In this paper, colorimetric analysis for biochemical samples has been realized, by developing an easy-to-use smartphone colorimetric sensing android application that can measure the molar concentration of the biochemical liquid analyte. The designed application can be used for on-site testing and measurement. We examined three different biochemical materials with the application after preparation with five different concentrations and testing in laboratory settings, namely glucose, triglycerides, and urea. Our results showed that for glucose triglycerides, and urea the absorbance and transmittance regression coefficient (R2) for the colorimetric sensing application were 0.9825, and 0.9899; 0.9405 and 0.9502; 0.9431 and 0.8597, respectively. While for the spectrophotometer measurement the (R2) values were 0.9973 @560 nm and 0.9793 @600 nm; 0.952 @620 nm and 0.9364 @410 nm; 0.9948 @570 nm and 0.9827 @530 nm, respectively. The novelty of our study lies in the accurate prediction of multiple biochemical materials concentrations in various lightning effects, reducing the measurement time in an easy-to-use portable environment without the need for internet access, also tackling various issues that arise in the traditional measurements like power consumption, heating, and calibration. The ability to convey multiple tasks, prediction of concentration, measurement of both absorbance and transmittance, with error estimation charts and (R2) values reporting within the colorimetric sensing application as far as our knowledge there has not been any application that can provide all the capabilities of our application.


Alawsi, T., Proietti Mattia, G., Al-Bawi, Z., & Beraldi, R. (2021). Smartphone-based colorimetric sensor application for measuring biochemical material concentration. Sensing and Bio-Sensing Research, 100404. https://doi.org/doi.org/10.1016/j.sbsr.2021.100404

  title = {Smartphone-based colorimetric sensor application for measuring biochemical material concentration},
  author = {Alawsi, Taif and {Proietti Mattia}, Gabriele and Al-Bawi, Zainab and Beraldi, Roberto},
  year = {2021},
  journal = {Sensing and Bio-Sensing Research},
  pages = {100404},
  doi = {doi.org/10.1016/j.sbsr.2021.100404},
  issn = {2214-1804},
  url = {https://www.sciencedirect.com/science/article/pii/S221418042100009X},
  keywords = {Smartphone sensors, Colorimetric analysis. Android application}