Integrating IoT and AI for Indoor Air Quality Assessment

Indoor air quality is a major concern for both developed and developing countries. The current populations spend most of their routine time indoors, either at home or office; which makes them susceptible to repeated exposure to hazardous pollutants in the indoor environment. Therefore, it is crucial to find trustworthy ways to monitoring and assessment of these harmful pollutant concentration levels. This chapter provides insights to the potential technologies that can be utilized to design real-time monitoring and assessment systems for indoor environments. Furthermore, it also presents the integration of different technologies to achieve enhanced outcomes.

Over the last decades, environmental pollution has become the main environmental risk to human being health due to the rise regarding waste production, in particular toward the air matrix. At the legislative level, European Directives set air quality objectives to prevent and protect human being health. Nevertheless, the European legislation only applies to outdoor environments, despite people pass ~90% of their time in inside spaces. It exists scientific studies sustain the presence of higher air pollutant levels in indoor than outdoor locations. For this reason, research studies for enlarging knowledge on indoor air quality result priority. Within the previous frame, this chapter aims to provide an indoor air quality benchmark, in terms of potential emission focuses, concentrations, impact on health, and methodologies for measuring air pollutants, focused on indoor air quality managers, control technicians, and potential students. The impact of indoor air quality should be considered at the global level due to several factors, such as indoor pollution is particular for each location, indoor-outdoor air inter-change, and atmospheric pollution is cross-border. The application of new computer tools (IoT and AI) on current and novel measuring air pollution technologies offers a unique chance for inside air quality management.

Bioaerosols, in addition to common gaseous or particulate pollutants, are also important air pollutants that deteriorate indoor air quality. Bioaerosols are the airborne particles present as or originating from living organisms such as fungi, bacteria, and viruses and include toxins, fragments, or waste product from various organisms. In this chapter, the characteristics of indoor bioaerosols are provided. The common type and sources of bioaerosols are summarized. These biological pollutants are commonly generated both by the activities and behaviors of the occupants, and by housing materials and substances that penetrate from the outdoor environment. Fungi and bacteria are the most common bioaerosols present in the indoor environment. After exposure, occupants may experience adverse health outcomes such as infection or allergy. If the indoor environment is severely contaminated, as observed in many places during the COVID-19 pandemic, especially in public areas, a large number of people may be affected by contamination. This chapter also summarizes monitoring and assessment technologies. The monitoring procedure can be chosen and performed according to the objective of the assessment. Advance technologies such as real-time sensor monitoring, Internet of Things, and artificial intelligence have been integrated, but their use for bioaerosols monitoring is still limited as compared to their use for other types of indoor air pollutants. Effective control strategies to reduce the contamination of indoor bioaerosols are also provided in this chapter that could benefit occupants to reduce the contamination and minimize exposure.

Despite being an active topic of discussion since the 1980s, Indoor Air Quality (IAQ) remains an emerging public health topic, with increasing recognition of dangerous health consequences for individuals in confined spaces affected by poor IAQ. IAQ is defined within the broader Scientific Community as the sum of the outdoor air quality and the contaminants emitted from internal sources affecting indoor environments. Because of these dual influences on IAQ, monitoring activities of IAQ should consider the indoor air, the outdoor air, and the interaction between them. Although there are several trends that emphasize actions such as “zero pollution” in outdoor and confined spaces, the main scope of the IAQ assessments should guarantee zero impacts on users’ health. The aim of the chapter is to highlight the user-centrality and to argue how users can live in healthy spaces and the best practices for guaranteeing adequate performances of the indoor spaces, as well as the key role of indoor air assessments and how the user can understand the risks. For this reason, the authors involved in the contribution have multidisciplinary backgrounds referring to air quality in confined spaces, public health, how living and working spaces can influence health status, and building hygiene.

In recent years, the trend has been to move the population from the countryside to the cities. As a result, we spend more and more time indoors. Outside in the fresh air, in our natural environment, we are less and less. This way of life is not only beginning to affect our health, but especially the negative effects of this emerging trend, such as lower performance, stress, etc., are beginning to show. Perception of indoor air quality is a subjective assessment, which can consist of various factors such as the quality of the outdoor air, the volume of air per person in the room, or even the amount of air pollutants. The source of pollutants in the interior can be residents, animals, plants, but also the material from which the building is built. Therefore, health and comfort are vital aspects of the design of buildings designed for people and are the basis of productivity. While the concept of smart and sustainable buildings has received considerable attention in recent decades, more and more attention is now being paid to the design of healthy buildings. The consequence of an unsuitable indoor environment in buildings is the so-called sick building syndrome. One of the solutions for monitoring the indoor environment of buildings is a combination of various sensors detecting various factors of indoor air with melts in combination with the Internet of Things (IoT). To a limited extent, this chapter addresses the internal environment of buildings with factors influencing the internal comfort of using buildings in the context of IoT. The main contribution of this chapter is the summarization of knowledge and the spread of awareness within the addressed issue of the internal environment of buildings in the context of IoT.

