Literature DB >> 25123734

Big data, smart homes and ambient assisted living.

V Vimarlund1, S Wass.   

Abstract

OBJECTIVES: To discuss how current research in the area of smart homes and ambient assisted living will be influenced by the use of big data.
METHODS: A scoping review of literature published in scientific journals and conference proceedings was performed, focusing on smart homes, ambient assisted living and big data over the years 2011-2014.
RESULTS: The health and social care market has lagged behind other markets when it comes to the introduction of innovative IT solutions and the market faces a number of challenges as the use of big data will increase. First, there is a need for a sustainable and trustful information chain where the needed information can be transferred from all producers to all consumers in a structured way. Second, there is a need for big data strategies and policies to manage the new situation where information is handled and transferred independently of the place of the expertise. Finally, there is a possibility to develop new and innovative business models for a market that supports cloud computing, social media, crowdsourcing etc.
CONCLUSIONS: The interdisciplinary area of big data, smart homes and ambient assisted living is no longer only of interest for IT developers, it is also of interest for decision makers as customers make more informed choices among today's services. In the future it will be of importance to make information usable for managers and improve decision making, tailor smart home services based on big data, develop new business models, increase competition and identify policies to ensure privacy, security and liability.

Keywords:  Big data; ambient assisted living; smart homes

Mesh:

Year:  2014        PMID: 25123734      PMCID: PMC4287073          DOI: 10.15265/IY-2014-0011

Source DB:  PubMed          Journal:  Yearb Med Inform        ISSN: 0943-4747


  23 in total

1.  Impact of legislation on nursing home care in the United States: lessons for the United Kingdom.

Authors:  C M Hughes; K L Lapane; V Mor
Journal:  BMJ       Date:  1999-10-16

2.  Using the Dempster-Shafer theory of evidence with a revised lattice structure for activity recognition.

Authors:  Jing Liao; Yaxin Bi; Chris Nugent
Journal:  IEEE Trans Inf Technol Biomed       Date:  2010-11-11

Review 3.  A review of smart homes- present state and future challenges.

Authors:  Marie Chan; Daniel Estève; Christophe Escriba; Eric Campo
Journal:  Comput Methods Programs Biomed       Date:  2008-03-25       Impact factor: 5.428

4.  Pulmonary telemedicine--a model to access the subspecialist services in underserved rural areas.

Authors:  Tasleem Raza; Manish Joshi; Ralph M Schapira; Zia Agha
Journal:  Int J Med Inform       Date:  2008-09-21       Impact factor: 4.046

5.  Big data: the management revolution.

Authors:  Andrew McAfee; Erik Brynjolfsson
Journal:  Harv Bus Rev       Date:  2012-10

6.  The future state of clinical data capture and documentation: a report from AMIA's 2011 Policy Meeting.

Authors:  Caitlin M Cusack; George Hripcsak; Meryl Bloomrosen; S Trent Rosenbloom; Charlotte A Weaver; Adam Wright; David K Vawdrey; Jim Walker; Lena Mamykina
Journal:  J Am Med Inform Assoc       Date:  2012-09-08       Impact factor: 4.497

7.  The inevitable application of big data to health care.

Authors:  Travis B Murdoch; Allan S Detsky
Journal:  JAMA       Date:  2013-04-03       Impact factor: 56.272

8.  Reliability of a telemedicine system designed for rural Kenya.

Authors:  Rosie Qin; Rachel Dzombak; Roma Amin; Khanjan Mehta
Journal:  J Prim Care Community Health       Date:  2012-10-03

9.  Assessment of a primary care-based telemonitoring intervention for home care patients with heart failure and chronic lung disease. The TELBIL study.

Authors:  Iñaki Martín-Lesende; Estibalitz Orruño; Carmen Cairo; Amaia Bilbao; José Asua; María I Romo; Itziar Vergara; Juan C Bayón; Roberto Abad; Eva Reviriego; Jesús Larrañaga
Journal:  BMC Health Serv Res       Date:  2011-03-08       Impact factor: 2.655

10.  Effect of home-based telemonitoring using mobile phone technology on the outcome of heart failure patients after an episode of acute decompensation: randomized controlled trial.

Authors:  Daniel Scherr; Peter Kastner; Alexander Kollmann; Andreas Hallas; Johann Auer; Heinz Krappinger; Herwig Schuchlenz; Gerhard Stark; Wilhelm Grander; Gabriele Jakl; Guenter Schreier; Friedrich M Fruhwald
Journal:  J Med Internet Res       Date:  2009-08-17       Impact factor: 5.428

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  5 in total

Review 1.  Big Data Technologies: New Opportunities for Diabetes Management.

Authors:  Riccardo Bellazzi; Arianna Dagliati; Lucia Sacchi; Daniele Segagni
Journal:  J Diabetes Sci Technol       Date:  2015-04-24

2.  Health-Enabling and Ambient Assistive Technologies: Past, Present, Future.

Authors:  R Haux; S Koch; N H Lovell; M Marschollek; N Nakashima; K-H Wolf
Journal:  Yearb Med Inform       Date:  2016-06-30

3.  Towards exergaming commons: composing the exergame ontology for publishing open game data.

Authors:  Giorgos Bamparopoulos; Evdokimos Konstantinidis; Charalampos Bratsas; Panagiotis D Bamidis
Journal:  J Biomed Semantics       Date:  2016-02-09

Review 4.  Ambient Sensors for Elderly Care and Independent Living: A Survey.

Authors:  Md Zia Uddin; Weria Khaksar; Jim Torresen
Journal:  Sensors (Basel)       Date:  2018-06-25       Impact factor: 3.576

5.  AI-Based Early Change Detection in Smart Living Environments.

Authors:  Giovanni Diraco; Alessandro Leone; Pietro Siciliano
Journal:  Sensors (Basel)       Date:  2019-08-14       Impact factor: 3.576

  5 in total

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