Ubiquitous Computing: Driving in the Intelligent Environment

Abstract

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.

Enhancing the Prediction of User Satisfaction with Metaverse Service Through Machine Learning

“…However, most studies adopt few sample questionnaires to obtain user satisfaction, using conventional methods such as Structural Equation Model (SEM) or Technology Acceptance Model (TAM). To overcome the limitation of conventional methodologies, resources such as big-size online data (e.g., online reviews) from ubiquitous computing are getting more pervasive [15]. Big data are collected and analyzed in various fields [16,17].…”

Efficient Cervical Cell Lesion Recognition Method Based on Dual Path Network

“…In recent years, ubiquitous computing and artificial intelligence technology have developed rapidly and have been widely used in the medical field [1], the automobile field [2], and the UAV communication field [3]. In the medical field, with the development of Wise Information Technology of Med (WITMED), people can obtain digital medical services anytime and anywhere in an environment full of computing and communication capabilities.…”