An Approach to Implementation of an IoT-Based Remote Water Quality Monitoring for Smart Cities | IJCT Volume 12 – Issue 6 | IJCT-V12I6P43
International Journal of Computer Techniques
ISSN 2394-2231
Author
Suhel Banik, Swarnendu Ghosh, Tridip Saha, Dhriti Rudrapal, Tapan Kumar Mohanta
Abstract
Water is an essential resource for life, but its quality is deteriorating due to industrialization and population growth. Consuming contaminated water leads to severe health issues, necessitating efficient monitoring systems. This project presents an IoT-Based Smart Water Purity Monitoring System designed to provide a low-cost, real-time solution for water quality assessment. The system utilizes a Total Dissolved Solids (TDS) sensor to measure impurities, an Arduino UNO for data processing, and a NodeMCU (ESP8266) for wireless transmission. Data is visualized on the Blynk IoT platform, allowing users to monitor water purity remotely via a smartphone application. This automated approach overcomes the limitations of manual laboratory testing, offering a scalable solution for households and industries.
Keywords
IoT, TDS Sensor, ESP8266, Water Purity, Remote Monitoring, Blynk Cloud.
Conclusion
The IoT-Based Smart Water Purity Monitoring System successfully addresses the need for an affordable and accessible water quality testing solution. By automating the measurement of Total Dissolved Solids (TDS), the system eliminates the reliance on expensive laboratory equipment and manual sampling.
The integration of Arduino and NodeMCU ensures accurate data processing and reliable cloud transmission, while the Blynk platform provides a user-friendly interface for real-time monitoring. The system is highly versatile, with applications ranging from household water purifiers to industrial quality control and agricultural irrigation.
Future Scope: The system is designed to be scalable. Future enhancements could include integrating additional sensors for pH, turbidity, and dissolved oxygen to provide a comprehensive analysis of water quality. Furthermore, Artificial Intelligence (AI) could be implemented to predict contamination patterns based on historical data, and automated control mechanisms (like solenoid valves) could be added to stop water flow if impurities exceed safe limits.
References
K. S. Adu-Manu, C. Tapparello, W. Heinzelman, F. A. Katsriku, and J.-D. Abdulai, “Water quality monitoring using wireless sensor networks: Current trends and future research directions,” ACM Transactions on Sensor Networks (TOSN), vol. 13, p. 4, 2017.
2. B. Chen, Y. Song, T. Jiang, Z. Chen, B. Huang, and B. Xu, “Real-time estimation of population exposure to PM2.5 using mobile- and station-based big data,” Int J Environ Res Public Health, vol. 15, Mar 23 2018.
3. B. Paul, “Sensor based water quality monitoring system,” BRAC University, 2018.
4. K. Andersson and M. S. Hossain, “Smart Risk Assessment Systems using Belief-rule-based DSS and WSN Technologies”, in 2014 4th International Conference on Wireless Communications, Vehicular Technology, Information Theory and Aerospace and Electronic Systems, VITAE 2014: Co-located with Global Wireless Summit, Aalborg, Denmark 11–14 May 2014, 2014.
5. Das, Brinda, Jain, P.C., 2017. Real-time water quality monitoring system using the internet of things. Int. Conf. Comput. Commun 78–82.
6. He, Donge, Zhang, Li-Xin, 2012. The water quality monitoring system based on wireless sensor network. In: Report: Mechanical and Electronic Information Institute, China University of GeoScience, Wu Hen, China.
7. Sugapriyaa, Tha, Rakshaya, S., Ramyadevi, K., Ramya, M., Rashmi, P.G., 2018. Smart water quality monitoring system for real-time applications. Int. J. Pure Appl. Math 118, 1363–1369.
8. Barabde, M.N., Danve, S.R., 2015. Continuous water quality monitoring system for Water resources at remote places. IJIRCEE 3, 2320–9798.
9. K.S. Adu-Manu, C. Tapparello, W. Heinzelman, F.A. Katsriku, J.-D. Ab-dulai, Water quality monitoring using wireless sensor networks: current trends and future research directions, ACM Trans. Sens. Networks. 13 (2017) 1–41, http://dx.doi.org/10.1145/3005719.
10. Eliades D, Lambrou T, Panayiotou C, Polycarpou M (2014) Contamination Event Detection in Water Distribution Systems using a Model-Based Approach. In: 16th Conference on Water Distribution System Analysis. 14–17 July 2014.
11. Ruan Y, Tang Y (2011) A water quality monitoring system based on wireless sensor network solar power supply. In: 2011 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent System, 20–23, Mar 2011.
12. Mitar S, Goran M, Libu M, Krzystof Z ( 2016 ) Multi-sensor system for remote environmental (air and water) quality monitoring. In: 24th telecommunications forum, 22–23 Nov. 2016.
13. Lambrou, Theofanis P., Anastasiou, Christos C., Panayiotou, Christos G., Polycarpou, Marios M., 2014. A low-cost sensor network for real-time monitoring and contamination detection in drinking water distribution systems. IEEE Sensor. J. 8, 2765–2772.
14. Prasad, A.N., Mamun, K.A., Islam, F.R., Haqva, H., 2015. Smart water quality monitoring system. In: The University of the South Pacific. 2nd Asia-Pacific World congress on Computer Science and Engineering IEEE Conference.
15. Omar Faruq, Md., Hoque Emu, Injamamul, Nazmul Haque, Md., Dey Maitry, Das, N.K., Dey Mrinmoy, 2017. Design and implementation of a cost-effective water quality evaluation system. In: IEEE Region 10 Humanitarian Technology Conference, Dhaka, Bangladesh, pp. 860–863.
16. N. Vijayakumar and R. Ramya, “The real time monitoring of water quality in IoT environment,” in 2015 International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS), 2015, pp. 1–5.
How to Cite This Paper
Suhel Banik, Swarnendu Ghosh, Tridip Saha, Dhriti Rudrapal, Tapan Kumar Mohanta (2025). An Approach to Implementation of an IoT-Based Remote Water Quality Monitoring for Smart Cities. International Journal of Computer Techniques, 12(6). ISSN: 2394-2231.
An Approach to Implementation of an IoT-Based Remote Water Quality Monitoring for Smart CitiesDownload
Related Posts:
