Real Time Indoor Air Quality Monitoring System with Platform based on IoT

Year 2020, Volume: 7 Issue: 1, 370 - 381, 28.06.2020

Hakan Üçgün , Fatmanur Gömbeci Uğur Yüzgeç , Nesibe Yalçın

https://doi.org/10.35193/bseufbd.730919

Cited By: 3

Abstract

Air pollution is one of the major problems in the world we face today. Air pollution, which has negative effects on human health, climate and ecosystem, increases due to the increase in the amounts of pollutants in the atmosphere and also indoor air pollution. People who spend most of their daily life indoor environments (e.g. homes, offices, schools, hospitals, shopping centers) are affected by harmful gases and particulates in the environment and may have health problems. Living standards in such environments should be kept at optimum values for human life, the factors that may threaten human health should be eliminated, and their effects should be reduced. Thanks to technological developments, it is possible to eliminate such problems with the systems where air quality is determined. Within the scope of this study, IoT based indoor air quality monitoring system has been developed. In the system, Raspberry Pi 3 controller card, temperature, humidity, gas and light sensors are used in the system. The environment data from the sensors has been processed by the control card and then saved to the database. Information about living conditions in the indoor environment can be monitored instantly via web user interface Indoor air quality is calculated using the developed air quality formula and presented to the users. The portable hardware platform enables the determination of air quality in any indoor environment.

Keywords

Indoor Air Quality, Real Time Monitoring, Internet of Things, Raspberry Pi, Sensor Technologies

IoT Tabanlı Platform ile Gerçek Zamanlı İç Ortam Hava Kalitesi İzleme Sistemi

Abstract

Hava kirliliği, günümüzde karşılaştığımız en büyük problemlerden bir tanesidir. İnsan sağlığı, iklim ve ekosistem üzerinde olumsuz etkilere yol açan hava kirliliğinin artmasında, atmosferdeki kirleticilerin miktarlarındaki artışın yanı sıra iç ortamlardaki hava kalitesininde katkısı olduğu bir gerçektir. Günlük yaşantısının büyük bir kısmını kapalı iç ortamlarda (evlerde, ofislerde, okullarda, hastanelerde, alışveriş merkezlerinde vb.) geçiren insanlar, ortamın havasındaki zararlı gazlardan ve partikül maddelerden etkilenmekte ve sağlık sorunları yaşayabilmektedir. Bu tarz ortamlardaki yaşam standartlarının insan yaşamı için optimum değerlerde tutulması ve insan sağlığını tehdit edebilecek faktörlerin belirlenerek ortadan kaldırılması ya da etkilerinin azaltılması gerekmektedir. Teknolojik gelişmeler sayesinde ortamın hava kalitesinin belirlendiği sistemler ile bu tarz sorunların ortadan kaldırılması mümkündür. Bu çalışma kapsamında, IoT tabanlı iç ortam hava kalitesi izleme sistemi gerçekleştirilmiştir. Oluşturulan sistem içerisinde Raspberry Pi 3 kontrol kartı, sıcaklık, nem, gaz ve ışık sensörleri kullanılmıştır. Sensörler aracılığıyla alınan iç ortam verileri, kontrol kartı aracılığıyla işlenerek elde edilmiş ve veri tabanına kaydedilmiştir. Hazırlanan web arayüzü ile iç ortamdaki yaşam koşullarına ilişkin bilgiler anlık olarak takip edilebilmektedir. Geliştirilen hava kalitesi formülü kullanılarak iç ortam hava kalitesi hesaplanarak kullanıcılara aktarılmaktadır. Taşınabilir donanım platformu ile herhangi bir iç ortamın hava kalitesinin tespit edilmesi sağlanmaktadır.

Keywords

İç Ortam Hava Kalitesi, Gerçek Zamanlı İzleme, Nesnelerin İnterneti, Raspberry Pi, Sensör Teknolojileri

