Ebook: Indoor Air Quality Assessment for Smart Environments

Indoor air pollution (IAP) has been a rising concern for populations in developed and developing nations over the decades. Indoor air quality significantly influences people’s general health and well-being since they spend most of their time inside, whether at home or work. According to health statistics, about 95% of the world’s population suffers from one or more acute or chronic health concerns, making maintaining an active lifestyle difficult. Unfortunately, respiratory and cardiovascular diseases have become the primary concerns of the general public. Furthermore, most of this healthcare burden is driven by poor indoor air quality and repeated exposure to dangerous pollutant concentration levels. Pollution-related health problems can contribute to increased absenteeism and lost productivity worldwide.

Several researchers have made significant breakthroughs in air quality control to help building occupants live in healthy environments. These efforts have resulted in several breakthroughs in the development of smart environments. The active involvement of emerging technologies in this problem domain is expected to reduce pollution exposure and healthcare expenditures. The Internet of Things (IoT) and Wireless Sensor Networks (WSN)-based intelligent building management systems can assist with real-time monitoring of pollutants that cause poor indoor air quality (IAQ). These smart environmental monitoring systems can send out rapid notifications to occupants and automate ventilation as necessary. Furthermore, artificial intelligence AI-based models can aid in the timely forecasting of changing pollutant concentration levels, allowing building occupants to take necessary precautions to prevent harmful exposure. The unique mix of new technologies for IAQ management and evaluation in smart environments provides for immediate feedback and response. However, there are several obstacles to overcome in establishing intelligent environmental management solutions for commercial and residential buildings.

This book explores the IAQ problem domain while also highlighting the field’s potential challenges, gaps, and opportunities. As the title suggests, it allows for assessing indoor air quality in smart environments using emerging technologies. The chapters in this book were written by various field experts from different corners of the world, and they address significant elements of IAQ management. The following is the outline of the book:

Chapter 1 explores the definition, current state of the art, and IoT/AI applications in the subject of indoor air quality. The authors cover IAQ management issues such as regulation, current measurement methodologies, and the possible integration of IoT and AI for indoor environment management. The book also describes how emerging technologies can promise outstanding returns to the communities in enhanced public health and well-being.

Chapter 2 focuses on the indoor environmental sensing technologies for occupant health and comfort. The research aims to provide an in-depth systematic review of various sensing technologies pertaining to indoor air quality, thermal conditions, acoustic comfort, odour, illumination, and vibrational disturbances. The chapter identified four potential research gaps in the problem domain, including cost-effectiveness, data interface and privacy, sensor range and positioning, subjective interactions and occupant expectations.

Chapter 3 summarizes the computational aids, automated solutions, and machine learning-based methods to smart environmental management. The main goal of this study is to critically analyze the available technologies based on IoT, cloud computing, and fuzzy logic controllers to forecast IAQ levels. The authors explored a variety of sensors in the context of IAQ, including metal oxide semiconductors, electrochemical cells, and infrared modules.

Chapter 4 presented an experimental analysis and risk assessment for real-time IAQ monitoring based on Zigbee-based wireless smart devices. Using Xbee wireless transmission modules, a microcontroller board, and low-cost IAQ sensors, the author designed an IoT-based portable device. Several important IAQ metrics, such as PM_2.5, NO₂, SO₂, CO, and O₃, were used to evaluate the system’s performance.

Chapter 5 provided a review in the context of IAQ while focusing on the observations made from green and smart hospitals. This chapter aims to determine the role of emerging technologies in creating a healthy indoor environment at green hospitals. This approach has the potential to encourage the development of green buildings in a variety of sectors, hence improving occupant comfort and well-being.

Chapter 6 performs an evaluation of Nano building products for reducing health risks in smart IAQ management. The authors in this chapter examined the potential effects of nanomaterials in sustainable building design and user health. This research sheds light on the need for appropriate nanomaterial selection for healthy building environments.

Chapter 7 describes the optimization options for household ventilation using an improved cookstove to enhance IAQ levels and public health. The authors reviewed several existing studies to gather scientific evidence in relation to the use of improved cookstoves to reduce the exposure of degraded air pollution levels for the building occupants.

We hope that the chapters included in this book will provide deep insights into the IAQ evaluation, management, and assessment using potential technologies. This book will work as a source of knowledge and information for upcoming researchers, field experts, policymakers, public health experts, and government agencies enhancing building air quality at different levels. It will also guide building occupants to take necessary measures to handle the built environment and ventilation arrangements.

This book would not have been accomplished without the contributions of the exceptional authors, professional reviewers, and IOS Press’s supporting editorial staff. We congratulate all the contributors for their valuable efforts in submitting articles and presenting potential findings to the scientific world. Furthermore, we thank the reviewers for their timely evaluation, comments, feedback, and recommendations on submitted chapters. Finally, we would like to express our gratitude towards Dr. Juan Carlos Augusto, the book series editor, for his consistent and unwavering support throughout this journey.

