Download PDF
Yearb Med Inform 2014; 23(01): 143-149
DOI: 10.15265/IY-2014-0011
Original Article
Georg Thieme Verlag KG Stuttgart

Big Data, Smart Homes and Ambient Assisted Living

V. Vimarlund
1   Jönköping International Business School, Jönköping, Sweden
2   Department of Computer Science, Linköping University, Linköping, Sweden
,
S. Wass
1   Jönköping International Business School, Jönköping, Sweden
› Author Affiliations
Further Information

Publication History

15 August 2014

Publication Date:
05 March 2018 (online)

Also available at
   Permissions and Reprints

Summary

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 - smart homes - ambient assisted living
 

  • References

  • 1 Hughes CM, Lapane K, Mor V. The impact of legislation on nursing home care in the United States: lessons for the United Kingdom. BMJ 1999; 319 7216 1060-3.
    CrossrefPubMedSearch in Google Scholar
  • 2 Venkatesh V, Davis FD. A theoretical extension of the technology acceptance model: Four longitudinal field studies. Manage Sci 2000; 46 (02) 186-204.
    CrossrefPubMedSearch in Google Scholar
  • 3 Venkatesh V. Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information systems research. 2000; 11 (04) 342-65.
    CrossrefPubMedSearch in Google Scholar
  • 4 Venkatesh V, Morris MG, Davis GB, Davis D. User acceptance of information technology: Toward a unified view. MIS Quarterly 2003; 27 (03) 425-78.
    CrossrefPubMedSearch in Google Scholar
  • 5 O’Brien J, Rodden T, Rouncefield M, Hughes J. At home with the technology: an ethnographic study of a set-top-box trial. ACM Trans Comput Hum Interact 1999; 6 (03) 282-308.
    CrossrefPubMedSearch in Google Scholar
  • 6 McKinsey Global Institute.. Big Data:The next frontier for innovation, competition, and productivity; 2011. Available from: www.mckinsey.com/insights/business_technology/big_data_the_next_frontier_for_innovation (last accessed 2012-08-04).
    PubMed
  • 7 Chen H, Chiang RH, Storey VC. Business Intelligence and Analytics: From Big Data to Big Impact. MIS Quarterly 2012; 36 (04) 1165-88.
    CrossrefPubMedSearch in Google Scholar
  • 8 Cusack CM, Hripcsak G, Bloomrosen M, Rosen-bloom ST, Weaver CA, Wright A. et al. The future state of clinical data capture and documentation: a report from AMIA’s 2011 Policy Meeting. JAMA 2013; 20 (01) 134-40.
    PubMedSearch in Google Scholar
  • 9 Hartzband DD. Using Ultra-Large Data Sets in Health Care. 2011 Sessions. p. 3. e-healthpolicy.org.
    PubMed
  • 10 McAfee A, Brynjolfsson E. Big data: the management revolution. Harvard business review 2012; 90 (10) 60-6.
    PubMedSearch in Google Scholar
  • 11 McNickle M. Health care IT News: 5 Basics of Big Data. 2013; Available from: www.healthcareitnews.com/news/5-basics-big-datacareitnews.com/news/5-basics-big-data (last accessed 2012-12-12).
    PubMed
  • 12 Riskin D. Healthcare IT News: Big Data: Opportunity and Challenge. 2013; Available from: http://www.healthcareitnews.com/news/big-data-opportunity-and-challenge (last accessed 2012-12-02).
    PubMed
  • 13 The Institute for Health Technology Transformation.. Population Health Management: A Roadmap for Provider-based Automation in a New Era of Healthcare. Washington DC: The Institute for Health Technology Transformation; 2001
    Search in Google Scholar
  • 14 Demiris G, Hensel BK. Technologies for an aging society: a systematic review of “smart home” applications. Yearb Med Inform 2008; 33-40.
    Thieme ConnectPubMedSearch in Google Scholar
  • 15 Arksey H, O’Malley L. Scoping studies: towards a methodological framework. Int J Soc Res Methodol 2005; 8 (01) 19-32.
    CrossrefPubMedSearch in Google Scholar
  • 16 Brien SE, Lorenzetti DL, Lewis S, Kennedy J, Ghali WA. Overview of a formal scoping review on health system report cards. Implement Sci 2010; 5 (02) 1-12.
