Applying kohonen self-organizing map as a software sensor to predict biochemical oxygen demand

Rabee Rustum, Adebayo J. Adeloye, Miklas Scholz

Research output: Contribution to journalArticlepeer-review

35 Citations (Scopus)


The 5 days at 20°C biochemical oxygen demand (BOD5) is an important parameter for monitoring organic pollution in water and assessing the biotreatability of wastewater. Moreover, BOD5 is used for wastewater treatment plant discharge consents and other water pollution control purposes. However, the traditional bioassay method for estimating the BOD5 involves the incubation of sample water for 5 days. It follows that BOD 5 is not available for real-time decisionmaking and process control purposes. On the other hand, previous efforts to solve this problem by developing more rapid biosensors had limited success. This paper reports on the development of Kohonen self-organizing map (KSOM)-based software sensors for the rapid prediction of BOD5. The findings indicate that the KSOM-based BOD5 estimates were in good agreement with those measured using the conventional bioassay method. This offers significant potential for more timely intervention and cost savings during problem diagnosis in water and wastewater treatment processes.

Original languageEnglish
Pages (from-to)32-40
Number of pages9
JournalWater Environment Research
Issue number1
Publication statusPublished - Jan 2008
Externally publishedYes


  • Bioassay
  • Biochemical oxygen demand
  • Biosensor
  • Cost saving
  • Decisionmaking
  • Kohonen self-organizing map
  • Neural networks
  • Process control
  • Software sensor
  • Wastewater treatment plant

ASJC Scopus subject areas

  • Environmental Chemistry
  • Ecological Modeling
  • Water Science and Technology
  • Waste Management and Disposal
  • Pollution


Dive into the research topics of 'Applying kohonen self-organizing map as a software sensor to predict biochemical oxygen demand'. Together they form a unique fingerprint.

Cite this