From Controls on the Steering Wheel to Controls on the Finger

Gheran, Bogdan-Florin; Vatavu, Radu-Daniel

doi:10.1145/3393914.3395851

Cited by 18 publications

(2 citation statements)

References 14 publications

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“…Finger augmentation devices (FADs) are finger-worn electronic tools conceived to provide supplemental capabilities through an additional augmentation other than their form [1]. FADs can have different form factors, spanning from proximalphalanx rings [2] to nail-pads [3], [4], and several possible applications, like driving vehicles [5], [6] or controlling aerial drones [7]. The most ambitious goal of FADs is the achievement of a sensorial ultrability, namely providing the user with an artificial sensation to either restore a lost or degraded natural ability or even to add a new sense, going beyond the natural physical feelings of humans [8].…”

Section: Introductionmentioning

confidence: 99%

Sensing Performance of Multi-Channel RFID-Based Finger Augmentation Devices for Tactile Internet

Naccarata

Bianco

Marrocco

2022

IEEE J. Radio Freq. Identif.

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Radiofrequency finger augmentation devices (R-FADs) are a recently introduced class of epidermal radiofrequency identification (RFID) sensor-tags attached to the fingers, communicating with a body-worn reader. These devices are promising candidates to enable Tactile Internet (TI) applications in the short term. R-FAD based on auto-tuning RFID microchips can be used as dielectric probes for the material of touched objects. However, due to the nearly unpredictable intrinsic variability of finger-object interaction, a single sensorized finger (single-channel device) is not enough to guarantee reliable data sampling. These limitations can be overcome by exploiting a multi-channel R-FAD sensorizing multiple fingers of the hand. In this paper, the dielectric-sensing performance of a multi-channel R-FAD, composed of sensors encapsulated into soft elastomers, is numerically and experimentally characterized, involving a set of volunteers. The inter-sensor coupling is negligible, thus enabling simultaneous independent dielectric measurements. The multi-sensor configuration allows for 100% reliability of the onhand communication link for touched objects in a wide range of permittivity. Experiments moreover demonstrate that multichannel measurements can halve the measurement uncertainty of the single-channel case. The achievable precision is suitable to discriminate among low-, medium-, and high-permittivity materials.

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Section: Introductionmentioning

confidence: 99%

Sensing Performance of Multi-Channel RFID-Based Finger Augmentation Devices for Tactile Internet

Naccarata

Bianco

Marrocco

2022

IEEE J. Radio Freq. Identif.

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“…The in-vehicle space is populated with smart devices such as wearables and insideables, that are smart sensors worn by people or implanted inside the human body [4]. These devices serve as natural interfaces for communication with the in-vehicle systems (IVIS) [5].…”

Section: Introductionmentioning

confidence: 99%

Ubiquitous Computing: Driving in the Intelligent Environment

et al. 2021

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In the context of hyper-connected cars and a growing heterogeneous digital ecosystem, we wish to make the most of the data available from the various sensors, devices and services that compose the ecosystem, in order to propose a proof of concept in-vehicle system that enhances the driving experience. We focus on improving the driving experience along three main directions, namely: (1) driving and trip planning, (2) health and well-being and (3) social and online activities. We approached the in-vehicle space as a smart interface to the intelligent driving environment. The digital data-producers in the ecosystem of the connected car are sources of raw data of various categories, such as data from the outside world, gathered from sensors or online services, data from the car itself and data from the driver gathered with various mobile and wearable devices, by means of observing his state and by means of his social media and online activity. Data is later processed into three information categories—driving, wellness, and social—and used to provide multi-modal interaction, namely visual, audio and gesture. The system is implemented to act in response to the trafficked information on different levels of autonomy, either in a reactive manner, by simple monitoring, or in a proactive manner. The system is designed to provide an in-vehicle system that assists the driver with planning the travel (Drive panel), by providing a comfortable environment for the driver while monitoring him (Wellness panel), and by adaptively managing interactions with their phone and the digital environment (Social panel). Heuristic evaluation of the system is performed, with respect to guidelines formulated for automated vehicles, and a SWOT analysis of the system is also presented in the paper.

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