasing the Utility of Public Spaces. Research Project within module T847-17K
EMA Word Count: 10,173 excluding cover, table of contents, references and appendices.
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Table of Contents Acknowledgements......................................................................................................................................... 5 Executive Summary ......................................................................................................................................... 6 Introduction .................................................................................................................................................... 8 Research Question .......................................................................................................................................... 9 Purpose and Focus ....................................................................................................................................... 9 Augmented Reality .................................................................................................................................. 9 Purpose................................................................................................................................................... 9 Focus....................................................................................................................................................... 9 Problem....................................................................................................................................................... 9 Identifying the Problem ........................................................................................................................... 9 Nature, Extent and Characteristics of the Problem? ................................................................................. 9 Why the Problem is Important to Organisations? ....................................................................................... 10 Why the Problem is Important to the Academic Discipline of Computer Science? ........................................ 11 Research Title ............................................................................................................................................ 11 Hypotheses ................................................................................................................................................ 11 Model of Causality ..................................................................................................................................... 11 Constructs ................................................................................................................................................. 12 Contributions to Theory and Practice.......................................................................................................... 12 Research Design and Methodology ............................................................................................................... 13 Research Paradigm .................................................................................................................................... 13 Key Features of the Research Approach...................................................................................................... 13 Congruence with Research Question .......................................................................................................... 13 Processes for Collecting Primary and Secondary Data ................................................................................. 15 Model and Taxonomies for Applying AR (Cycle 1) ......................................................................................... 16 Tools and Techniques for Analysing the Data.............................................................................................. 16 Findings for the Model and Constructs and Taxonomies ............................................................................. 16 Construct: Augmented Reality Devices................................................................................................... 17 Construct: Augmented Reality Augmentation ........................................................................................ 19 Construct: Augmented Reality Software ................................................................................................ 21 Construct: Augmented Reality Use Cases ............................................................................................... 23 The Model for AR Strategy & Roadmap Development (Theoretical Proposition) .......................................... 29 Validating the Research Model and AR Taxonomies ................................................................................... 30 POC Case Study Applying the Model and Taxonomies (Cycle 2) .................................................................... 31
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POC Methodology ...................................................................................................................................... 31 About the North Acton Playing Fields ......................................................................................................... 31 Location .................................................................................................................................................... 32 Analysis of AR Devices for Applying AR to this Public Space......................................................................... 34 Stand out device(s): ............................................................................................................................... 34 Analysis of AR Augmentation for Applying AR to this Public Space .............................................................. 34 Stand out augmentation(s): ................................................................................................................... 34 Analysis of AR Software for Applying AR to this Public Space ...................................................................... 35 Stand out augmentation(s): ................................................................................................................... 35 Analysis of Generic AR Use Cases for Applying AR to this Public Space ........................................................ 36 Stand out AR Use Cases ......................................................................................................................... 40 AR Strategy or Roadmap ............................................................................................................................ 41 Proof of Concept of Using the Model and Taxonomies for Developing AR Applications ................................ 42 AR Application Platform Selection.......................................................................................................... 42 AR Applications for North Acton Playing Fields ........................................................................................... 43 Activities Completed.............................................................................................................................. 43 AR Application for Use Case: AR Labels Overlaid Over Trees, Shrubs, Flower Beds .................................. 43 AR Application for Use Case: AR Guided Tour of Space for New People to the Area ................................ 44 AR Application for Use Case: Additional Community Notice Boards using AR .......................................... 44 AR Application for Use Case: AR Notices on Personal Safety and Use of Equipment................................ 45 AR Application for Use Case: Interactive AR Noticeboard for Dog Owners .............................................. 46 AR Application for Use Case: Short Term Offers from Café, Tennis Courts, etc. ....................................... 46 Evaluation of Application of Model and Taxonomies (Cycle 3) ...................................................................... 48 Research Model .................................................................................................................................... 48 Taxonomies ........................................................................................................................................... 48 Simulated Application to a Real-World Scenario..................................................................................... 48 Developing Proof of Concept AR Applications ........................................................................................ 48 Overall Methodology ............................................................................................................................. 48 Limitations ............................................................................................................................................ 48 Future Research & Development Activities ................................................................................................... 49 Future Research .................................................................................................................................... 49 Vehicles for Continuing this Work .......................................................................................................... 49 Conclusions ................................................................................................................................................... 50 Contributions to the Professional Development of the Student .............................................................. 50 Contributions for AR Practitioners ......................................................................................................... 50 Contributions to AR Research and Thought Leadership .......................................................................... 50
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References .................................................................................................................................................... 51 Appendix A – Validating the AR Taxonomies ................................................................................................. 60 Message Posted on LinkedIn AR Discussion Group ...................................................................................... 60 Posting .................................................................................................................................................. 60 Message Posted on MeetUp’s UK Augmented Reality Discussion Group...................................................... 61 Posting at Meetup ................................................................................................................................. 61 Supporting Posting of Information & Materials at Google Groups .......................................................... 61 Appendix B – Project Plan ............................................................................................................................. 66
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Acknowledgements The project benefitted from advice from several people and organisations. Dr Dave Lawrence, Course Tutor at the Open University, provided considerable advice throughout the project. This shaped the project into a more coherent contribution and challenged the work, particularly in areas such as validity and clarity of presentation. Dr Saroj Patel, IT and Innovation Director at the Royal National Orthopaedic Hospital NHS Trust, reviewed the outcomes from the project offering advice and validation based on her many years of experience of computer-based innovations. The following vendors provided advice on the general value of the project to practitioners and also commentary on the taxonomies developed and trialed: • • • • •
3CUBED Happy Finish Mbryonic Surround Vision Admix
The free course in AR technologies with Coursera from the French Institut Mines-Télécom (Coursera, 2017) was gratefully used to add AR skills to the researcher’s wider developer and computer science skills. BlippAR provided free “education sector” versions of their AR development platform along with cloud based resources for the creation and testing of the proof of concept AR applications.
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Executive Summary The project contributes to research and practice in the emerging field of augmented reality (AR) and as it applies to enhancing the utility of public spaces. Harborth (2017) commented after a systematic review of peer reviewed journal articles that there was a complete absence of research in mobilephoned enabled AR generally and especially for public services. The research utilised the Problem Resolving Action Research (PRAR) Model (Piggot-Irvine, 2002), reflecting the early stage in the development of theory observed by Harboth. A research model was proposed as an aid to decision making and for each of the independent constructs in the model a taxonomy was developed. The development of the taxonomies used the Grounded Theory Literature Review Method from Wolfswinkel, et al. (2013) drawing upon a wide selection of academic and practitioner and industry literature. In summary the taxonomies developed were as follows: AR Devices
AR Screens AR Heads Up Display (HUD) Mobile AR (MAR) Phones & Tablets AR Headsets AR Glasses AR Contact Lenses
AR Augmentation
Marker-based AR Marker-less AR Projection-based AR Superimposition-based AR
AR Software
AR-Enabled Web Browsers Specialist AR Browsers AR Development Libraries Vendor Proprietary Deployment Platforms Device Specific Platforms
AR Use Cases
Print and Object Augmentation Advertising using AR AR Signage AR Overlays AR Tours for Museums, Cities, Sites & Events AR 3D Models & Other Objects AR 3D Models for Purchasing Decisions AR 3D Models for Product Design AR Pets AR Overlays & Information for Maintenance Activities AR Surgical (and other complex tasks) Guidance AR Training Materials AR Holographic Trainer AR Games Art Works Displayed using AR AR Bogus Window Screen Creation using AR Displaying Recalled Information using AR
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A proof of concept application of these taxonomies to a public space was carried out successfully. The taxonomies applied with normal management decision criteria, provided an AR strategy or roadmap that included technical decisions and the best use cases localised to the public space. The proof of concept extended into the creation of proof of concept applications for a selection of the use cases within the AR roadmap. The technology decisions on AR platform reflected the use of the taxonomies that suggested an AR browser based technology, that was marker-less and available on both IOS and Android devices and low cost. The BlippAR platform was selected and delivered simple working AR applications for the use cases. The combination of AR model, AR taxonomies, AR roadmaping techniques and AR applications developments, all sum up to a methodology that organisations could use to get their responses to the opportunities and threats from augmentation shaped up through an AR strategy and their early implementations of AR identified and then implemented. The outcomes from the project have limitations arising from the difficulties experienced engaging AR practitioners to participate in reviews (efforts continue to address this). This leaves validity and rigour lower than planned. Further research is proposed into this area, validating and developing further aspects of the methodology and measuring its effectiveness in a range of situations for AR strategy and implementation. The project has made contributions to both practitioner and academic communities.
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Introduction Academic work on augmented reality (AR) can be traced back over 50 years to the 1960s (Arth, et al., 2015) with the first working AR system being attributed to Ivan Sutherland in 1968 (Sutherland, 1968). More recently Harborth (2017) conducted a systematic review of selected, premier, peerreviewed academic research in the AR field and amongst his conclusions was that there was a deficiency of research in mobile phone-based AR (MAR) and amongst use case, there was a deficiency in AR use cases for all aspects of public services. This project makes a contribution to these deficiencies in the area of mobile augmented reality for public services. It provides – as both a theoretical proposition and as a tool/methodology for practitioners – a research model and taxonomies for AR technologies and their use cases. Tobar (2014) asked the question of the AR research community via ResearchGate: “Is there a Taxonomy, Classification or Typology on Augmented Reality Applications? I'm classifying the works that have been done in AR and Education and I can't find a standard taxonomy or a hierarchy to organize my findings.” The AR research community responded with some advice but that such a taxonomy has yet to be developed. Recently, Porter and Heppleman (2017b) have proposed a very early and simple conceptual model with dimensions for applying AR to problems. But this is not grounded in independent evidence, instead being a product of Heppleman’s experience from his privileged informant status as an AR industry leader - he is the Chairman and President of an AR company (Porter & Heppleman, 2017a). This project contributes to current research and practice in AR by developing a model for AR’s successful application. The focus is AR applied to public spaces but the model has far wider applications. The constructs from the research model were developed into taxonomies for each of the constructs contributing to the successful application of AR. This was achieved through qualitative content analysis of research literature, industry research and publications and news articles and blog posts. It was judged that the use of refereed journal articles alone would be insufficient and would not allow recent developments by practitioners and industry to be included. To help promote rigour, the sources – which are from research databases and web sources and vendor publications – were analysed using the Grounded Theory Literature Review Method from Wolfswinkel, et al. (2013). This method to theory building from literature involves five systematic stages being 1) define the criteria for inclusion; 2) search for content; 3) select to avoid duplication and ensure coverage; 4) analyse content; 5) structure and represent the content. The outcome was a taxonomy for the four constructs and the identification of one additional construct to add to the model (i.e. AR augmentation type). The project also undertook validation and testing of the model and its taxonomies. This was through multiple reviews by practitioners combined with the application of the model and taxonomies to one case study. The project therefore contributes to AR research with a theoretical proposition for a taxonomy of key constructs for applying AR to public spaces. For practitioners it also contributes and illustrates the application of the model and taxonomies to a real-world case study demonstrating how it can be used to derive a strategy or roadmap for AR and the potential follow through into AR applications development.
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Research Question Purpose and Focus Augmented Reality The Gartner (2018) definition for augmented reality (AR) is, “Augmented reality (AR) is the real-time use of information in the form of text, graphics, audio and other virtual enhancements integrated with real-world objects. It is this “real world” element that differentiates AR from virtual reality. AR integrates and adds value to the user’s interaction with the real world, versus a simulation.” Purpose The project aims to explore important aspects of the contemporary area of augmented reality (AR) by investigating and applying the recently emerging AR technologies to the area of augmenting the value of a public space such as a community park. To do this within a small project it must be focused and then draw wider inferences. Focus The project focus will therefore be constrained as follows: -
Technologies constrained to mobile augmented reality (MAR) Use cases constrained to those relevant to augmenting public spaces and focused on one such space in West London for specific use cases The technical proof of concept (POC) to explore the practical readiness of AR technologies constrained to one West London public space and one of the AR applications development platforms.
