Relevant bibliographies by topics / Smart city, air quality, low-cost sensors

Academic literature on the topic 'Smart city, air quality, low-cost sensors'

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Published: 10 March 2023

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Journal articles on the topic "Smart city, air quality, low-cost sensors"

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Morris, E., X. Liu, A. Manwar, D. Y. Zang, G. Evans, J. Brook, B. Rousseau, C. Clark, and J. MacIsaac. "APPLICATION OF DISTRIBUTED URBAN SENSOR NETWORKS FOR ACTIONABLE AIR QUALITY DATA." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences VI-4/W2-2020 (September 15, 2020): 119–26. http://dx.doi.org/10.5194/isprs-annals-vi-4-w2-2020-119-2020.

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Abstract. Ambient air pollution continues to be a major human health burden around the world. Cities with existing smart data infrastructure, and those with smart city aspirations, would benefit from the integration of real-time data from an air quality sensor network. AirSENCE™ is one such sensor which monitors eight common pollutants at low cost. It has been deployed in Canada in cities of the Greater Toronto Area, e.g. the City of Oshawa, to augment the existing urban data network and study the impacts of traffic flow and land usage on air quality. Results reveal that distributed sensors are highly useful for detecting localized pollution events that would otherwise go undetected, providing policymakers with a valuable, actionable data for protecting public health. Coupling air quality sensors with other smart city data (traffic monitors in this case) was shown to provide a more comprehensive representation of how air pollutant levels are affected by human activity, which can better inform city planning decisions.
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Stavroulas, Iasonas, Georgios Grivas, Panagiotis Michalopoulos, Eleni Liakakou, Aikaterini Bougiatioti, Panayiotis Kalkavouras, Kyriaki Fameli, Nikolaos Hatzianastassiou, Nikolaos Mihalopoulos, and Evangelos Gerasopoulos. "Field Evaluation of Low-Cost PM Sensors (Purple Air PA-II) Under Variable Urban Air Quality Conditions, in Greece." Atmosphere 11, no. 9 (August 29, 2020): 926. http://dx.doi.org/10.3390/atmos11090926.

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Recent advances in particle sensor technologies have led to an increased development and utilization of low-cost, compact, particulate matter (PM) monitors. These devices can be deployed in dense monitoring networks, enabling an improved characterization of the spatiotemporal variability in ambient levels and exposure. However, the reliability of their measurements is an important prerequisite, necessitating rigorous performance evaluation and calibration in comparison to reference-grade instrumentation. In this study, field evaluation of Purple Air PA-II devices (low-cost PM sensors) is performed in two urban environments and across three seasons in Greece, in comparison to different types of reference instruments. Measurements were conducted in Athens (the largest city in Greece with nearly four-million inhabitants) for five months spanning over the summer of 2019 and winter/spring of 2020 and in Ioannina, a medium-sized city in northwestern Greece (100,000 inhabitants) during winter/spring 2019–2020. The PM2.5 sensor output correlates strongly with reference measurements (R2 = 0.87 against a beta attenuation monitor and R2 = 0.98 against an optical reference-grade monitor). Deviations in the sensor-reference agreement are identified as mainly related to elevated coarse particle concentrations and high ambient relative humidity. Simple and multiple regression models are tested to compensate for these biases, drastically improving the sensor’s response. Large decreases in sensor error are observed after implementation of models, leading to mean absolute percentage errors of 0.18 and 0.12 for the Athens and Ioannina datasets, respectively. Overall, a quality-controlled and robustly evaluated low-cost network can be an integral component for air quality monitoring in a smart city. Case studies are presented along this line, where a network of PA-II devices is used to monitor the air quality deterioration during a peri-urban forest fire event affecting the area of Athens and during extreme wintertime smog events in Ioannina, related to wood burning for residential heating.
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Penza, Michele, Domenico Suriano, Valerio Pfister, Mario Prato, and Gennaro Cassano. "Wireless Sensors Network Monitoring of Saharan Dust Events in Bari, Italy." Proceedings 2, no. 13 (December 5, 2018): 898. http://dx.doi.org/10.3390/proceedings2130898.

