Design and Build Integrated Water Filter Automation for Android Smartphones (IoT)
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Keywords

Filter Air
Internet of Things
NodeMCU ESP32
Sensor pH
Sensor Turbidity

How to Cite

Septiyan, M. D., Anshory, I., Ahfas, A., & Jamaaluddin, J. (2021). Design and Build Integrated Water Filter Automation for Android Smartphones (IoT). Indonesian Journal of Innovation Studies, 14, 10.21070/ijins.v14i.538. https://doi.org/10.21070/ijins.v14i.538

Abstract

In the internet of things, one of the current developments is smartphone-based water automation which makes it easier for users to control water. The working principle of this research is the water contained in the water storage tank if the water level is below 25 cm then the water pump (water input) will be active until the water is above 25 cm. Then the solenoid valve (water output) can be opened and closed via the Blynk application. When the solenoid is opened, the water in the holding tank will pass through filters 1 and 2 into the filter reservoir. The water in the filtered reservoir will measure the level of acidity and turbidity and then display it on the Blynk application. The results of this study, the water filter can reduce the level of turbidity of water by 0.568 NTU and increase the level of acidity by 0.132. The PH sensor used has an accuracy rate of 93.53%. The Turbidity sensor or turbidity has an average of 1.00 NTU in measuring clean water (Aqua).

https://doi.org/10.21070/ijins.v14i.538
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References

M. S. Bennet Praba, N. Rengaswamy, Vishal, and O. Deepak, “IoT Based Smart Water System,” in Proceedings of the 3rd International Conference on Communication and Electronics Systems, ICCES 2018, Oct. 2018, pp. 1041–1045, doi: 10.1109/CESYS.2018.8723969.

E. A. Suprayitno, I. Anshory, and Jamaaluddin, “Smart Home Integrated with Internet of Things (Iot) in the Digital Era of Industry 4.0,” in IOP Conference Series: Materials Science and Engineering, Jul. 2020, vol. 874, no. 1, p. 012010, doi: 10.1088/1757-899X/874/1/012010.

Y. K. Taru and A. Karwankar, “Water monitoring system using arduino with labview,” in Proceedings of the International Conference on Computing Methodologies and Communication, ICCMC 2017, Feb. 2018, vol. 2018-January, pp. 416–419, doi: 10.1109/ICCMC.2017.8282722.

“Rancang Bangun Filter Air Berbasis Arduino Pada Penampungan Air Menggunakan Metode Fuzzy | Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer.” https://j-ptiik.ub.ac.id/index.php/j-ptiik/article/view/2634 (accessed May 10, 2021).

L. A. Gama-Moreno, A. Corralejo, A. Ramirez-Molina, J. A. Torres-Rangel, C. Martinez-Hernandez, and M. A. Juarez, “A design of a water tanks monitoring system based on mobile devices,” in Proceedings - 2016 International Conference on Mechatronics, Electronics, and Automotive Engineering, ICMEAE 2016, Dec. 2016, pp. 133–138, doi: 10.1109/ICMEAE.2016.032.

M. Kumar Jha, R. Kumari Sah, M. S. Rashmitha, R. Sinha, B. Sujatha, and K. V. Suma, “Smart Water Monitoring System for Real-Time Water Quality and Usage Monitoring,” in Proceedings of the International Conference on Inventive Research in Computing Applications, ICIRCA 2018, Dec. 2018, pp. 617–621, doi: 10.1109/ICIRCA.2018.8597179.

A. Imran and M. Rasul, “PENGEMBANGAN TEMPAT SAMPAH PINTAR MENGGUNAKAN ESP32,” Mar. 2020. doi: 10.26858/METRIK.V17I2.14193.

A. Setiawan and A. I. Purnamasari, “Pengembangan Smart Home Dengan Microcontrollers ESP32 Dan MC-38 Door Magnetic Switch Sensor Berbasis Internet of Things (IoT) Untuk Meningkatkan Deteksi Dini Keamanan Perumahan,” J. RESTI (Rekayasa Sist. dan Teknol. Informasi), vol. 3, no. 3, pp. 451–457, Dec. 2019, doi: 10.29207/resti.v3i3.1238.

A. Andang, N. Hiron, A. Chobir, and N. Busaeri, “Investigation of ultrasonic sensor type JSN-SRT04 performance as flood elevation detection,” in IOP Conference Series: Materials Science and Engineering, Aug. 2019, vol. 550, no. 1, p. 012018, doi: 10.1088/1757-899X/550/1/012018.

L. Parra, J. Rocher, J. Escrivá, and J. Lloret, “Design and development of low cost smart turbidity sensor for water quality monitoring in fish farms,” Aquac. Eng., vol. 81, pp. 10–18, May 2018, doi: 10.1016/j.aquaeng.2018.01.004.

P. Serikul, N. Nakpong, and N. Nakjuatong, “Smart Farm Monitoring via the Blynk IoT Platform : Case Study: Humidity Monitoring and Data Recording,” in International Conference on ICT and Knowledge Engineering, Jan. 2019, vol. 2018-November, pp. 70–75, doi: 10.1109/ICTKE.2018.8612441.

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