Problem Identifying the Problem Liaio and Humphreys (2015) researched how a particular AR platform caller Layar was being used to enhance public spaces. Their case-based investigation found early, but profound, uses for AR in public spaces. They raised intriguing issues from the fields of social and economic research on how AR changes the meaning of a public space for the AR creator and the citizens using AR. Their paper raised questions on governance and control of public spaces and the implications AR could have for altering the usually unconsciously accepted conditions and characteristics of public spaces. Nature, Extent and Characteristics of the Problem? Augmented Reality (AR) technologies have recently undergone a significant change. Until mid 2017, AR utilised glasses and proprietary technologies. A good example is Microsoft’s Hololens technology. Very recently, the use of mobile phones for AR has been enhanced with the latest iPhones being able to exploit AR by adding 3D objects into the scene being experienced by the camera’s phone. These objects can be anchored into geometric planes (horizontal and soon vertical) in the image’s view. Interactivity with AR images is also an increasing possibility. Importantly, to the Page 9 of 67
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open standards (IEEE, 2017) for AR, both Google and Apple have published, as open sourced assets, sophisticated code libraries – ARCore (Google, 2017(a)) and ARKit (Apple, 2017). Importantly, Apple’s recent acquisition of an AR glasses company (Tech Crunch, 2017) and continued investment by Google in Google Glass (Google, 2017(b)) and Microsoft in Hololens (Microsoft, 2017) suggest a place for glasses within AR. But the ubiquity of mobile phones and their relatively low cost compared to glasses means that commentators are seeing AR on mobile phones as the most significant area of growth in AR in the short term. (Porter & Hepplemann, 2017). Industry commentators and research organisation have throughout 2017 and 2018 become to increasingly feature AR as a transformative frontier technology. Today, a chorus of journalistic commentary is hailing AR on mobile phones as having a massive potential. To validate these forecasts requires only a simple consideration of what could come about. Today, economic growth is slowing across the world with the UK now projecting decades of slow growth in living standards. Yet the growth in knowledge, information and data continues to accelerate. AR offers the prospect of “augmenting” assets in the physical world (“reality”) with images that can be seen only by the observer through their mobile phone (or glasses where the higher cost can be justified). A question worth asking is can the wealth - in a wider than just the financial sense - of citizens be increased by applying AR to public goods such as public spaces or government services. If we take a public good like a public park could it be augmented by using the new AR technologies on mobile phones to attach AR-based services to physical assets (“reality”). And this could be tailored and personalised to the characteristics of the observer. Taking a public space such as a park as a test. Examples in that use case might be attaching botanical knowledge to the trees, shrubs and plants for an observer interested in that. Another might be a series of keep fit exercise regimes utilising the assets in the park for those with health issues. Another might be AR-generated notice boards providing context relevant information. The tennis court could have a notice board of tennis events and information. Each entrance could have a notice board of the rules for the use of the park and numbers to report problems and the council’s future plans for the park. The café could have opening times and today’s specials. All tailored, potentially, to the individual AR enabled citizen. The public space could be augmented almost without limit and how would this increase its utility to the local citizens? And without changing the public space in any physical way or investing further directly in it. The problem explored in this project is what models can be used by practitioners and their organisations to develop strategies and roadmaps for realising the potential of AR and following through into implementation of AR. Why the Problem is Important to Organisations? The business strategy guru Professor Michael Porter of Harvard Business School and AR pioneer and CEO James Heppelmann recently explained the significance of AR for business in the Harvard Business Review (Porter and Heppelmann, 2017). Whilst acknowledging unreservedly that AR is still in its infancy they found that, “pioneering organisations including GE, Mayo Clinic and the US Navy are using AR to improve productivity, quality and training. By combining the strengths of humans and machines, AR will dramatically increase value creation.” Porter and Heppelman (2017) go on to argue that all organisations now need an AR strategy or roadmap to guide their exploitation of AR. Page 10 of 67
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Why the Problem is Important to the Academic Discipline of Computer Science? Harborth (2017) recently conducted a funded systematic review of the research literature on augmented reality and commented on the early stage of this area of research. He found that the research literature was dominated by technology questions and that use cases and user’s reactions were under-researched. His systematic review provides strong support for AR research in general, “as the practical importance of AR is so large, we want to encourage researchers to engage in this promising and fascinating research field” (p8). His work found almost a complete absence of research into AR on mobile phones despite acknowledging the importance of this device type for AR. The review found academic AR research on a range of sector use cases but few yet in the public sector in general or in the use for enhancing public space. The augmented reality market was valued at USD 2.39 billion in 2016 and is expected to reach USD 61.39 billion by 2023, growing at a CAGR of 55.71% during the forecast period. (MarketsAndMarkets, 2017). Research Title Action research investigating the technical and use case determinants of success for the application of mobile augmented reality (MAR) for increasing the utility of public spaces. Hypotheses Hypothesis 1: That choices of mobile augmented reality (MAR) technologies – mobile devices and software – relates to the success in applying MAR to public spaces. Hypothesis 2: That the selection of use cases relates to the success in applying MAR to public spaces. Hypothesis 3: That there is a contingency relationship between MAR technologies and MAR use cases that relates to the success in applying MAR to public spaces Model of Causality
MAR Devices
MAR Software
MAR Use Cases
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MAR Success
Utility of Public Spaces
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Constructs C1 Augmented Reality (AR)
Augmented Reality (AR) “allows the user to see the real world, with virtual objects superimposed upon or composited with the real world. Therefore AR supplements reality.” (Azuma, 1997)
C2 Mobile Augmented Reality (MAR)
The implementation of AR on mobile devices is known as Mobile Augmented Reality (MAR). (Munro, Calitz & Vogts, 2017)
C3 MAR Devices
Types of mobile devices able to be used for AR applications typically comprising the device, its sensors and operating system.
C4 MAR Software
Types of software able to be used by mobile devices for AR applications (excludes development SDKs).
C5 MAR Use Cases
Categories of use cases known to be of value for MAR.
C6 Public Space
Spaces with public access managed to deliver facilities for a population. Examples would be parks, public exhibitions, public concerts, public accessible spaces in hospitals, etc.
C7 Utility
In this study utility is a broad concept of the utility of public spaces.
C8 MAR Success
Success is a two-dimensional construct comprising success in the process of creating MAR and success of the MAR product within the use case(s).
Contributions to Theory and Practice This project contributes to the knowledge of the student by: • • • •
Developing deeper knowledge of computer science generally in pursuit of the wider OU studies. Developing deeper knowledge of AR strategies, AR use cases and AR technologies. Developing AR skills to the level of a deployable Proof of Concept (POC). Developing skills in project execution and project report writing.
The project contributes to practitioner knowledge by: • •
Providing taxonomies for use cases, software and devices for AR Creating a proof of concept that explores practical challenges deploying current AR technologies
The project contributes to theory by providing: • • • •
Models and insights of contemporary AR use cases. Technology maps for AR platforms and libraries. Theoretical propositions for the deployment of AR in public spaces. Action research on AR applications.
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Research Design and Methodology Research Paradigm The project will use a participatory action research paradigm. Action research has a rich history having arisen as an accepted paradigm for investigation in the 1940s. Action research emphasises reflective learning through the researcher becoming the participant in the phenomena being studied and investigating through interventions and reflection, often in an iterative way (Open University, 2005). In information systems research, action research has established itself as an accepted approach. Action research also lends itself to resolving problems in real-world practice. This project employed the Piggot-Irvine model which is an iterative, problem solving form of action research (Piggot-Irvine, 2002) labelled the Problem Resolving Action Research (PRAR) Model. The project will combine the causal model pragmatically with the philosophy and practice of Participatory Action Research (PAR) to achieve relevance in its outcomes for both academic and practitioner communities. Key Features of the Research Approach Cycle 1 allows the project to build up the understanding of the independent variables using evidence from the AR industry for use cases, devices and software. Through content analysis of academic and practitioner literature it will develop a decision making model and taxonomies for the key variables. Cycle 2 provides an opportunity to undertake a proof of concept implementation of mobile augmented reality for a public space using the model and the taxonomies. Cycle 3 will evaluate the researcher’s experiences in developing the proof of concepts. Congruence with Research Question The following table presents the key characteristics of the research question and how action research is congruent with those characteristics. Practice Focused: The question is about the practice of AR in a context
Action research allows the researcher to plan and take actions directly as a practitioner in the field and do so within the context. Rich data is generated from direct observations allowing reflection to generate insights into the question.
Rapid Recent Changes in Technologies: AR is rapidly developing technically with very recent technologies being of major significance
Action research is less dependent upon being able to build upon a research-based body of prior research and so can handle less well-developed constructs (variables) and the absence of construct measures.
Validation: AR practice is hard to validate as information is tainted by commercial agendas
Participatory action research allows the involvement of stakeholders in the reflection on outcomes and insights providing a measure of validation and helping to overcome the threat from researcher bias.
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Examination of the Existing Situation
Implementation of Change
Evaluation of Implementation of Change
This will generate models and taxonomies of key constructs
This will employ the models and taxonomies within a single real-world case study
Researcher observations and reflections will be documented and used for future actions
Define Issue
Continued Action
Cycle 1
Reference: Piggot-Irvine, 2002
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Cycle 2
Cycle 3
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Processes for Collecting Primary and Secondary Data
Data
Processes
Stage 1 – Examination of the Current Situation This will generate models and taxonomies of key constructs Taxonomies will be developed for the constructs within the causal model (secondary data)
Systematic review of academic and industry research to date. Content analysis of qualitative information. Multiple case studies from industry write ups and direct usage where published. Content analysis of qualitative information.
Practitioner observations on the causal model (primary data).
Sharing causal model on on-line forums for AR practitioners and asking a set of questions to encourage discussion of AR practitioners’ current experiences. Semi structured enquiry of a practitioner community.
Stage 2 – Implementation of Change This will employ the model and taxonomies within a single real-world case study Combinations of device, software and use case for a Proof Of Concept (POC) from applying the model and taxonomies to a single public space. (primary data)
Derived from analysis using the taxonomies and causal model. Simulation of practitioner application to a real-world public space.
Data on experience of researcher in developing POCs and the evaluation of the outcomes (primary data).
Development notes & experiences will be evaluated and the POCs’ outputs will be investigated. Content analysis of POC development and evaluation research journal notes and subsequent evaluation, reflection and insights.
Stage 3 – Evaluation of Implementation of Change Researcher observations and reflections will be documented and used for future actions Evaluation of the Change (primary data).
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Researcher will use the data previously derived against general perceptions of success. Researcher reflection and reporting.
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Model and Taxonomies for Applying AR (Cycle 1) Tools and Techniques for Analysing the Data In cycle 1, the taxonomies were developed using the Grounded Theory Literature Review Method from Wolfswinkel, et al. (2013). This method to theory building from literature involves five systematic stages. 1. Define the Criteria for Inclusion A broad review of academic and practitioner literature was undertaken to find the key constructs and propose the research model. Systematic reviews and broad-based academic journal articles were given more weight. 2. Search for Contents The OU library and ACM library were used to identify the relevant published journal literature. And Google was used to review published practitioner and vendor materials. The search strings were kept broad. This increased the amount that needed to be reviewed to eliminate the non relevant literature and materials. • • • •
“augmented reality” AND “devices” “augmented reality” AND (“software” OR “platforms” OR “browsers”) “augmented reality” AND (“use cases” OR “case studies”) “augmented reality” AND “vendors”
For each valid data point found a post-it note was created and grouped separately under each construct. 3. Select to Avoid Duplication 4. Analyse Content The post-it notes within each construct were reviewed in turn and analysed and clustered around similar themes aiming for a manageable number of themes. 5. Structure and Represent the Content The clusters were each individually reviewed referring back to the source materials to validate them and order them and label them and create meta-data such as a description and representative references back into published materials. Findings for the Model and Constructs and Taxonomies The analysis derived taxonomies for the three independent constructs (devices, software and use cases). The qualitative clustering aimed to keep the types across the constructs sufficiently small in number, for practitioners to be able to use within organisations with time-pressured public-sector managers A fourth construct kept emerging in the industry literature being the type of augmentation being delivered by the devices and software. This was added to the model. The following tables describe these taxonomies with references that are representative of the academic and industry literature reviewed.
