Abstract
Conventional wireless home automation networks (WHANs) incorporate embedded wireless sensors and actuators that monitors and control home living environment. WHAN's primary goal is to maintain user comfort and efficient home management. Conventional WHAN lacks “intelligence” in terms of managing compound human comfort, and it deals with multitude of human comfort factors individually instead of collectively. This paper presents wireless sensor networks-based Human Comfort Ambient Intelligence system. A fuzzy-rule-based system for the measurement of human comfort index in a living space is presented. The system is evaluated and tested with simulated and empirical data. It explores the complex relationship between multiple comfort factors. The comfort factors considered here include thermal comfort, visual comfort, indoor air comfort and acoustical comfort.
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References
Dobson S, Delaney K (2006) Embedded intelligence. ERCIM News 67(67):37–38
Munoz A, Augusto JC, Villa A, Botia JA (2011) Design and evaluation of an ambient assisted living system based on an argumentative multi-agent system. Pers Ubiquit Comput 15(4):377–387
Garcia-Vazquez JP, Rodriguez MD, Andrade AG, Bravo J (2011) Supporting the strategies to improve elders’ medication compliance by providing ambient aids. Pers Ubiquit Comput 15(4):389–397
Alessia G, Alexandra T, Wolfram S, Paolo B (2009) Comfort analysis of a passive house at different locations in italy. In: 13th International passive house conference 2009, Frankfurt, Germany, p 93
Lorant K (2009) Passive houses in the climate conditions of slovakia. In: 13th International passive house conference 2009, Frankfurt, Germany, p 99
Ursula E (2009) Climate control and summer comfort in passive office buildings. In: 13th International passive house conference 2009, Frankfurt, Germany, p 421
Taherkordi A, Rouvoy R, Le-Trung Q, Eliassen F (2008) A self-adaptive context processing framework for wireless sensor networks. In: MidSens ’08. Leuven, Belgium
Feng M-W, Wen S-L, Tsai K-C, Liu Y-C, Lai H-R (2008) Wireless sensor network and sensor fusion technology for ubiquitous smart living space applications. In: 2008 Second international symposium on universal communication. Osaka, Japan, pp 295–302
Naadimuthu G, Liu D, Lee E (2007) Application of an adaptive neural fuzzy inference system to thermal comfort and group technology problems. Comput Math Appl 54:1395–1402
Atthajariyakul S, Leephakpreeda T (2004) Real-time determination of optimal indoor-air condition for thermal comfort, air quality and efficient energy usage. Energy Build 36:720–733
Surie D, Laguionie O, Pederson T (2008) Wireless sensor networking of everyday objects in a smart home environment. In: Fourth international conference on intelligent sensors, sensor networks and information processing ISSNIP 2008. Sydney, Australia, pp 189–194
Hamdi M, Lachiver G, Michaud F (1999) A new predictive thermal sensation index of human response. Energy Build 29:167–178
Davis G (1986) Building performance: function, preservation, and rehabilitation. ASTM, Baltimore
Orosa JA (2009) Research on general thermal comfort models. Eur J Sci Res 27(2):217–227
Lee D (2008) Development of light powered sensor networks for thermal comfort measurement. Sensors 8(10):6417–6432
Rawi MIM, Al-Anbuky A (2009) Passive house sensor networks: Human centric thermal comfort concept. In: Fifth international conference on intelligent sensors, sensor networks and information processing ISSNIP 2009. Melbourne, Australia, pp 255–260
ISO7730 (2005) Iso 7730 ergonomics of the thermal environment—analytical determination and interpretation of thermal comfort using calculation of the pmv and ppd indices and local thermal comfort criteria
Gouda M, Danaher S, Underwood C (2001) Thermal comfort based fuzzy logic controller. Chart Inst Build Serv Eng 22(4):237–253
Chen K, Jiaob Y, Lee ES (2005) Fuzzy adaptive networks in thermal comfort. Appl Math Lett 19:420–426
Lah MT, Zupancic B, Krainer A (2005) Fuzzy control for the illumination and temperature comfort in a test chamber. Build Environ 40:1626–1637
CIBSE (1994) CIBSE code for interior lighting. 222 Balham High Road, London SW12 9BS. Chartered Institution of Building Services Engineers, United Kingdom
CIBSE (1994) CIBSE guide: air infiltration and natural ventilation. 222 Balham High Road, London SW12 9BS. Chartered Institution of Building Services Engineers, United Kingdom
Commission E (1996) Green Paper on Future Noise Policy (COM(96) 540). European Commission, Brussels
ISO1999, Iso 1999:1990 acoustics—determination of occupational noise exposure and estimation of noise induced hearing impairment
Sazonov E (2011) Open source fuzzy inference engine for java,” 2011. [Online]. Available: http://people.clarkson.edu/esazonov/FuzzyEngine.htm
ASHRAE (2005) ASHRAE fundamental handbook. American Society of Heating, Refrigerating and Air-Conditioning Engineers
Houghten FC, Yaglou CP (1923) Determining lines of equal comfort. ASHVE Trans 29:163–176
Gagge AP, Stolwijk AJ, Nish Y (1971) An effective temperature scale based on a simple model of human physiological regulatory response. ASHRAE Trans 77:247–257
Gonzalez RR, Gagge AP (1973) Magnitude estimates of thermal discomfort during transients of humidity and operative temperature and their relation to the new ashrae effective temperature. ASHRAE Trans 79:88–96
Yaglou CP (1957) Control of heat casualties at military training centers. AMA Arch Ind Health 16:302–316
Thom EC (1959) The discomfort index. Weatherwise 12:57–60
Pepi J (1987) The summer simmer index. Weatherwise 40:143–145
Reffat RM, Harkness EL (2001) Environmental comfort criteria: weighting and intergration. J Perform Constr Facil 15(3):104–108
Microsystems S (2011) Home of sun spot world [Online]. Available: http://www.sunspotworld.com/
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Rawi, M.I.M., Al-Anbuky, A. Wireless sensor networks and human comfort index. Pers Ubiquit Comput 17, 999–1011 (2013). https://doi.org/10.1007/s00779-012-0547-9
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DOI: https://doi.org/10.1007/s00779-012-0547-9