Skip to main content
SpringerLink
Log in

Towards the Green Analytics: Design and Development of Sustainable Drinking Water Quality Monitoring System for Shekhawati Region in Rajasthan

  • Original Paper
  • Published:
MAPAN Aims and scope Submit manuscript

Abstract

In rural areas, there is limited monitoring of drinking water quality. Reliable water quality monitoring stations are expensive and require high costs for maintenance and calibration process. In this paper, the development of a sustainable water quality monitoring system is proposed. The green analytics principles were considered for developing the proposed system to reduce the measurement’s time consumption and labor cost. Five water quality parameters [pH, oxidation reduction potential (ORP), dissolved oxygen (DO), electrical conductivity (EC), and temperature] have been measured using the developed system. The overall drinking water quality is measured by the proposed partial least squares regression (PLSR) model. The developed system’s performance is determined by mean average percentage error (MAPE), root-mean-square error (RMSE), and R2. The traceability of water quality sensors is defined with required uncertainty in water quality parameters. The measured uncertainty is 0.002, 0.892, 0.015, 0.029, and 0.017 for pH, EC, DO, ORP, and temperature, respectively. The relation between estimated and predicted water quality parameters (R2 > 0.93) shows that the developed system can be a suitable replacement for traditional water quality monitoring techniques.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

References

  1. F. and A. O. of the UN, AQUASTAT, (2016) http://www.fao.org. (25 August 2017).

  2. R. Kumar, U. Vaid and S. Mittal, Water crisis: Issues and challenges in Punjab. Springer, Singapore (2018).

    Google Scholar 

  3. World Health Organization (WHO), WHO|drinking water. Fact sheet No. 391. World Health Organization. 2017. Available from: http://www.who.int/mediacentre/factsheets/fs391/en/, (1996).

  4. K. Anan, ‘Water-related diseases responsible for 80 per cent of all illnesses, deaths in developing world’, says secretary-general in environment day message, UN, (2003) http://www.un.org/press/en/2003/sgsm8707.doc.htm (5 December 2017).

  5. W. H. Organization, Drinking-water, https://www.who.int/news-room/fact-sheets/detail/drinking-water (25 May 2020).

  6. G. Kaur, R. Kumar, S. Mittal, P.K. Sahoo and U. Vaid, Ground/drinking water contaminants and cancer incidence: A case study of rural areas of South West Punjab, India. Hum. Ecol. Risk Assess. An Int. J., 27 (2021) 205–226.

    Article  Google Scholar 

  7. R. Kumar, S. Mittal, S. Peechat, P.K. Sahoo and S.K. Sahoo, Quantification of groundwater–agricultural soil quality and associated health risks in the agri-intensive Sutlej River Basin of Punjab, India. Environ. Geochem. Health, 42 (2020) 4245–4268.

    Article  Google Scholar 

  8. S. Sharma, R. Kumar, P.K. Sahoo and S. Mittal, Geochemical relationship and translocation mechanism of arsenic in rice plants: A case study from health prone south west Punjab, India. Groundw. Sustain. Dev., 10 (2020) 100333.

    Article  Google Scholar 

  9. P. Khatri, K. K. Gupta and R. K. Gupta, Raspberry Pi-based smart sensing platform for drinking-water quality monitoring system: A Python framework approach. Drink. Water Eng. Sci., 12 (2019) 31–37.

    Article  Google Scholar 

  10. P. Ferguson, M. Harding and J. Young, Green analytical chemistry, in Green techniques for organic synthesis and medicinal chemistry (2012).

  11. J. Namieśnik, Green analytical chemistry—Some remarks. J. Sep. Sci., 24 (2001) 151–153.

    Article  Google Scholar 

  12. Central Polution Control Board, Central Polution Control Board; Environmental standards; Water quality criteria, (2007) http://cpcb.nic.in/Water_Quality_Criteria.php (25 November 2017).

  13. J. Bhardwaj, K. K. Gupta and R. Gupta, A review of emerging trends on water quality measurement sensors, in 2015 international conference on technologies for sustainable development, IEEE, (2015).

  14. S.G. Aggarwal, S. Kumar, P. Mandal, B. Sarangi, K. Singh, J. Pokhariyal, S.K. Mishra, S. Agarwal, D. Sinha, S. Singh and C. Sharma, Traceability Issue in PM2.5 and PM10 Measurements. Mapan - J. Metrol. Soc. India, 28 (2013) 153–166.

    Google Scholar 

  15. A. Williams, Traceability and uncertainty—A comparison of their application in chemical and physical measurement, Traceability Chem. Meas., (2005) 264–266.

  16. T. P. Lambrou, C. C. Anastasiou and C. G. Panayiotou, A nephelometric turbidity system for monitoring residential drinking water quality, in Lecture notes of the institute for computer sciences, social informatics and telecommunications engineering 29 LNICST, (2010).

