Abstract
The quality of air that we breathe is one of the more serious environmental challenges that the government faces all around the world. It is a matter of concern for almost all developed and develo** countries. The National Air Quality Index (NAQI) in India was first initiated and unveiled by the central government under the Swachh Bharat Abhiyan (Clean India Campaign). It was launched to spread cleanliness, and awareness to work towards a clean and healthy environment among all citizens living in India. This index is computed based on values obtained by monitoring eight types of pollutants that are known to commonly permeate around our immediate environment. These are particulate matter PM10; particulate matter PM2.5; nitrogen dioxide; sulfur dioxide; carbon monoxide; lead; ammonia; and ozone. Studies conducted have shown that almost 90% of particulate matters are produced from vehicular emissions, dust, debris on roads, and industries and from construction sites spanning across rural, semi-urban, and urban areas. While the State and Central governments have devised and implemented several schemes to keep air pollution levels under control, these alone have proved inadequate in cases such as the Delhi region of India. Internet of Things (IoT) offers a range of options that do extends into the domain of environmental management. Using an online monitoring system based on IoT technologies, users can stay informed on fluctuating levels of air pollution. In this paper, the design of a low-price pollution measurement kit working around a dust sensor, capable of transmitting data to a cloud service through a Wi-Fi module, is described. A system overview of urban route planning is also proposed. The proposed model can make users aware of pollutant concentrations at any point of time and can also act as useful input towards the design of the least polluted path prediction app. Hence, the proposed model can help travelers to plan a less polluted route in urban areas.
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References
Ahmedabad Municipal Corporation, Indian Institute of Tropical Meteorology – SAFAR, Indian Institute of Public Health, Gandhinagar, Natural Resources Defense Council (2017) Protecting health from increasing air pollution in Ahmedabad. Supporting Research and Analysis for the Ahmedabad Air Information & Response (AIR) Plan. Issue brief, 1 - 40
Arling J, O’Connor K, Mercieca M (2010) Air quality sensor network for Philadelphia - Data validation. 1-7. https://www.fijnstofmeter.com/documentatie/Data-Validation.pdf. Accessed on 3rd Jun 2019
Benammar M, Abdaoui A, Ahmad SHM, Touati F, Kadri A (2018) A modular iot platform for real-time indoor air quality monitoring. Sensors. 18(2):581. https://doi.org/10.3390/s18020581
Brienza S, Galli A, Anastasi G, Bruschi P (2015) A Low-cost sensing system for cooperative air quality monitoring in urban areas. Sensors. 15:12242–12259. https://doi.org/10.3390/s150612242
Castell N, Kobernus M, Liu HY, Schneider P, Lahoz W, Berre AJ, Noll J (2015) Mobile technologies and services for environmental monitoring: the citi-sense-mob approach. Urban Clim 14(3):370–382. https://doi.org/10.1016/j.uclim.2014.08.002
Central Pollution Control Board (2014-15) Control of urban pollution series: CUPS/82/2014-15. Ministry of Environment, Forest and Climate Change, Government of India http://www.indiaenvironmentportal.org.in/files/file/Air Quality Index.pdf. Accessed 15th Mar 2019
Central Pollution Control Board (2019) National air quality index. Ministry of Environment, Forest and Climate Change, Government of India. https://app.cpcbccr.com/AQI_India/. Accessed 27th Jul 2019
DIY Projects (2017) Calculate the air quality index (IAQ, IQA) with a DSM501 on Arduino or ESP8266. Diyprojects.https://diyprojects.io/calculate-air-quality-index-iaq-iqa-dsm501-arduino-esp8266/#.XYCdcGbh VPZ. Accessed on 22nd Apr 2019
Duvall RM, Long RW, Beaver MR, Kronmiller KG, Wheeler ML, Szykman JJ (2016) Performance evaluation and community application of low-cost sensors for ozone and nitrogen dioxide. Sensors. 16(10):1698. https://doi.org/10.3390/s16101698
Dye T, Graham A, Hafner H (2016) Air sensor study design details matter. Air Waste Manag Assoc Mag Environ Manag:1–5
EPA (2017) What is particle pollution? United States Environment Protection Agency. https://www.epa.gov/pmcourse/what-particle-pollution. Accessed 20th Jun 2019
EPA (2018) Introduction to indoor air quality. United States Environmental Protection Agency. https://www.epa.gov/indoor-air-quality-iaq/introduction-indoor-air-quality. Accessed 20th Jun 2019
Espressif Systems (2018) Espressif. WikiDevi. https://wikidevi.com/wiki/Espressif. Accessed on 22nd Apr 2019
Fazziki AE, Benslimane D, Sadiq A, Ouarzazi J, Sadgal M (2017) An agent based traffic regulation system for the roadside air quality control. IEEE Access Sp Sec Heterogeneous Crowdsourced Data Analytics 5:13192–13201. https://doi.org/10.1109/ACCESS.2017.2725984
Mansour S, Nasser N, Karim L, Ali A (2014) Wireless sensor network-based air quality monitoring system. Int Conf Comp, Netw Comm (ICNC). https://doi.org/10.1109/ICCNC.2014.6785394
MediBulletin Bureau (2019) Air pollution mask market in India will grow by over 100% by 2023. https://medibulletin.com/air-pollution-mask-market-in-india-will-grow-by-over-100-by-2023/. Accessed 25th Aug 2019
Pasha S (2016) Thingspeak based sensing and monitoring system for IoT with Matlab analysis. IJNTR. 2(6):19–23
Peters J, Theunis J, Van Poppel M, Berghmans P (2013) Monitoring PM10 and ultrafine particles in urban environments using mobile measurements. Aerosol Air Qual Res 13:509–522. https://doi.org/10.4209/aaqr.2012.06.0152
Reuters (2019) New Delhi is world’s most polluted capital. https://www.reuters.com/article/us-india-pollution-idUSKCN1QM1FH. Accessed 20th Jun 2019
Spinelle L, Gerboles M, Villani MG, Aleixandre M, Bonavitacola F (2017) Field calibration of a cluster of low-cost commercially available sensors for air quality monitoring. Part B: NO, CO and CO2. Sensors Actuators B Chem 238:706–715. https://doi.org/10.1016/j.snb.2016.07.036
WHO (2003) Health aspects of air pollution with particulate matter, ozone, and nitrogen dioxide. Report on a WHO Working Group. EUR/03/5042688, 1 – 94
WHO (2018a) Ambient (outdoor) air quality and health. World Health Organization. Fact sheet https://www.who.int/news-room/fact-sheets/detail/ambient-(outdoor)-air-quality-and-health. Accessed 27th Jun 2019
WHO (2018b) WHO Global urban ambient air pollution database. World Health Organization. http://www.who.int/airpollution/data/cities/en/. Accessed 27th Jun 2019
Yang X, Yang L, Zhang J (2017) A WiFi-enabled indoor air quality monitoring and control system: the design and control experiments. 13th IEEE Int Conf Cont Auto (ICCA). https://doi.org/10.1109/ICCA.2017.8003185
Zahmatkesh H, Saber M, Malekpour M (2015) A new method for urban travel route planning based on air pollution sensor data. Spl. Issue of Current World Env. 10 (Special issue 1), 699 – 704. https://doi.org/10.12944/CWE.10.Special-Issue1.83
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Deep, B., Mathur, I. & Joshi, N. Coalescing IoT and Wi-Fi technologies for an optimized approach in urban route planning. Environ Sci Pollut Res 27, 34434–34441 (2020). https://doi.org/10.1007/s11356-020-09477-7
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DOI: https://doi.org/10.1007/s11356-020-09477-7