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Construct: Augmented Reality Devices Ref
Type of AR Device
Description
References (Device Name in Square Brackets]
D1
AR Screens
Large screens positioned to display to the observer the scene augmented with added media content and potentially interactivity with the observer.
Indestry, 2018. [Broadcast AR & Hero Mirror]; Luminvision, 2018. [Luminvision]; Realfiction, 2018. [DeepFrame].
D2
AR Heads Up Display (HUD)
Projecting images and information onto a surface to augment the scene through the surface in the case of glass or augment a solid object.
Haidar, 2018. [Panasonic]; Wayray, 2018. [WayRay].
D3
Mobile AR (MAR) Phones & Tablets
MAR employs a mobile phone or tablet using the camera and other sensors to display a scene live and augment it with media content and interactivity.
Apple (b), 2018. [iPhone & iPad AR]; Samsung, 2018. [Samsung S9/S9+].
D4
AR Headsets
Augmented reality experiences through a virtual reality headset adapted so that an augmented scene is captured by a camera and augmented with rich media and displayed via the VR headset.
Aryzon, 2018. [Aryzon].
D5
AR Glasses
Glasses or headsets containing projector, camera and other sensors, with which the wearer can experience their view of a scene or object augmented with rich content and interactivity.
Constine, 2018. [Facebook/Oculus]; Epson, 2018. [Moverio BT]; Google, 2018. [Google Glass]; Lynch, 2018. [Apple AR Glasses]; Magic Leap, 2018. [Magic Leap]; Microsoft, 2018. [Hololens]; Slashgear, 2017 and Feltham, 2018. [Samsung]; Vuzix, 2018. [Vuzix].
D6
AR Contact Lenses
'Smart' contact lenses, which can project images straight into the users' eyes. Wearing the lenses would allow users to experience 'augmented' reality, with computergenerated images superimposed over the real world.
Contact Lenses, 2016. [Apple/EPGL]; Chowdry, 2016. [Samsung]
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D1 – AR Screens
D2 – AR Heads Up Projection
D3 – Mobile AR (MAR) Phones & Tablets
D4 – AR Headsets
D5 – AR Glasses
D6 – AR Contact Lenses
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Construct: Augmented Reality Augmentation Ref
Type of AR Augmentation
Description
References
T1
Marker-based AR
Marker-based augmented reality apps focus on using the device software to identify patterns (like QR code) in the image obtained from the device camera. Then an overlay is cast on the device screen over the real-world image procured from the camera.
Jung et al., 2016; NewGenApps, 2017; ThinkMobiles, 2018.
T2
Marker-less AR
Marker-less augmented reality app focus on recognising an object within the image from the device camera or the GPS location from the device sensors. Then an overlay is cast on the device screen and typically adjusted for the overlay in relation to the object or geo-position.
Ababsa, et al., 2008; Bardi, 2017; Wang, et al., 2018.
T3
Projection-based AR
This type of AR projects digital images on physical objects in the physical space. It can be interactive and project a digital keyboard on your desk, or a dialer on your hand.
Cebulla, 2013; Mine, et al., 2012.
T4
Superimposition-based AR
In superimposition-based AR, the augmented view is superimposed on the real view of any object. For example this augmented view could be the internal view of the object.
Argotti, 2002; Kumar, 2016.
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T1 – Marker Based AR
T4 – Superimposition-Based AR
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T2 – Marker-Less AR
T3 – Projection-Based AR
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Construct: Augmented Reality Software Ref
Type of AR Software
Description
References (Software Name in Square Brackets]
S1
AR-Enabled Web Browsers
Web browsers on phones and tablets developed to enable augmented reality experiences from AR applications running within a standard browser. Examples would include Google’s Article Web AR toolset.
Ali & Carpenter, 2018. [Google Article]; Etienne, 2018. [AR.js]; ARKit, 2018. [ARKit]. Argon.js, 2018. [ArgonJS]
S2
Specialist AR Browsers
Browsers developed specifically for augmented reality. Users download the AR browser and then can access AR applications developed for that browser. Examples would include Layar browser and ARAF browser.
Multimediaworld, 2018. [ARAF]; Augment.com, 2018. [Augment]; Aurasma, 2018. [Aurasma]; Blippar, 2018. [Blippar]; Layar,2018. [Layar]; Zapworks, 2018. [Zapar].
S3
AR Development Libraries
Libraries for use within SDKs for the development of AR applications to run on devices or within browsers. Examples would include ARKit from Apple and ARCore from Google.
Apple, 2018. [ARKit]; Google Developers, 2018. [ARCore]; Unity, 2018. [Unity Engine]; Vuforia, 2018. [Vuforia]; WebAR, 2018. [WebAR Playground];
S4
Vendor Proprietary Deployment Platforms
General vendor platforms for the development, cloud hosting and deployment of AR applications. Examples would include Aurasma.
Aurasma, 2018. [Aurasma]; ScopeAR [ScopeAR]; Wikitude, 2008. [Wikitude];
S5
Device Specific Platforms
Specialist devices need their own AR SDKs and development environments. Examples would include Microsoft’s HoloLens AR glasses.
Aryzon, 2018. [Aryzon]; Google, 2018. [Google Glass]; Light Guide Systems, 2018. [Illumination]; Microsoft, 2018. [Microsoft HoloLens]; Sony, 2018. [Sony SmartEyeGlass]; Vuzix, 2018. [Vuzix Smart Glass & SDK]
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S1 - AR-Enabled Web Browsers
S2 - Specialist AR Browsers
S4 - Vendor Proprietary Deployment Platforms
S5 - Device Specific Platforms
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S3 - AR Development Libraries
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Construct: Augmented Reality Use Cases Scholz and Smith (2016) describe the importance of defining the audience for an augmented reality application. Their discussion opens up the dimensions that might apply to such audiences. They propose that the type of adopter is important, for example if the audience is early adopters then they are better candidates for new technologies. They also identify three types of AR user engagement: 1. Users of the application who use and interact with the content. 2. Observers of the use of an AR application by others who may interact with the augmented user. 3. People (or objects) that are augmented by the application by the user of the augmented reality application. This is a contextual consideration for AR use cases but is not viewed as a selectable independent variable for success, so was not added to the model. Research has not yet arrived at an authoritative typology or taxonomy. The following table brings together a taxonomy of AR use cases from a wide and representative sample of academic and industry research. The types are qualitative clusters of common application types based on a) the process being augmented, b) the trigger for augmentation, c) the value being achieved from augmentation. The types are deliberately agnostic of software and device and industry.
Ref
Type of AR Use Case
Description
References
U1
Print and Object Augmentation
Recognising a print or an object and adding information or images or media.
Downey, 2017; Index AR Solutions, 2016; Scope, 2017; Scholz & Smith, 2016; Stroobandt, 2016.
U2
Advertising using AR
Creatively employing AR as another media for advertising a product or service or place.
Scope, 2017; Yeo, 2017.
U3
AR Signage
AR signs overlaid onto reality to label or provide direction.
Biaanes, 2017; Downey, 2017; Kohles, 2017; Mehta, 2017; NXP 2018; Rockafella, 2017.
U4
AR Overlays
Overlaying measures, data, labels and lines onto scenes (e.g. sports overlays).
Downey, 2017; Kohles, 2017.
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Ref
Type of AR Use Case
Description
References
U5
AR Tours for Museums, Cities, Sites & Events
AR content and media overlaid during tours onto objects and scenes to enrich the experience.
Claudia et al, 2018; Downey, 2017; Kohles, 2017; Total Immersion, 2017; Yeo, 2017.
U6
AR 3D Models & Other Objects
Overlaying 3D models onto real world views.
Bassan, 2017; Biaanes, 2017; Index AR Solutions, 2016; Scholz & Smith, 2016.
U7
AR 3D Models for Purchasing Decisions
Positioning 3D models of possible purchases in a room or on a person.
Biaanes, 2017; Downey, 2017; Kohles, 2017; Oldhan, 2016; Rockafella, 2017; Total Immersion, 2018.
U8
AR 3D Models for Product Design
3D models presented for viewing within a scene potentially for groups to view.
Biannes, 2017; Downey, 2017; Oldham, 2016; Rockafella, 2017.
U9
AR Pets
Interactions with a dynamic 3D pet overlaid into a scene.
Downey, 2017.
U10 AR Overlays & Information for Maintenance Activities
Specific AR media and models to guide maintenance tasks.
Biaanes, 2017; Bassan, 2017; Scope, 2017; Harboth, 2017; Immersion, 2018; Index Solutions, 2016; Kohles, 2017; Oldham, 2016; Total Metra, 2017; Yeo, 2017.
U11 AR Surgical (and other complex tasks) Guidance
Overlaying a 3D AR image across a body or physical object to guide surgery or other intervention.
Harboth, 2017; Yeo, 2017.
U12 AR Training Materials
Learning materials presented using AR positioned within a scene or related to an object.
Index Solutions, 2016; Downey, 2017; Bassan, 2017; Total Immersion, 2018; Metra, 2017; Oldham, 2016; Biaanes, 2017; Harboth, 2017; Yeo, 2017.
U13 AR Holographic Trainer
Overlaying a dynamic and potentially interactive avatar into the vision of the user within their environment to motivate and train.
Biaanes, 2017; Downey, 2017.
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Description
References
U14 AR Games
Games utilising AR to display within a scene or based on geo-location.
Downey, 2017; Rockafella, 2017; Total Immersion, Biaanes, 2017; Augment, 2018; Rauschnabel et al., 2017; Harboth, 2017.
U15 Art Works Displayed using AR
Art (incl. graffiti) and pictures overlaid on walls or other scenes.
Downey, 2017; Kohles, 2017; Rockafella, 2017.
U16 AR Bogus Window
Video screen installation overlaying AR content onto the scene behind the screen.
Scholz & Smith, 2016.
U17 Screen Creation using AR
Interactive screens of content, media & applications (incl. communications) overlaid on a scene or object.
Downey, 2017; Rockafella, 2017.
U18 Displaying Recalled Information using AR
Recalling past interactions and other information dynamically potentially using objects in a scene and attaching information to these recognised objects.
Downey, 2017.
