Cognitive assisted living ambient system: a survey

Li, Ruijiao; Lu, Bowen; McDonald-Maier, Klaus

doi:10.1016/j.dcan.2015.10.003

Cited by 108 publications

(47 citation statements)

References 120 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Earlier, Manyika et al (2011) estimated a total shortcoming of 190,000 new data scientists. • Societal impact : data analytics affects medical care (Parekh, 2015), political opinion making (Harding, 2017;also Krogerus & Grassegger, 2016 and the aftershocks of the US presidential election 2016 with regards to the involvement of the company Cambridge Analytica) and personal liberty (Li et al, 2015; see also Clemens Cap's later chapter on risks and side effects). • Scientific influence : data-intensive analysis as the fourth paradigm of scientific discovery promises breakthroughs in disciplines from physics to life sciences (Hey et al, 2009; see also Brodie's later chapter "on developing data science").…”

Section: Data Science Business and Hypementioning

confidence: 99%

Introduction to Applied Data Science

Stadelmann

Braschler

Stockinger

2019

Applied Data Science

View full text Add to dashboard Cite

Section: Data Science Business and Hypementioning

confidence: 99%

Introduction to Applied Data Science

Stadelmann

Braschler

Stockinger

2019

Applied Data Science

View full text Add to dashboard Cite

“…During the practical implementation of the CR and spectrum sensing (SS) technique researchers had to design cooperative frameworks, choose cooperative secondary users and transmit cooperative information during the spectrum sensing, further developing the framework and algorithms for the group handoff of secondary users and enhancing security [29]. Researchers are already working on designs of protocols for different IoT application, based on cognitive radio, and some of them are presented in [49][50][51]122]. Technologies in this group are used together to optimize 5G performance requirements (e.g., a prototype of mmWave integrated HetNet in [123] and HetNet that incorporates massive multiple-input and multiple-output (mMIMO) and mmWave technologies [217]).…”

Section: Wide and Flexible Bandwidth Technologymentioning

confidence: 99%

IoT’s Tiny Steps towards 5G: Telco’s Perspective

Cero¹,

Husić

Baraković

2017

Symmetry

View full text Add to dashboard Cite

Abstract:The numerous and diverse applications of the Internet of Things (IoT) have the potential to change all areas of daily life of individuals, businesses, and society as a whole. The vision of a pervasive IoT spans a wide range of application domains and addresses the enabling technologies needed to meet the performance requirements of various IoT applications. In order to accomplish this vision, this paper aims to provide an analysis of literature in order to propose a new classification of IoT applications, specify and prioritize performance requirements of such IoT application classes, and give an insight into state-of-the-art technologies used to meet these requirements, all from telco's perspective. A deep and comprehensive understanding of the scope and classification of IoT applications is an essential precondition for determining their performance requirements with the overall goal of defining the enabling technologies towards fifth generation (5G) networks, while avoiding over-specification and high costs. Given the fact that this paper presents an overview of current research for the given topic, it also targets the research community and other stakeholders interested in this contemporary and attractive field for the purpose of recognizing research gaps and recommending new research directions.

show abstract

“…Different issues and obstacles to ICT adherence for elder people are addressed in literature from preliminary works [13], going through important developments [14,15]. Policy conforming documents in the European reality [16][17][18][19][20][21][22]. In our work developments we take in consideration the myriad of issues when developing natural interfaces directed to the diverse caregivers ranging from the auto-care to specialized professional teams.…”

Section: From Smart Homes To Intelligent Homesmentioning

confidence: 99%

Deep Learning and IoT to Assist Multimorbidity Home Based Healthcare

Fonseca¹,

Mendes²,

Lopes³

et al. 2017

J Health Med Inform

View full text Add to dashboard Cite

The authors present a proposal to develop intelligent assisted living environments for home based healthcare in the presence of multimorbidity chronic patients. These environments unite the chronicle patient clinical history sematic representation ICP (Individual Care Process) with the ability of monitoring the living conditions using IoT technologies and events recurring to a fully managed Semantic Web of Things (SWoT) and Machine Learning Algorithms in order to activate the LDC (Less Differentiated Caregiver) for a specific care need. With these capabilities at hand, home based healthcare providing becomes a viable possibility reducing the institutionalization needs. The resulting integrated healthcare framework will provide significant savings while improving the generality of health and satisfaction indicators.

show abstract

Cognitive assisted living ambient system: a survey

Cited by 108 publications

References 120 publications

Introduction to Applied Data Science

Introduction to Applied Data Science

IoT’s Tiny Steps towards 5G: Telco’s Perspective

Deep Learning and IoT to Assist Multimorbidity Home Based Healthcare

Contact Info

Product

Resources

About