Design of an Integrated System for Modeling of Functional Air Quality Index Integrated with Health-GIS Using Bayesian Neural Network
- 167 Downloads
Air pollution is a major problem, conscious both for health and surroundings. This is a novel approach for the design & development of a system for the monitoring of different air pollutants especially at remote places where it is difficult to install any conventional air quality monitoring stations as well as for the cities. In this research work, a framework of Functional air quality index which is an indicator of susceptibility to respiratory illness has been built using the Bayesian neural network to provide the random real-time data about a location through wireless communication. The monitoring system is integrated with different types of sensors to measure the level of different air pollutants or air quality parameters such as Suspended particulate matters, (PM2.5), Nitrogen dioxide, Sulphur dioxide, Ozone which are directly associated with airways inflammatory diseases such as Asthma, Bronchitis, COPD. Each location in Map (GPS) can be updated automatically with fAQI to the user through mobile computing and satellite commutation. The user gets information about the neighborhood location with health-related information such as- whether a particular location is sensitive to respiratory diseases such as Bronchitis, asthma, COPD etc. due to suspended allergen/pollutants in the ambient air. This novel approach is designed with its’ own prototype and an application of Inter of Things in Health GIS for the benefit of humanity.
KeywordsAmbient air quality monitoring Bayes network Wireless communication fAQI Health GIS
- Cairncross, E. K. & John, J. (2004). Communicating air pollution exposure: a novel air pollution index system based on the relative risk of mortality associated with exposure to the common urban air pollutants. In Proceedings of IUAPPA 13th Annual World Clean Air and Environmental Protection congress.Google Scholar
- CENTRAL POLLUTION CONTROL BOARD. (2011). Guidelines for the measurement of ambient air pollutants (Vol. 2, pp. p-iii–p-v). Delhi: Air Laboratory CPCB.Google Scholar
- Epa, U. (2006). Air quality criteria for ozone and related photochemical oxidants. Washington, DC: US Environmental Protection Agency.Google Scholar
- Epa, D. (2009). Integrated science assessment for particulate matter. Washington, DC: US Environmental Protection Agency.Google Scholar
- European Commission, Joint Research Centre (JRC)/PBL Netherlands Environmental Assessment Agency. (2010). Emission Database for Global Atmospheric Research (EDGAR), release version 4.2. http://edgar.jrc.ec.europe.eu.
- Institute for Health Metrics and Evaluation (IHME). GBD Compare Data Visualization. Seattle, WA: IHME, University of Washington, 2017. Available from http://vizhub.healthdata.org/gbd-compare. (Accessed 25.10.2017).
- National Ambient Air Quality Standards, Central Pollution Control Board Notification in the Gazette of India, Extraordinary, New Delhi, 18th November, 2009.Google Scholar
- Singhi, S., Gupta, G., & Jain, V. (2004). Comparison of pediatric emergency patients in a tertiary care hospital vs a community hospital. Indian Pediatrics, 41, 67–72.Google Scholar
- Spiroska, J., Rahman, A., & Pal, S. (2011). Air pollution in Kolkata: An analysis of current status and interrelation between different factors. SEEU Review, 8(1), 182–214.Google Scholar
- Srikanth, S. N., & John, W. H. (2015). Air pollution and health effects (1st ed.). London: Springer.Google Scholar
- UK Department of Health (UK DH). (2006) Cardiovascular disease and air pollution. In A report by the committee on the medical effects of air pollutants (pp. 21–137). UK DH, London.Google Scholar
- USEPA. (1999) The benefits and costs of the clean Air Act 1990 to 2010. USEPA, Washington DC, D-58Google Scholar
- Völgyesi, P., Nádas, A., Koutsoukos, X. & Lédeczi, Á. (2008). Air quality monitoring with sensormap. In IEEE St. Louis, Missouri, USA.Google Scholar
- Wai, W. T., San, W. T. W., Shun, M. A. W. H., Hon, A. L. K., Ng, M. S. K., Yeung, M. D., et al. (2012). A study of the air pollution index reporting system. Statistical Modelling, 13, 15.Google Scholar
- Williams, R., Kilaru, V., Snyder, E., Kaufman, A., Dye, T., Rutter, A., et al. (2004). Air sensor guidebook. Technical report. Washington: United States Environmental Protection Agency.Google Scholar
- Williams, R., Kilaru, V., Snyder, E., Kaufman, A., Dye, T., Rutter, A., Russell, A., Hafner, H. (2014). Air sensor guidebook. Washington DC: US Environmental Protection Agency.Google Scholar
- World Health Organization. (2002). The World Health Report. Geneva: WHO.Google Scholar
- World Health Organization. (2006). WHO Air quality guidelines for particulate matter, ozone, nitrogen dioxide and sulfur dioxide: Global update 2005-Summary of risk assessment. Geneva: WHO.Google Scholar