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U1 - Print and Object Augmentation
U2 - Advertising using AR
U3 - AR Signage
U4 - AR Overlays
U5 - AR Tours for Museums, Cities, Sites & Events
U6 - AR 3D Models & Other Objects
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U7 - AR 3D Models for Purchasing Decisions
U8 - AR 3D Models for Product Design
U9 - AR Pets
U10 - AR Overlays & Information for Maintenance
U11 - AR Surgical (and other complex tasks)
U12 - AR Training Materials
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Guidance
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U13 - AR Holographic Trainer
U14 - AR Games
U15 - Art Works Displayed using AR
U16 - AR Bogus Window
U17 - Screen Creation using AR
U18 - Displaying Recalled Information using AR
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The Model for AR Strategy & Roadmap Development (Theoretical Proposition)
AR Screens AR Heads Up Display (HUD) Mobile AR (MAR) Phones & Tablets AR Headsets AR Glasses AR Contact Lenses
AR Devices
Marker-based AR Marker-less AR Projection-based AR Superimposition-based AR AR-Enabled Web Browsers Specialist AR Browsers
AR Augmentation
AR Development Libraries
AR Product Success
Vendor Proprietary Deployment Platforms Device Specific Platforms
Print and Object Augmentation
AR Success
Advertising using AR AR Signage
AR Software
AR Overlays AR Tours for Museums, Cities, Sites & Events AR 3D Models & Other Objects AR 3D Models for Purchasing Decisions AR 3D Models for Product Design AR Pets
AR Overlays & Information for Maintenance AR Surgical (and other tasks) Guidance AR Training Materials AR Holographic Trainer AR Games Art Works Displayed using AR AR Bogus Window Screen Creation using AR Displaying Recalled Information using AR
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AR Use Cases
AR Development Success
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Validating the Research Model and AR Taxonomies Validation was only partially successful in the time available within the project for reasons that were not expected and, as a result, validation is continuing. Five approaches to validation were employed to “triangulate” and inform the evaluation. 1. Industry Listings from Articles and Blogs Materials from the AR industry and IT research industry that purported to cover broadly the areas represented by the constructs were reviewed. These materials were not well developed and usually were opinion based, albeit by privileged informants operating from positions within the industry that helped them be well informed. 2. Researcher Review Dr Saroj Patel was used throughout the project to review both methods and outcomes. Dr Patel holds a PhD from Cranfield in information systems with her specialism being “informating” organisations. She is also the IT and Innovation Director at the Royal National Orthopaedic Hospital NHS Trust in Hertfordshire and so also bring practitioner expertise. 3. Participation from Members of AR Forums in Reviews This was expected to be the main source of validation and it was anticipated that this would also enhance the taxonomies. Postings to two forums were undertaken with over 28,000 followers. But initially there were no volunteers that came forward to assist with the reviews. Investigations suggested that members of these forums were especially busy and that explained the slow response. Recently, several weeks after posting requests, volunteers are starting to respond and will be followed up. But at the time of this report those discussions are being arranged. The posts and accompanying materials are included in Appendix A. 4. Vendor Reviews A VR and AR exhibition and conference in London corresponded with the finalising of the project – Future Tech Now, 05-07 April 2018, at the London Design Centre. The findings were shared with five AR vendors at this exhibition: • • • • •
3CUBED Happy Finish Mbryonic Surround Vision Admix
The project, research model and constructs were discussed along with the motivations and how the outcomes would assist future AR practitioners working with organisations. These discussions were quite one sided with the researcher working hard to convey the project outcomes which exceeded the knowledge of the vendor staff who were in organisations that majored on VR and where AR was in its early stages. However, the discussions were supportive and validating of the project at a general level. Validation is a part of this project that has not worked as expected. This is not through lack of effort, but instead because of the early and fragmented nature of AR practice at this time. The validation efforts will continue and look likely to deliver. Additionally, efforts are being made to reach out to AR researchers through ResearchGate.
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POC Case Study Applying the Model and Taxonomies (Cycle 2) POC Methodology Cycle 2 of the project takes the research model and taxonomies and applies them to a public space in West London. It does this by employing the taxonomies to develop an AR strategy or roadmap for the public space. Some of the viable AR applications identified are then developed into proof of concept AR applications to validate the end-to-end methodology. The simulation has deficiencies from the project’s small size, that are important to acknowledge. The first relates to the development of the AR strategy. When used in real-world situations a model and set of taxonomies such as developed here, would typically be employed by facilitating workshops or meetings involving a varied selection of people knowledgeable about the public space. Sometimes these working sessions might include IT professionals with awareness of AR. In this simulation the development will be undertaken by the researcher. Consequently the evaluations will be more opinion-based and employ a single person’s experiences of the public space. The second limitation relates to the development of the POC AR applications. In a real-world situation such AR applications would ideally be developed by experienced AR developers. Since this is a project within an educational course, these AR developer skills need to be developed. They have been developed but only to a level that will create relatively simple examples of such AR applications. But these can act as proof of concept applications demonstrating that a) the methodology can yield a valid portfolio of AR applications within its roadmap, and b) the technology platforms for AR can be explored to help evaluate their readiness. These deficiencies have an effect on rigour, meaning that the project is achieving propositions rather than new theory for the research community and early methods for practitioners. About the North Acton Playing Fields The public space chosen was the North Acton Playing Fields in West London which is approx. 10 acres in size and has the following major areas of (physical) utility – that can potentially be augmented using AR: • • • • • • • • • • • • • • • • •
Sport Facilities Community Café & Meeting Room Children’s Playground Outdoor Gym & Jogging Track Dog Walking Trees, Shrubs & Greenspace Wildlife Pick-nick Area Relaxing Areas (e.g. for sunbathing) Community Notice Boards Park Notice Boards Car Parking Bus Stops Local Tube Stations Maintenance Tennis Coaching Business Graffiti & Tags & Street Art
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Location The space is North Acton Playing Fields in the borough of Ealing in West London. Chosen as a space that is very basic and so allows the model to be tested as a process and tests whether valuable outcomes result, even from simple public spaces. It is also a site the researcher is familiar with as his residence borders this public space.
Figure A1 – Aerial Photo of North Acton Playing Fields & it’s Local Community
Sport Facilities
Community Café & Meeting Room
Children’s Playground
Outdoor Gym & Jogging Track
Dog Walking
Trees, Shrubs & Greenspace
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Wildlife
Pick-nick Area
Relaxing
Community Notice Boards
Park Notice Boards
Car Parking
Bus Stops
Local Tube Stations
Maintenance
Tennis Coaching Business
Graffiti & Tags & Street Art
Figure A2 – Photos of Major Uses for the Community from the Playing Fields
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Analysis of AR Devices for Applying AR to this Public Space Criteria applied to AR devices, augmentation and software: • • • •
Cost – from perspectives of both the AR users and the AR developers Reach – how readily available to the populations of users and developers Security – IT and info security but also physical security (e.g. to theft) Practical – Wider concept about practicality of the artefacts in the context of public spaces
Ref
Type of AR Device
Cost
Reach
Security
Practical
D1
AR Screens
L
L
L
L
D2
AR Heads Up Display (HUD)
L
L
L
L
D3
Mobile AR (MAR) Phones & Tablets
J
J
J
J
D4
AR Headsets
K
L
K
J
D5
AR Glasses
L
L
L
J
D6
AR Contact Lenses
L
L
J
L
Stand out device(s): •
Mobile AR (MAR) Phones & Tablets
Analysis of AR Augmentation for Applying AR to this Public Space Ref
Type of AR Augmentation
Cost
Reach
Security
Practical
T1
Marker-based AR
J
J
K
K
T2
Marker-less AR
J
J
J
J
T3
Projection-based AR
L
K
L
L
T4
Superimposition-based AR
K
K
J
L
Stand out augmentation(s): • •
Marker-based AR Marker-less AR
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Analysis of AR Software for Applying AR to this Public Space Ref
Type of AR Software
Cost
Reach
Security
Practical
S1
AR-Enabled Web Browsers
K
J
J
L
S2
Specialist AR Browsers
J
J
J
J
S3
AR Development Libraries
J
J
J
J
S4
Vendor Proprietary Deployment Platforms
L
J
K
K
S5
Device Specific Platforms
L
L
L
L
Stand out augmentation(s): • •
Specialist AR Browsers AR Development Libraries
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Analysis of Generic AR Use Cases for Applying AR to this Public Space Note that this analysis has been restricted to the first 30 specific use cases for AR for North Acton Playing Fields (NAPF). Commentary in square brackets is indicating the generic type of utility or value being delivered by the AR use case.
Ref
Type of AR Use Case
Specific Use Cases for NAPF
Value
Cost
Risk
U1
Print and Object Augmentation
• AR marker triggered video demo of the gym equipment [Increased and improved usage of outdoor gym]
M
M
L
U2
Advertising using AR
• AR advertising of businesses e.g. café, tennis, dog walkers [Increased revenues for business using this public space] *
H
L
L
H
L
L
• Promoting how best to use the facilities and the space. [Increased usage and better usage] *
H
L
L
• Interactive AR noticeboard for dog owners [Easier for dog owners to interact & organize play times] *
H
L
L
H
L
L
• AR information on meeting rooms, layouts, booking, etc. [Increased usage of under-used facilities] * • Short term offers from the café, tennis courts, etc. in AR [Increase revenues and utilisation of businesses in space] *
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Ref
Type of AR Use Case
Specific Use Cases for NAPF
Value
Cost
Risk
U3
AR Signage
• AR signs to places of interest in the space and outside [Increase ease of use and promotes greater usage]
M
L
L
• Additional AR generated notice boards around the space [Improved usage behaviours and wider participation] *
H
L
L
H
M
M
H
L
L
• AR labels overlaid over trees, shrubs, flower beds [Educational and entertainment value] *
H
L
L
• AR overlay scenes with areas where dogs can defecate [Better behaviours by dog users of the space] *
H
L
L
• AR overlays of next bus due over bus shelters [Ease of access of space from public transport] *
H
L
L
• AR guided tours of space for people new to the area [Promotes great usage] *
H
L
L
• AR information on the history of the fields and area [Increased interest and entertainment]
M
L
L
• Interactive notice board at tennis courts allowing booking [More convenience for tennis players promoting usage] • Dynamic signage to litter bins [Reducing littering & collection costs] * U4
U5
AR Overlays
AR Tours for Museums, Cities, Sites & Events
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Ref
Type of AR Use Case
Specific Use Cases for NAPF
Value
Cost
Risk
U6
AR 3D Models & Other Objects
• Augmenting the space with 3D objects and creatures [Increased entertainment] *
H
L
L
• Additional community noticeboards using AR [Increasing utility of the space] *
H
L
L
• Additional notice boards on park regulations using AR [Increased adherence to regulations and bye-laws] *
H
L
L
U7
AR 3D Models for Purchasing Decisions
• Users of the space do not purchase items.
-
-
-
U8
AR 3D Models for Product Design
• AR representation of how planned building impact skyline [Easier public consultation about over-development]
L
H
M
U9
AR Pets
• Range of interactive pets that behave within the scenes [Promotes great usage and higher levels of entertainment]
M
H
H
U10 AR Overlays & Information for Maintenance Activities
• AR maintenance information for gardeners & ground staff [Improved maintenance & lower maintenance costs]
H
H
M
U11 AR Surgical (and other complex tasks) Guidance
• AR measurement of pitches for line painting [Productivity improvements for ground staff]
L
M
M
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Type of AR Use Case
U12 AR Training Materials
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Specific Use Cases for NAPF • AR notices on personal safety and safe use of equipment [Reduces barriers to usage of the space] *
Value
Cost
Risk
H
L
L
H
H
H
• AI recognition of flora and wildlife adding AR information [Educational and entertainment value] U13 AR Holographic Trainer
• Holographic fitness coach for jogging and exercise track [Improved fitness and health and increased usage]
H
H
M
U14 AR Games
• AR games using the space (e.g. virtual Easter egg hunt) [Increases usage and widens age range of users]
H
M
M
• AR guidance to play diverse set of games in the space [Increases usage and widens participation]
M
L
L
• AR artwork added to the open spaces (e.g. sculptures) [Entertainment and interest increased and broaden users]
M
M
L
M
H
H
U15 Art Works Displayed using AR
• AR graffiti and tagging on vertical surfaces and objects [Lower costs of removing physical graffiti] U16 AR Bogus Window
• AR screen overlaying past history on view of the space [Increases enjoyment by adding interest]
L
H
M
U17 Screen Creation using AR
• AR screens allowing people to work in space [Increased usage]
L
H
H
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Type of AR Use Case
U18 Displaying Recalled Information using AR
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Specific Use Cases for NAPF
Value
Cost
Risk
• Using facial recognition to add AR – based information [Increased social interaction amongst space users]
M
H
H
• Recognising facilities to add AR-based usage information [Increased usage by reminding users of past usages]
L
H
M
Stand out AR Use Cases •
• •
•
Advertising using AR: § AR advertising of businesses e.g. café, tennis, dog walkers § Promoting how best to use the facilities and the space. § Interactive AR noticeboard for dog owners § AR information on meeting rooms, layouts, booking, etc. § Short term offers from the café, tennis courts, etc. in AR AR Signage: § Additional AR generated notice boards around the space § Dynamic signage to litter bins AR Overlays: § AR labels overlaid over trees, shrubs, flower beds § AR overlay scenes with areas where dogs can defecate § AR overlays of next bus due over bus shelters AR Tours for Museums, Cities, Sites & Events: § AR guided tours of space for people new to the area
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AR Strategy or Roadmap The model and the taxonomy were effective and could deliver an AR strategy or roadmap for the chosen public space and provided the following strategies for device, software, augmentation and use cases.
