SEEE DIGIBOOK ON ENGINEERING & TECHNOLOGY, VOL. 03, MAY 2021 PP.(6-11)


Abstract—Air, Water and Land are the three main resources that every living thing depends on it. It was estimated that around 40 per cent of piped water in India is lost to leakage. In order to control that leakage issues, this article, author offered a design and expansion of a real time water management system using Internet of Things(IoT) at a low cost. To compute the physical parameter of the water such as water flow and other sensor were used. The E system continuously monitors the water flow by using various sensors over a period of time. If it detects the prolonging in the flow of water, it will alerts the concern author that leakage of water is happening, through the Wi-Fi system.

 

Index TermsArduino MEGA; Wi-Fi Module; Water Flow Sensor;

REFERENCE

  1. Herlina A.R., Kharulanam A.H & Hafilah Z. A. [2015]. Early Detection of Pipeline Using Ultrasonic Sensor. Jurnal Teknologi (Science and Engineering), 3(73),9-11.Retrieved 28 August,2017
  2. Arjun K.Latha C.A & Prithviraj [2017].Detection of Water Lever, Quality and Leakage Using Raspberry Pi with Internet of Things. International Research Journal of Engineering and Technology (IRJET), 4(6), 2875-2880. Retrieved August,2017
  3. Perumal T., Sulaiman M.N & Leong C.Y. [2015]. Internet of Things(IoT) enabled water monitoring system. IEEE 4th Global Conference on Consumer Electronics (GCCE), 86- 87.doi:10.1109/GCCE.2015.7398710
  4. Bhad Vidya, Kale Poonam, Gavhale Priyanka, Darekar Gaurav, A.S Chandgude, “Water Level Monitoring System  In Real Time Mode Using WSN”, International Journal of Emerging Technology and Advanced Engineering (ISSN 2250-2459,ISO 9001:2008 Certified Journal, Volume  6, Issue 9, September2016
  5. Mithila Barabde, Shruti Danve, “Real Time Water Quality Monitoring System”, International Journal of Innovative Research in Computer and CommunicationEnginnering Vol.3,Issue 6, June2015.
  6. Jaytibhatt, Jigneshpatoliya,”IoT based water quality monitoring system”, International Journal Of Industrial Electronics And Electrical Engineering Volume-4, Issue- 4,Apr.-2016.
  7. Nagaraj, B. and Vijayakumar, P., 2011. Soft computing based PID controller tuning and application to the pulp and paper industry. Sensors & Transducers, 133(10), p.30.
  8. Arunkumar, R. and Balakrishnan, N., 2018. Medical image classification for disease diagnosis by DBN methods. Pakistan Journal of Biotechnology, 15(1), pp.107-110.
  9. J.Navarajan, B.Aswinkumar, S.Venkatesh, T.Jayachandran. “Detection of Water Pollution and Water Management Using Smart Sensor with IOT”, International Research Journal of Engineering and Techonlogy (IRJET) Volume: 04 Issue: 04 | Apr-2017.
  10. Behera, S.K., & Gupta, M.K. (2019). Implementaion of IOT for energy management. Test Engineering and Management, 81(11-12), 4856-4860.
  11. Goar, V.K., Tanwar, P., & Kuri, M. (2019), IoT based climate-smart agriculture. Test Engineering and Management, 81(11-12), 4856-4860.
  12. S.Geetha and S.Gouthami, “Internet of things enabled real time water quality monitoring system”, Department of Electrical and Electronics Engineering”, (2016) 2:1, https://doi.org/10.1186/s40713-017-0005-y.
  13. M.Thilagaraj,N.N. Swetha, R.Pugazhendhi, R.Rahul, “Finger Vein Based Bank Security System,” International Journal of Control and Automation, Vol 13, No 3, 2020, pp 01-08.
  14. Jeyakkannan, N. and Nagaraj, B., 2014. Online Monitoring of Geological Methane Storage and Leakage Based on Wireless Sensor Networks. Asian Journal of Chemistry, 26.
  15. M.Thilagaraj, M.Pallikonda Rajasekaran, “Classification of Non alcoholic and alcoholic based EEG Signal using Fuzzy Neutral Network Classifier”, Journal of Advanced Research in Dynamical and Control Systems – Vol -9, Sp-16/2017 pp 671-680
  16. Balakrishnan, N., Rajendran, A. and Palanivel, K., 2019. Meticulous fuzzy convolution C means for optimized big data analytics: adaptation towards deep learning. International Journal of Machine Learning and Cybernetics, 10(12), pp.3575-3586.
  17. M.Thilagaraj and M.Pallikonda Rajasekaran, “Epileptic Seizure Mining via Novel Empirical Wavelet Feature with J48 and KNN Classifier”, Intelligent Engineering Informatics, Advances in Intelligent Systems and Computing 695, https://doi.org/10.1007/978-981-10-7566-7_23 ,2018.
  18. Sethuramalingam, T.K. and Nagaraj, B., 2015. A soft computing approach on ship trajectory control for marine applications. ARPN J Eng Appl Sci, 10(9), pp.4281-4286.
  19. ESP8266 serial Wi-Fi wireless Transceiver Module for IoT,ESPRUINO-Wireless.
  20. Purdum, Jack J.(30 June 2015). Beginning C for Arduino: learn C programming for the Arduino (Second ed.).[New York]. ISBN 9781484209400. OCLC 972875060.
  21. Agalya, A. and Nagaraj, B., 2013. Certain investigation on concentration control of CSTR—a comparative approach. Int J Adv Soft Comput Appl, 5(2), pp.1-14.

1 Palpandian P, 2 Govindaraj V, 3 Dharmashastha.S, 4 Gokul.S, 5 MariSelvam.K, 6 Aijin Anson
1 Assistant professor, Electronics and Instrumentation Engineering, Karpagam College of Engineering, Tamil Nadu,
2 Assistant professor, Electrical and Electronics Engineering, Karpagam College of Engineering, Tamil Nadu, India,
3,4,5,6 UG Scholar, Electronics and Instrumentation, Karpagam College of Engineering, Tamil Nadu, India
palpandian@kce.ac.in , dharmashastha2000s@gmail.com,gokulkrishb300@gmail.com, pksmari3012@gmail.com, aijinansonzzzz@gmail.com