Chandigarh, India, Jagriti Saini

Chandigarh, India, Maitreyee Dutta

Coimbra, Portugal, Gonçalo Marques

Melbourne, Australia, Malka N. Halgamuge

Atmospheric pollution is the leading environmental risk for human health, with particular emphasis on indoor environments, due to people spending more than 90% of their time indoors. Higher pollution levels at indoor than outdoor locations have been reported by scientific studies, thereby sustaining the need for developing air quality studies in indoor environments worldwide. In this sense, this chapter aims to provide state of art on indoor air quality, encompassing aspects such as legislation, new and current measuring methodologies, and potential applications of the internet of things (IoT) and artificial intelligence (AI) in indoor environment management. As a relevant conclusion of this chapter, the IoT and AI implementation on indoor air quality management may result in an outstanding profit for citizens in terms of Public Health. Its versatility would easy a global solution for controlling air quality in indoor spaces. Nonetheless, in order to enforce this actuation, the betterment of the performance of IoT and AI tools should be addressed as a future challenge, mainly focusing on sensor devices, connectivity, network security or privacy, offering exciting opportunities to control indoor air quality.

Sensing technologies are essential parts of the smart building paradigm. In recent years, an increasing number of research studies are focusing on using sensing technologies to understand the influences of indoor environmental conditions on the occupant’s health and comfort. Such studies provide a critical perspective on improved human-building interactions and optimized building operations. This research aims to provide a systematic literature review of various sensing techniques and their applications in improving occupant well-being. The authors consulted the guideline put forward by the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE), ASHRAE Guideline 10-2016, as a framework to categorize different research studies. This research summarizes and discusses both academic and applied studies pertaining to indoor air quality, acoustic comfort, thermal conditions, illumination, odor, and vibrational disturbances. The review results show that, in the built environment, using sensing technologies to mitigate factors disturbing occupant well-being is critical but relevant research is still in its early stage, and most of the current research has focused on indoor air quality and thermal condition. This chapter has identified four main research gaps, 1) cost-effectiveness, 2) sensor range and positioning, 3) data interface and privacy, and 4) occupant expectations and subjective interactions, and provided recommendations for future research.

Indoor air quality (IAQ) is among the topmost environmental hazards associated with the health of human beings. The concentrations of indoor pollutants could be several times more than outdoors. Increasing environmental pollution and global warming are also responsible for climate change. Variations in climatic conditions also add to the worsening of IAQ. The majority of time is spent indoors and adequate ventilation, thermal performance and desirable IAQ are important parameters of concern in indoor settings. Usage of HVAC (heating, ventilation, air conditioning) equipment accounts for the huge consumption of energy and reduced energy consumption can be met by reduced air circulation leading to more airtight buildings which compromise the air quality and health of inhabitants. Several strategies have been devised and being implemented to monitor indoor air quality. Smart environments are insidious systems consisting of integrable net-aware devices. Smart environments are augmented with computational resources providing information and services when and where needed. Over the last few years, IAQ monitoring has developed into smart environment monitoring (SEM) which is based on the internet of things (IoT) and the development of sensor technology. This chapter is an attempt to summarize the automated, computational aids and machine learning techniques that can predict the IAQ in smart environment. It is imperative to know the pollutants and factors governing the IAQ and the chapter has critically analyzed the available technological interventions based on IoT like sensors, Fuzzy logic controller and cloud computing technology which aid in the prediction of air quality in smart environment. Different types of sensors including infrared and electrochemical cells, Metal oxide semiconductor (MOS) gas sensor along with their principle has been discussed in context to IAQ. Recent developments in the field like the usage of the fuzzy logic controller for the calculation of air quality index by combining PM₁₀, PM_2.5, CO, and NO₂ etc. has also been explored. The information can be utilized in dynamic situations to suggest alternative methods https://worldpopulationreview.com/world-cities/lucknow-population for the improvement of air quality which can be influenced by artificial intelligence and machine learning for futuristic predictions. However, there are some challenges as well including the development of systems working on a real-time basis and evaluation of the impact of different pollutants in diverse geographic conditions and variable living set-ups by highly accurate and calibrated systems. Nevertheless, as compared to the conventional solutions which predict IAQ instantly, the computational predictions furnish futuristic data and imminent crucial changes in the indoor air quality to implement anticipatory measures to prevent hazardous health impacts. Nevertheless there are several challenges like data security, data conversion, and connectivity issues etc. which have been discussed in the chapter.

This chapter deals with the development of a smart real-time indoor (offices and family homes) air quality monitoring device based on Internet of Things (IoT). Environmental data from the sensor nodes are sent over the ZigBee wireless communication protocol, and after collection are subjected to careful statistical analysis for exposure risk assessment. The free XCTU platform application in interaction with the XBee modules is used to visualize real-time temporal evolution of the measured data. This portable device is composed of a microcontroller board, XBee wireless transmission modules, and some low-cost air pollutant sensors including particulate matter (PM_2.5) and toxic gas (ground-level ozone O₃, carbon monoxide CO, sulfur dioxide SO₂, nitrogen dioxide NO₂) sensors. Particular attention is paid to indoor air quality in this chapter due to the long-term occupation of confined spaces by people. The results of measurements taken from September 21 to October 22, 2020, in two different confined spaces (home and office), in the city of Yaoundé-Cameroon, gave maximum exposure rates of 13.06 µg/m³ (home) and 10.71 µg/m³ (office) for PM_2.5; 18.65 ppm (office) and 17.72 ppm (home) for SO₂; 4.97 ppm (office) and 7.49 ppm (home) for NO₂; 2.42 ppm (office) and 1.30 ppm (home) for O₃ and, 18.03 ppm (office) and 13.66 ppm (home) for CO. Thus, both office and home spaces gave an internal Air Quality Index (AQI) lower than 50 and an Air Quality Health Index (AQHI), less than 1. The values are low, very varied but still acceptable compared to the WHO standard values. This is due to the diversity of potential sources of pollution which are the number of inhabitants of the confined space, the gas emissions of the installed devices and the intake of outside air. From the results obtained, it emerges that in addition to its low-cost and its flexibility, the proposed device exhibits interesting performance in terms of reliability and global functionality.

With the digital age, notable transformations have been experienced in all areas of society. Innovations from technological developments have changed user requirements. Architecture aiming to respond to user needs has been one of the main areas where transformations are seen. Technological advancements starting with the Industrial Revolution have brought many problems such as environmental pollution, depletion of natural resources. They have also provided opportunities to users. Consequently, sustainability and green thinking in architecture have gained importance. Integrating technology into this understanding has become possible to design green and smart buildings. Green buildings are environmentally friendly structures that use natural resources efficiently and minimize waste while providing healthy environmental conditions to their users. On the other hand, smart buildings are structures designed with automation systems using technology, saving labour and resource consumption while providing user comfort. In this respect, smart buildings respond to green hospitals’ environmentally friendly and healthy design needs with their technological infrastructure. This study, which examines green and smart hospital buildings in the context of indoor air quality, aims to determine the role of smart building technologies in supporting and controlling healthy indoor air quality in green hospitals.

Smart technologies create controlled and sustainable systems to meet rapid urbanisation and various needs arising from this urbanisation throughout the world. Some of these systems are realised with nano-technology. Especially in the construction industry, nano products are used in smart building and smart material applications. Some of the products developed with this technology are also used to control indoor air. However, it is seen that nano-sized materials produced artificially with nano-technology have possible health risks on the environment and human health due to various unknowns. In addition, nanomaterials in the content of nanoproducts, can enter the human body through respiration, ingestion and skin contact due to their very small size. This chapter examined the possible effects of nanomaterials in sensors and healing nanoproducts produced to control indoor air quality on user health. The role of nano-smart materials in sustainable building design was evaluated. With the data obtained in this context, it aims to reveal the positive and negative situations caused by the use of nanoproducts to benefit from their improved properties and allow users to make choices considering this information.

Several research attempts were made but the World Health Organization’s (WHO) intermediate indoor environmental quality guidelines were not achieved targets by replacing traditional biomass chulhas with cleaner cookstoves in many parts of the world. Millions of deaths are still occurring due to uncomfortable indoor air, which is well recognized as one of the foremost causes of death reported in the recent estimates of the global burden of diseases. However, health benefits can be expected through the extensive use of improved cookstoves (ICSs) in households with the support of better ambient air quality. Optimization of indoor ventilation status may come out as a significant addition to ICSs in mitigating indoor air pollution exposure for better public health. It is worthwhile to note that the WHO recommends the reduction of Particulate Matter (PM_2.5) and Carbon Monoxide (CO) exposure in the perspective of good public health. Uses of solid biomass cooking fuels have been steadily decreasing in developing countries for the last decade. In spite of that, almost 50 percent of the world population is still being exposed to the indoor air pollution produced by solid fuel burning. The main purpose of this paper is to review the existing scientific evidences concerning improved cookstoves with household ventilation and health improvement. Keeping the above facts in mind, current indoor air quality research should focus on stringent and periodic exposure assessment with modified ventilation and ICSs to improve public health and well-being.

Indoor air quality (IAQ) has been a critical matter of concern for public health, environmental, and government agencies over the years due to its negative influence on building occupants. The outcomes of degraded air quality levels have been a challenge not just for developing countries; it puts the potential burden of disease on developed nations. Healthcare cost in the United States is reported to be $150 billion because of air pollution-related consequences. Furthermore, increased air pollutants exposure causes 412,000 premature deaths in Europe each year. Therefore, the research communities are expected to work actively to find potential solutions to IAQ assessment and management. Fortunately, the latest technologies such as the Internet of Things and Artificial Intelligence show great potential in developing smart environments that permit real-time assessment of IAQ levels from building premises. Such systems can be useful to create healthy living conditions in residential and commercial buildings while promising enhanced outcomes for public health management. This chapter provides conclusive thoughts on how IAQ assessment plays an essential role in building smart environments while throwing light on the effective utilization of emerging technologies to create healthy living environments. Along with the summary of potential contributions made by various field experts to address challenges in this problem domain, this chapter also provides insights into future scopes in IAQ assessment for smart environments.