The Internet of Things and Next-generation Public Health Information Systems

Abstract

The Internet of things has particularly novel implications in the area of public health. This is due to (1) The rapid and widespread adoption of powerful contemporary Smartphone’s; (2) The increasing availability and use of health and fitness sensors, wearable sensor patches, smart watches, wireless-enabled digital tattoos and ambient sensors; and (3) The nature of public health to implicitly involve connectivity with and the acquisition of data in relation to large numbers of individuals up to population scale. Of particular relevance in relation to the Internet of Things (IoT) and public health is the need for privacy and anonymity of users. It should be noted that IoT capabilities are not inconsistent with maintaining privacy, due to the focus of public health on aggregate data not individual data and broad public health interventions. In addition, public health information systems utilizing IoT capabilities can be constructed to specifically ensure privacy, security and anonymity, as has been developed and evaluated in this work. In this paper we describe the particular characteristics of the IoT that can play a role in enabling emerging public health capabilities; we describe a privacy-preserving IoT-based public health information system architecture; and provide a privacy evaluation.

Share and Cite:

R. Steele and A. Clarke, "The Internet of Things and Next-generation Public Health Information Systems," Communications and Network, Vol. 5 No. 3B, 2013, pp. 4-9. doi: 10.4236/cn.2013.53B1002.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] P. Klasnja and W. Pratt, “Methodological Review: Healthcare in the Pocket: Mapping the Space of Mobile-Phone Health Interventions,” Journal of Biomedical Informatics, Vol. 45, No. 1, 2012, pp. 184-198. doi:10.1016/j.jbi.2011.08.017
[2] A. Clarke and R. Steele, “Health Participatory Sensing Networks,” Mobile Information Systems, 2013 (in press).
[3] K. Sampigethaya and R. Poovendran., "A Survey on Mix Networks and Their Secure Applications," Proceedings of the IEEE, Vol. 94, No. 12, 2006, pp. 2142-2181. doi:10.1109/JPROC.2006.889687
[4] S. Mauw, J. H. S. Verschuren and E. P. Vink, "A Formalization of Anonymity and Onion Routing," in (Samarati, P., Ryan, P., Gollmann, D., and Molva, R., 'eds.'): Computer Security – Esorics 2004, Springer Berlin Heidelberg, 2004, pp. 109-124.
[5] M. Swan, “Sensor Mania! The Internet of Things, Wearable Computing, Objective Metrics, and the Quantified Self 2.0,” Journal of Sensor and Actuator Networks, Vol. 1, No. 3, 2012, pp. 217-253. doi:10.3390/jsan1030217
[6] R. Steele, "Social Media, Mobile Devices and Sensors: Categorizing New Techniques for Health Communication." Proceedings of the Fifth International Conference on Sensing Technology (ICST), 2011, pp. 187-192.
[7] R. Steele, A. Lo, C. Secombe and Y. K. Wong, “Elderly Persons’ Perception and Acceptance of using Wireless Sensor Networks to Assist Healthcare,” International Journal of Medical Informatics, Vol. 78, No. 12, 2009, pp. 788-801. doi:10.1016/j.ijmedinf.2009.08.001
[8] Jawbone, “UPTM by Jawbone® with MotionX® Technology Empowers You to Live a Healthier Life,” 2011 [accessed 2013 April 20]; Available from: http://content.jawbone.com/static/www/pdf/press-releases/up-press-release-110311.pdf.
[9] Mobi Health News, “Google Adds Activity Tracking to Android App,” 2012, [accessed 18th Jun 2013]; Online: http://mobihealthnews.com/19551/google-adds-activity-tracking-to-android-app/
[10] Sano Intelligence [Online], Accessed 10th June 2013, http://rockhealth.com/accelerator/portfolio-companies/sano-intelligence/
[11] B. Network, “Riderlog,” 2011; Available from: http://www.bv.com.au/general/ride-to-work/91481/.
[12] C. Outram, C. Ratti and A. Biderman, “The Copenhagen Wheel: An Innovative Electric Bicycle System that Harnesses the Power of Real-time Information and Crowd Sourcing,” in EVER Monaco International Exhibition & Conference, 2010, pp. 8.
[13] D. E. Warburton, W. C. W. Nicol and S. S. Bredin. "Health Benefits of Physical Activity: The Evidence," Canadian Medical Association Journal, Vol. 174, No. 6, 2006, pp. 801-809. doi:10.1503/cmaj.051351
[14] R. Steele, “An Overview of the State of the Art of Automated Capture of Dietary Intake Information,” Critical Reviews in Food Science and Nutrition, 2013.
[15] AIHW, “Biomedical Component of the Australian Health Survey: Public Health Objectives,” 2011, [Online]. Available:http://www.health.gov.au/internet/main/publishing.nsf/Content/health-pubhlth-strateg-food-monitoring.htm/$File/Biomedcal%20component%20AHS-public%20health%20objectives.pdf
[16] P. Kalnis and G. Ghinita, "Spatial K-Anonymity", in (Liu, L., and ?zsu, M.T., 'eds.'): Encyclopedia of Database Systems, Springer US, 2009, pp. 2714-2714.
[17] A. Clarke and R. Steele, "Summarized Data to Achieve Population-Wide Anonymized Wellness Measures," Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE, 2012, pp. 2158-2161.
[18] A. Clarke and R. Steele, “Secure and Reliable Distributed Health Records: Achieving Query Assurance across Repositories of Encrypted Health Data,” in System Science (HICSS), 2012 45th Hawaii International Conference on, 2012, pp. 3021-3029.
[19] Austroads, "Australian Cycling Participation "2011, http://www.austroads.com.au/abc/images/pdf/AP-C91-11.pdf.
[20] Australian Bureau of Statistics, "Census Community Profiles Greater Sydney", 2011, http://www.censusdata.abs.gov.au/census_services/getproduct/census/2011/communityprofile/1GSYD,accessed 28/03/2013

Copyright © 2024 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.