Strategy for AR Devices
Mobile AR (MAR) Phones & Tablets
Strategy for AR Software
Specialist AR Browsers AR Development Libraries (deployed within mobile browsers)
Strategy for AR Augmentation
Marker-based AR, and Marker-less AR
Strategy for AR Use Cases (Roadmap)
Advertising using AR: • • • • •
AR advertising of businesses e.g. café, tennis, dog walkers Promoting how best to use the facilities and the space. Interactive AR noticeboard for dog owners AR information on meeting rooms, layouts, booking, etc. Short term offers from the café, tennis courts, etc. in AR
AR Signage: • •
Additional AR generated notice boards around the space Dynamic signage to litter bins
AR Overlays: • • •
AR labels overlaid over trees, shrubs, flower beds AR overlay scenes with areas where dogs can defecate AR overlays of next bus due over bus shelters
AR Tours for Museums, Cities, Sites & Events: •
AR guided tours of space for people new to the area
AR 3D Models & Other Objects: • • •
Augmenting the space with 3D objects and creatures Additional community noticeboards using AR Additional notice boards on park regulations using AR
AR Training Materials: •
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AR notices on personal safety and safe use of equipment
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Proof of Concept of Using the Model and Taxonomies for Developing AR Applications AR Application Platform Selection The project moved on to developing POCs for a selection of the use cases identified in the roadmap. The selection of the AR application platform used the strategy developed for AR devices, software and augmentation: • • •
Devices – supporting AR on phones and tablets and on Android and IOS operating systems Software – AR browser based deployment with low or no cost Augmentation – Marker less AR ideally as it has less visual impact on a public space
Additionally the platform would need to be easy to learn and easy to deploy as we are simulating the situation where end users in public services and the general public may deploy the AR solutions. There are many AR platforms at this stage in the development of the field and reviewing them was elaborate and time consuming. It emerged that none of the current platforms met all the criteria. Many were proprietary and cost prohibitive. Very few operated on both the Android and IOS operating systems, which is important because the users of public spaces will have both. Much store has been placed by IT industry commentators on the mid 2017 launch by Apple of ARKit by Google of CoreAR but both only support their vendor’s respective operating systems. Two platforms stood out – ARAF and BlippAR. The first was the ARAF browser (Google Commercial, 2018) which operationalises the new ISO standard, Augmented Reality Application Format (ARAF). This is only available for Andriod but an IOS ARAF browser was intended. It is open source software and freely available. For AR applications for public spaces it offered potential availability at very low cost. The ARAF language could be learned from a free course available via Coursera from the Institut Mines-Télécom (subsequently this course is now charged for by Coursera). Significant effort and elapsed time were applied to the ARAF option using the Coursera training and trying to apply it to AR applications. But the browser proved too difficult to use being too early (it is a beta) and oversold and without an IOS version this option was abandoned. Unfortunately this had an impact on the project, putting schedules back several weeks. That said, this is not an unusual situation to encounter in the early part of the innovation life cycle for a new technology. The second stand-out option was employed next being BlippAR. This platform has the deficiency for the use cases for public spaces, that it is proprietary and costly to utilise. But it is available with AR Browsers for IOS and Android and Microsoft operating systems and via Javascript libraries and APIs could be deployed within common mobile browsers. It has a sophisticated development toolkit and common AR functionality can be created through a standard browser on BlippAR’s cloud services. Cost would be an issue for real-world deployments but BlippAR provide free access to the platform for educational purposes and this offer was used by this project. What also makes BlippAR very interesting for this project is that BlippAR has a machine language component for image recognition that is learning about objects. As this develops, it offers potential for using image recognition of real-world objects as the trigger for augmentation in public spaces. BlippAR is not well supported with learning materials but sufficient is available for the POCS in this project. BlippAR became the platform used.
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AR Applications for North Acton Playing Fields Activities Completed The project had only sufficient time to complete the initial POC applications. This confirms the ability of the taxonomy to provide a roadmap that is sufficiently clear and detailed to form the basis for implementation. These POC applications also explore the practical deployment of AR software platforms, albeit that this is at an introductory level. As discussed later in this report, the project does not end with the course submission. Instead the R&D work will continue including developing further POCs leading onto the full augmentation of the North Acton Playing Fields as an example of what can be achieved with contemporary bodies of knowledge and software tools and devices. AR Application for Use Case: AR Labels Overlaid Over Trees, Shrubs, Flower Beds The BlippAR browser is linked to an AI (artificial intelligence/machine learning) cloud service that recognises objects and automatically augments them with labelling. This “out of the box” functionality of the BlippAR browser was used for this use case. The POC was able to identify and label many of the trees, shrubs and flowers in this public space within a few seconds of the image being available in the camera of the i-phone. The label that identifies the specie in latin links, when touched on the screen, to further information. Example screens captured:
AR Application identifies Ulmus Hollandica or Dutch Elm)
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AR Application incorrectly identifies a hawthorn bush as atriplex canescens, a native of Portugal
AR Application identifies the genus of Narcissus of which daffodil is a member.
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AR Application for Use Case: AR Guided Tour of Space for New People to the Area The POC for this use case was not attempted in full due to the time it will take. But a part of the tour was developed. In this part of the tour an artwork installation in the public space is augmented with the information on the name of the artwork with a link to the artist and a link to the wider Art in the Park Council Initiative. Touching the augmentation on the phone screen activates the links and brings up further information.
Photo of the Art Installation
Augmented Close Up
Augmented from a Distance (Shows dynamic repositioning of augmentation)
AR Application for Use Case: Additional Community Notice Boards using AR This POC isn’t really providing an additional community notice board but instead enhances the community notice boards already in place. The augmentation featured is adding interactivity and information to a normal poster, in this case for a show at a local community theatre. The augmentation allows the person to buy tickets and find out more about the theatre from their phone.
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Photo of the Noticeboard
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Links through to Information
AR Application for Use Case: AR Notices on Personal Safety and Use of Equipment This POC aims to encourage local people to use the outdoor gym that is rarely used after several years of being available. The information on how to use it on the equipment itself is very limited. AR offers the potential to augment each of the machines in the outdoor gym and provide video coaching to users.
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Augmentation of Dips
Video Coaching for Dips
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AR Application for Use Case: Interactive AR Noticeboard for Dog Owners This POC recognises that the signage in the park has to address too many different users and age ranges and language, so is very general. AR offers the potential to have much more signage without creating new physical boards that take away from the natural outdoor space. This POC uses the existing noticeboard as a trigger to reveal other notices and noticeboards for different types of users. In this example choosing the notice board for dog owners, reveals a notice on problem usage of the public space.
Photo of General Noticeboard
Augmented with Specialist Boards
Dog Owners Board
AR Application for Use Case: Short Term Offers from Café, Tennis Courts, etc. The café is underused and possibly - in part - because park users don’t know what it serves and its opening times. This POC provides a menu without needing to enter the café and opening times even when closed. In this example, a special offer of tea and muffin is also made available with AR.
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Photo of Community Cafe
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Augmented with Menu and Opening Times
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Promotions from the Cafe
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Evaluation of Application of Model and Taxonomies (Cycle 3) Research Model The proposed research model was more fully explored for the independent constructs of device, software, augmentation and use case. The dependent construct of success was not developed in this project (will need to be addressed in future work). The model was useful in focusing on the options available within these independent constructs and how they need to be aligned if AR is to be a success. Taxonomies The taxonomies for AR devices, AR software, AR augmentation and AR use cases are useful contributions for practitioners to assist them as a checklist to ensure all options are addressed and as a means to focus down on the best options. They are framed at a level of specificity which is still sufficient high level not to overwhelm managers trying to make progress in AR, but containing sufficient detail to guide decision making. For AR researchers, there are no taxonomies at present, so the taxonomies developed could be useful as general theoretical propositions. But for use in research they lack rigour at the moment and need better validation. Simulated Application to a Real-World Scenario The application of the model and taxonomies to the North Acton Playing Fields provided assurance that it could be employed to guide the creation of an AR strategy or roadmap for a simple public space. The application worked well for narrowing the options that made sense for that situation and that is likely to be a valuable capability for AR practitioners and managers seeking to exploit AR. Developing Proof of Concept AR Applications Flowing the project through into creating AR applications helped to illustrate the end-to-end coverage of this work – from AR strategy to AR applications. It also served to highlight that there are significant problems finding ideal application platforms for AR from the many vendors in this market space. This confirms industry commentators’ views that the AR field is still early in its development Overall Methodology The combination of AR model, AR taxonomies, AR roadmaping techniques and AR applications developments, all sum up to a methodology that organisations could use to get their responses to the opportunities and threats from augmentation shaped up through an AR strategy and early implementations of AR identified and then implemented. Limitations The outcomes have significant limitations that warrant further work. The rigour and validation could usefully be increased for aspects of the project. This would help with both achieving better results for organisation from their application of the project’s outcomes, and in building confidence. Another limitation is that it has been tested narrowling with a single site and one AR development platform. Testing more widely would engender more confidence in its use. Finally more could be made of the success construct by drawing on economics research more forcefully, and in so doing providing better focus and discrimination for the methodology. Page 48 of 67
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Future Research & Development Activities Future Research Future research could therefore address: •
Developing the constructs of utility of public spaces and dimensions of success. This should be possible by drawing on economic research into the general utility of public goods and for success drawing on research into IS success.
•
Widening the number and diversity of public spaces the model is trialled upon. This can be undertaken perhaps, most easily, by extending the work at North Acton Playing Fields to other local but more complicated public spaces like London’s Royal Parks. One of the contributors, Dr Saroj Patel, has offered her NHS Trust as a test-bed for using the methodology to create an AR strategy or roadmap and to take it through into implementation. This would most likely make her Trust the first in the NHS to have an explicit strategy for AR.
•
Understanding how such a model would be applied to organisations who already have developed IT and digital strategies. This project has taken an example which is a “green field site”. For most organisations they will have wider information systems strategies and programmes underway and any work on AR will need to fit into that.
Vehicles for Continuing this Work It is planned to take the project work beyond the end of the T847 module with: 1. Continuing the development and trialling of the model. 2. Open source publication of the model. 3. A talk to a British Computer Society meeting to present the project within an event on AR in November 2018. 4. Longer term, it is hoped that the research will develop further. A potential home on offer is the Wave Lab at the University of the Aegean which specialises in digital transformation. A Wave Lab working paper is feasible for 2019 to publish progress at that time.
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Conclusions Contributions to the Professional Development of the Student The T847 project has been a relentless and demanding challenge but through that experience has developed skills in project management and research methods, along with increased knowledge of the emerging technical fields of augmented reality and AI-based image recognition. The project has build upon, consolidated and integrated knowledge from a number of prior modules including M865 Project Management, M813 Software Development, M814 Software Engineering and M847 Information Security. Contributions for AR Practitioners The project aimed to make a contribution to both academic research in AR and also into AR practice by balancing a need for rigour with a need for relevance to practice. The end-to-end methodology can be applied not just to public spaces but to other organisational situations. It integrates with wider digital strategy methods and with agile applications development methods. It provides an over-arching model, taxonomies as checklists to ensure complete coverage of important AR areas and a framework for creating an AR roadmap that can be taken forwards into implementation. It operationalises and provides vehicles to support the advice of Porter & Heppleman (2017) that all organisations now need a pragmatic and implementable AR strategy. Contributions to AR Research and Thought Leadership The project responded to observations by Harborth (2017) after conducting a systematic review of premier, peer-reviewed academic research in the field of AR. He concluded that there was a deficiency in AR use cases for all aspects of public services. The response includes a contribution directly into AR for public services (in this case public spaces). An end-to-end example of applying AR to a public space is demonstrated. Additionally, theoretical propositions are developed for taxonomies for AR devices, AR software and AR use cases.