  17. S. K. Priya, G. Shenbagalakshmi and T. Revathi, IoT based automation of real time in-pipe contamination detection system in drinking water, in 2018 International conference on communication and signal processing, IEEE, (2018).

  18. J. Bhardwaj, K. K. Gupta and P. Khatri, Real time assessment of potable water quality in distribution network based on low cost multi-sensor array, in IOP conference series: Materials science and engineering 331, (2018).

  19. S. Geetha and S. Gouthami, Internet of things enabled real time water quality monitoring system. Smart Water, 2 (2016) 1.

    Article  Google Scholar 

  20. T.P. Lambrou, C.G. Panayiotou and C.C. Anastasiou, A low-cost system for real time monitoring and assessment of potable water quality at consumer sites. Sensors J., 14 (2012) 2765–2772.

    Article  Google Scholar 

  21. I. Campos, M. Alcañiz, D. Aguado, R. Barat, J. Ferrer, L. Gil, M. Marrakchi, R. Martínez-Mañez, J. Soto et al., A voltammetric electronic tongue as tool for water quality monitoring in wastewater treatment plants. Water Res., 46 (2012) 2605–2614.

    Article  Google Scholar 

  22. 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, IEEE, (2015).

  23. M.S.U. Chowdury, T. Bin Emran, S. Ghosh, A. Pathak, M.M. Alam, N. Absar, K. Andersson and M.S. Hossain, IoT based real-time river water quality monitoring system. Procedia Comput. Sci., 155 (2019) 161–168.

    Article  Google Scholar 

  24. A.T. Demetillo, M.V. Japitana and E.B. Taboada, A system for monitoring water quality in a large aquatic area using wireless sensor network technology. Sustain. Environ. Res., 1 (2019) 12.

    Article  Google Scholar 

  25. D. Zeng, L. Gu, L. Lian, S. Guo, H. Yao and J. Hu, On cost-efficient sensor placement for contaminant detection in water distribution systems. IEEE Trans. Ind. Informatics, 12 (2016) 2177–2185.

    Article  Google Scholar 

  26. B. Das and P. C. Jain, Real-time water quality monitoring system using internet of things, in 2017 international conference on computer, communications and electronics, IEEE, (2017).

  27. R. Yue and T. Ying, 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 systems, CYBER 2011, (2011).

  28. Z. Shareef and S. Reddy, Design and wireless sensor network analysis of water quality monitoring system for aquaculture, in 2019 3rd international conference on computing methodologies and communication, IEEE, (2019).

  29. M. Li, D. Li, Q. Ding, Y. Chen and C. Ge, A multi-parameter integrated water quality sensors system, in IFIP Advances in Information and Communication Technology 392 AICT, Springer, Berlin, Heidelberg, (2013).

  30. Atlas Scientific https://www.atlas-scientific.com/ (7 December 2019).

  31. S. Diaz, T. Krohmer, A. Moreira, S.E. Godoy and M. Figueroa, An instrument for accurate and non-invasive screening of skin cancer based on multimodal imaging. IEEE Access, 7 (2019) 176646–176657.

    Article  Google Scholar 

  32. A. Monteiro, M. De Oliveira, R. De Oliveira and T. Da Silva, Embedded application of convolutional neural networks on Raspberry Pi for SHM. Electron. Lett., 54 (2018) 680–682.

    Article  ADS  Google Scholar 

  33. R. A. Rodriguez, P. Cammarano, D. A. Giulianelli, P. M. Vera, A. Trigueros and L. J. Albornoz, Using Raspberry Pi to create a solution for accessing educative questionnaires from mobile devices, Rev. Iberoam. Tecnol. del Aprendiz., 13, Education Society of IEEE (Spanish Chapter), (2018) 144–151.

  34. A. Pal, A. Mehta, H. Goonesinghe, D. Mirshekar-Syahkal and H. Nakano, Conformal beam-steering antenna controlled by a raspberry Pi for sustained high-throughput applications. IEEE Trans. Antennas Propag., 66 (2018) 918–926.

    Article  ADS  Google Scholar 

  35. R.E. Sweeney, V. Nguyen, B. Alouidor, E. Budiman, R.K. Wong and J.Y. Yoon, Flow rate and Raspberry Pi-based paper microfluidic blood coagulation assay device. IEEE Sens. J., 19 (2019) 4743–4751.

    Article  ADS  Google Scholar 

  36. 7inch HDMI LCD (B) (Firmware Rev 2.1) User Manual - Waveshare Wiki https://www.waveshare.com/wiki/7inch_HDMI_LCD_(B)_(Firmware_Rev_2.1)_User_Manual (4 March 2018).

  37. YSI EXO1 Water Quality Sonde|YSI|ysi.com, https://www.ysi.com/exo1 (30 May 2020).

  38. Conductivity K 10 Kit|Atlas scientific, https://www.atlas-scientific.com/kits/conductivity-k-10-kit/ (5 June 2020).

  39. Python.org, Python 3.4 documentation, (2018).

  40. P. Khatri, K.K. Gupta and R.K. Gupta, A review of partial least squares modeling (PLSM) for water quality analysis. Model. Earth Syst. Environ., 1 (2020) 3.

