[month] [year]

Huzaifa Nayeem – MS ECE

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.