Indoor air pollutants in certain environments, such as a damp home or a low-ventilation office, are more concentrated indoors than outdoors. As people spend most of their time indoors, there is a high chance that they are exposed to indoor air pollution. This exposure might lead to adverse health outcomes such as allergies, infection, and respiratory diseases. Therefore, proper indoor environment management is crucial for promoting indoor air quality, consequently benefiting the health and well-being of occupants. In commercial spaces, a lot of people gather and perform various activities together, and higher concentrations of indoor air pollution are generated, which leads to accumulation of pollutants if proper management is not achieved, especially during the COVID-19 pandemic when biological pollutants (i.e., viral particle) can accumulate indoors due to poor ventilation environment. In residential spaces, indoor air quality may worsen due to activities such as cooking, painting, using personal care products, and washing. These activities generate indoor air pollution, thus affecting the health of occupants. In addition, poor air quality in microenvironments apparently affects sleep quality. This chapter proposes a concept of indoor air quality management in commercial and residential spaces including sources and control. Moreover, the management technologies have been summarized varying from a simple technique that can be handled by the occupants to a more complicated technique that requires more equipment and professional skill. The methods provided here can benefit the occupants, especially the occupants living in limited-space residences, such as apartment buildings in urban areas.

In recent decades, the building and scientific research industries have experimented with adaptable facades to meet European energy efficiency standards. Climate adaptive building shells (CABSs) are one of the potential approaches for reaching the sustainability objective in the building industry. However, CABS components frequently fail to satisfy occupant demands, resulting in significant levels of occupant discontent. As a result, when evaluating the facade adaptation for indoor environment quality (IEQ) and occupant satisfaction, comprehensive real-time data collection is critical. Indoor air quality (IAQ) is essential for occupant comfort; however, few studies have focused on this topic. Wireless sensor networks (WSNs) comprised of sensors and actuators, often known as the Internet of Things (IoT), have been incorporated into building systems in recent years. To date, most IoT solutions have been created to adapt to environmental conditions, with lighting and thermal being the primary actuator targets. This research intends to provide a thorough assessment of current IoT advancements for IAQ control to improve occupant satisfaction by stressing the relevance of IAQ domains. In this way, this qualitative research offers an in-depth literature assessment, highlighting the need for more research in this area to improve occupant satisfaction in CABS-designed buildings. Finally, the study proposes an initial framework of indoor air quality monitoring (IAQM) for CABS based on IoT principles. With the integration of this model into the design process of CABS, IAQ can become one of the facade adaptation parameters, improving occupants’ comfort and satisfaction.

Monitoring and control of Indoor Air Quality (IAQ) have become more important, both because people spend more time indoors, especially in crowded public buildings, and because bad air has serious effects on health. Therefore, in this study, a new IAQ monitoring system is proposed that evaluates indoor comfort parameters online to provide an acceptable indoor environment for users. The online web-based, distributed, and fog computing-based monitoring system has been developed in a flexible and scalable fashion, and a distributed architecture has been used, unlike other studies. In the data processing part, a new fuzzy decision tree model is used to analyze independent measurements and environment parameters (CO₂ level, thermal comfort value, number of people, and light intensity) and to obtain IAQ information. In the study, a faculty building of Sakarya University is selected as the testbed to manage case studies and to verify the model. The IAQ monitoring system has been compared with conventional systems in terms of transmission infrastructure. A fuzzy decision model has been proposed as a data processing technique as a result of comparison with fuzzy logic and Artificial Neural Networks (ANNs) under the same scenarios. The obtained results show that the proposed fuzzy decision model has 9–12% better performance than fuzzy logic and 5–7% better than ANN in the same scenarios. In addition, at the end of each case study, a survey with questions about air quality and thermal comfort has been applied to the students in the classroom. The system outputs have been compared to the survey data, and it has been observed that the proposed system produced successful results for classroom air quality.

The poultry is the most consumed meat product in Russia; and its consumption grows constantly. When growing poultry, it is necessary to observe the standards of the admissible content of microorganisms (MCO) in the air. At the microorganisms’ concentration higher than 280 thousand MCO/m³, the diseases incidence grows, and the poultry death rate increases. A special trouble with the air disinfection in livestock premises makes the need to carry it out in the presence of the animals, which reduces the air handling time. In the research, there were analyzed the ways of premises disinfection and chosen the safest and most effective methods to do it. The analysis of the efficiency dependence of a UV radiation source on the air velocity was carried out. Experimental studies were carried out to inactivate pathogenic microflora; comparative measurements were made during operation of one irradiator and several ones. The most effective disinfection methods were found to be the UV radiation and the chemical aerosols use. Based on the study results, for the efficiency improvement of the air disinfection in poultry keeping premises, the substantiation was developed for combining of a UV-irradiator and a chemical aerosol in a single device. The use of the combined effect of the selected methods enables to reduce the required time for the pathogenic microflora inactivation significantly, for example, in the case of the Koch’s bacillus, by 50%.

Air pollution is one of the biggest contributors to the global burden of disease and mortality and contributes to over a million deaths worldwide every year. Short- and long-term exposures to air pollutants, when they are present in high concentration, lead to respiratory illnesses, aggravation of cardiovascular diseases, and premature deaths. The accurate assessment of health risk and impact due to ambient and indoor air pollution is imperative for policymaking, prevention, and rectification efforts. Technological intervention and advancement in data science and modelling predictions could be of use for accurate health risk assessment and exposure to the pollution which includes exposure to small and large populations. Internet of Things includes sensors, smartphones, and air pollution models based on big data sources which are not only used to assess the exposure, but also aid in devising prevention opportunities. Key features of these tools include accessibility, spatial resolution, specific health outcomes associated with pollutants, population exposure, and application. This chapter is a state-of-the-art review that elaborates the attempts and technological interventions and advancements made to address the health risk assessment associated with air pollution and strategies adopted for personalized treatment to avert exacerbation and refractory symptoms. Technological advancement and its involvement may revolutionize the air pollution prediction, exposure, and risk assessment research in the coming time, if they meet the logistical and data science challenges along with the integration of health impact and related risks’ assessment which is linked to the exposure of air pollution.