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A sensors network based on 8 stationary nodes distributed in Bari (Southern Italy) hasbeen deployed for urban air quality monitoring during advection events of Saharan dust in theperiod 2015–2017. The low-cost sensor-systems have been installed in specific sites (buildings,offices, schools, streets, airport) to assess the PM10 concentration at high spatial and temporalresolution in order to supplement the expensive official air monitoring stations for citizen sciencepurposes. Continuous measurements were performed by a cost-effective optical particle counter(PM10), including temperature and relative humidity sensors. They are operated to assess theperformance during a long-term campaign (July 2015–December 2017) of 30 months for smart citiesapplications. The sensor data quality has been evaluated by comparison to the reference data of the9 Air Quality Monitoring Stations (AQMS), managed by local environmental agency (ARPA-Puglia)in the Bari city.
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Chapman, Lee, Catherine L. Muller, Duick T. Young, Elliott L. Warren, C. S. B. Grimmond, Xiao-Ming Cai, and Emma J. S. Ferranti. "The Birmingham Urban Climate Laboratory: An Open Meteorological Test Bed and Challenges of the Smart City." Bulletin of the American Meteorological Society 96, no. 9 (September 1, 2015): 1545–60. http://dx.doi.org/10.1175/bams-d-13-00193.1.

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Abstract The Birmingham Urban Climate Laboratory (BUCL) is a near-real-time, high-resolution urban meteorological network (UMN) of automatic weather stations and inexpensive, nonstandard air temperature sensors. The network has recently been implemented with an initial focus on monitoring urban heat, infrastructure, and health applications. A number of UMNs exist worldwide; however, BUCL is novel in its density, the low-cost nature of the sensors, and the use of proprietary Wi-Fi networks. This paper provides an overview of the logistical aspects of implementing a UMN test bed at such a density, including selecting appropriate urban sites; testing and calibrating low-cost, nonstandard equipment; implementing strict quality-assurance/quality-control mechanisms (including metadata); and utilizing preexisting Wi-Fi networks to transmit data. Also included are visualizations of data collected by the network, including data from the July 2013 U.K. heatwave as well as highlighting potential applications. The paper is an open invitation to use the facility as a test bed for evaluating models and/or other nonstandard observation techniques such as those generated via crowdsourcing techniques.
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Twahirwa, Evariste, James Rwigema, and Raja Datta. "Design and Deployment of Vehicular Internet of Things for Smart City Applications." Sustainability 14, no. 1 (December 24, 2021): 176. http://dx.doi.org/10.3390/su14010176.

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A novel computing paradigm, called the Internet of things emerged a few years ago. IoT is materialized by connecting both real and digital worlds together. The deployment of IoT in vehicular networks has introduced a new vehicular communication technology-themed vehicular internet of things (V-IoT). With the introduction of miniaturized sensors and actuators, V-IoT has demonstrated the ability to improve the level of urban transport systems through the development and deployment of low-cost but powerful technologies which seamlessly upgrade the level of smart transportation in urban environments. In this research article, we have presented the features of V-IoT that encompass both the benefits and potential challenges of the technology. Low-cost IoT prototypes have been built and tested for numerous functions in vehicular environments. The monitored parameters include air, road conditions such as traffics flow sizes, air quality, weather parameters, and signal status in terms of Received signal strength indicator, and Signal noise ratio for both road and intra-vehicular environments. Devices are implemented at every IoT architectural layer and tested on a web-based IoT front-end application using different protocols like LoRaWAN. Two LoRa sensors have been deployed in the public bus to monitor some of the mentioned parameters on a real-time basis and historical data could be retrieved through the developed web-based dashboard. Simplistic algorithms are implemented for both real-time and historical data demonstration.
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Shakhov, Vladimir, Andrei Materukhin, Olga Sokolova, and Insoo Koo. "Optimizing Urban Air Pollution Detection Systems." Sensors 22, no. 13 (June 24, 2022): 4767. http://dx.doi.org/10.3390/s22134767.

