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BIBLIOGRAFIA prodotta dal laboratorio
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| A hybrid, integrated IEDDS for the management of Sequencing Batch Reactors | ||
| Autori | Sottara, D., Bragaglia, S., Pulcini, D., Mello, P., Luccarini, L. Anno 2014 | |
| Tipologia | Articolo Conferenza internazionale con referaggio | |
| Abstract | A Sequencing Batch Reactor (SBR) is a particular kind of wastewater treatment plant (WWTP), where all treatment processes take place in a single reactor tank, according to a fixed temporal sequence. SBR offers several advantages in terms of reduced costs, minor impact and greater flexibility with respect to traditional WWTPs. However, an optimal cost/performance ratio can only be achieved if the treatment processes are continuously monitored and controlled. In this paper, we present a hybrid, distributed, knowledge-based (Intelligent) Environmental Decision Support System (IEDSS) specifically dedicated to the management of SBRs. The IEDSS is responsible for verifying, ensuring and enforcing the compliance of the processes with the optimal operation policies and the current regulations. The core of the IEDSS is composed by a hybrid, declarative knowledge base that encodes the knowledge and best practices for the management of the plant. It relies on OWL ontologies to describe the plant and its hardware equipment, business processes to model the plants treatment cycles, business rules to encode decision-making policies, an improved variant of Event Calculus (EC) to manage the temporal aspects and a compliance mechanism based on extended Event-Condition-Action rules (ECA rule) to monitor and check the compliance of its evaluations and decisions. The system as a whole has been implemented using open source technologies and has been tested on data coming from a pilot plant fed with real urban wastewater. |
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| Referenza_Bibliografica | In: Ames, D.P., Quinn, N.W.T., Rizzoli, A.E. (Eds.), Proceedings of the 7th International Congress on Environmental Modelling and Software, June 15-19, San Diego, California, USA. ISBN: 978-88-9035-744-2. |
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| Unita di Ricerca | X-LAB | |
| LastUpdate | 14/03/2017 | |
| impact factor | Falso |
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