A Comparative Review on Image Analysis with Machine Learning for Extended Reality (XR) Applications

Vijayakumar, P.; Dilliraj, E.

doi:10.1007/978-981-19-2541-2_24

Cited by 2 publications

(1 citation statement)

References 33 publications

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“…The Snapchat app's embellishments, which can put hats or spectacles on human heads, the Pokemon GO show's overlay of virtual creatures over actual life, and other applications are a few instances of augmented reality. With the head-mounted screen, also known as a VR headset, consumers of VR will be wholly submerged in a digital environment that is a replica and is created to enjoy the view of the artificial world from all angles [143]. XR offers numerous real-world and practical implications in various industries where clients can save time and money traveling, including entertaining, shopping, healthcare, property investment, advertising, working remotely, and disaster risk management.…”

Section: E Xr Applicationsmentioning

confidence: 99%

Explainable AI for Industry 5.0: Vision, Architecture, and Potential Directions

Trivedi,

Bhattacharya,

Prasad

et al. 2024

IEEE Open J. Ind. Applicat.

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The Industrial Revolution has shifted towards Industry 5.0, reinventing the Industry 4.0 operational process by introducing human elements into critical decision processes. Industry 5.0 would present massive customization via transformative technologies like cyber-physical systems, artificial intelligence (AI), and big-data analytics. In Industry 5.0, the AI models must be transparent, valid, and interpretable. AI models employ machine learning (ML) and deep learning (DL) mechanisms to make the industrial process autonomous, reduce downtime, and improve operational and maintenance costs. However, the models require explainability in the learning process. Thus explainable AI (EXAI) adds interpretability and improves the diagnosis of critical industrial processes, which augments the machine-to-human (M2H) explanations and vice-versa. Recent surveys of EXAI in industrial applications are mostly oriented towards EXAI models, the underlying assumptions. Still, fewer studies are conducted towards a holistic integration of EXAI with human-centric processes that drives the Industry 5.0 applicative verticals. Thus, to address the gap, we propose a first-of-its-kind survey that systematically untangles EXAI integration and its potential in Industry 5.0 applications. First, we present the background of EXAI in Industry 5.0 and cyber-physical systems (CPS) and a reference EXAI-based Industry 5.0 architecture with insights into Large Language Models (LLMs). Then, based on the research questions, a solution taxonomy of EXAI in Industry 5.0 is presented, which is ably supported by applicative use cases (cloud, digital twins, smart grids, augmented reality, and unmanned aerial vehicles). Finally, a case study of EXAI in manufacturing cost assessment is discussed, followed by open issues and future directions. The survey is designed to extend novel prototypes and designs to realize EXAI-based in real-time Industry 5.0 applications.

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Section: E Xr Applicationsmentioning

confidence: 99%

Explainable AI for Industry 5.0: Vision, Architecture, and Potential Directions

Trivedi,

Bhattacharya,

Prasad

et al. 2024

IEEE Open J. Ind. Applicat.

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Mapping the Emergent Trends in Industrial Augmented Reality

et al. 2023

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Augmented reality (AR) is a rapidly developing technology with the potential to revolutionize various sectors of industry by integrating digital information with the real world. This paper presents an overview of the emergent trends in industrial augmented reality (IAR) over the past five years. The study utilizes a comprehensive literature review analysis of industrial studies (searched on two scientific databases: Scopus and Clarivate Web of Science) to map the evolution of IAR trends from 2018 to 2022. The results revealed ten trending topics of AR application: Industry 4.0, artificial intelligence, smart manufacturing, industrial robots, digital twin, assembly, Internet of Things, visualization, maintenance, and training. Each topic is discussed in detail, providing insight into existing applications and research trends for each application field.

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A Comparative Review on Image Analysis with Machine Learning for Extended Reality (XR) Applications

Cited by 2 publications

References 33 publications

Explainable AI for Industry 5.0: Vision, Architecture, and Potential Directions

Explainable AI for Industry 5.0: Vision, Architecture, and Potential Directions

Mapping the Emergent Trends in Industrial Augmented Reality

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