AI techniques for waste water treatment plant control case study: Denitrification in a pilot-scale SBR

Davide Sottara, Luca Luccarini, Paola Mello

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

We propose to show how different AI techniques might be used in the development of a modular expert system, acting as a manager and advisor for the operation of a pilot-scale SBR urban wastewater treatment plant, fed with real sewage. The plant's depurative effectiveness and global biomass' health depend on the reactions of nitrification and denitrification, with the former taking place as soon as the latter is complete. Since the duration of the reaction cannot be predicted, we have trained an intelligent software to recognize the event analyzing the profiles of some available signals, namely pH, orp and dissolved oxygen, thus allowing us to optimize the process' yield and detect possible failures. Using a SOM neural network, the system has been trained to remember an adequate set of reference signals, which have been given meaning using Bayesian belief techniques. Eventually, using the formalism provided by logical languages, reasoning capabilities have been imparted to the system, allowing the real-time, online deduction of new pieces of needed information. Thanks to the integration of these techniques the system is able to assess the status of the plant and act according to the adequate known policies.

Original languageEnglish (US)
Title of host publicationKnowledge-Based Intelligent Information and Engineering Systems
Subtitle of host publicationKES 2007 - WIRN 2007 - 11th International Conference, KES 2007, XVII Italian Workshop on Neural Networks, Proceedings
PublisherSpringer Verlag
Pages639-646
Number of pages8
EditionPART 1
ISBN (Print)9783540748175
DOIs
StatePublished - 2007
Event11th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2007, and 17th Italian Workshop on Neural Networks, WIRN 2007 - Vietri sul Mare, Italy
Duration: Sep 12 2007Sep 14 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume4692 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other11th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2007, and 17th Italian Workshop on Neural Networks, WIRN 2007
CountryItaly
CityVietri sul Mare
Period9/12/079/14/07

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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    Sottara, D., Luccarini, L., & Mello, P. (2007). AI techniques for waste water treatment plant control case study: Denitrification in a pilot-scale SBR. In Knowledge-Based Intelligent Information and Engineering Systems: KES 2007 - WIRN 2007 - 11th International Conference, KES 2007, XVII Italian Workshop on Neural Networks, Proceedings (PART 1 ed., pp. 639-646). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4692 LNAI, No. PART 1). Springer Verlag. https://doi.org/10.1007/978-3-540-74819-9_79