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References Ababsa, F., Didier, J., Zendjebil, I. and Mallem, M. (2008). ‘Marker Less Vision-Based Tracking of Partially Known 3D Scenes for Outdoor Augmented Reality Applications’. Published in International Conference on Computer Vision and Graphics, Warsaw, Poland, November 10-12, 2008, p218-227. Available at http://pmteu.hosted.exlibrisgroup.com/primo_library/libweb/action/display.do?tabs=viewOnlineTab&ct=displ ay&fn=search&doc=TN_scopus2-s2.0-68749084649&indx=13&recIds=TN_scopus2-s2.068749084649&recIdxs=12&elementId=12&renderMode=poppedOut&displayMode=full&frbrVersion =4&frbg=&dscnt=0&scp.scps=scope%3A%2844OPN_EPR_DS%29%2Cscope%3A%2844OPN_INST%29 %2Cscope%3A%2844OPN_ALMA_DS%29%2Cprimo_central_multiple_fe&fctV=peer_reviewed&vid= 44OPN_VU1&mode=Basic&rfnGrp=show_only&tab=default_tab&srt=rank&fctN=facet_tlevel&dum= true&vl(freeText0)=marker-less%20augmented%20reality&dstmp=1519983036011. (Accessed on 02 March 2018). Ali, R. and Carpenter, J. (2018). ‘Augmented Reality on the Web, for Everyone.’ Published by Google on 22 Jan 18. Available at https://blog.google/products/google-vr/augmented-reality-webeveryone/. (Accessed on 02 March 2018). Apple. (2017). ‘Apple Developer: Introducing ARKit.’ Retrieved from https://developer.apple.com/arkit/ (Accessed on 01 Nov 2017). Apple. (2018). ‘ARKit’. Available at https://developer.apple.com/arkit/. (Accessed on 02 March 2018). Apple (b). (2018). ‘Augmented Reality for IOS.’ Available at https://www.apple.com/uk/ios/augmented-reality/. (Accessed on 03 Mar 18). ARAF. (2018). ‘ARAF Browser’. Available at https://play.google.com/store/apps/details?id=com.gpac.Osmo4&hl=en. (Accessed 01 Nov 17) Argon.js. (2018). Available at https://www.argonjs.io. (Accessed on 02 March 2018). Argotti, Y., Davis, L., Outters, V., and Rolland, J. (2002). ‘Dynamic Superimposition of Synthetic Objects on Rigid and Simple-Deformable Real Objects.’ Computers & Graphics, Vol.26(6), pp.919930. Available at http://pmteu.hosted.exlibrisgroup.com/primo_library/libweb/action/display.do?frbrVersion=2&tabs=viewOnli neTab&ct=display&fn=search&doc=TN_sciversesciencedirect_elsevierS0097-8493(02)001802&indx=1&recIds=TN_sciversesciencedirect_elsevierS0097-8493(02)001802&recIdxs=0&elementId=0&renderMode=poppedOut&displayMode=full&frbrVersion=2&frbg=&&ds cnt=0&scp.scps=scope%3A%2844OPN_EPR_DS%29%2Cscope%3A%2844OPN_INST%29%2Cscope%3 A%2844OPN_ALMA_DS%29%2Cprimo_central_multiple_fe&mode=Basic&vid=44OPN_VU1&srt=ran k&tab=default_tab&vl(freeText0)=Dynamic%20superimposition%20of%20synthetic%20objects%20o n%20rigid%20and%20simple-deformable%20real%20objects&dum=true&dstmp=1520000262244. (Accessed on 02 March 2018). ARKit. (2018). Available at https://medium.com/journey-of-one-thousand-apps/arkit-andcorelocation-part-one-fc7cb2fa0150. (Accessed on 02 March 2018).
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Arth C., Gruber, L., Grasset, R., Langlotz, T., Mulloni, A., Schmalstieg, D., and Wagner, D. (2015). ‘The History of Mobile AugmentedRealityDevelopments in Mobile AR over the last almost 50 years’. Published by Researchgate, May 2015. Available at https://www.researchgate.net/publication/275974448. (Accessed on 02 March 2018). Aryzon. (2018) ‘Aryzon: Experience 3D Augmented Reality.’ Available at https://www.aryzon.com. (Accessed on 02 March 2018). Augment. (2017). Available at http://www.augment.com.(Accessed on 30 December 2017). Augment. (2018) ‘10 Use cases of Augmented Reality in Marketing’. Available at http://www.augment.com/blog/10-use-cases-of-augmented-reality-marketing/. (Accessed on 13 Feb 18). Augment.com. (2018). ‘Augment: Seamless Product Visualisation with AR.’ Available at http://www.augment.com. (Accessed on 02 March 2018). Aurasma. (2017). Available at https://www.aurasma.com. (Accessed on 30 December 2017). Aurasma. (2018). ‘HP Aurasma is Changing the Way We Interact with The World.’ Available at https://www.aurasma.com. (Accessed on 02 March 2018). Azuma, R. T. (1997). ‘A Survey of Augmented Reality.’ Presence: Teleoperators and Virtual Environments, 6, 4, pp 355-385. Available at http://pmteu.hosted.exlibrisgroup.com/primo_library/libweb/action/display.do?frbrVersion=2&tabs=viewOnli neTab&ct=display&fn=search&doc=TN_mitpress10.1162%2fpres.1997.6.4.355&indx=11&recIds=TN _mitpress10.1162%2fpres.1997.6.4.355&recIdxs=10&elementId=10&renderMode=poppedOut&disp layMode=full&frbrVersion=2&frbg=&&dscnt=0&scp.scps=scope%3A%2844OPN_EPR_DS%29%2Csco pe%3A%2844OPN_INST%29%2Cscope%3A%2844OPN_ALMA_DS%29%2Cprimo_central_multiple_fe &mode=Basic&vid=44OPN_VU1&srt=rank&tab=default_tab&vl(freeText0)=azuma%20augmented%2 0reality&dum=true&dstmp=1519074739647. (Accessed on 19 Feb 18) Bardi, J. (2017). ‘Markerless Augmented Reality: Everything You Need to Know.’ Published online in Marxent’s AR Blog: Augmented Reality Marketing Resources, Trends, Videos and Case Studies. Available at https://www.marxentlabs.com/markerless-augmented-reality-everything-you-need-toknow/. (Accessed on 02 Mar 18). Bassan, J. (2017) ‘5 killer use-cases for augmented reality in the enterprise’. Published on-line by DXC.Technology on 05 May 2017. Available at https://blogs.dxc.technology/2017/05/05/5-killeruse-cases-for-augmented-reality-in-the-enterprise/. (Accessed on 13 Feb 18). Beccue, M. (2017) ‘Augmented Reality: The Rise of Enterprise Use Cases’. Published on-line by Tractica on 21 Sept 2017. Available at https://www.tractica.com/user-interfacetechnologies/augmented-reality-the-rise-of-enterprise-use-cases/. (Accessed on 13 Feb 18). Bjaanes, G. (2017) ‘Use Cases for Augmented Reality.’ Available at http://www.gjermundbjaanes.com/use-cases-for-augmented-reality/. (Accessed on 13 Feb 18). Bittner, K. & Spence, I. (2003). ‘Use Case Modelling’, Pearson Education, Boston. Blippar. (2018). ‘Blippar: Where AR & AI Meet.’ Available at https://web.blippar.com. (Accessed on 02 Mar 18). Page 52 of 67
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Boganov, V. (2016). ‘Augmented Reality Browsers and Engines Overview’. Available at http://intersog.com/blog/augmented-reality/augmented-reality-browsers-and-engines-overview/ . (Accessed on 31 December 2017). Business Dictionary. (2017). ‘Public Good’. Retrieved from http://www.businessdictionary.com/definition/public-good.html (Accessed on 27 Nov 2017). Castellanos, A. &Pérez, C. (2017) ‘New Challenge in Education: Enhancing Student’s Knowledge through Augmented Reality.’ In Ed. Ariso, J. ‘Augmented Reality: Reflections on its Contribution to Knowledge Formation’, published by De Gruyter, Berlin. Available at http://www.oapen.org/search?identifier=628401. (Accessed on 13 Feb 18). Caulfield, E. (2017). ‘Augmented Reality in Your Browser’. June 8, 2017. Available at http://www.arintelligence.info/2017/06/augmented-reality-in-your-browser/. (Accessed on 31 December 2017). Cebulla, A. (2013). ‘Projection-Based Augmented Reality.’ Published in proceedings of Distributed Systems Seminar FY2013. Available at: https://www.semanticscholar.org/paper/Projection-BasedAugmented-Reality-Cebulla/3ac51199009c8252c5861166fa3a341e2408ec7c?tab=abstract. (Accessed on 02 Mar 18). Chowdrey, A. (2016). ‘Samsung Patent Unveils Idea for Smart Contact Lenses with A Camera And Display.’ Forbes, 11 Apr 2016. Available at https://www.forbes.com/sites/amitchowdhry/2016/04/11/samsung-patent-unveils-smart-contactlenses-with-a-camera-and-display/#4504dc42103b. (Accessed on 02 Mar 18). Claudia, M., Dieck, T., Jung, T. & Rauschnable, P. (2018) ‘Determining visitor engagement through augmented reality at science festivals: An experience economy perspective’. Computers in Human Behavior 82. Available at http://pmteu.hosted.exlibrisgroup.com/primo_library/libweb/action/display.do?frbrVersion=2&tabs=viewOnli neTab&ct=display&fn=search&doc=TN_sciversesciencedirect_elsevierS0747-5632(17)30729X&indx=9&recIds=TN_sciversesciencedirect_elsevierS0747-5632(17)30729X&recIdxs=8&elementId=8&renderMode=poppedOut&displayMode=full&frbrVersion=2&frbg=&&d scnt=0&scp.scps=scope%3A%2844OPN_EPR_DS%29%2Cscope%3A%2844OPN_INST%29%2Cscope% 3A%2844OPN_ALMA_DS%29%2Cprimo_central_multiple_fe&mode=Basic&vid=44OPN_VU1&srt=ra nk&tab=default_tab&vl(freeText0)=%27augmented%20reality%27%20&dum=true&dstmp=1518557 503401. (Accessed on 13 Feb 18). Constine, J. (2018). ‘Facebook's plan to unite AR, VR and News Feed with 3D posts.’ Published online in TechCrunch on 20 Feb 18. Available at https://beta.techcrunch.com/2018/02/20/facebook-3dposts/. (Accessed on 03 Mar 2018]. Contact Lenses. (2016). ‘Apple Announces Partnership With EPGL To Create Revolutionary Augmented Reality App.’ Published in Contact Lenses online magazine on 02 Nov 2016. Available at https://www.contactlenses.fr/contactlensesnews/article74075/apple-announces-partnership-withepgl-to-create-revolutionary-augmented-reality-app.html. (Accessed on 03 Mar 2018]. Coursera. (2017). ‘Getting started with Augmented Reality.’ Retrieved from https://www.coursera.org/learn/augmented-reality (Accessed on 01 Nov 2017). Downey, S. (2017). ‘The massive list of AR use cases’. Available at https://www.youtube.com/watch?v=JrZsmfA56Sw. (Accessed on 13 Feb 18).