    Google Scholar 

  41. S. Wold, M. Sjöström and L. Eriksson, PLS-regression: A basic tool of chemometrics. Chemom. Intell. Lab. Syst., 58 (2001) 109–130.

    Article  Google Scholar 

  42. R. G. Brereton, Multiclass Classifiers, in Chemometrics for pattern recognition, John Wiley & Sons, Ltd, Chichester, UK, (2009).

  43. A. Sargaonkar and V. Deshpande, Development of an overall index of pollution for surface water based on a general classification scheme in Indian context. Environ. Monit. Assess., 89 (2003) 43–67.

    Article  Google Scholar 

  44. J. Bhardwaj, K.K. Gupta and R. Gupta, Towards a cyber-physical era: Soft computing framework based multi-sensor array for water quality monitoring. Drink. Water Eng. Sci., 11 (2018) 9–17.

    Article  Google Scholar 

  45. G.D. Astudillo, L.E. Garza-Castanon and L.I. Minchala Avila, Design and evaluation of a reliable low-cost atmospheric pollution station in urban environment. IEEE Access, 8 (2020) 51129–51144.

    Article  Google Scholar 

  46. J. Pokhariyal, A. Mandal and S.G. Aggarwal, Uncertainty estimation in PM 10 mass measurements. Mapan - J. Metrol. Soc. India, 34 (2019) 129–133.

    Google Scholar 

  47. X. Inc, Hardness,Conductivity,TDS measurement, (2011) http://www.globalw.com/support/hardness.html (24 March 2021).

  48. P. Dadgar and P.E. Payandeh, Investigation of nitrate concentration and its correlation with water pH in drinking water distribution network of the City of Tabriz. Int. J. Sci. Study, 5 (2017) 726–731.

    Google Scholar 

  49. N. Soni and A. Bhatia, Analysis of quality of drinking water of private bore-well and piped water supply in Jaipur city, Rajasthan, India. Res. J. Recent Sci., 4 (2014) 313–316.

    Google Scholar 

  50. S. Chandra, T. Saxena, S. Nehra and M. Krishna Mohan, Quality assessment of supplied drinking water in Jaipur city, India, using PCR-based approach. Environ. Earth Sci., 75 (2016) 153.

    Article  Google Scholar 

  51. A. Halder, A. B. Roy, R. Sharma, V. N. Hegde and S. Kumuda, AquaPredicto—Freshwater quality management system for lakes, in IEEE region 10 humanitarian technology conference 2016, R10-HTC 2016—proceedings, Institute of Electrical and Electronics Engineers Inc., (2017).

  52. N. R. Moparthi, C. Mukesh and P. Vidya Sagar, Water quality monitoring system using IOT, in Proceedings of 4th IEEE international conference on advances in electrical, electronics, information, communication and bio-informatic, AEEICB 2018, Institute of Electrical and Electronics Engineers Inc., (2018).

  53. S. Chandra and T. Saxena, Smart water quality monitoring system with cost-effective using IoT. Heliyon, 6 (2020) e4096.

    Article  Google Scholar 

Download references

Acknowledgements

The authors are pleased to acknowledge the Birla Institute of Technology and Science (BITS), Pilani, India, for providing an enabling environment to carry out the research work. The authors thank the Director, CSIR-CEERI, Pilani, for their support during the research work. The authors also thank the Editor, Associate Editor, and anonymous reviewers for reviewing the manuscript. Authors thank the Department of Science and Technology, Govt. of India, New Delhi, for setting up the research facility (Grant No. DST/TM/WTI/2K16/103). The authors also thank the Council of Scientific and Industrial Research-Human Resource Development Group (CSIR-HRDG) for providing financial support as a fellowship (Award No. 09/719(0101)/2019-EMR-I).

Author information

Authors and Affiliations

  1. Department of Electrical and Electronics Engineering, Birla Institute of Technology and Science (BITS), Pilani, Rajasthan, India

    Punit Khatri & Karunesh Kumar Gupta

  2. Department of Physics, Birla Institute of Technology and Science (BITS), Pilani, Rajasthan, India

    Raj Kumar Gupta

  3. CSIR-Central Electronics Engineering Research Institute (CSIR-CEERI), Pilani, Rajasthan, India

    P. C. Panchariya

Authors
  1. Punit Khatri
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Karunesh Kumar Gupta
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Raj Kumar Gupta
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. P. C. Panchariya
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Punit Khatri.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Khatri, P., Gupta, K.K., Gupta, R.K. et al. Towards the Green Analytics: Design and Development of Sustainable Drinking Water Quality Monitoring System for Shekhawati Region in Rajasthan. MAPAN 36, 843–857 (2021). https://doi.org/10.1007/s12647-021-00465-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12647-021-00465-x

Keywords

Search

Navigation