Authors : Pillar Satya Mahardika; Ainie Khuriati Riza Sulistiati; Jatmiko Endro Suseno

Volume/Issue : Volume 9 - 2024, Issue 5 - May

Google Scholar : https://tinyurl.com/3zbf2f5h

Scribd : https://tinyurl.com/4zrkkzdt

DOI : https://doi.org/10.38124/ijisrt/IJISRT24MAY1888

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : The increase in air pollution due to industrialization and transportation growth in developing countries raises concerns about public health impacts and financial burdens for governments. Traditional monitoring equipment is limited in deployment and real-time capabilities. This research aims to design an air quality monitoring system based on Wireless Sensor Network (WSN) and Internet of Things (IoT) integrated with solar panels. The system utilizes three sensor nodes and one sink node to monitor parameters such as temperature, humidity, and CO. Data from the sensor nodes are transmitted to the sink node via Long Range (LoRa) network, then sent to the server via WiFi for storage and online display, processed into graphs accompanied by Air Quality Index (AQI) to facilitate data analysis. Sensor calibration is conducted using standard equipment and AQMS. Calibration results show a high correlation between the sensors and standard equipment, with R2 approaching 1 for all sensors. The system is tested in the environment of the Faculty of Science and Mathematics, Diponegoro University, and shows good average air quality results. This system is expected to contribute effectively and efficiently to maintaining and improving air quality.

Keywords : Wireless Sensor Network (WSN), Internet of Things (IOT), Air Quality Monitoring, Solar Panel, Long Range (Lora) Network, Real-Time Monitoring, Air Quality Index (AQI)

References :

1. Fotopoulou, E., Zafeiropoulos, A., PAPASPYROS, D., HASAPIS, P., TSIOLIS, G., BOURAS, T., MOUZAKITIS, S., & Zanetti, N. (2016). Linked data analytics in interdisciplinary studies:The health impact of air pollution in urban areas. IEEE Access 4, 149–164.
2. Cabaneros, S., M., Calautit, J., K., Hughes, B. R. (2019). A review of artificial neural network models for ambient air pollution prediction, Environmental Modelling & Software, Volume 119, Pages 285-304, ISSN 1364-8152.
3. Shaban, K., B., Kadri, A., Rezk, E. (2016). Urban air pollution monitor-ing system with forecasting models. IEEE Sensor, 16 (8), 2598–2606.
4. Li, W., Y., Lo, K., M., Mak, T., Leung, K., S., Leung, Y., Meng, M., L. (2015). A Survey of wireless sensor networkbased air pollution monitoring systems. Sensors, 15(12), 31392–31427.
5. William, P., Kiran, Y., V., U., Rana, A., Gangodkar, D., Khan, I., Ashutosh, K., (2022). Design and implementation of IoT based framework for air quality sensing and monitoring. in: 2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS), 197–200.
6. Sinha, S., Makkar, P. (2021). In Advances in ubiquitous sensing applications for healthcare. Security and Privacy Issues in IoT Devices and Sensor Networks,Academic Press, Pages 1-27, ISSN 25891014, ISBN 9780128212554.
7. Singh, S., Singh, U.  (2022). The effect of chaotic mapping on naked mole-rat algorithm for energy efficient smart city wireless sensor network. Computers & Industrial Engineering, 173(1), pp 1-19.
8. Liu, J., Sui, X. (2021). Hospital wireless sensor network coverage and ambroxol hydrochloride in the treatment of mycoplasma pneumonia in children. Microprocessors and Microsystems, 81(1), 103707-103712.
9. Sharma, N., Gupta, V. (2022). A Framework for Wireless Sensor Network Optimization Using Fuzzy-Based Fractal Clustering to Enhance Energy Efficiency. Journal of Circuits, Systems and Computers, 34(13), 29-54.
10. Laksmana, I., Jingga, T., Z., Febrina,, W., Khomarudin, A., N., Putri, E., E., Novita, R., N., R., Amrizal, 2022, teknologi internet of things (iot) dan hidroponik, Goresan Pena, isbn 9786233674683.
11. Juliando, D., E., Putra, R., Sartika, D., A., Yudha, R., G., P. (2021). Study of Lora Module Ra-02 For Long Range, Low Power, LowRate Picture Transfer Applications. Journal of Physics Conference Series, 1845(1).
12. Jacobson, M., Z., & Delucchi, M., A. (2011). Providing all global energy with wind, water, and solar power, Part I: Technologies, energy resources, quantities and areas of infrastructure, and materials. Energy Policy, 39(3), 1154-1169.
13. Barbose, G., Darghouth, N., & Millstein, D. (2017). The impact of rate design and net metering on the bill savings from distributed PV for residential customers in California. Energy Policy, 105, 385-394.
14. Salman, N., Andrew, Kemp, H., Khan, A., & Noakes, C., J. (2019). Real Time Wireless Sensor Network (WSN) based Indoor Air Quality Monitoring System. IFAC-PapersOnLine, 52(24), 324-327.