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Elgan, M. (2017). ‘The augmented reality boom will transform phones (and business): with lasers, holograms and more, smartphone makers are scrambling to optimize devices. One use that's coming soon: augmented reality collaboration’. Computerworld, 15 July 2017. https://www.computerworld.com/article/3208047/virtual-reality/the-augmented-reality-boom-willtransform-phones.html. (Accessed on 31 December 2017). Epson. (2018). ‘Epson: Augmented Reality and Mixed Reality.’ Available at https://epson.com/moverio-augmented-reality. (Accessed on 02 Mar 18). Etienne, J. (2018). ‘ARJS - Efficient Augmented Reality for the Web - 60fps on Mobile!’ Published at GitHub. Available at https://github.com/jeromeetienne/AR.js. (Accessed on 02 Mar 18). Feltham, J. (2018). ‘Samsung Is Making AR Glasses To Help The Visually Impaired.’ Published online at UploadVR on 02 Jan 18. Available at https://uploadvr.com/samsung-making-ar-glasses-helpvisually-impaireds-sight/. (Accessed on 02 Mar 18). Financial Times Lexicon. (2017). ‘Definition of Augmented Reality.’ Retrieved from http://lexicon.ft.com/Term?term=augmented-reality (Accessed on 27 Nov 2017). Gartner (2018). ‘Gartner IT Glossary > Augmented Reality (AR).’ Available at https://www.gartner.com/it-glossary/augmented-reality-ar/ (Accessed on 06 Apr 18). Google. (2017(a)). ‘ARCore: Build The Future.’ Retrieved from https://developers.google.com/ar/ (Accessed on 01 Nov 2017). Google. (2017(b)). ‘Glass Explorer Edition.’ Retrieved from https://developers.google.com/glass/ (Accessed on 27 Nov 2017). Google. (2018). ‘Google Glass’. Available at https://developers.google.com/glass/distribute/glassenterprise. (Accessed on 02 Mar 18). Google Developers. (2018). ‘ARCore: Build the Future.’ Available at https://developers.google.com/ar/. (Accessed on 02 Mar 18). Haidar, H. (2018). ‘Panasonic Automotive Systems Europe's latest HUD innovation shown @ #CES2018.’ Published in LinkedIn on 15 Jan 18. Available at https://www.linkedin.com/pulse/panasonic-automotive-systems-europes-latest-hud-shown-haidarpmp/. (Accessed on 02 Mar 18). Harborth, D. (2017). ‘Augmented Reality in Information Systems Research: A Systematic Literature Review.’ Twenty-Third Americas Conference on Information Systems, Boston, 2017. Available at https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1211&context=amcis2017. (Accessed on 31 December 2017). IEEE. (2017). ‘IEEE Standards Association. Augmented Reality: Provides a concise reference point for IEEE Standards related to Augmented Reality (AR).’ Retrieved from http://standards.ieee.org/innovate/ar/stds.html (Accessed on 01 Nov 2017). Information Systems, South Korea, 2017. Available at http://aisel.aisnet.org/cgi/viewcontent.cgi?article=1010&context=icis2017. http://aisel.aisnet.org/amcis2017/AdvancesIS/Presentations/16/. (Accessed on 19 Feb 18)
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Oldham, P. (2016) ‘5 Best Augmented Reality Use Cases’. Published in on-line site Tom’s IT Pro on 12 Dec 2016. Available at http://www.tomsitpro.com/articles/best-augmented-reality-uses,13440.html. (Accessed on 13 Feb 18). Open University. (2005). ‘Action Research: A Guide for Associate Lecturers’, published by Centre for Outcomes-Based Education, April 2005. Retrieved from http://www.open.ac.uk/cobe/docs/ARGuide-final.pdf. (Accessed on 06 Dec 2017). Piggott-Irvine, E. (2002). ‘Rhetoric and Practice in Action Research’. Annual Conference of the British Education Research Association, University of Exeter, 12-14 September 2002. Available at http://www.leeds.ac.uk/educol/documents/00002471.htm . (Accessed on 07 January 2018 Porter, M. E. and Heppelmann, J. E. (2017a) ‘Why Every Organisation Needs and Augmented Reality Strategy’, Harvard Business Review, November-December 2017. Retrieved from http://pmteu.hosted.exlibrisgroup.com/primo_library/libweb/action/display.do?tabs=viewOnlineTab&ct=displ ay&fn=search&doc=TN_gale_ofa513798437&indx=1&recIds=TN_gale_ofa513798437&recIdxs=0&el ementId=0&renderMode=poppedOut&displayMode=full&frbrVersion=&frbg=&&dscnt=0&scp.scps= scope%3A%2844OPN_EPR_DS%29%2Cscope%3A%2844OPN_INST%29%2Cscope%3A%2844OPN_AL MA_DS%29%2Cprimo_central_multiple_fe&mode=Basic&vid=44OPN_VU1&srt=rank&tab=default_t ab&vl(freeText0)=what%20every%20organisation%20needs%20an%20augmented%20reality%20str ategy&dum=true&dstmp=1512589171834 (Accessed on 01 Nov 2017). Porter, M.E. and Heppelmann, J. E. (2017b) ‘Why Business Leaders Need an Augmented Reality Strategy‘, Webinar, 01 December 2017, PTC Inc. Retrieved from https://www.ptc.com/en/resources/ar/webcast/business-leaders-strategy-replay/thank-you (Accessed on 30 Jan 2018) Rauschnabel, P., Rossmann, A., Diek, T. & Claudia, M. (2017). ‘An adoption framework for mobile augmented reality games: The case of Pokémon Go.’ Computers in Human Behaviour, November 2017, Vol.76, pp.276-286. Available at http://pmteu.hosted.exlibrisgroup.com/primo_library/libweb/action/display.do?frbrVersion=4&tabs=viewOnli neTab&ct=display&fn=search&doc=TN_sciversesciencedirect_elsevierS0747-5632(17)304521&indx=12&recIds=TN_sciversesciencedirect_elsevierS0747-5632(17)304521&recIdxs=11&elementId=11&renderMode=poppedOut&displayMode=full&frbrVersion=4&frbg=& &dscnt=0&scp.scps=scope%3A%2844OPN_EPR_DS%29%2Cscope%3A%2844OPN_INST%29%2Cscop e%3A%2844OPN_ALMA_DS%29%2Cprimo_central_multiple_fe&mode=Basic&vid=44OPN_VU1&srt =rank&tab=default_tab&vl(freeText0)=%27augmented%20reality%27%20&dum=true&dstmp=1518 557883184. (Accessed on 13 Feb 18). Realfiction. (2018). ‘Deepframe’. Available online at https://www.realfiction.com/solutions/mixedreality/deepframe. (Accessed on 03 Mar 18). Rockafella, N. (2017) ‘Business Use Cases of Augmented Reality’. Published by Media Innovation on 06 Jun 2017. Available at http://www.numediainnovations.com/blog/business-use-cases-ofaugmented-reality. (Accessed on 13 Feb 18). Samsung. (2018). ‘Samsung – S9/S9+ - Augmented Reality.’ Available at http://www.samsung.com/global/galaxy/galaxy-s9/augmented-reality/. (Accessed on 03 Mar 18). Skwarek, M. (2013). ‘CreatAR: Augmented Reality App.’ ACM SIGGRAPH 2013 Mobile, 21 July 2013, pp.1-1. Retrieved from http://pmt-
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eu.hosted.exlibrisgroup.com/primo_library/libweb/action/display.do?frbrVersion=2&tabs=viewOnli neTab&ct=display&fn=search&doc=TN_acm2503539&indx=1&recIds=TN_acm2503539&recIdxs=0& elementId=0&renderMode=poppedOut&displayMode=full&frbrVersion=2&frbg=&&dscnt=0&scp.sc ps=scope%3A%2844OPN_EPR_DS%29%2Cscope%3A%2844OPN_INST%29%2Cscope%3A%2844OPN _ALMA_DS%29%2Cprimo_central_multiple_fe&mode=Basic&vid=44OPN_VU1&srt=rank&tab=defau lt_tab&vl(freeText0)=creatAR&dum=true&dstmp=1512330882160 (Accessed on 03 December 2017). Stroobandt, T. (2016). ‘Augmented reality for BNP Paribas Fortis Bank’. Available at https://www.youtube.com/watch?v=S41rJUbYtjM. (Accessed on 13 Feb 18). Scope. (2017) ‘Scope AR Use Case: Gearbox’. Available at https://www.youtube.com/watch?v=aG7hvZe1nt4. (Accessed on 13 Feb 18). Scholz, J. & Smith, A. (2016). ‘Augmented Reality: Designing Immersive Experiences that Maximise Consumer Engagement’, Business Horizons, 59, pp 149-161. Available at https://ac-els-cdncom.libezproxy.open.ac.uk/S0007681315001421/1-s2.0-S0007681315001421main.pdf?_tid=0501be38-154a-11e8-a08000000aab0f6c&acdnat=1519027009_3dce1c71a258eca20f19bcc707e1de4f. (Accessed on 19 Feb 18) ScopeAR. (2018). ‘ScopeAR’. Available at https://www.scopear.com. (Accessed on 02 March 18). Slashgear. (2017). ‘Samsung plans just revealed new Holographic AR Glasses.’ Published online at Slashgear on 18 Aug 17. Available at https://www.slashgear.com/samsung-plans-just-revealed-newholographic-ar-glasses-18495777/. (Accessed on 02 March 18). Sony. (2018). ‘SmartEyeGlass’. Available at https://developer.sony.com/develop/smarteyeglass-sede1/. (Accessed on 02 March 18). Sutherland, I. (1968). ‘A Head-Mounted Three-Dimensional Display,’ in Proceedings of the December 9-11, 1968, Fall Joint Computer Conference, Part I, AFIPS ’68 (Fall, part I), (New York, NY, USA), pp. 757–764, ACM, 1968. Available at https://www.cise.ufl.edu/research/lok/teaching/ves07/papers/sutherland-headmount.pdf. (Accessed on 02 March 18). ThinkMobiles. (2018) ‘What is Augmented Reality and How Does it Work?’. Available at https://thinkmobiles.com/blog/what-is-augmented-reality/. (Accessed on 01 March 18). Tobar, H. (2014). ‘Is there a Taxonomy, Classification or Typology on Augmented Reality Applications?.’ A research community discussion in ResearchGate. Available at https://www.researchgate.net/post/Is_there_a_Taxonomy_Classification_or_Typoology_on_Augme nted_Reality_Applications. (Accessed on 01 March 18). Total Immersion. (2018) ‘Top 10 Augmented Reality Use Cases’. Available at http://www.timmersion.com/augmented-reality/use-cases. (Accessed on 13 Feb 18). Unity. (2018). ‘Unity for Mobile AR: Powering the majority of AR experiences, Unity is the best platform to unleash your creative potential.’ Available at https://unity3d.com/solutions/mobile-ar. (Accessed on 02 Mar 18). Venkatraman, N. (1989). ‘The Concept of Fit in Strategy Research: Towards Verbal and Statistical Correspondence.’ Academy of Management Review, Vol. 14, No. 3, pp 942-962. Available at http://pmtPage 58 of 67
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eu.hosted.exlibrisgroup.com/primo_library/libweb/action/display.do?frbrVersion=6&tabs=viewOnli neTab&ct=display&fn=search&doc=TN_proquest210962158&indx=2&recIds=TN_proquest21096215 8&recIdxs=1&elementId=1&renderMode=poppedOut&displayMode=full&frbrVersion=6&frbg=&&ds cnt=0&scp.scps=scope%3A%2844OPN_EPR_DS%29%2Cscope%3A%2844OPN_INST%29%2Cscope%3 A%2844OPN_ALMA_DS%29%2Cprimo_central_multiple_fe&mode=Basic&vid=44OPN_VU1&srt=ran k&tab=default_tab&vl(freeText0)=venkatraman%20and%20fit&dum=true&dstmp=1515702277008 (Accessed on 30 December 2017). ViewAR. (2017). Available at http://www.viewar.com. (Accessed on 30 December 2017). Visidraft. (2017). Available at http://www.visidraft.com/HowItWorks.php. (Accessed on 30 December 2017). Vuzix. (2018). ‘Vuzix Smart Class.’ Available at https://www.vuzix.com. (Accessed on 02 Mar 18). Vuforia. (2018). ‘Vuforia’. Available at https://www.vuforia.com. (Accessed on 02 Mar 18). Vuforia. (2017). Available at https://www.vuforia.com. (Accessed on 30 December 2017). Wang, Y., Zhang, S., Yang, S., He, W.and Bai X. (2018). ‘Mechanical assembly assistance using markerless augmented reality system’, Assembly Automation, Vol. 38 Issue: 1, pp.77-87. Available at https://doi.org/10.1108/AA-11-2016-152. (Accessed on 02 Mar 18). Wayray. (2018). ‘WayRay: Experience True Augmented Reality.’ Available at https://wayray.com. (Accessed on 02 Mar 18). WebAR. (2018). ‘WebAR Playground.’ Available at https://webxr.io/webar-playground/app/. (Accessed on 02 Mar 18). Wikitude. (2017). Available at https://www.wikitude.com. (Accessed on 30 December 2017). Wikitude. (2018). ‘Wikitude: Smart, Seemless AR Tracking.’ Available at https://www.wikitude.com. (Accessed on 02 Mar 18). Wolfswinkel, J., Furtmueller, E. & Wilderom, C. (2013). “Using grounded theory as a method for rigorously reviewing literature.’ European Journal of Information Systems (2013) pp22-45. Available at https://link-springer-com.libezproxy.open.ac.uk/article/10.1057/ejis.2011.51#citeas. (Accessed on 02 Mar 18). Yeo, J. (2017). ‘The Theory of Process Augmentability.’ Thirty-Eighth International Conference on Index AR Solutions. (2016) ‘Augmented Reality: Four Use Cases for Industry’. Available at https://www.youtube.com/watch?v=qMEJnYKpwog. (Accessed on 13 Feb 18).
