Agent-Based Context-Aware Service in a Smart Space

Jih, Wan-rong; Hsu, Jane Yung-jen

doi:10.2991/978-94-91216-31-2_8

Cited by 6 publications

(6 citation statements)

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“…ese systems are not conceived to be smart and user-centered. e authors of [1,2,[15][16][17][18] proposed the use of the contextawareness system collecting a large volume of information about the learner's environment. According to these data, the system will automatically adapt to the user's preferences.…”

Section: Related Workmentioning

confidence: 99%

“…For instance, e-learning comes as a solution for most of the learning constraints such as lack of time and resources. e-Learning is an integrated system based on the effective employment of Information and Communication Technology (ICTs) in the teaching and learning processes by creating an environment rich in computer and Internet applications that enables the learner to access the learning resources anytime and anywhere and to achieve mutual interaction between the elements of the system [1]. e-Learning is the most commonly used term.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Cognitive IoT-Based e-Learning System: Enabling Context-Aware Remote Schooling during the Pandemic

Zaguia

Ameyed

Haddar

et al. 2021

Journal of Healthcare Engineering

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The 2019–2020 coronavirus pandemic had far-reaching consequences beyond the spread of the disease and efforts to cure it. Today, it is obvious that the pandemic devastated key sectors ranging from health to economy, culture, and education. As far as education is concerned, one direct result of the spread of the pandemic was the resort to suspending traditional in-person classroom courses and relying on remote learning and homeschooling instead, by exploiting e-learning technologies, but many challenges are faced by these technologies. Most of these challenges are centered around the efficiency of these delivery methods, interactivity, and knowledge testing. These issues raise the need to develop an advanced smart educational system that assists home-schooled students, provides teachers with a range of smart new tools, and enable a dynamic and interactive e-learning experience. Technologies like the Internet of things (IoT) and artificial intelligence (AI), including cognitive models and context-awareness, can be a driving force in the future of e-learning, opening many opportunities to overcome the limitation of the existing remote learning systems and provide an efficient reliable augmented learning experience. Furthermore, virtual reality (VR) and augmented reality (AR), introduced in education as a way for asynchronous learning, can be a second driving force of future synchronous learning. The teacher and students can see each other in a virtual class even if they are geographically spread in a city, a country, or the globe. The main goal of this work is to design and provide a model supporting intelligent teaching assisting and engaging e-learning activity. This paper presents a new model, ViRICTA, an intelligent system, proposing an end-to-end solution with a stack technology integrating the Internet of things and artificial intelligence. The designed system aims to enable a valuable learning experience, providing an efficient, interactive, and proactive context-aware learning smart services.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Cognitive IoT-Based e-Learning System: Enabling Context-Aware Remote Schooling during the Pandemic

Zaguia

Ameyed

Haddar

et al. 2021

Journal of Healthcare Engineering

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“…While the comparison might not be comprehensive, it provides an overview of the differences between the UFIT and other similar systems to our best knowledge. With the advent of smart devices and the emergence of technologies including Global Positioning System (GPS), ubiquitous sensor networks (USNs), 3G/4G data networks, and radio frequency identification (RFID), smart spaces can be established to deliver context-aware services [ 52 ]. The next reasonable step for UFIT development would be to integrate context-aware services.…”

Section: Discussionmentioning

confidence: 99%

Ontological Knowledge Engine and Health Screening Data Enabled Ubiquitous Personalized Physical Fitness (UFIT)

Chiang

Chih³

2014

Sensors

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Good physical fitness generally makes the body less prone to common diseases. A personalized exercise plan that promotes a balanced approach to fitness helps promotes fitness, while inappropriate forms of exercise can have adverse consequences for health. This paper aims to develop an ontology-driven knowledge-based system for generating custom-designed exercise plans based on a user's profile and health status, incorporating international standard Health Level Seven International (HL7) data on physical fitness and health screening. The generated plan exposing Representational State Transfer (REST) style web services which can be accessed from any Internet-enabled device and deployed in cloud computing environments. To ensure the practicality of the generated exercise plans, encapsulated knowledge used as a basis for inference in the system is acquired from domain experts. The proposed Ubiquitous Exercise Plan Generation for Personalized Physical Fitness (UFIT) will not only improve health-related fitness through generating personalized exercise plans, but also aid users in avoiding inappropriate work outs.

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“…Reference [21] proposes a Context-aware Service Platform (a prototype system) that utilizes Semantic Web technologies to analyze the ambient contexts and contrive service plans. They have integrated ontology with rule-based reasoning to automatically infer high-level contexts and deduce a goal of context-aware services.…”

Section: Context Aware Multi-agent Systemsmentioning

confidence: 99%

“…In this work we use a multidimensional context model that subscribes to a meronomy that articulates various works from the literature [15,16,21,22,23,24,47,48,49] and it is enriched to fulfil ePH's specific functionality. Thus, the context is multidimensional within the ubiquitous environment, having the following facets: • task context: operations, goals, operating mode -static or dynamic, etc;…”

Section: Learning With Ephmentioning

confidence: 99%