References

• Hammami, A. (2019). Smart Environment Data Monitoring. 2019 International Conference on Computer and Information Sciences (ICCIS), 3-4 April, Sakaka, Saudi Arabia, pp. 1-6.
• Majumder, A.J.A., Mcwhorter, T.M., Ni, Y., Nie, H., Iarve, J., Ucci, D.R. (2019). sEmoD: A Personalized Emotion Detection Using a Smart Holistic Embedded IoT System. 2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC), 15-19 July, Milwaukee, WI, USA, pp. 850-859.
• Shah J., Mishra, B. (2016). Customized IoT enabled wireless sensing and monitoring platform for smart buildings. Procedia Technology, 23, 256-263.
• Venkatanarayanan, A., Vijayavel, A., Rajagopal, A., Nagaradjane, P. (2019). Design of sensor system for air pollution and human vital monitoring for connected cyclists. IET Communications, 13(19), 3181-3186.
• Ghosh, R., Gardner, J.W., Guha, P.K. (2019). Air Pollution Monitoring Using Near Room Temperature Resistive Gas Sensors: A Review. IEEE Transactions on Electron Devices, 66(8), 3254-3264.
• Firdhous, M.F.M., Sudantha, B.H., Karunaratne, P.M. (2017). IoT enabled proactive indoor air quality monitoring system for sustainable health management. 2017 2nd International Conference on Computing and Communications Technologies (ICCCT), 23-24 February, Chennai, India, pp. 216-221.
• Pham, N.Q, Rachim, V.B., Chung, W.Y. (2018). EMI-Free Bidirectional Real-Time Indoor Environment Monitoring System. IEEE Access, 7, 5714-5722.
• Abraham, S., Li, X. (2014). A cost-effective wireless sensor network system for indoor air quality monitoring applications. [J]. Procedia Computer Science, 34, 165-171.
• Spiru, P., Simona, P.L. (2017). A review on interactions between energy performance of the buildings, outdoor air pollution and the indoor air quality. Energy Procedia, 128, 179–186.
• Başaran, D., Karanfil, B., Tüysüz, B. (2018). Çoklu modül destekli enerji etkin akıllı kontrol sistemi. Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 22(2), 468-479.
• Huang, K., Song, J., Feng, G., Chang, Q., Jiang, B., Wang, J., Sun, W., Li, H., Wang F., Fang, X. (2018). Indoor air quality analysis of residential buildings in northeast China based on field measurements and longtime monitoring. Building and Environment, 144, 171-183.
• Yalçın, N. (2017). Gaz Sensörleri ile Ölçüm Sistemleri için Ortam Modelleme ve Simülatör Geliştirilmesi. Doktora Tezi, Sakarya Üniversitesi Fen Bilimleri Enstitüsü, Sakarya.
• Quang Phuc Ha, Q.P., Metia, S., Phung, M.D. (2020). Sensing Data Fusion for Enhanced Indoor Air Quality Monitoring. IEEE Sensors Journal, 20(8), 4430-4441.
• Jo, J.H., Jo, B.W., Kim, J.H., Kim, S.J., Han, W.Y. (2020). Development of an IoT-Based Indoor Air Quality Monitoring Platform. Journal of Sensors, 2020, Article ID 8749764, 1-14.
• Le, H.A., Linh, V.T.Q. (2020). Investigation of Indoor and Outdoor Air Quality at Elementary Schools in Hanoi, Vietnam. VNU Journal of Science: Earth and Environmental Sciences, 36(1), 30-37.
• Marques, G., Ferreira C.R., Pitarma, R. (2019). Indoor Air Quality Assessment Using a CO2 Monitoring System Based on Internet of Things. Journal of Medical Systems, 43(67), 1-10.
• Sung, W.T., Hsiao, S.J., Shih, J.A. (2019). Construction of Indoor Thermal Comfort Environmental Monitoring System Based on the IoT Architecture. Journal of Sensors, 2019, Article ID 2639787, 1-16.
• Tiele, A., Esfahani, S., Covington, J. (2018). Design and Development of a Low-Cost, Portable Monitoring Device for Indoor Environment Quality. Journal of Sensors, 2018, Article ID 5353816, 1-14.
• Salamone, F., Belussi, L., Danza, L., Ghellere, M., Meroni, I. (2015). Design and development of nEMoS, an all-in-one, low-cost, web connected and 3D-printed device for environmental analysis. Sensors, 15(6), 13012–13027.
• Zhao, Z., Wang, J., Fu, C., Liu, Z. Liu, D., Li, B. (2018). Design of a Smart Sensor Network System for Real-Time Air Quality Monitoring on Green Roof. Journal of Sensors, 2018, Article ID 1987931, 1-13.
• Zhao, L., Wu, W., Li., S. (2019). Design and Implementation of an IoT-Based Indoor Air Quality Detector with Multiple Communication Interfaces. IEEE Internet of Things, 6(6), 9621-9632.
• Chen, P.H., Cross, N. (2018). IoT in Radiology: Using Raspberry Pi to Automatically Log Telephone Calls in the Reading Room. Journal of Digital Imaging, 31, 371-378.
• Divya, M., Subhash, N., Vishnu, P., Tejesh, P. (2020). Smart Health Care Monitoring Based on Internet of Things (IoT). International Journal of Scientific Research and Engineering Development, 3(1), 409 - 414.
• Nowshin, N., Mazumder, P., Soikot, M.A., Probal, M., Qadir, M.U. (2019). Designing and Implementation of Microcontroller Based Non-Invasive Health Monitoring System. 2019 International Conference on Robotics, Electrical and Signal Processing Techniques (ICREST), 10-12 January, Dhaka, Bangladesh, pp. 134-139.
• Dheena, P. P. F., Raj, G.S., Dutt, G., Jinny, S.V. (2017). IOT based smart street light management system. 2017 IEEE International Conference on Circuits and Systems (ICCS), 20-21 December, Thiruvananthapuram, India, pp. 368-371.
• Light Dependent Resistor Datasheet. (1997). http://www.bilimteknik.tubitak.gov.tr/sites/default/files/ gelisim/elektronik/dosyalar/40/LDR_NSL19_M51.pdf, (11.16.2020)
• Hanwei Electronics. (2020). Technical Data MQ-2 Gas Sensor Datasheet, http://www.haoyuelectronics.com/Attachment/MQ-2/MQ-2.pdf, (11.16.2020)
• Olesen, B.W. (2000). Guidelines for Comfort. ASHRAE Journal, 40-45.
• Perera, I. E., Litton, C. D. (2014). Evaluation of Smoke and Gas Sensor Responses for Fires of Common Mine Combustibles. Transactions of Society for Mining, Metallurgy, and Exploration, Inc, 336(1), 381–390.