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Air pollution has become a serious problem in all megacities. It is necessary to continuously monitor the state of the atmosphere, but pollution data received using fixed stations are not sufficient for an accurate assessment of the aerosol pollution level of the air. Mobility in measuring devices can significantly increase the spatiotemporal resolution of the received data. Unfortunately, the quality of readings from mobile, low-cost sensors is significantly inferior to stationary sensors. This makes it necessary to evaluate the various characteristics of monitoring systems depending on the properties of the mobile sensors used. This paper presents an approach in which the time of pollution detection is considered a random variable. To the best of our knowledge, we are the first to deduce the cumulative distribution function of the pollution detection time depending on the features of the monitoring system. The obtained distribution function makes it possible to optimize some characteristics of air pollution detection systems in a smart city.
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Marek, L., M. Campbell, M. Epton, M. Storer, and S. Kingham. "REAL-TIME ENVIRONMENTAL SENSORS TO IMPROVE HEALTH IN THE SENSING CITY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B2 (June 9, 2016): 729–33. http://dx.doi.org/10.5194/isprs-archives-xli-b2-729-2016.

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The opportunity of an emerging smart city in post-disaster Christchurch has been explored as a way to improve the quality of life of people suffering Chronic Obstructive Pulmonary Disease (COPD), which is a progressive disease that affects respiratory function. It affects 1 in 15 New Zealanders and is the 4th largest cause of death, with significant costs to the health system. While, cigarette smoking is the leading cause of COPD, long-term exposure to other lung irritants, such as air pollution, chemical fumes, or dust can also cause and exacerbate it. Currently, we do know little what happens to the patients with COPD after they leave a doctor’s care. By learning more about patients’ movements in space and time, we can better understand the impacts of both the environment and personal mobility on the disease. This research is studying patients with COPD by using GPS-enabled smartphones, combined with the data about their spatiotemporal movements and information about their actual usage of medication in near real-time. We measure environmental data in the city, including air pollution, humidity and temperature and how this may subsequently be associated with COPD symptoms. In addition to the existing air quality monitoring network, to improve the spatial scale of our analysis, we deployed a series of low-cost Internet of Things (IoT) air quality sensors as well. The study demonstrates how health devices, smartphones and IoT sensors are becoming a part of a new health data ecosystem and how their usage could provide information about high-risk health hotspots, which, in the longer term, could lead to improvement in the quality of life for patients with COPD.
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Marek, L., M. Campbell, M. Epton, M. Storer, and S. Kingham. "REAL-TIME ENVIRONMENTAL SENSORS TO IMPROVE HEALTH IN THE SENSING CITY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B2 (June 9, 2016): 729–33. http://dx.doi.org/10.5194/isprsarchives-xli-b2-729-2016.

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The opportunity of an emerging smart city in post-disaster Christchurch has been explored as a way to improve the quality of life of people suffering Chronic Obstructive Pulmonary Disease (COPD), which is a progressive disease that affects respiratory function. It affects 1 in 15 New Zealanders and is the 4th largest cause of death, with significant costs to the health system. While, cigarette smoking is the leading cause of COPD, long-term exposure to other lung irritants, such as air pollution, chemical fumes, or dust can also cause and exacerbate it. Currently, we do know little what happens to the patients with COPD after they leave a doctor’s care. By learning more about patients’ movements in space and time, we can better understand the impacts of both the environment and personal mobility on the disease. This research is studying patients with COPD by using GPS-enabled smartphones, combined with the data about their spatiotemporal movements and information about their actual usage of medication in near real-time. We measure environmental data in the city, including air pollution, humidity and temperature and how this may subsequently be associated with COPD symptoms. In addition to the existing air quality monitoring network, to improve the spatial scale of our analysis, we deployed a series of low-cost Internet of Things (IoT) air quality sensors as well. The study demonstrates how health devices, smartphones and IoT sensors are becoming a part of a new health data ecosystem and how their usage could provide information about high-risk health hotspots, which, in the longer term, could lead to improvement in the quality of life for patients with COPD.
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Zaripova, Viktoriia, Irirna Petrova, and Yuliya Lezhnina. "Biosensors application for the life systems quality in a smart city." E3S Web of Conferences 135 (2019): 03006. http://dx.doi.org/10.1051/e3sconf/201913503006.