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Appendix A – Validating the AR Taxonomies Message Posted on LinkedIn AR Discussion Group Name of Group: LinkedIn: Augmented Reality (AR), Virtual Reality (VR) & Virtual Worlds (VWs) Number of Subscribers to Group: 28,533 url to Group: https://www.linkedin.com/groups/37782 url to Posting: https://www.linkedin.com/groups/37782/37782-6379099227515080706 Posting Practitioner Participation Requested for an AR Research Project I am conducting an augmented reality (AR) research project at the Open University in the UK. I need to reach out to AR practitioners who are willing to review the initial research model and its early application. Are you able to assist? What is needed is constructive critique of the model proposed. This critique could be provided within this discussion or directly to myself as the researcher at
[email protected] This feedback would be used to improve the model and the research project as it is progressed. The project is exploring the strategic application of augmented reality (AR) and in particular mobile (device) augmented reality (MAR) to increase the utility of public spaces. Its aims to help managers and other professionals to identify the AR applications they should be developing. And will focus on AR for public spaces. This model proposes that four key areas of AR need considering when identifying and evaluating potential augmented reality opportunities: - Types of augmented reality devices - Types of augmented reality software - Types of augmentation - Generic use cases for augmented reality In a context like a public space, these areas would be explored to identify the opportunities. And they would also be used to qualify the relative attractiveness of the portfolio of augmented reality opportunities. For each of the four areas in the model, the types to be considered have been derived from literature and case studies and this is available in a document available at https://1drv.ms/b/s!Agluz2_t7Nkkgp4DBMVsc5bT56Dq_Q And a first application of the model to a public space to generate an AR strategy or roadmap using desk-research methods is described in a document available at https://1drv.ms/b/s!Agluz2_t7Nkkgp4E4vVY4XvrjW8t7Q Thanks and regards, Dr Alan Warr, London, UK. Page 60 of 67
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Message Posted on MeetUp’s UK Augmented Reality Discussion Group Name of Group: MeetUp: Augmented Reality Number of Members of Group: 5,348 url to Group: https://www.meetup.com/Augmenting-Reality/ url to Posting: https://www.meetup.com/AugmentingReality/discussions/5675388998516736/chat/ url of supporting Google group: https://groups.google.com/forum/#!topic/ar_research/fF0HsJmq744 Posting at Meetup AR research project at the Open University needs practitioner reviews of early models at https://groups.google.com/forum/#!forum/ar_research Supporting Posting of Information & Materials at Google Groups I am conducting an augmented reality (AR) research project at the Open University in the UK. I need to reach out to AR practitioners who are willing to review the initial research model and its early application. Are you able to assist? What is needed is constructive critique of the model proposed. This critique could be provided within this discussion or directly to me. This would be used to improve the model and the research project as it is progressed. The project is exploring the strategic application of augmented reality (AR) and in particular mobile (device) augmented reality (MAR) to increase the utility of public spaces. Its aims to help managers and other professionals to identify the AR applications they should be developing. And will focus on AR for public spaces. The motivation is the belief that there is value to be created from public spaces from current and future AR technologies. A model has been proposed that general managers and AR practitioners could use to explore the key aspects of AR that need to be considered for effective AR strategies to be identified and developed. This model proposes that four key areas of AR need considering when identifying and evaluating potential augmented reality opportunities: - Types of augmented reality devices - Types of augmented reality software - Types of augmentation - Generic use cases for augmented reality
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In a context like a public space these areas would be explored to identify the opportunities. And they would also be used to qualify the relative attractiveness of the portfolio of augmented reality opportunities. Using analysis of academic literature and practitioner articles and industry web sites each of these areas have been developed into a typology, or the different types that need to be considered. The broad types of AR devices to be considered within an AR strategy: D1 AR Screens Large screens positioned to display to the observer the scene augmented with added media content and potentially interactivity with the observer. D2 AR Heads Up Display (HUD) Projecting images and information onto a surface to augment the scene through the surface in the case of glass or augment a solid object. D3 Mobile AR (MAR) Phones & Tablets MAR employs a mobile phone or tablet using the camera and other sensors to display a scene live and augment it with media content and interactivity. D4 AR Headsets Augmented reality experiences through a virtual reality headset adapted so that an augmented scene is captured by a camera and augmented with rich media and displayed via the VR headset. D5 AR Glasses Page 62 of 67
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Glasses or headsets containing projector, camera and other sensors, with which the wearer can experience their view of a scene or object augmented with rich content and interactivity. D6 AR Contact Lenses 'Smart' contact lenses, which can project images straight into the users' eyes. Wearing the lenses would allow users to experience 'augmented' reality, with computer-generated images superimposed over the real world. The broad types of AR software to be considered within an AR strategy: S1 AR-Enabled Web Browsers Web browsers on phones and tablets developed to enable augmented reality experiences from AR applications running within a standard browser. Examples would include Google’s Article Web AR toolset. S2 Specialist AR Browsers Browsers developed specifically for augmented reality. Users download the AR browser and then can access AR applications developed for that browser. Examples would include Layar browser and ARAF browser. S3 AR Development Libraries Libraries for use within SDKs for the development of AR applications to run on devices or within browsers. Examples would include ARKit from Apple and ARCore from Google. S4 Vendor Proprietary Deployment Platforms General vendor platforms for the development, cloud hosting and deployment of AR applications. Examples would include Aurasma. S5 Device Specific Platforms Specialist devices need their own AR SDKs and development environments. Examples would include Microsoft’s HoloLens AR glasses. The broad types of AR augmentation to be considered within an AR strategy: A1 Marker-based AR Marker-based augmented reality apps focus on using the device software to identify patterns (like QR code) in the image obtained from the device camera. Then an overlay is cast on the device screen over the real-world image procured from the camera. A2 Marker-less AR Marker-less augmented reality app focus on recognising an object within the image from the device camera or the GPS location from the device sensors. Then an overlay is cast on the device screen and typically adjusted for the overlay in relation to the object or geo-position. A3 Projection-based AR This type of AR projects digital images on physical objects in the physical space. It can be interactive and project a digital keyboard on your desk, or a dialer on your hand. A4 Superimposition-based AR In superimposition-based AR, the augmented view is superimposed on the real view of any object. For example, this augmented view could be the internal view of the object. Page 63 of 67
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The generic AR use cases to be considered within an AR strategy: U1 Print and Object Augmentation Recognising a print or an object and adding information or images or media. U2 Advertising using AR Creatively employing AR as another media for advertising a product or service or place. U3 AR Signage AR signs overlaid onto reality to label or provide direction. U4 AR Overlays Overlaying measures, data, labels and lines onto scenes (e.g. sports overlays). U5 AR Tours for Museums, Cities, Sites & Events AR content and media overlaid during tours onto objects and scenes to enrich the experience. U6 AR 3D Models & Other Objects Overlaying 3D models onto real world views. U7 AR 3D Models for Purchasing Decisions Positioning 3D models of possible purchases in a room or on a person. U8 AR 3D Models for Product Design 3D models presented for viewing within a scene potentially for groups to view. U9 AR Pets Interactions with a dynamic 3D pet overlaid into a scene. U10 AR Overlays & Information for Maintenance Activities Specific AR media and models to guide maintenance tasks. U11 AR Surgical (and other complex tasks) Guidance Overlaying a 3D AR image across a body or physical object to guide surgery or other intervention. U12 AR Training Materials Learning materials presented using AR positioned within a scene or related to an object. U13 AR Holographic Trainer Overlaying a dynamic and potentially interactive avatar into the vision of the user within their environment to motivate and train. U14 AR Games Games utilising AR to display within a scene or based on geo-location. U15 Art Works Displayed using AR Art (incl. graffiti) and pictures overlaid on walls or other scenes. Page 64 of 67
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U16 AR Bogus Window Video screen installation overlaying AR content onto the scene behind the screen. U17 Screen Creation using AR Interactive screens of content, media & applications (incl. communications) overlaid on a scene or object. U18 Displaying Recalled Information using AR Recalling past interactions and other information dynamically potentially using objects in a scene and attaching information to these recognised objects. For any practitioner or researcher needing to look at the underlying references a working document is attached. And a first application of the model to a public space to generate an AR strategy or roadmap using desk-research methods is described in a document attached. Thank you. Dr Alan Warr, London, UK. Attachments (2)
Detailed Model & Construct Findings v01.pdf 1 MB View Download Proof of Concept Findings From Application of Model to a Public Space v01.pdf 778 KB View Download
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Appendix B – Project Plan No
Module Weeks
Description 1
2
3
4
5
6
November 1 Stage 0 – Define Issue 1
Project Design
2
Literature Review
3
Develop Models for AR in Public Spaces
4
AR Technical Training
5
Technology Review
6
TMA01
Stage 1 – Examination of the Current Situation 7
Analyses to Create Constructs
8
TMA02
9
Gain feedback from AR Practitioner Forums
10
Analyse feedback to improve constructs
11
Write Up Stage 1 Parts of Project Report
Stage 2 – Implementation of Change 12
Analyse Model to Identify POCs
13
Develop the POCs with dev. journal record
14
Analyse journal records to derive insights
15
Gain feedback from AR Practitioner Forums
16
Analyse feedback to improve evaluations
17
Write Up Stage 2 Parts of Project Report
Stage 3 – Evaluation of Implementation of Change
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8
15 22 29
7
8
9
10 11 12 13 14 15 16 17 18 19 20 21 22 23
December 6
13 20 27
January 3
10 17 24 31
February 6
13 20 27
March 7
14 21 28 4
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Module Weeks
Description 1
2
3
4
November 18
Generate Insights from Changes Made
19
Identify Gaps & Propose Further Research
20
Write Up Stage 3 Parts of Project Report
21
TMA 03
Stage 4 – Project Report 22
Write Conclusions & Recommendations
23
EMA Submission
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5
6
7
8
December
9
10 11 12 13 14 15 16 17 18 19 20 21 22 23 January
February
March
