Data analytics, digitalization, and decision-support systems in wastewater management

Le résumé fourni par la source

Recent advances in wastewater treatment systems have made data an integral part of planning, operation, and long-term management. The traditional methods based on periodic sampling and reactive decision-making are no longer able to cope with changing influent loads, energy constraints, and tightening regulations. This chapter reports on how data analytics and digitalization are changing wastewater management in ways that enable more informed, timely, and adaptive decisions. This chapter also examines how real-time data acquisition, advanced analytics, and decision-support systems can help improve process efficiency and operation reliability. The emphasis is on the application of predictive models, performance indicators and digital platforms to translate complex data into actionable insights for operators and planners. Instead of presenting digital tools as part of a solution, the chapter reflects how useful they are when incorporated into existing infrastructure and human expertise. In addition, concern is raised with data quality, system interoperability, and institution readiness, particularly with limited resources. This chapter draws out the potential for technology as well as the actuals of implementation by emphasizing how data-driven approaches can lead to sustainable, resilient, and transparent wastewater management systems.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.