Adaptive Interface for Smart Home: A New Design Approach

Gullà, Francesca; Ceccacci, Silvia; Menghi, Roberto; Cavalieri, Lorenzo; Germani, Michele

doi:10.1007/978-3-319-54283-6_8

Cited by 7 publications

(5 citation statements)

References 8 publications

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“…It occurs through a constant communication between Core and DBMS, which also allows increasing the network knowledge and managing the adaptation. As a consequence, the Interface content and graphics elements are subject to change [54].…”

Section: The System Adaptive Frameworkmentioning

confidence: 99%

Prototyping adaptive systems in smart environments using virtual reality

Gullà

Menghi

Papetti

et al. 2018

Int J Interact Des Manuf

Self Cite

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Smart environment is a key challenge for current ICT research: it is one of the solutions that can enhance people's quality of life and enable users with impairment to live independently. Over the years, scientific research has proposed several solutions to help and improve the capabilities of its occupants, but they are often developed for a specific context (e.g. particular disease or impairment). These systems do not adapt to the real needs of users with different profiles, and neglect that the user's requirements may evolve over time. This research work aims to develop a new adaptive smart system able to support users (with and without disabilities) in performing daily tasks by recognizing their preferences and actions and adapting the system feedback consequently. With the aim to develop an easy, efficient and usable adaptive smart system, the final users have been involved in the whole design and development process. The system was validated through a virtual reality system allowing the user interaction evaluation and helping the usability improvement. Keywords Smart environment • Adaptive and adaptable user interface • Virtual reality system • Bayesian network • ICT • User-centered design B Francesca Gullà

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Section: The System Adaptive Frameworkmentioning

confidence: 99%

Prototyping adaptive systems in smart environments using virtual reality

Gullà

Menghi

Papetti

et al. 2018

Int J Interact Des Manuf

Self Cite

View full text Add to dashboard Cite

show abstract

“…The multimodal nature of our system (speech, text, and graphics) is aligned with several works [ 34 , 36 , 37 , 38 , 39 , 40 , 43 , 44 ]. Some authors relied on user and/or context awareness for interaction adaptation [ 45 , 46 , 47 , 48 , 49 ], but this capability was not integrated into a home assistant. In contrast with these works, we used both multimodal and adaptive interaction to improve the accessibility of smart homes.…”

Section: Discussionmentioning

confidence: 99%

“…Regarding smart homes, adaptation to the user/context has been used for improving interaction with the home [ 45 , 46 , 47 , 48 , 49 ]. Some contributions relied mainly on a single modality (voice, gesture) and context only [ 45 , 48 ].…”

Section: Background and Related Workmentioning

confidence: 99%

“…Both user and context awareness (based on user modeling, user-defined home rules, and context data obtained from smart city sensors) was used to personalize the content presented to the user and automate home control [ 49 ]. Moreover, a design approach and system were proposed with the aim of adapting the graphic features of the interface and the presented content [ 46 ].…”

Section: Background and Related Workmentioning

confidence: 99%

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An Accessible Smart Home Based on Integrated Multimodal Interaction

Rocha

Ketsmur

Almeida

et al. 2021

Sensors

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Our homes are becoming increasingly sensorized and smarter. However, they are also becoming increasingly complex, making accessing them and their advantages difficult. Assistants have the potential for improving the accessibility of smart homes, by providing everyone with an integrated, natural, and multimodal way of interacting with the home’s ecosystem. To demonstrate this potential and contribute to more environmentally friendly homes, in the scope of the project Smart Green Homes, a home assistant highly integrated with an ICT (Information and communications technology) home infrastructure was developed, deployed in a demonstrator, and evaluated by seventy users. The users’ global impression of our home assistant is in general positive, with 61% of the participants rating it as good or excellent overall and 51% being likely or very likely to recommend it to others. Moreover, most think that the assistant enhances interaction with the smart home’s multiple devices and is easy to use by everyone. These results show that a home assistant providing an integrated view of a smart home, through natural, multimodal, and adaptive interaction, is a suitable solution for enhancing the accessibility of smart homes and thus contributing to a better living ambient for all of their inhabitants.

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“…ML can be leveraged by UI/UX designers to power applications more common in our current lives, such as personalized interfaces [18,35,41] and conversational agents [16]. To employ ML tactics in ways currently not seen in commercial design, designers of these systems need support in understanding ML so they can use ML as a design material [12,53,54,57].…”

Section: Related Workmentioning

confidence: 99%

A Game-Based Approach for Helping Designers Learn Machine Learning Concepts

Myers¹,

Xie²,

Zhu³

2020

Preprint

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Machine Learning (ML) is becoming more prevalent in the systems we use daily. Yet designers of these systems are under-equipped to design with these technologies. Recently, interactive visualizations have been used to present ML concepts to non-experts. However, little research exists evaluating how designers build an understanding of ML in these environments or how to instead design interfaces that guide their learning. In a user study (n=21), we observe how designers interact with our interactive visualizer, QUBE, focusing on visualizing Q-Learning through a game metaphor. We analyze how designers approach interactive visualizations and game metaphors to form an understanding of ML concepts and the challenges they face along the way. We found the interactive visualization significantly improved participants' high-level understanding of ML concepts. However, it did not support their ability to design with these concepts. We present themes on the challenges our participants faced when learning an ML concept and their self-guided learning behaviors. Our findings suggest design recommendations for supporting an understanding of ML concepts through guided learning interfaces and game metaphors.

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Adaptive Interface for Smart Home: A New Design Approach

Cited by 7 publications

References 8 publications

Prototyping adaptive systems in smart environments using virtual reality

Prototyping adaptive systems in smart environments using virtual reality

An Accessible Smart Home Based on Integrated Multimodal Interaction

A Game-Based Approach for Helping Designers Learn Machine Learning Concepts

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