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The article shows that the smart city management systems requires continuous monitoring of environmental parameters (air, soil and water quality, temperature, humidity, toxic impurities, etc.) and the placement of a large number of different sensors, among which biosensors occupy a leading position. The study analyzed patent documents for leading countries of the world (Great Britain, France, Japan, Germany, USA, Russia) and it showed a steady increase in the number of patents on biosensors. The reasons for the growth and continuous expansion of the scope of biosensors are: cost reduction, increased durability, speed, reliability, accuracy and sensitivity; increase in their functionality. The article presents a classification of biosensors indicating the percentage of patents by type of transducer and the number of patents by bioselective elements, as well as a description of an automated system for the synthesis of new biosensor designs based on the energy-information method. Paper is given the resulting solution can be used as a skeletal structure to create new biosensors, or improved using the knowledge base on techniques for improving the technical and operational characteristics of physical and technical effects.
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Lal, Raj M., Kirti Das, Yingling Fan, Karoline K. Barkjohn, Nisha Botchwey, Anu Ramaswami, and Armistead G. Russell. "Connecting Air Quality with Emotional Well-Being and Neighborhood Infrastructure in a US City." Environmental Health Insights 14 (January 2020): 117863022091548. http://dx.doi.org/10.1177/1178630220915488.

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Cities in the United States have announced initiatives to become more sustainable, healthy, resilient, livable, and environmentally friendly. However, indicators for measuring all outcomes related to these targets and the synergies between them have not been well defined or studied. One such relationship is the linkage between air quality with emotional well-being (EWB) and neighborhood infrastructure. Here, regulatory monitoring, low-cost sensors (LCSs), and air quality modeling were combined to assess exposures to PM2.5 and traffic-related NOx in 6 Minneapolis, MN, neighborhoods of varying infrastructure parameters (median household income, urban vs suburban, and access to light rail). Residents of the study neighborhoods concurrently took real-time EWB assessments using a smart phone application, Daynamica, to gauge happiness, tiredness, stress, sadness, and pain. Both LCS PM2.5 observations and mobile-source-simulated NOx were calibrated using regulatory observations in Minneapolis. No statistically significant (α = 0.05) PM2.5 differences were found between urban poor and urban middle-income neighborhoods, but average mobile-source NOx was statistically significantly (α = 0.05) higher in the 4 urban neighborhoods than in the 2 suburban neighborhoods. Close proximity to light rail had no observable impact on average observed PM2.5 or simulated mobile-source NOx. Home-based exposure assessments found that PM2.5 was negatively correlated with positive emotions such as happiness and to net affect (the sum of positive and negative emotion scores) and positively correlated (ie, a higher PM2.5 concentration led to higher scores) for negative emotions such as tiredness, stress, sadness, and pain. Simulated mobile-source NOx, assessed from both home-based exposures and in situ exposures, had a near-zero relationship with all EWB indicators. This was attributed to low NOx levels throughout the study neighborhoods and at locations were the EWB-assessed activities took place, both owing to low on-road mobile-source NOx impacts. Although none of the air quality and EWB responses were determined to be statistically significant (α = 0.05), due in part to the relatively small sample size, the results are suggestive of linkages between air quality and a variety of EWB outcomes.
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Dissertations / Theses on the topic "Smart city, air quality, low-cost sensors"

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Young, Matthew W. "Towards the Integration of Low-cost Sensors into Smart Building Systems for Indoor Air Quality Purposes." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1573798188009717.