    CrossrefPubMedSearch in Google Scholar
  • 17 Chakravorty A, Wlodarczyk T, Chunming R. Privacy Preserving Data Analytics for Smart Homes. Security and Privacy Workshops (SPW), 2013 IEEE. IEEE; 2013
    Search in Google Scholar
  • 18 Chen D, Zhao H. Data Security and Privacy Protection Issues in Cloud Computing, International Conference on Computer Science and Electronics Engineering (ICCSEE), vol.1; Mar. 2012 p. 647-51.
    PubMedSearch in Google Scholar
  • 19 Drosatos G, Efraimidis P. Privacy-preserving statistical analysis on ubiquitous health data, 8th International Conference on Trust, Privacy and Security in Digital Business. Springer-Verlag; 2011. p. 24-36.
    Search in Google Scholar
  • 20 Shen Yi, Varvel Jr. VE. Developing Data Management Services at the Johns Hopkins University. The Journal of Academic Librarianship 2013; 39 (06) 552-5.
    CrossrefPubMedSearch in Google Scholar
  • 21 Jain SH, Rosenblatt M, Duke J. Is Big Data the New Frontier for Academic-Industry Collaboration?. JAMA 2014; 311 (21) 2171-2.
    CrossrefPubMedSearch in Google Scholar
  • 22 Murdoch TB, Detsky AS. The Inevitable Application of Big Data to Health Care. JAMA 2013; 309 (13) 1351-2.
    CrossrefPubMedSearch in Google Scholar
  • 23 Weber GM, Mandl KD, Kohane IS. Finding the Missing Link for Big Biomedical Data. JAMA Published online May 22, 2014 doi:10.1001/ jama.2014.4228.
    PubMedSearch in Google Scholar
  • 24 European Commission.. Green Paper on mobile Health (“mHealth). 2014. Retrieved from ec.europa.eu/digital-agenda/en/news/green-paper-mobile-health-mhealth (last accessed 14-06-27).
    PubMed
  • 25 Communication from the commission to the European Parliament, the Council, The European Economic and Social Committee and the Committee of the Regions. A Digital Agenda for Europe.
    PubMed
  • 26 European Commisson.. eHealth Action Plan 2012-2020 - Innovative healthcare for the 21st century;. 2012 p. 1-14.
    PubMedSearch in Google Scholar
  • 27 Feldman B, Martin EM, Skotnes T. Big Data in Healthcare Hype and Hope. Retrieved from www.west-info.eu/files/big-data-in-health-care.pdf (last accessed 12-12-12).
    PubMed
  • 28 Groves P, Kayyali B, Knott D, Van Kuiken S. The ”big data” revolution in healthcare. Accelerating value and innovation. Center for US Health system Reform. Business Technology Office; 2013
    PubMedSearch in Google Scholar
  • 29 Eysenbach G. What is eHealth?. J Med Internet Res 2001; 3 (02) e20.
    CrossrefPubMedSearch in Google Scholar
  • 30 Wen H. O’Reilly. Strata.com Big ethics for big data 2012 Retrieved from strata.oreilly.com/2012/06/ethics-big-data-business-decisions.html (last accessed 12-12-12).
    PubMed
  • 31 Hervás R, Bravo J, Fontecha J. Awareness marks: adaptive services through user interactions with augmented objects. Pers Ubiquitous Comput 2011; 15 (04) 409-18.
    CrossrefPubMedSearch in Google Scholar
  • 32 Liao J, Bi Y, Nugent C. Using the Dempster-Shafer Theory of Evidence With a Revised Lattice Structure for Activity Recognition. IEEE Trans Inf Technol Biomed 2011; 15 (01) 74-82.
    CrossrefPubMedSearch in Google Scholar
  • 33 Storf H, Kleinberger T, Becker M, Schmitt M, Bomarius F, Prueckner S. An Event-Driven Approach to Activity Recognition in Ambient Assisted Living in Ambient Intelligence. In: Tscheligi M. et al, editors. Ambient Intelligence. Berlin Heidelberg: Springer; 2009. p. 123-32.
    Search in Google Scholar
  • 34 Parra J, Hossain MA, Uribarren A, Jacob E, El Saddik A. Flexible Smart Home Architecture using Device Profile for Web Services: a Peer-to-Peer Approach. International Journal of Smart Home 2009; 3 (02) 39-56.
    PubMedSearch in Google Scholar
