Indoor Air Quality Monitoring Network Design based on Uncertainty and Mutual Information
Monika Maciejewska, Andrzej Szczurek
2014
Abstract
Poor quality of indoor air is an important problem in the world today. Although credible methodology of indoor air quality (IAQ) assessment has not been developed so far, the provision of relevant information is necessary for taking actions towards its control. The currently accepted compromise is to focus on the measurable physical and chemical parameters of indoor air as the basis for judging the thermal comfort and chemical IAQ. These quantities show spatial and temporal variability, therefore infrequent or single location measurements are usually insufficient for gaining an outlook of indoor air quality. Therefore, there are preferred multipoint, continuous measurements. They may be realized by the indoor air quality monitoring system. An interesting option for such system is a sensor network. This work presents a statistical method of choosing the location of the nodes of the sensor network for indoor air quality monitoring. The method is based on the information measures. The novelty of the presented approach consists in basing the nodes selection on the information content of the data provided by the sensor network in discrete time moments. The method was demonstrated as applied to the revision of an indoor air quality monitoring network in an office building.
References
- Chen Y. L., Wen J., 2008. Sensor system design for building indoor air protection, Building and Environment, 43, 1278?1285.
- Choi I. J., Edwards J. R, 2008. Large eddy simulation and zonal modeling of human-induced contaminant transport, Indoor Air, 18, 233?249.
- Church K. W., Hanks P., 1990. Word association norms, mutual information and lexicography, Computational Linguistics, 16(1), 22?29.
- Elkamel A., Fatehifar E., Taheri M., Al-Rashidi M.S., Lohi A., 2008. A heuristic optimization approach for Air Quality Monitoring Network design with the simultaneous consideration of multiple pollutants, Journal of Environmental Management, 88(3), 507- 516.
- Fanger P. O., 1988, Introduction of the olf and decipol units tu quantify air pollution perceived by humans indoors and outdoors, Energy and Building, 12, 1?6.
- Fanger P. O., 2006. What is IAQ? Indoor air, 16, 328?334.
- Fano R., 1961. Transmission of Information: A Statistical Theory of Communications. MIT Press, Cambridge, MA.
- Fuentes M., Chaundhuri A., Holland D. M., 2007. Bayesian entropy for spatial sampling design of environmental data, Environmental and Ecological Statistics, 14(3), 323?340.
- Gunay H. B., O'Brien W., Beausoleil-Morrison I., 2013, A critical review of observation studies, modelling and simulation of adaptive occupant behaviors in offices, Building and Environment, 70, 31?47.
- Hartley R. V. L., 1927. Transmission of information, International congress of Telegraphy and Telephony, Lake Como, Italy.
- Heinzerling D., Schiavon S., Webster T., Arens E., 2013, Indoor environmental quality assessment models: A literature review and a proposed weighting and classification scheme, Building and Environment, 70, 210?222.
- Husain T., Khan U., 1983. Shannon's entropy concept in optimum air monitoring network design, The Science of Total Environment, 30, 181?190.
- Li Q., Yoshino H., Mochida A., Lei B., Meng Q. Zhao L., Lun Y., 2009. CFD study of the thermal environment in an air-conditioned train station building, Building and Environment, 44, 1452?1465.
- Ng L.C., Musser A., Persily A.K., Emmerich S.J., 2012. Indoor air quality analyses of commercial reference buildings, Building and Environment, 58, 179?187.
- Marsik T, Johnson R., 2008. HVAC air-quality model and its use to test a PM2.5control strategy, Building and Environment, 43, 1850-1857.
- Persily A.K., Emmerich S.J., 2012. Indoor air quality in sustainable, energy efficient buildings, HVAC&R Research, 18(1), 1?17.
- Peng H., Long F., Ding Ch., 2005. Feature selection based on mutual information: Criteria od Max-Dependency, Max-relevance and Min-Redundancy, IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(8), 1226?1238.
- Postolache O., Pereira M., GirĂ£o P., 2005. Smart Sensor Network for Air Quality Monitoring Applications, IMTC 2005 - Instrumentation and Measurement Technology Conference, Ottawa, Canada, 17?19 May 2005.
- Weschler C. J., 2011. Chemistry in indoor environments - 20 years of research, Indoor Air, 21, 205-218.
- Wyon D. P., 2004. The effects of indoor air quality on performance and productivity, Indoor Air, 14(7), 92?101.
Paper Citation
in Harvard Style
Maciejewska M. and Szczurek A. (2014). Indoor Air Quality Monitoring Network Design based on Uncertainty and Mutual Information . In Proceedings of the 3rd International Conference on Sensor Networks - Volume 1: SENSORNETS, ISBN 978-989-758-001-7, pages 337-344. DOI: 10.5220/0004697403370344
in Bibtex Style
@conference{sensornets14,
author={Monika Maciejewska and Andrzej Szczurek},
title={Indoor Air Quality Monitoring Network Design based on Uncertainty and Mutual Information},
booktitle={Proceedings of the 3rd International Conference on Sensor Networks - Volume 1: SENSORNETS,},
year={2014},
pages={337-344},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004697403370344},
isbn={978-989-758-001-7},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 3rd International Conference on Sensor Networks - Volume 1: SENSORNETS,
TI - Indoor Air Quality Monitoring Network Design based on Uncertainty and Mutual Information
SN - 978-989-758-001-7
AU - Maciejewska M.
AU - Szczurek A.
PY - 2014
SP - 337
EP - 344
DO - 10.5220/0004697403370344