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Cavaliere, Alice. "Low-cost air quality stations and control network for a smart city." Doctoral thesis, 2018. http://hdl.handle.net/2158/1114106.

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A Smart City (SC) is a city structured and organized with sensors and information networks so that its resources can be accessed through an efficient telematic infrastructure. Prefiguring urban settings where new technologies enable and interact with individuals is one of the most fascinating research themes and deepest issues in the field of urban sciences. The environmental monitoring and protection in urban context plays a crucial role in people’s physical, mental and social well-being. Aimed at investigating the usefulness and potential of next generation monitoring systems for higher temporal-spatial resolution air quality measurements, this thesis addresses the challenging issue of improving the reliability of low-cost air quality sensor by performing both laboratory and field testing.
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Book chapters on the topic "Smart city, air quality, low-cost sensors"

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Gitahi, Joseph, and Michael Hahn. "Evaluation of Crowd-Sourced PM2.5 Measurements from Low-Cost Sensors for Air Quality Mapping in Stuttgart City." In iCity. Transformative Research for the Livable, Intelligent, and Sustainable City, 225–40. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-92096-8_14.

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AbstractExposure to particulate matter (PM) pollution poses a major risk to the environment and human health. Monitoring PM pollution is thus crucial to understand particle distribution and mitigation. There has been rapid development of low-cost PM sensors and advancement in the field of Internet of Things (IoT) that has led to the deployment of the sensors by technology-aware people in cities. In this study, we evaluate the stability and accuracy of PM measurements from low-cost sensors crowd-sourced from a citizen science project in Stuttgart. Long-term measurements from the sensors show a strong correlation with measurements from reference stations with most of the selected sensors achieving Pearson correlation coefficients of r > 0.7. We investigate the stability of the sensors for reproducibility of measurements using five sensors installed at different height levels and horizontal distances. They exhibit minor variations with low correlation of variation (CV) values of between 10 and 14%. A CV of ≤10% is recommended for low-cost sensors. In a dense network, the sensors enable extraction pollution patterns and trends. We analyse PM measurements from 2 years using space-time pattern analysis and generate two clusters of sensors that have similar trends. The clustering shows the relationship between traffic and pollution with most sensors near major roads being in the same cluster.
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Jacob, Mbarndouka Taamté, Nducol Nasser, Kountchou Noubé Michaux, Tchuente Siaka Yvette Flore, and Saïdou. "Zigbee-Based Wireless Smart Device for Enclosed Space Real-Time Air Quality Monitoring: Experiment, Data Analysis and Risk Assessment." In Indoor Air Quality Assessment for Smart Environments. IOS Press, 2022. http://dx.doi.org/10.3233/aise220005.

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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 (PM2.5) 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 PM2.5; 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.
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Sharma, Navuday, Maurizio Magarini, and Muhammad Mahtab Alam. "Internet of Drones-Enabled Smart Cities." In IoT Architectures, Models, and Platforms for Smart City Applications, 107–33. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-1253-1.ch006.

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Unmanned aerial vehicles (UAVs) are expected to provide data service to users as aerial base stations, as gateways to collect the data from various sensors, and as sensor-mounted aerial platforms deployed in smart cities. The study in this chapter initially starts with the air-to-ground (A2G) channel model. Due to the unavailability of channel parameters for UAVs at low altitudes, measurements were performed using a radio propagation simulator for generalized environments developed using ITU-R parameters. Further, cell coverage analysis is shown with simulation results obtained from the ray tracing. Later, an optimal replacement to UDNs was proposed to support the flash crowds and smart cites known as ultra-dense cloud drone network. This system is advantageous as it offers reduction in total cost of ownership due to its on-demand capability. Further, work is shown on implementing parameters for 5G physical layer with generalized frequency division multiplexing modulation over A2G channel on the UAV network to provide reliable and faster connectivity for ground users and sensors.
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Elsarrag, Esam, and Mohammad Elsarraj. "Post Covid 19: An Innovative System to Supply 100% Treated Fresh Air for Improving City Liveability." In Urban Transition - Perspectives on Urban Systems and Environments [Working Title]. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.101645.

