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Record W3180335730

Preface:Augmenting Space: The role of immersive technologies in future cities

2021· article· en· W3180335730 on OpenAlexaboutno aff
Callum Parker, Soojeong Yoo, Waldemar Jenek, Young-ho Lee

Bibliographic record

VenueQUT ePrints (Queensland University of Technology) · 2021
Typearticle
Languageen
FieldEngineering
TopicArchitecture and Computational Design
Canadian institutionsnot available
Fundersnot available
KeywordsSpace (punctuation)Human–computer interactionComputer scienceMultimedia
DOInot available

Abstract

fetched live from OpenAlex

As digital technologies are advancing, contemporary interactions within cities are beginning to emerge. These interactions are commonly enabled through sensors to implicitly automate manual processes, such as turning on lights or walking up stairs. However, cities were not necessarily built from the ground up to be smart, rather they are gradually becoming smarter over time as technology becomes more extensible and embedded within them [1, 2]. These digital technologies create information layers that exist over the physical space, resulting in the space being filled with dynamically changing information, thus augmenting the space [3]. Augmented reality (AR) is one such technology that has recently seen a lot of development in this area and is only now starting to become more viable as hardware and computer vision algorithms have caught up. Films such as Minority Report (2002), Ghost in the Shell (2016), and Blade Runner (2017) have predicted AR’s future emergence in public spaces and cities [4, 5, 6]. These films featured AR advertising and information holograms in public spaces, enabled by smart contact lenses and holograms. Currently however, AR has been introduced to public spaces in a number of interesting ways. For instance, Pokemon GO became a global phenomenon which resulted in people physically playing the game in urban spaces and caused ripple effects on the physical spaces people were playing in [7, 8, 9]. Recent work has also shown that AR can have more engaging applications, in areas such as community engagement [10], personalised digital signage [11], in-situ visualisations [12], cultural heritage [13], and remote collaboration [14, 15]. On a consumer level, AR is most common on smartphones, particularly after the release of ARKit and ARCore - improving the functionality. AR smart glasses are also becoming more accessible and bring with them the possibility of more natural integration of virtual content into our daily lives. For instance, the Microsoft Hololens contains an array of sensor technologies giving it a sense of depth which allows it to place objects naturally in physical space. It has been successfully applied by planners to visualise underlying parts of the city in-situ [16, 17]. While AR is becoming more advanced, accessible, and has demonstrated potential, more knowledge is needed around the key benefits it will bring to cities and how it will change our interactions with the urban environment. Additionally, the use of such technologies raises the question of how the virtual and physical spaces can co-exist - creating an augmented space [3]. To address this gap in knowledge, this focus section builds on from our initial workshops [18] at Media Architecture Biennale (MAB) 2018 and IEEE International Symposium on Mixed and Augmented Reality (ISMAR) 2019 with the goal of bringing together researchers to explore the applications of AR and other immersive technologies, such as Virtual Reality (VR) and Mixed Reality (MR), within the context of enhancing architecture, public spaces and cities. In response, seven papers were selected for the focus section through a single-blinded peer-review process with at least two reviewers per paper. The papers showcase the applicability of various methods in a wide variety of different use cases, providing insights into current possibilities and Interaction Design and Architecture(s) Journal - IxD&A, N.48, 2021, pp. 5 - 7 5 challenges for digital technologies and the ways in which they can augment cities around the world. References 1. Tomitsch, M. (2018). Making cities smarter: designing interactive urban applications. Jovis. 2. Parker, C., Tomitsch, M., & Fredericks, J. (2021). Smart engagement for smart cities: Design patterns for digitally augmented, situated community engagement. In Shaping Smart for Better Cities (pp. 177-200). Academic Press. 3. Manovich, L. The poetics of augmented space. Visual Communication 5, 2 (2006), 219–240. 4. Arthur, C. Why minority report was spot on, 2010. 5. Jones, E. How soon could ghost in the shell’s fantasy technology become a reality?, 2017. 6. Ghahramani, A. What “blade runner 2049” gets right (and wrong) about ar, 2017. 7. Adlakha, D., Marquet, O., Hipp, J. A., and Tully, M. A. Pokemon go or pokemon gone: How can cities respond to trends in technology linking people and space? Cities & Health 1, 1 (2017), 89–94. 8. Colley, A., Thebault-Spieker, J., Lin, A. Y., Degraen, D., Fischman, B., Hakkila, J., Kuehl, K., Nisi, V., Nunes, N. J., Wenig, N., et al. The geography of pokemon go: beneficial and problematic effects on places and movement. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (2017), ACM, pp. 1179–1192. 9. Boulos, M. N. K., Lu, Z., Guerrero, P., Jennett, C., and Steed, A. From urban planning and emergency training to pokemon go: applications of virtual reality gis (vrgis) and augmented reality gis (argis) in personal, public and environmental health, 2017. 10. Fredericks, J., Hespanhol, L., Parker, C., Zhou, D., and Tomitsch, M. Blending pop-up urbanism and participatory technologies: Challenges and opportunities for inclusive city making. City, Culture and Society (2017). 11. Parker, C., Kay, J., Baldauf, M., and Tomitsch, M. Design implications for interacting with personalised public displays through mobile augmented reality. In Proceedings of the 5th ACM International Symposium on Pervasive Displays (2016), ACM, pp. 52–58. 12. Lee, G. A., Du¨nser, A., Kim, S., and Billinghurst, M. Cityviewar: A mobile outdoor ar application for city visualization. In Mixed and Augmented Reality (ISMAR-AMH), 2012 IEEE International Symposium on (2012), IEEE, pp. 57–64. 13. Park, H., Kim, E., Kim, H., Shin, J. E., Kim, J., Kim, K., & Woo, W. (2018, July). K-culture time machine: A mobile ar experience platform for korean cultural heritage sites. In International Conference on Human Interface and the Management of Information (pp. 167- 180). Springer, Cham. 14. Lee, Y., Masai, K., Kunze, K., Sugimoto, M., and Billinghurst, M. A remote collaboration system with empathy glasses. In 2016 IEEE International Symposium on Mixed and Augmented Reality (ISMAR-Adjunct) (Sep. 2016), pp. 342–343 Interaction Design and Architecture(s) Journal - IxD&A, N.48, 2021, pp. 5 - 7 6 15. Jenek, W. Architecture with immersive technologies: Next generation architects and clients. 16. Hockett, P., and Ingleby, T. Augmented reality with hololens: Experiential architectures embedded in the real world. arXiv preprint arXiv:1610.04281 (2016). 17. Zhang, L., Chen, S., Dong, H., and El Saddik, A. Visualizing toronto city data with hololens: Using augmented reality for a city model. IEEE Consumer Electronics Magazine 7, 3 (2018), 73–80. 18. Parker, C., Jenek, W., Yoo, S., and Lee, Y. Augmenting cities and architecture with immersive technologies. In Proceedings of the 4th Media Architecture Biennale Conference (2018), ACM, pp. 174–177.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.423
Threshold uncertainty score0.349

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.003
GPT teacher head0.158
Teacher spread0.156 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Published2021
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