Sense2Health - A Quantified Self Application for Monitoring Personal Exposure to Environmental Pollution

Sara Hachem, Georgios Mathioudakis, Animesh Pathak, Valerie Issarny, Rajiv Bhatia

Abstract

Sense2Health is a Quantified Self application that monitors personal exposure to environment pollution and assesses its heath-related risks. The novelty of the application is that it requires little to no active involvement by users and unlike existing applications, it correlates the individual’s well-being to their environment as opposed to their physical activity alone. Consequently, when health and environment data are acquired, our application enables users to better identify behavior changes towards enhancing their health by enhancing their environments. Furthermore, Sense2Health is an open platform for integrating existing domain-specific sensing applications (environmental and health monitoring) focused on decreasing required specialized development efforts. We present in this paper the design of Sense2Health in addition to a proof-of-concept implementation for a noise-monitoring use case. Afterwards, we assess its performance while integrating it with a dedicated open source noise sensing application.

References

  1. Ahtinen, A., Mattila, E., Vaatanen, A., Hynninen, L., Salminen, J., Koskinen, E., and Laine, K. (2009). User experiences of mobile wellness applications in health promotion: User study of wellness diary, mobile coach and selfrelax. In Pervasive Computing Technologies for Healthcare, 2009. PervasiveHealth 2009. 3rd International Conference on, pages 1-8. IEEE.
  2. Angelini, L., Caon, M., Carrino, S., Bergeron, L., Nyffeler, N., Jean-Mairet, M., and Mugellini, E. (2013). Designing a desirable smart bracelet for older adults. In Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication, pages 425-434. ACM.
  3. Bennett, G., King, E. A., Curn, J., Cahill, V., Bustamante, F., and Rice, H. J. (2010). Environmental noise mapping using measurements in transit. In International Conference on Noise and Vibration Engineering, pages 1795-1810.
  4. Brauer, M., Amann, M., Burnett, R. T., Cohen, A., Dentener, F., Ezzati, M., Henderson, S. B., Krzyzanowski, M., Martin, R. V., Van Dingenen, R., et al. (2012). Exposure assessment for estimation of the global burden of disease attributable to outdoor air pollution. Environmental science & technology, 46(2):652-660.
  5. Burnett, R. T., Pope, C. A., Ezzati, M., Olives, C., Lim, S. S., Mehta, S., Shin, H. H., Singh, G., Hubbell, B., Brauer, M., et al. (2014). An integrated risk function for estimating the global burden of disease attributable to ambient fine particulate matter exposure.
  6. Denning, T., Andrew, A., Chaudhri, R., Hartung, C., Lester, J., Borriello, G., and Duncan, G. (2009). Balance: towards a usable pervasive wellness application with accurate activity inference. In Proceedings of the 10th workshop on Mobile Computing Systems and Applications, page 5. ACM.
  7. D'Hondt, E., Stevens, M., and Jacobs, A. (2013). Participatory noise mapping works! an evaluation of participatory sensing as an alternative to standard techniques for environmental monitoring. Pervasive and Mobile Computing, 9(5):681-694.
  8. Fritz, T., Huang, E. M., Murphy, G. C., and Zimmermann, T. (2014). Persuasive technology in the real world: a study of long-term use of activity sensing devices for fitness. In Proceedings of the 32nd annual ACM conference on Human factors in computing systems, pages 487-496. ACM.
  9. Gong, J. and Tarasewich, P. (2004). Guidelines for handheld mobile device interface design. In Proceedings of DSI 2004 Annual Meeting, pages 3751-3756. Citeseer.
  10. Hicks, J., Ramanathan, N., Kim, D., Monibi, M., Selsky, J., Hansen, M., and Estrin, D. (2010). Andwellness: an open mobile system for activity and experience sampling. In Wireless Health 2010, pages 34-43. ACM.
  11. Hurtley, C. (2009). Night noise guidelines for Europe. WHO Regional Office Europe.
  12. Kanjo, E. (2010). Noisespy: A real-time mobile phone platform for urban noise monitoring and mapping. Mobile Networks and Applications, 15(4):562-574.
  13. Lane, N. D., Chon, Y., Zhou, L., Zhang, Y., Li, F., Kim, D., Ding, G., Zhao, F., and Cha, H. (2013). Piggyback crowdsensing (pcs): energy efficient crowdsourcing of mobile sensor data by exploiting smartphone app opportunities. In Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems, page 7. ACM.
  14. Lane, N. D., Mohammod, M., Lin, M., Yang, X., Lu, H., Ali, S., Doryab, A., Berke, E., Choudhury, T., and Campbell, A. (2011). Bewell: A smartphone application to monitor, model and promote wellbeing. In 5th International ICST Conference on Pervasive Computing Technologies for Healthcare, pages 23-26.
  15. Maisonneuve, N., Stevens, M., and Ochab, B. (2010). Participatory noise pollution monitoring using mobile phones. Information Polity, 15(1):51-71.
  16. Miedema, H. M. (2007). Annoyance caused by environmental noise: Elements for evidence-based noise policies. Journal of social issues, 63(1):41-57.
  17. Priyantha, B., Lymberopoulos, D., and Liu, J. (2011). Littlerock: Enabling energy-efficient continuous sensing on mobile phones. Pervasive Computing, IEEE, 10(2):12-15.
  18. Rana, R. K., Chou, C. T., Kanhere, S. S., Bulusu, N., and Hu, W. (2010). Ear-phone: an end-to-end participatory urban noise mapping system. In Proceedings of the 9th ACM/IEEE International Conference on Information Processing in Sensor Networks, pages 105- 116. ACM.
  19. Seong, K. E., Lee, K. C., and Kang, S. J. (2014). Self M2M based wearable watch platform for collecting personal activity in real-time. In Big Data and Smart Computing (BIGCOMP), 2014 International Conference on, vol., no, volume 286, pages 15-17.
  20. Swan, M. (2013). The quantified self: fundamental disruption in big data science and biological discovery. Big Data, 1(2):85-99.
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Paper Citation


in Harvard Style

Hachem S., Mathioudakis G., Pathak A., Issarny V. and Bhatia R. (2015). Sense2Health - A Quantified Self Application for Monitoring Personal Exposure to Environmental Pollution . In Proceedings of the 4th International Conference on Sensor Networks - Volume 1: SENSORNETS, ISBN 978-989-758-086-4, pages 36-44. DOI: 10.5220/0005332100360044


in Bibtex Style

@conference{sensornets15,
author={Sara Hachem and Georgios Mathioudakis and Animesh Pathak and Valerie Issarny and Rajiv Bhatia},
title={Sense2Health - A Quantified Self Application for Monitoring Personal Exposure to Environmental Pollution},
booktitle={Proceedings of the 4th International Conference on Sensor Networks - Volume 1: SENSORNETS,},
year={2015},
pages={36-44},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005332100360044},
isbn={978-989-758-086-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 4th International Conference on Sensor Networks - Volume 1: SENSORNETS,
TI - Sense2Health - A Quantified Self Application for Monitoring Personal Exposure to Environmental Pollution
SN - 978-989-758-086-4
AU - Hachem S.
AU - Mathioudakis G.
AU - Pathak A.
AU - Issarny V.
AU - Bhatia R.
PY - 2015
SP - 36
EP - 44
DO - 10.5220/0005332100360044