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Prior to COVID-19, densely occupied areas were already suspected of making employees sick. Post-COVID-19, there is an urgent need to improve air quality and ventilation standards shall change. However, any changes to ventilation must consider other negative consequences including energy and health and well-being impacts from thermal discomfort and exposure to pollutants. The need for moving away from traditional energy sources and to find alternate energy sources is undoubtedly one of the primary objectives for a sustainable progress to humankind. The design and construction of buildings in hot-humid climates requires high energy consumption typically for air conditioning due to higher thermal loads. A further increase in ventilation rates will have intensive impact in energy consumption and infrastructure loads. This chapter presents the performance of an innovative fully integrated smart ventilation system with low energy consumption. It is all in one ventilating and air conditioning system that provides efficient, cost-effective, and sustainable cooled fresh air for open or enclosed spaces whilst achieving thermal comfort. Based on the application, it consists of multistages that can dehumidify and cool the air to the required comfort level. The system has shown 50–60% reduction in energy consumption compared with conventional systems.
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Conference papers on the topic "Smart city, air quality, low-cost sensors"

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Penza, Michele, Domenico Suriano, Maria Gabriella Villani, Laurent Spinelle, and Michel Gerboles. "Towards air quality indices in smart cities by calibrated low-cost sensors applied to networks." In 2014 IEEE Sensors. IEEE, 2014. http://dx.doi.org/10.1109/icsens.2014.6985429.

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Krupp, Brian. "Fine-Grained Air Quality Monitoring with Low-Cost Sensors and IoT: Trends, Challenges, and Future Directions." In 2022 7th International Conference on Smart and Sustainable Technologies (SpliTech). IEEE, 2022. http://dx.doi.org/10.23919/splitech55088.2022.9854310.

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Ostermeyer, Georg-Peter, Malte Sandgaard, and Guido Lehne-Wandrey. "Investigation of Particle Dynamics with Real Vehicles and Swarm Sensors." In EuroBrake 2021. FISITA, 2021. http://dx.doi.org/10.46720/6016593eb2021-ebs-006.

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In recent years, the improvement of air quality in Germany, but also worldwide, has increasingly moved into the public focus. Since the turn of the millennium, a significant aspect of improving air quality has been seen in the reduction of household emissions, for example, and in the adjustment of traffic-related emissions. Due to legal requirements, exhaust emissions have been significantly reduced as a result of technological innovations, whereby other emission sources have moved to the fore. In particular, non-exhaust emissions, such as tire abrasion, resuspension of fine dust and brake emissions are major sources of emissions that have a sustained impact on air quality. Air quality monitoring is carried out throughout Europe with high precision and very expensive measuring stations, which are distributed locally to individual locations in a city. Based on this data, measures such as driving bans or road closures are initiated. Due to the high price, a comprehensive and locally high-resolution measurement in a city is not feasible, which means that individual events such as acceleration and braking cannot be detected. In this work, swarm measurements are performed in a controlled environment with the help of low-cost fine dust sensors in order to be able to conclude about individual traffic events. Thereby a temporal and local dynamic of the emitted particles, for example during braking, will be investigated. The aim is to measure the distribution of particles around a vehicle during a specific driving event. A differentiation of the particle concentration will be investigated for different measurement scenarios.
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Reports on the topic "Smart city, air quality, low-cost sensors"

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Hains, Bryant, Rawad Abi Saab, Tylesha Giddings, Hugh Magande, Jenna Grygier, Donghai Liang, Han Gao, Jeremy Sarnat, and Elliott Horner. Field Validation of a Smart Energy Recovery Ventilation System Using Low-Cost Indoor Air Quality Sensors. Office of Scientific and Technical Information (OSTI), March 2021. http://dx.doi.org/10.2172/1772579.

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