Photonic Sensors

, Volume 5, Issue 4, pp 289–297 | Cite as

Early warning smartphone diagnostics for water security and analysis using real-time pH mapping

  • Md. Arafat Hossain
  • John Canning
  • Sandra Ast
  • Peter J. Rutledge
  • Abbas Jamalipour
Open Access


Early detection of environmental disruption, unintentional or otherwise, is increasingly desired to ensure hazard minimization in many settings. Here, using a field-portable, smartphone fluorimeter to assess water quality based on the pH response of a designer probe, a map of pH of public tap water sites has been obtained. A custom designed Android application digitally processed and mapped the results utilizing the global positioning system (GPS) service of the smartphone. The map generated indicates no disruption in pH for all sites measured, and all the data are assessed to fall inside the upper limit of local government regulations, consistent with authority reported measurements. This implementation demonstrates a new security concept: network environmental forensics utilizing the potential of novel smartgrid analysis with wireless sensors for the detection of potential disruption to water quality at any point in the city. This concept is applicable across all smartgrid strategies within the next generation of the Internet of Things and can be extended on national and global scales to address a range of target analytes, both chemical and biological.


Lab-in-a-phone Internet of Things optical sensing and sensor smartphone sensor photonic sensor fluorescence water security 


  1. [1]
    Australian government’s National Health and Medical Research Council, “Australian drinking water guidelines 6,” National Water Quality Management Strategy, 2013, 2: 174.Google Scholar
  2. [2]
    Sydney Water, Quarterly Drinking Water Quality Report, 1 Jul. 2013 to 30 Sep. 2013, Sydney, Australian: Sydney Water., 2014.Google Scholar
  3. [3]
    P. H. Gleick, “Water and terrorism,” Water Policy, 2006, 8(6): 481–503.CrossRefGoogle Scholar
  4. [4]
    J. S. Hall, J. G. Szabo, S. Panguluri, and G. Meiners, Distribution System Water Quality Monitoring: Sensor Technology Evaluation Methodology and Results, Cincinnati, U. S. A.: U. S. Environmental Protection Agency, 2009.Google Scholar
  5. [5]
    J. V. Capella, A. Bonastre, R. Ors, and M. Peris, “A wireless sensor network approach for distributed in-line chemical analysis of water,” Talanta, 2010, 80(5): 1789–1798.CrossRefGoogle Scholar
  6. [6]
    M. A. Hossain, J. Canning, S. Ast, T. L. Yen, P. J. Rutledge, and A. Jamalipour, “A smartphone fluorometer - the lab-in-a-phone,” in Conference: Optical Sensor, pp. SeTh2C.1, 2014.Google Scholar
  7. [7]
    M. A. Hossain, J. Canning, S. Ast, P. J. Rutledge, T. L. Yen, and A. Jamalipour, “Lab-in-a-phone: smartphone-based portable fluorometer for pH measurements of environmental water,” IEEE Sensor Journal, 2015, 15(9): 5095–5102.CrossRefGoogle Scholar
  8. [8]
    A. F. Coskun, J. Wong, D. Khodadadi, R. Nagi, A. Teya, and A. Ozcan, “A personalized food allergen testing platform on a cell phone,” Lab Chip, 2013, 13(4): 636–640.CrossRefGoogle Scholar
  9. [9]
    Q. Wei, R. Nagi, K. Sadeghi, S. Feng, E. Yan, S. J. Ki, et al., “Detection and spatial mapping of mercury contamination in water samples using a smart-phone,” ACS Nano, 2014, 8(2): 1121–1129.CrossRefGoogle Scholar
  10. [10]
    S. Sumriddetchkajorn, K. Chaitavon, and Y. Intaravanne, “Mobile-platform based colorimeter for monitoring chlorine concentration in water,” Sensors and Actuators B: Chemical, 2014, 191: 561–566 2014.CrossRefGoogle Scholar
  11. [11]
    Y. Intaravannea, S. Sumriddetchkajorn, and J. Nukeawa, “Cell phone-based two-dimensional spectral analysis for banana ripeness estimation,” Sensors and Actuators B: Chemical, 2012, 168: 390–394.CrossRefGoogle Scholar
