Evidence map›Paper›PMID 39700470›Full record

ArticlePloS one2024

Enhancing unity-based AR with optimal lossless compression for digital twin assets.

Mohammed Hlayel, Hairulnizam Mahdin, Mohammad Hayajneh, Saleh H AlDaajeh, Siti Salwani Yaacob, Mazidah Mat Rejab

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Mohammed HlayelFatima College of Health Sciences, Institute of Applied Technology, Al-Ain, Abu Dhabi, UAE.ORCID 0000-0002-3410-3679
Hairulnizam MahdinFaculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Johor, Malaysia.
Mohammad HayajnehCollege of Information Technology, United Arab Emirates University, Al-Ain, Abu Dhabi, UAE.
Saleh H AlDaajehDepartment of Information Systems & Security, College of Information Technology, United Arab Emirates University, Al-Ain, Abu Dhabi, UAE.
Siti Salwani YaacobFaculty of Computing, Universiti Malaysia Pahang Al-Sultan Abdullah, Pekan, Pahang, Malaysia.
Mazidah Mat RejabFaculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Johor, Malaysia.ORCID 0000-0003-3922-5795

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The rapid development of Digital Twin (DT) technology has underlined challenges in resource-constrained mobile devices, especially in the application of extended realities (XR), which includes Augmented Reality (AR) and Virtual Reality (VR). These challenges lead to computational inefficiencies that negatively impact user experience when dealing with sizeable 3D model assets. This article applies multiple lossless compression algorithms to improve the efficiency of digital twin asset delivery in Unity's AssetBundle and Addressable asset management frameworks. In this study, an optimal model will be obtained that reduces both bundle size and time required in visualization, simultaneously reducing CPU and RAM usage on mobile devices. This study has assessed compression methods, such as LZ4, LZMA, Brotli, Fast LZ, and 7-Zip, among others, for their influence on AR performance. This study also creates mathematical models for predicting resource utilization, like RAM and CPU time, required by AR mobile applications. Experimental results show a detailed comparison among these compression algorithms, which can give insights and help choose the best method according to the compression ratio, decompression speed, and resource usage. It finally leads to more efficient implementations of AR digital twins on resource-constrained mobile platforms with greater flexibility in development and a better end-user experience. Our results show that LZ4 and Fast LZ perform best in speed and resource efficiency, especially with RAM caching. At the same time, 7-Zip/LZMA achieves the highest compression ratios at the cost of slower loading. Brotli emerged as a strong option for web-based AR/VR content, striking a balance between compression efficiency and decompression speed, outperforming Gzip in WebGL contexts. The Addressable Asset system with LZ4 offers the most efficient balance for real-time AR applications. This study will deliver practical guidance on optimal compression method selection to improve user experience and scalability for AR digital twin implementations.

Indexed as

AlgorithmsData CompressionHumansMobile ApplicationsModels, TheoreticalVirtual Reality

Identifiers

PMID39700470
PMCPMC11658801

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.