Data and Information Systems Management for the Urban Water Infrastructure Condition Assessment

Abstract

Most of urban water infrastructure around the world were built several decades ago and nowadays they are deteriorated. So, the assets that constitute these infrastructures need to be rehabilitated. Since most of the assets are buried, water utilities face the challenge of deciding how, where and when to rehabilitate. Condition assessment is a vital component on plan rehabilitation actions and is mostly based on the data collected from the managed networks. This collected data need to be put together in order to be transformed into useful information. Nonetheless, the large amount of assets and data involved makes data and information management a challenging task for water utilities, especially in those with as lower digital maturity level. This paper highlights the importance of data and information systems' management for urban water infrastructure condition assessment based on the authors' experience.

Lessons Learnt from the Application of MCDA Sorting Methods to Pipe Network Rehabilitation Prioritization

“…The available data in the water utility limits the selection of possible assessment criteria. Due to the lack of human resources, technical and financial capacity, it is usually not possible for the water utilities to systematically generate the required information through daily routines [48]. Therefore, an attempt was made to select possible criteria considering the available data existing in the utility.…”

Computational Tools for Supporting the Operation and Management of Water Distribution Systems towards Digital Transformation

“…Acknowledging that the core business of water utilities is to provide drinking water and wastewater services to residential, commercial, and industrial sectors of the economy, information is the key element for operating and managing these services [1,2]. Water services bring together a wide variety of collected data (e.g., flow rate, pressure, energy consumption, end-user consumption) [3][4][5]. Depending on the water utility maturity level, different data can be collected with different acquisition frequencies, manually in situ by an operator (e.g., domestic consumption) or automatically by smart meters or by sensors installed in the systems (e.g., flow rate, pressure) [6].…”

“…Therefore, these big data require the use of artificial intelligence (AI) techniques, such as data mining and machine learning, to extract relevant information and present them in a more user-friendly format that can assist utility experts in the decision-making processes. As a result, new tools and processes are needed to collect, gather, manage, analyze, and extract knowledge from existing data [5,14,15] and to assist decision-making processes [16].…”

An Information Systems for Infrastructure Asset Management Tailored to Portuguese Water Utilities: Platform Conceptualization and A Prototype Demonstration

“…Several information systems (IS) are typically used to produce, transform, manipulate, and analyze the desired information. The most widely used IS by water utilities are geographic information system (GIS), customer relationship management (CRM), customer information system (CIS), enterprise resource planning system (ERP), and supervisory control and data acquisition system (SCADA), computerized maintenance management system (CMMS), laboratory information management system (LIMS), among others [5].…”

“…In many utilities, the lack of human resources and their vulnerability to commercial pressures are often the basis for reactively acquiring solutions (e.g. miraculous software packages that solve all the WSS problems) and, thus, lacking longterm planning for the use of the acquired software [5]. As such, the complete IS capabilities are usually not fully explored since they are acquired due to just a set of functionalities.…”