  12. [12]
    A. García, M. M. Erenas, E. D. Marinetto, C. A. Abada, I. O. Paya, A. J. Palma, et al., “Mobile phone platform as portable chemical analyzer,” Sensors and Actuators B: Chemical, 2011, 156(1): 350–359, 2011.CrossRefGoogle Scholar
  13. [13]
    Z. Iqbal and R. B. Bjorklund, “Assessment of a mobile phone for use as a spectroscopic analytical tool for foods and beverages,” International Journal of Food Science & Technology, 2011, 46(11): 2428–2436.CrossRefGoogle Scholar
  14. [14]
    J. Canning, A. Lau, M. Naqshbandi, I. Petermann, and M. J. Crossley, “Measurement of fluorescence in a rhodamine-123 doped self-assembled’ giant’ meso-structured silica sphere using a smartphone as optical hardware,” Sensors, 2011, 11(7): 70551–7062.Google Scholar
  15. [15]
    Z. Iqbal and R. B. Bjorklund, “Colorimetric analysis of water and sand samples performed on a mobile phone,” Talanta, 2011, 84(4): 1118–1123.CrossRefGoogle Scholar
  16. [16]
    T. S. Park and J. Y. Yoon, “Smartphone detection of escherichia coli from field water samples on paper microfluidics” IEEE Sensor Journal, 2015, 15(3): 1902–1907.MathSciNetCrossRefGoogle Scholar
  17. [17]
    D. N. Breslauer, R. N. Maamari, N. A. Switz, W. A. Lam, and D. A. Fletcher, “Mobile phone based clinical microscopy for global health applications,” PLoS ONE, 2009, 4(7): e6320-1–e6320-7, 2009.Google Scholar
  18. [18]
    Z. J. Smith, K. Chu, A. R. Espenson, A. Gryshuk, M. Molinaro, D. M. Dwyre, et al., “Cell phone-based platform for biomedical device development and education applications,” PLoS ONE, 2011, 6(3): e17150-1–e17150-11.Google Scholar
  19. [19]
    Q. Wei, H. Qi, W. Luo, D. Tseng, S. J. Ki, Z. Wan, et al., “Fluorescent imaging of single nanoparticles and viruses on a smart phone,” ACS Nano, 2013, 7(10): 9147–9155.CrossRefGoogle Scholar
  20. [20]
    A. Skandarajah, C. D. Reber, N. A. Switz, and D. A. Fletcher, “Quantitative imaging with a mobile phone microscope,” PLoS ONE, 2014, 9(5): e96906-1–e96906-12.Google Scholar
  21. [21]
    S. Lee and C. Yang, “A smartphone-based chip-scale microscope using ambient illumination,” Lab Chip, 2014, 14(16): 3056–3063.CrossRefGoogle Scholar
  22. [22]
    H. C. Koydemir, Z. Gorocs, D. Tseng, B. Cortazar, S. Feng, R. Y. L. Chan, et al., “Rapid imaging, detection and quantification of Giardia lamblia cysts using mobile-phone based fluorescent microscopy and machine learning,” Lab Chip, 2015, 15(5): 1284–1293.CrossRefGoogle Scholar
  23. [23]
    S. K. J. Ludwig, H. Zhu, S. Phillips, A. Shiledar, S. Feng, D. Tseng, et al., “Cellphone-based detection platform for rbST biomarker analysis in milk extracts using a microsphere fluorescence immunoassay,” Analytical and Bioanalytical Chemistry, 2014, 406(27): 6857–6866.CrossRefGoogle Scholar
  24. [24]
    D. Gallegos, K. D. Long, H. Yu, P. P. Clark, Y. Lin, S. George, et al., “Label-free bio-detection using a smartphone,” Lab Chip, 2013, 13(11): 2124–2132.CrossRefGoogle Scholar
  25. [25]
    H. Yu, Y. Tan, and B. T. Cunningham, “Smartphone fluorescence spectroscopy,” Analytical Chemistriy, 2014, 86(17): 8805–8813.CrossRefGoogle Scholar
  26. [26]
    S. Dutta, A. Choudhury, and P. Nath, “Evanescent wave coupled spectroscopic sensing using smartphone,” IEEE Photonics Technology Letters, 2014, 26(6): 568–570.CrossRefADSGoogle Scholar
  27. [27]
    M. A. Hossain, J. Canning, S. Ast, K. Cook, P. J. Rutledge, and A. Jamalipour, “Combined ‘dual’ absorption and fluorescent smartphone spectrometers,” Optics Letters, 2015, 40(8): 1737–1740.CrossRefADSGoogle Scholar
  28. [28]
