Internet of Tangible Things (IoTT): Challenges and Opportunities for Tangible Interaction with IoT
August 08, 2017 Β· Declared Dead Β· π Informatics
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Leonardo Angelini, Nadine Couture, Omar Abou Khaled, Elena Mugellini
arXiv ID
1708.02664
Category
cs.HC: Human-Computer Interaction
Citations
53
Venue
Informatics
Last Checked
3 months ago
Abstract
In the Internet of Things era, an increasing number of household devices and everyday objects are able to send to and retrieve information from the Internet, offering innovative services to the user. However, most of these devices provide only smartphone or web interfaces to control the IoT object properties and functions. As a result, generally, the interaction is disconnected from the physical world, decreasing the user experience and increasing the risk of isolating the user in digital bubbles. We argue that tangible interaction can counteract this trend and this paper discusses the potential benefits and the still open challenges of tangible interaction applied to the Internet of Things. To underline this need, we introduce the term Internet of Tangible Things. In the article, after an analysis of current open challenges for Human-Computer Interaction in IoT, we summarize current trends in tangible interaction and extrapolate eight tangible interaction properties that could be exploited for designing novel interactions with IoT objects. Through a systematic literature review of tangible interaction applied to IoT, we show what has been already explored in the systems that pioneered the field and the future explorations that still have to be conducted.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Human-Computer Interaction
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Improving fairness in machine learning systems: What do industry practitioners need?
R.I.P.
π»
Ghosted
Identifying Stable Patterns over Time for Emotion Recognition from EEG
R.I.P.
π»
Ghosted
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
R.I.P.
π»
Ghosted
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
R.I.P.
π»
Ghosted
Educational data mining and learning analytics: An updated survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted