Huzaifa Nayeem received his MS in Electronics and Communication Engineering (ECE). His research work was supervised by Dr. Azeemuddin Syed. Here’s a summary of Huzaifa Nayeem’s MS thesis, Design and Development of Wavelength Specific Technique for Select Water Quality Parameters Measurement as explained by him:
Water quality assessment has undeniable value for humanity’s well-being. It is a principle strategy that aids in ascertaining water contaminants, providing information about the state of water supplies, and plays a vital role in their efficient management. Despite that, most of the existing techniques struggle to rapidly measure the quality of water due to costly infrastructure or large evaluation time. Recently, quality measurement has been demonstrated using spectrum analysis. Although this method has been investigated in studies, the focus has been on analysing spectrum of wavelengths to predict the quality of water, which relies on commercial spectrometers for spectrum acquisition. However, these modern systems need complicated signal processing algorithms and high processor capabilities for decision making. They have elaborate optical assemblies and sizable power requirements, making them bulky and expensive to operate. Thus, a refined technique with simplified implementation, low cost, and reliable long-time operation is essential to address this challenge.
We present a holistic approach towards a simple and rapid method for determining water quality parameters in sampled and flowing water. This is based on the selection of characteristic wavelengths for the parameters considered and the usage of narrowband LEDs as the inspection light source. Thereby incorporating the benefits of optical sensing such as electromagnetic immunity, selectivity, sensitivity, etc. The specific wavelengths of 560nm, 860nm, and 635nm have been demonstrated to have a dominant effect due to pH, turbidity, and total dissolved solids (TDS), respectively, from the regression analysis. Partial least square regression was applied on the dataset of absorption spectra prepared to estimate the significant wavelengths. This selection of wavelengths was supported by determining wavelength significance using neighbourhood components analysis, which gave similar wavelengths. To visualise the spread and distribution in spectral data, t-distributed stochastic neighbour embedding was used.
Using only these wavelengths, an evaluation system capable of determining the light absorption after passing through water has been designed and developed. A prototype structure was designed, and LEDs of the selected wavelengths were utilized as light sources along with the corresponding photodiode to determine absorbance. The obtained optical responses are subsequently related to water parameters, specifically pH, turbidity, and TDS. Experiments were performed to evaluate samples and then validate this technique against standard instruments for flowing and sampled water setups. It is shown from the measurement results that pH, turbidity, and TDS have linear regression coefficients of 0.9773, 0.9617, 0.8271 and0.9691, 0.9729, 0.76 for flowing and sampled water arrangements, respectively. This study asserts the application of wavelength-specific absorption to assess water quality parameters and provides results based on spectral analysis and experimental implementation using LEDs, leading to a similar conclusion.