Context-Awareness and Mobile HCI: Implications, Challenges and Opportunities

Qin, Xiangang; Tan, Chee Wee; Clemmensen, Torkil

doi:10.1007/978-3-319-58481-2_10

Cited by 5 publications

(7 citation statements)

References 40 publications

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“…In other words, context is any piece of information used to describe the situation of an entity that can be a place, a person, or an object. The aspects of context comprise, but are not restricted to, location, weather, identity, activity, and time [12].…”

Section: Related Workmentioning

confidence: 99%

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Ontological Model to Predict user Mobility

Zaguia¹,

Alroobaea²

2019

ijacsa

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With the remarkable technological evolution of mobile devices, the use of computing resources has become possible at any time and independent of the geographical position of the user. This phenomenon has various names such as omnipresent diffuse computing, pervasive computing, or ubiquitous systems. This new form of computing allows users to have access to shared and ubiquitous services focused on their needs, and it is based on context prediction, especially the prediction of the user's location. This paper aims to present a new approach for predicting a user's next probable location, by presenting an ontological model which is based on the pattern technique. This is carried out by using an ontological model that comprises different user behaviors and presents details about the environment, where the user is located. The results after tested on real data show that the presented ontological model was able to achieve 85% future location-prediction accuracy (in the case of no similar patterns). Future work will focus on the integration of the Bayesian network to improve the results. This approach will be implemented in smart homes or smart cities to reduce energy consumption.

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Section: Related Workmentioning

confidence: 99%

“…history location (C2_PC9_PC4_PC6_P) and contexts of time (12)(13)(14)(15)(16)(17)(18)(19)(20), day (Sunday), and weather (good weather).…”

Section: Ontology Creationmentioning

confidence: 99%

Ontological Model to Predict user Mobility

Zaguia¹,

Alroobaea²

2019

ijacsa

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“…The proposal is a HiTL system presenting explicit information about the new or updated context to the user, who then defines their health status and makes a decision considering this context [28]. Thus, the system will ask the user to assess their health status when they wake up, before going to sleep and whenever the user feels like in order to create new cases for the databases of previous cases, and when the CBR detects a potentially threatening context in order to revise this prediction.…”

Section: Cbr For Personalised Asthma Managementmentioning

confidence: 99%

“…It is a mobile application using the ACQ to complete and store context-related data in form of cases to be used by the CBR component of the system. The design of the mobile application as a system showing explicit information [28] is described and then evaluated from a usability perspective.…”

Section: Introductionmentioning

confidence: 99%

A Human-in-The-Loop Context-Aware System Allowing the Application of Case-Based Reasoning for Asthma Management

Quinde

Khan

Augusto

et al. 2019

Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management. Healthcare Applications

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“…Consequently, we collected data on (a) 'Turning Screen On' events to examine the Human Active-Computer Passive mode; (b) 'Light change' and 'Auto-brightness' events to explore the Computer Active-Human Passive mode, as well as; (c) conducted surveys to ascertain users' subjective assessment of select context-aware services. Building on our earlier work [30] [31], where we put forth a preliminary framework to explicate the UX of mobile context-aware applications from users' perspective based on focus group discussions, this study embraces a mixed-methods approach to unravel UX considerations related to such services [32]. In this way, findings from our study contribute to an in-depth appreciation of how UX is shaped by the interplay in between smart phones' and users' awareness, which in turn can inform the design of mobile context-aware applications.…”

Section: Introductionmentioning

confidence: 97%