  • 35 Kadouche R, Abdulrazak B, Mokhtari M, Giroux S, Pigot H. Personalization and Multi-user Management in Smart Homes for Disabled People. International Journal of Smart Home 2009; 3 (01) 39-48.
    PubMedSearch in Google Scholar
  • 36 Seitz C, Schönfelder R. Rule-based OWL reasoning for specific embedded devices: papers presented at the 10th international conference on The semantic web - Volume Part II2011. Bonn, Germany: 2011. p. 237-52.
    Search in Google Scholar
  • 37 Wagner S, Toftegaard T, Bertelsen O. Context Assessment during Blood Pressure Self-measurement Utilizing the Sensor Chair Ambient Intelligence. In: Keyson D. et al, editors. Ambient Intelligence. Berlin Heidelberg: Springer; 2011. p. 295-9.
    Search in Google Scholar
  • 38 Liang Y, Zhou X, Yu Z, Wang H, Guo B. A context-aware multimedia service scheduling framework in smart homes. EURASIP Journal on Wireless Communications and Networking 2012; (01) 67.
    PubMedSearch in Google Scholar
  • 39 Bono-Nuez A, Martín-del-Brío B, Blasco-Marín R, Casas-Nebra R, Roy-Yarza A. Quality of Life Evaluation of Elderly and Disabled People by Using Self-Organizing Maps. In: Omatu S. et al, editors. Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living. Berlin Heidelberg: Springer; 2009. p. 906-13.
    Search in Google Scholar
  • 40 Grosse-Puppendahl TA, Marinc A, Braun A. Classification of user postures with capacitive proximity sensors in AAL-Environments: papers presented at the Second international conference on Ambient Intelligence. Amsterdam, The Netherlands; 2001. p. 314-23.
    Search in Google Scholar
  • 41 Heerink M, Kröse B, Evers V, Wielinga B. Assessing Acceptance of Assistive Social Agent Technology by Older Adults: the Almere Model. Int J Soc Robot 2010; 2 (04) 361-75.
    CrossrefPubMedSearch in Google Scholar
  • 42 Laflamme FM, Pietraszek WE, Rajadhyax NV. Reforming hospitals with IT investment. McKinsey Quarterly 2010: 10.
    PubMedSearch in Google Scholar
  • 43 Roger M, Lorica B. Big data: Technologies and techniques for large scale data. O’Reilly. 2009 2(11).
    PubMedSearch in Google Scholar
  • 44 García-Vázquez JP, Marcela DR. Ambient Information Systems to Support the Elderly in Carrying Out Their Activities of Daily Living, in Proceedings of the Confederated International Workshops and Posters on On the Move to Meaningful Internet Systems. ADI, CAMS, EI2N, ISDE, IWSSA, MONET, OnToContent, ODIS, ORM, OTM Academy, SWWS, SEMELS, Beyond, SAWSDL and COMBEK 2009, Vilamoura, Portugal: Springer-Verlag; 2009. p. 779-88.
    Search in Google Scholar
  • 45 Maier E, Kempter G. AAL in the Wild - Lessons Learned, in Proceedings of the 5th International on Conference Universal Access in Human-Computer Interaction. Part II: Intelligent and Ubiquitous Interaction Environments San Diego, CA: Springer-Verlag; 2009. p. 218-27.
    Search in Google Scholar
  • 46 Laurila JK, Gatica-Perez D, Aad I, Blom J, Bornet O, Do T. et al. From big smartphone data to worldwide research: The Mobile Data Challenge. Pervasive Mob Comput 2013; 9 (06) 752-71.
    CrossrefPubMedSearch in Google Scholar
  • 47 Toledo FG, Triola A, Ruppert K, Siminerio LM. Telemedicine consultations: an alternative model to increase access to diabetes specialist care in underserved rural communities. JMIR Res Protoc 2012 1(2).
    PubMedSearch in Google Scholar
  • 48 Baig MM, Gholamhosseini H. Smart Health Monitoring Systems: An Overview of Design and Modeling. J Med Syst 2013; 37 (02) 1-14.
    PubMedSearch in Google Scholar
  • 49 Chronaki CE, Vardas P. Remote monitoring costs, benefits, and reimbursement: a European perspective. Europace 2013; 15 (Suppl. 01) i59-i64.
    CrossrefPubMedSearch in Google Scholar
