A smart indoor air quality sensor network

The indoor air quality (IAQ) has an important impact on public health. Currently, the indoor air pollution, caused by gas, particle, and bio-aerosol pollutants, is considered as the top five environmental risks to public health and has an estimated cost of $2 billion/year due to medical cost and lost productivity. Furthermore, current buildings are especially vulnerable for chemical and biological warfare (CBW) agent contamination because the central air conditioning and ventilation system serve as a nature carrier to spread the released agent from one location to the whole indoor environment within a short time period. To assure the IAQ and safety for either new or existing buildings, real time comprehensive IAQ and CBW measurements are needed. With the development of new sensing technologies, economic and reliable comprehensive IAQ and CBW sensors become promising. However, few studies exist that examine the design and evaluation issues related to IAQ and CBW sensor network. In this paper, relevant research areas including IAQ and CBW sensor development, demand control ventilation, indoor CBW sensor system design, and sensor system design for other areas such as water system protection, fault detection and diagnosis, are reviewed and summarized. Potential research opportunities for IAQ and CBW sensor system design and evaluation are discussed.

[1]  Muhammad A. Al-Zahrani,et al.  Locating Optimum Water Quality Monitoring Stations in Water Distribution System , 2001 .

[2]  Victor Pérez-Abreu,et al.  INDEX OF EFFECTIVENESS OF A MULTIVARIATE ENVIRONMENTAL MONITORING NETWORK , 1996 .

[3]  Jae-Heung Yoon,et al.  Optimal Monitoring Sites Based on Water Quality and Quantity in Water Distribution Systems , 2001 .

[4]  Mohammad S. Al-Homoud,et al.  Effect of ventilation strategies on air contaminant concentrations and energy consumption in buildings , 2001 .

[5]  Gian Carlo Cardinali,et al.  An electronic nose based on solid state sensor arrays for low-cost indoor air quality monitoring applications , 2004 .

[6]  A. Nace,et al.  Optimal Supervision of Drinking Water Distribution Network , 1999 .

[7]  D. Ucinski Optimal measurement methods for distributed parameter system identification , 2004 .

[8]  Kaisa Miettinen,et al.  Nonlinear multiobjective optimization , 1998, International series in operations research and management science.

[9]  Avi Ostfeld,et al.  Optimal Layout of Early Warning Detection Stations for Water Distribution Systems Security , 2004 .

[10]  Avi Ostfeld,et al.  Detecting Accidental Contaminations in Municipal Water Networks , 1998 .

[11]  D. Kolokotsa,et al.  Advanced fuzzy logic controllers design and evaluation for buildings’ occupants thermal–visual comfort and indoor air quality satisfaction , 2001 .

[12]  Che-Ming Chiang,et al.  A study on the comprehensive indicator of indoor environment assessment for occupants’ health in Taiwan , 2002 .

[13]  W. F. Caselton,et al.  Optimal monitoring network designs , 1984 .

[14]  Miguel J. Bagajewicz,et al.  Cost-optimal design of reliable sensor networks , 2000 .

[15]  C. Chao,et al.  Development of a dual-mode demand control ventilation strategy for indoor air quality control and energy saving , 2004 .

[16]  Chang W. Sohn,et al.  Analysis of numerical models for dispersion of chemical/biological agents in complex building environments , 2004 .

[17]  R. C. Wanta,et al.  Design and Interim Meteorological Evaluation of a Community Network for Meteorological and Air Quality Measurements , 1957 .

[18]  Refrigerating ASHRAE handbook of fundamentals , 1967 .

[19]  D. Chmielewski,et al.  On the theory of optimal sensor placement , 2002 .

[20]  Keith Worden,et al.  Optimal sensor placement for fault detection , 2001 .

[21]  Miguel J. Bagajewicz,et al.  Design and upgrade of nonredundant and redundant linear sensor networks , 1999 .

[22]  R. A. Deininger,et al.  Optimal Locations of Monitoring Stations in Water Distribution System , 1992 .

[23]  Zhiqiang Zhai,et al.  Application of CFD to Predict and Control Chemical and Biological Agent Dispersion in Buildings , 2003 .

[24]  Harvey J. Greenberg,et al.  A Multiple-Objective Analysis of Sensor Placement Optimization in Water Networks , 2004 .

[25]  J. E. Janssen,et al.  Ventilation for acceptable indoor air quality , 1989 .

[26]  Y. Lisa Chen,et al.  Sensor system design for building indoor air protection , 2008 .

[27]  Cynthia A. Phillips,et al.  Sensor Placement in Municipal Water Networks , 2003 .

[28]  David T. Grimsrud,et al.  Residential pollutants and ventilation strategies: Volatile organic compounds and radon , 1999 .

[29]  Carlos S. Kubrusly,et al.  Sensors and controllers location in distributed systems - A survey , 1985, Autom..

[30]  William J. Fisk,et al.  Energy Savings in Cleanrooms from Demand-Controlled Filtration , 1996 .

[31]  M. J. Brandemuehl,et al.  The impact of demand-controlled and economizer ventilation strategies on energy use in buildings , 1999 .

[32]  Ming He,et al.  Multiple fuzzy model-based temperature predictive control for HVAC systems , 2005, Inf. Sci..

[33]  John Carrano Chemical and Biological Sensor Standards Study , 2005 .

[34]  Mitthan Lal Kansal,et al.  Identification of Monitoring Stations in Water Distribution System , 1997 .

[35]  Anibal T. de Almeida,et al.  Sensor-based demand-controlled ventilation: a review , 1998 .

[36]  Vitalijus Pavlovas,et al.  Demand controlled ventilation: A case study for existing Swedish multifamily buildings , 2004 .

[37]  Kenneth E. Noll,et al.  Design methodology for optimum dosage air monitoring site selection , 1983 .

[38]  D. Kolokotsa,et al.  Comparison of the performance of fuzzy controllers for the management of the indoor environment , 2003 .

[39]  Song Zhang,et al.  Zeolite-modified microcantilever gas sensor for indoor air quality control , 2003 .

[40]  Yuanhui Zhang,et al.  Indoor Air Quality Engineering , 2004 .

[41]  Shengwei Wang,et al.  Optimal and robust control of outdoor ventilation airflow rate for improving energy efficiency and IAQ , 2004 .

[42]  R. Rengaswamy,et al.  Comprehensive design of a sensor network for chemical plants based on various diagnosability and reliability criteria. 1. Framework , 2002 .

[43]  William J. Batty,et al.  Fuzzy control strategies to provide cost and energy efficient high quality indoor environments in buildings with high occupant densities , 2003 .

[44]  Jeffrey D. Spitler,et al.  An enhanced multizone model and its application to optimum placement of CBW sensors: Discussion , 2002 .

[45]  D. Kolokotsaa,et al.  Genetic algorithms optimized fuzzy controller for the indoor environmental management in buildings implemented using PLC and local operating networks , 2003 .