Risk assessment of sewer condition using artificial intelligence tools: application to the SANEST sewer system

• Published in: Water science and technology Vol. 69; no. 3; pp. 622 - 627
• Main Authors: SOUSA, V, MATOS, J. P, ALMEIDA, N, MATOS, J. Saldanha
• Format: Journal Article
• Language: English
• Published: London International Water Association 01-01-2014; IWA Publishing
• Subjects: Ageing; Aging (artificial); Applied sciences; Artificial intelligence; Artificial neural networks; Asset management; Case studies; Discriminant Analysis; Drainage, Sanitary; Exact sciences and technology; Infrastructure; Neural networks; Neural Networks (Computer); Pollution; Portugal; Rehabilitation; Risk Assessment; Sewer maintenance; Sewer systems; Support Vector Machine; Support vector machines; Sustainability; Wastewater; Water treatment and pollution; Portugal; Portugal, Lisboa, Costa do Estoril; Statistical method; artificial neural networks; Sewer; sewer condition; support vector machines; Risk assessment; Sewer network; Support vector machine; Neural network; Risk analysis; Risk management; Artificial intelligence
• ISSN: 0273-1223; 1996-9732
• DOI: 10.2166/wst.2013.758

Operation, maintenance and rehabilitation comprise the main concerns of wastewater infrastructure asset management. Given the nature of the service provided by a wastewater system and the characteristics of the supporting infrastructure, technical issues are relevant to support asset management decisions. In particular, in densely urbanized areas served by large, complex and aging sewer networks, the sustainability of the infrastructures largely depends on the implementation of an efficient asset management system. The efficiency of such a system may be enhanced with technical decision support tools. This paper describes the role of artificial intelligence tools such as artificial neural networks and support vector machines for assisting the planning of operation and maintenance activities of wastewater infrastructures. A case study of the application of this type of tool to the wastewater infrastructures of Sistema de Saneamento da Costa do Estoril is presented.