    A. W. Martinez, S. T, Phillips, E. Carrilho, S. W. Thomas, H. Sindi, and G. M. Whitesides, “Simple telemedicine for developing regions: camera phones and paper-based microfluidic devices for real-time, off-site diagnosis,” Analytical Chemistriy, 2008, 80(10): 3699–3707.CrossRefGoogle Scholar
  29. [29]
    L. Shen, J. A. Hagan, and I. Papautsky, “Point-of-care colorimetric detection with a smartphone,” Lab Chip, 2012, 12(21): 4240–4243.CrossRefGoogle Scholar
  30. [30]
    J. I. Hong and B. Y. Chang, Development of “Smartphone-based colorimetry for multi-analyte sensing arrays,” Lab Chip, 2014, 14(10): 1725–1732.CrossRefGoogle Scholar
  31. [31]
    J. E. Smith, D. K. Griffin, J. K. Leny, J. A. Hagen, J. L. Chávez, and N. K. Loughnane, “Colorimetric detection with aptamer-gold nanoparticle conjugates coupled to an android based color analysis application for use in the field,” Talanta, 2014, 121: 247–255.CrossRefGoogle Scholar
  32. [32]
    O. M. Mancuso and D. Erickson, “Cholesterol testing on a smartphone,” Lab Chip, 2014, 14(4): 759–763.CrossRefGoogle Scholar
  33. [33]
    N. S. K. Gunda, S. Naicker, S. Shinde, S. Kimbahune, S. Shrivastava, and S. Mitra, “Mobile water kit (MWK): a smartphone compatible low-cost water monitoring system for rapid detection of total coliform and E. coli,” Analytical Methods, 2014, 6(16): 62361–6246.Google Scholar
  34. [34]
    D. Erickson, D. O’Dell, L. Jiang, V. Oncescu, A. Gumus, S. Lee, et al., “Smartphone technology can be transformative to the deployment of lab-on-chip diagnostics,” Lab Chip, 2014, 14(17): 3159–3164.CrossRefGoogle Scholar
  35. [35]
    T. S. Park, C. Baynes, S. I. Cho, and J. Y. Yoon, “Paper microfluidics for red wine tasting,” RSC Advance, 2014, 4(46): 24356–24362.CrossRefGoogle Scholar
  36. [36]
    International Telecommunication Union, Mobile-cellular subscriptions 2013, Available online:, 2015.Google Scholar
  37. [37]
    B. Oram, Water Research Centre, Available online:, 2014.Google Scholar
  38. [38]
    J. Buffle and G. Horvai, In Situ Monitoring of Aquatic Systems: Chemical Analysis and Speciation. New York, U. S. A.: Willey, 2000.Google Scholar
  39. [39]
    J. Canning, M. Naqshbandi, and M. J. Crossley, “Measurement of rhodamine B absorption in self-assembled silica microwires using a Tablet as the optical source,” in Proc. SPIE, vol. 8351, pp. 83512E-1–83512E -5, 2012.Google Scholar
  40. [40]
    S. Feng, R. Caire, B. Cortazar, M. Turan, A. Wong, and A. Ozcan “Immunochromatographic diagnostic test analysis using Google Glass,” ACS Nano, 2014, 8(3): 3069–3079.CrossRefGoogle Scholar
  41. [41]
    B. Cortazar, H. C. Koydemir, D. Tseng, S. Feng, and A. Ozcan, “Quantification of plant chlorophyll content using google glass,” Lab Chip, 2015, 15(7): 1708–1716.CrossRefGoogle Scholar
  42. [42]
    Sesorex, SAM-1 for iPhone, iPad and Android, Avialable online: /more/sam_1, 2015.Google Scholar
  43. [43]
    A. P. D. Silva, H. Q. N. Gunaratne, J. L. Habib-Jiwan, C. P. McCoy, T. E. Rice, and J. P. Soumillion, “New fluorescent model compounds for the study of photoinduced electron transfer: the influence of a molecular electric field in the excited state,” Angewandte Chemie International Edition, 1995, 34(16): 1728–1731.CrossRefGoogle Scholar

Copyright information

© The Author(s) 2015

Authors and Affiliations

  • Md. Arafat Hossain
    • 1
    • 3
  • John Canning
    • 1
    • 2
  • Sandra Ast
    • 2
  • Peter J. Rutledge
    • 2
  • Abbas Jamalipour
    • 3
  1. 1.interdisciplinary Photonics Laboratories (iPL), School of ChemistryThe University of SydneySydneyAustralia
  2. 2.School of ChemistryThe University of SydneySydneyAustralia
  3. 3.Wireless Networking Group (WiNG), School of Electrical and Information EngineeringThe University of SydneySydneyAustralia

Personalised recommendations