A Machine Learning Framework for E. coli Bacteria Detection and Classification

  • Bushra Naz 1Department of Computer Systems Engineering, Mehran University of Engineering and Technology, Jamshoro, Pakistan
  • Shahzad Hyder Nanjing University of Science and Technology, China
  • Azlan Ahmed Department of Telecommunications, FET Sindh University, Pakistan
  • Ali Hasnain Department of Environment Engineering, Mehran University of Engineering and Technology, Jamshoro, Pakistan
Keywords: bacteria detection, machine learning


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Water plays an important role in physiological processes, such as the body's thermal equilibrium, the transfer of nutrients to the intended destination through the body, and the lubrication of joints. In Pakistan, the existing water availability is about 79%. Inadequate and adequate drinking water quality is a significant public health concern. In the project, we explain different machine learning techniques which are used to locate exact bacteria in a water sample, their shape, and scale. This technology promises sufficient identification and division. This invention allows for early identification of bacterial water pollution, requires minimal labor, etc. A robotic frame will speed up the treatment period without human power. It will reduce water emissions dramatically. The methods available for bacterial detection are effective but require lengthy waiting periods for results and expensive and laborious equipment. Via images with PYTHON (Its libraries), this research aims to detect bacteria utilizing images. This system tends to be effective and efficient way for water quality monitoring in different sectors in Pakistan. E.g., Wastewater treatment plants, Power plants, Industries, RO plants, and Laboratories.


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