Human Factors in Ambient Intelligence Environments

Stephanidis, Constantine; Antona, Margherita; Ntoa, Stavroula

doi:10.1002/9781119636113.ch41

Cited by 11 publications

(6 citation statements)

References 135 publications

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“…Collaborative efforts that involve human factors specialists ensure that robotic systems are designed with the end-users-human workers-in mind. Interdisciplinary collaboration in human-centered design contributes to the creation of user-friendly interfaces, intuitive control systems, and ergonomic work environments (Stephanidis et al, 2021). By prioritizing the needs and preferences of human operators, collaborative teams can enhance the acceptance and effectiveness of AI-driven robotic systems in manufacturing.…”

Section: Future Outlookmentioning

confidence: 99%

AI-enhanced manufacturing robotics: A review of applications and trends

Riliwan Adekola Adebayo,

Nwankwo Constance Obiuto,

Oladiran Kayode Olajiga

et al. 2023

World J. Adv. Res. Rev.

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This review explores the transformative impact of artificial intelligence (AI) on manufacturing robotics, elucidating a comprehensive overview of applications and emerging trends within the realm of smart manufacturing. As industries increasingly embrace Industry 4.0 principles, the integration of AI into manufacturing robots has become pivotal for enhancing efficiency, flexibility, and adaptability. The synergy of AI and manufacturing robotics has resulted in a plethora of applications that redefine traditional manufacturing processes. Machine learning algorithms empower robots with predictive maintenance capabilities, allowing them to anticipate and address equipment issues before they escalate. Computer vision technologies enable robots to perceive and interpret visual information, enhancing their ability to handle complex tasks such as quality inspection and object recognition. AI-driven collaborative robots, or cobots, seamlessly interact with human workers, optimizing workflow and productivity. Furthermore, AI-enhanced robotics play a crucial role in autonomous material handling, logistics, and supply chain management, streamlining operations in diverse manufacturing environments. Recent trends in AI-enhanced manufacturing robotics underscore the dynamic evolution of this field. Edge computing is gaining prominence, allowing robots to process data locally and respond in real-time, minimizing latency and enhancing overall system performance. The advent of reinforcement learning has empowered robots to adapt and optimize their actions based on dynamic manufacturing environments, leading to improved flexibility and adaptability. The integration of digital twins facilitates virtual simulations, enabling manufacturers to model and analyze the behavior of robotic systems before physical implementation. Explainable AI is emerging as a critical trend, ensuring transparency and interpretability in complex decision-making processes of AI-driven robotic systems. The integration of AI into manufacturing robotics represents a paradigm shift, revolutionizing traditional manufacturing practices. This review highlights the myriad applications and trends shaping the landscape of AI-enhanced manufacturing robotics. As industries continue to invest in smart manufacturing technologies, the collaborative synergy of AI and robotics is poised to drive unprecedented advancements in efficiency, quality, and agility within the manufacturing sector.

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Section: Future Outlookmentioning

confidence: 99%

AI-enhanced manufacturing robotics: A review of applications and trends

Riliwan Adekola Adebayo,

Nwankwo Constance Obiuto,

Oladiran Kayode Olajiga

et al. 2023

World J. Adv. Res. Rev.

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“…To alleviate difficulties entailed in creating XR environments accessible to all, a universal access approach needs to be adopted, to design systems that take diversity into account and satisfy the variety of implied requirements in a proactive approach [1]. To this end, this paper introduces an ongoing XR accessibility framework designed to provide developers with a cohesive approach to incorporating diverse accessibility features into their XR applications.…”

Section: Introductionmentioning

confidence: 99%

A Framework for Accessibility in XR Environments

Valakou,

Margetis,

Ntoa

et al. 2023

Communications in Computer and Information Science

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Digital accessibility is vital for ensuring equal access and usability for individuals with disabilities. However, addressing the unique challenges faced by individuals with disabilities in XR environments remains a complex task. This paper presents an ongoing accessibility framework designed to empower developers in creating inclusive XR applications. The framework aims to provide a comprehensive solution, addressing the needs of individuals with disabilities, by incorporating various accessibility features, based on XR accessibility guidelines, best practices, and state of the art approaches. The current version of the framework has focused on the accessibility of XR environments for blind or partially sighted users, enhancing their interaction with text, images, videos, and 3D artefacts. The proposed work lays the foundation for Extended Reality (XR) developers to easily encompass accessible assets. In this respect, it offers customizable text settings, alternative visual content text, and multiple user interaction control mechanisms. Furthermore, it includes features such as edge enhancement, interactive element descriptions with dynamic widgets, scanning for navigation, and foreground positioning of active objects. The framework also supports scene adaptations upon user demand to cater to specific visual needs.

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“…Motivated by similar broad concerns, the Human-Computer Interaction (HCI) community has ofered notable and numerous contributions to interface AI with various domains of social science, mostly as attempts to make compatible automation and efciency of AI-enabled technologies with human priorities, needs, emotions, and passions (e.g. [1,32,39,51,64,70,74]). The resulting Human-Centered AI campaigns have recognized that in the current forces that shape the evolving world of AI, it is the market-led technology sector that dominantly determines what AI is, how it should be invested in, and in what shape and function will reach the societies [57].…”

Section: Introductionmentioning

confidence: 99%

AI beyond Deus ex Machina – Reimagining Intelligence in Future Cities with Urban Experts

Mlynář

Bahrami

Ourednik

et al. 2022

CHI Conference on Human Factors in Computing Systems

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The current mechanisms that drive the development of AI technologies are widely criticized for being tech-oriented and market-led instead of stemming from societal challenges. In Human-Centered AI discourses, and more broadly in Human-Computer Interaction research, initiatives have been proposed to engage experts from various domains of social science in determining how AI should reach our societies, predominantly through informing the adoption policies. Our contribution, however, seeks a more essential role for social sciences, namely to introduce discursive standpoints around what we need AI to be. With a focus on the domain of urbanism, the specifc goal has been to elicit -from interviews with 16 urban experts -the imaginaries of how AI can and should impact future cities. Drawing on the social science literature, we present how the notion of "imaginary" has essentially framed this research and how it could reveal an alternative vision of non-human intelligent actors in future cities. CCS CONCEPTS• Human-centered computing → Empirical studies in HCI; HCI theory, concepts and models; • Computing methodologies → Philosophical/theoretical foundations of artifcial intelligence.

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Human Factors in Ambient Intelligence Environments

Cited by 11 publications

References 135 publications

AI-enhanced manufacturing robotics: A review of applications and trends

AI-enhanced manufacturing robotics: A review of applications and trends

A Framework for Accessibility in XR Environments

AI beyond Deus ex Machina – Reimagining Intelligence in Future Cities with Urban Experts

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