To maintain a clean and secure workplace, it is crucial to appropriately handle and dispose of waste materials. Wastewater treatment is a crucial component of waste material processing that plays a vital role in maintaining the well-being of our ecosystem. Various challenges arise in the sewage treatment process, which is both intricate and exhausting. The processes utilized for sewage treatment require a significant amount of power consumption and may also produce by-products, such as carbon dioxide and nitrogen dioxide, that might potentially harm the environment. The key parameters of sewage water are Biochemical Oxygen Demand (BOD), ammonia, and Total Suspended Solids (TSS). This research paper presents a classification model that can accurately assess the quality of influent water and assist processing plants in optimizing resource usage for wastewater treatment.

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Influent Sewage Water Classification Using Machine Learning

  • Suman Goswami,
  • Subir Panja,
  • Subhasis Dasgupta,
  • Arindrajit Pal

摘要

To maintain a clean and secure workplace, it is crucial to appropriately handle and dispose of waste materials. Wastewater treatment is a crucial component of waste material processing that plays a vital role in maintaining the well-being of our ecosystem. Various challenges arise in the sewage treatment process, which is both intricate and exhausting. The processes utilized for sewage treatment require a significant amount of power consumption and may also produce by-products, such as carbon dioxide and nitrogen dioxide, that might potentially harm the environment. The key parameters of sewage water are Biochemical Oxygen Demand (BOD), ammonia, and Total Suspended Solids (TSS). This research paper presents a classification model that can accurately assess the quality of influent water and assist processing plants in optimizing resource usage for wastewater treatment.