  • 50 Martín-Lesende I, Orruño E, Cairo C, Bilbao A, Asua J, Romo MI. et al. Assessment of a primary care-based telemonitoring intervention for home care patients with heart failure and chronic lung disease. The TELBIL study. BMC Health Serv Res 2011 11(1).
    PubMedSearch in Google Scholar
  • 51 Toledo FG, Triola A, Ruppert K, Siminerio LM. Telemedicine consultations: an alternative model to increase access to diabetes specialist care in underserved rural communities. JMIR Res Protoc 2012 1(2).
    PubMedSearch in Google Scholar
  • 52 Baig MM, Gholamhosseini H. Smart Health Monitoring Systems: An Overview of Design and Modeling. J Med Syst 2013; 37 (02) 1-14.
    PubMedSearch in Google Scholar
  • 53 Martín-Lesende I, Orruño E, Cairo C, Bilbao A, Asua J, Romo MI. et al. Assessment of a primary care-based telemonitoring intervention for home care patients with heart failure and chronic lung disease. The TELBIL study. BMC Health Serv Res 2011 11(1).
    PubMedSearch in Google Scholar
  • 54 Chan M, Estève D, Escriba C, Campo E. A review of smart homes—Present state and future challenges. Comput Methods Programs Biomed 2008; 91 (01) 55-81.
    CrossrefPubMedSearch in Google Scholar
  • 55 Grauel J, Spellerberg A. Attitudes and Requirements of Elderly People Towards Assisted Living Solutions. In: Mühlhäuser M, Ferscha A, Aitenbichler E. editors. Constructing Ambient Intelligence. Berlin Heidelberg: Springer; 2008. p. 197-206.
    Search in Google Scholar
  • 56 Stojmenova E, Debevc M, Zebec L, Imperl B. Assisted living solutions for the elderly through interactive TV. Multimed Tools Appl 2013; 1-15.
    PubMedSearch in Google Scholar
  • 57 Subedi RR, Peterson CB, Kyriazakos S. Telemedicine for Rural and Underserved Communities of Nepal. In: Dremstrup K, Rees S, Olgaard Jensen M. editors. 15th Nordic-Baltic Conference on Biomedical Engineering and Medical Physics. Berlin Heidelberg: Springer; 2011. p. 117-20.
    Search in Google Scholar
  • 58 Qin R, Dzombak R, Amin R, Mehta K. Reliability of a telemedicine system designed for rural Kenya. J Prim Care Community Health 2013; 4 (03) 177-81.
    CrossrefPubMedSearch in Google Scholar
  • 59 Raza T, Joshi M, Schapira RM, Agha Z. Pulmonary telemedicine—a model to access the subspecialist services in underserved rural areas. Int J Med Inform 2009; 78 (01) 53-9.
    CrossrefPubMedSearch in Google Scholar
  • 60 Seto E, Leonard KJ, Cafazzo JA, Barnsley J, Masino C, Ross HJ. Mobile phone-based telemonitoring for heart failure management: a randomized controlled trial. J Med Internet Res 2012 14(1).
    PubMedSearch in Google Scholar
  • 61 Chaudhry SI, Mattera JA, Curtis JP, Spertus JA, Herrin J, Lin Z. et al. Telemonitoring in patients with heart failure. N Engl J Med 2010; 363 (24) 2301-2309.
    CrossrefPubMedSearch in Google Scholar
  • 62 Bowles KH, Holland DE, Horowitz DA. A comparison of in-person home care, home care with telephone contact and home care with telemonitoring for disease management. J Telemed Telecare 2009; 15 (07) 344-50.
    CrossrefPubMedSearch in Google Scholar
  • 63 Scherr D, Kastner P, Kollmann A, Hallas A, Auer J, Krappinger H. et al. Effect of home-based tele-monitoring using mobile phone technology on the outcome of heart failure patients after an episode of acute decompensation: randomized controlled trial. J Med Internet Res 2009 11(3).
    PubMedSearch in Google Scholar
  • 64 Greenhalgh T, Robert G, Macfarlane F, Bate P, Kyriakidou O. Diffusion of innovations in service organizations: systematic review and recommendations. Milbank Q 2004; 82 (04) 581-629.
    CrossrefPubMedSearch in Google Scholar
  • 65 Vimarlund V, Olve NG, Scandurra I, Koch S. Information and Communication Technology (ICT) and elderly homecare - The Hudiksvall Case. Health Informatics J 2008; 14 (03) 195-209.
    CrossrefPubMedSearch in Google Scholar