Secure Collaborative Augmented Reality Framework for Biomedical Informatics

Djenouri, Youcef; Belhadi, Asma; Srivastava, Gautam; Lin, Jerry Chun‐Wei

doi:10.1109/jbhi.2021.3139575

Cited by 12 publications

(4 citation statements)

References 40 publications

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“…Runtime efficiency and visualization are still critical issues when managing biomedical healthcare data and detecting diseases in real time. To improve the performance of NUMERATE, creating hybrid systems that combine augmented reality, evolutionary, and deep learning approaches could be a promising avenue (Djenouri, Belhadi, et al, 2021; Djenouri & Comuzzi, 2017; Khamparia & Singh, 2019; Liu et al, 2022). Diseases were effectively detected by the recommended methods.…”

Section: Discussion and Future Directionsmentioning

confidence: 99%

Artificial intelligence of medical things for disease detection using ensemble deep learning and attention mechanism

et al. 2022

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In this paper, we present a novel paradigm for disease detection. We build an artificial intelligence based system where various biomedical data are retrieved from distributed and homogeneous sensors. We use different deep learning architectures (VGG16, RESNET, and DenseNet) with ensemble learning and attention mechanisms to study the interactions between different biomedical data to detect and diagnose diseases. We conduct extensive testing on biomedical data. The results show the benefits of using deep learning technologies in the field of artificial intelligence of medical things to diagnose diseases in the healthcare decision‐making process. For example, the disease detection rate using the proposed methodology achieves 92%, which is greatly improved compared to the higher‐level disease detection models.

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Section: Discussion and Future Directionsmentioning

confidence: 99%

Artificial intelligence of medical things for disease detection using ensemble deep learning and attention mechanism

et al. 2022

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“…There has been a lack of trust and security concerns during this remote collaboration. There are more chances of intrusion and vulnerabilities that can be possibly exploited [ 331 , 339 , 340 ]. One such collaboration is from the tourism sector, which has boosted the economy, especially in the pandemic era when physical interactors were not allowed [ 341 ].…”

Section: Discussionmentioning

confidence: 99%

In-Depth Review of Augmented Reality: Tracking Technologies, Development Tools, AR Displays, Collaborative AR, and Security Concerns

Syed

Siddiqui

Abdullah

et al. 2022

Sensors

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Augmented reality (AR) has gained enormous popularity and acceptance in the past few years. AR is indeed a combination of different immersive experiences and solutions that serve as integrated components to assemble and accelerate the augmented reality phenomena as a workable and marvelous adaptive solution for many realms. These solutions of AR include tracking as a means for keeping track of the point of reference to make virtual objects visible in a real scene. Similarly, display technologies combine the virtual and real world with the user’s eye. Authoring tools provide platforms to develop AR applications by providing access to low-level libraries. The libraries can thereafter interact with the hardware of tracking sensors, cameras, and other technologies. In addition to this, advances in distributed computing and collaborative augmented reality also need stable solutions. The various participants can collaborate in an AR setting. The authors of this research have explored many solutions in this regard and present a comprehensive review to aid in doing research and improving different business transformations. However, during the course of this study, we identified that there is a lack of security solutions in various areas of collaborative AR (CAR), specifically in the area of distributed trust management in CAR. This research study also proposed a trusted CAR architecture with a use-case of tourism that can be used as a model for researchers with an interest in making secure AR-based remote communication sessions.

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“…Besides, augmented reality can provide a visual experience for biomedical health informatics applications. In [286], the authors propose a blockchain-based AR framework for collecting, processing, and managing data in health applications. Specifically, they build a system for managing medical models based on Ethereum.…”

Section: Blockchain In Edge Resource Managementmentioning

confidence: 99%

A Full Dive into Realizing the Edge-enabled Metaverse: Visions, Enabling Technologies,and Challenges

Xu¹,

Ng²,

Lim³

et al. 2022

Preprint

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Dubbed "the successor to the mobile Internet", the concept of the Metaverse has grown in popularity. While there exist lite versions of the Metaverse today, they are still far from realizing the full vision of an immersive, embodied, and interoperable Metaverse. Without addressing the issues of implementation from the communication and networking, as well as computation perspectives, the Metaverse is difficult to succeed the Internet, especially in terms of its accessibility to billions of users today. In this survey, we focus on the edge-enabled Metaverse to realize its ultimate vision. We first provide readers with a succinct tutorial of the Metaverse, an introduction to the architecture, as well as current developments. To enable the ubiquitous, seamless, and embodied access to the Metaverse, we discuss the communication and networking challenges and survey cutting-edge solutions and concepts that leverage next-generation communication systems for users to be telepresent and teleoperate in the Metaverse. Moreover, given the high computation costs required, e.g., to render immersive 3D worlds and run data hungry artificial intelligence (AI) driven applications, we discuss the computation challenges and cloud-edge-end computation framework driven solutions to realize the Metaverse on resource-constrained edge devices. Next, we explore how blockchain technologies can aid in the interoperable development of the Metaverse, not just in terms of empowering the economic circulation of virtual usergenerated contents, but also to manage physical edge resources in a decentralized, transparent, and tamper-proof manner. Finally, we discuss the future research directions towards realizing the true vision of the edge-enabled Metaverse.

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Secure Collaborative Augmented Reality Framework for Biomedical Informatics

Cited by 12 publications

References 40 publications

Artificial intelligence of medical things for disease detection using ensemble deep learning and attention mechanism

Artificial intelligence of medical things for disease detection using ensemble deep learning and attention mechanism

In-Depth Review of Augmented Reality: Tracking Technologies, Development Tools, AR Displays, Collaborative AR, and Security Concerns

A Full Dive into Realizing the Edge-enabled Metaverse: Visions, Enabling Technologies,and Challenges

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