Water/Waste Water: Clean Water AI – Automated Water

Image 1: Smart City model, Source: Laremenko, iStock

Executive Summary

Leading tech companies in industrialized countries already deploy artificial intelligence (AI) applications at scale to improve business practices, administration, environmental protection or health services. But also, for low- and middle-income coun-

tries, AI applications offer a range of new opportunities for

service providers and governments on all levels. AI-powered approaches can break down existing barriers to human development and social inclusion and help to achieve the global Sustainable Development Goals in a more efficient manner. Cities worldwide are home to many of the key requirements for AI innovation, including vibrant ecosystems, data sources and infrastructure. Urban areas are thus ideal places to harness the power of AI for sustainable development.

In this study, the Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH together with the Austrian Institute of Technology (AIT) examine promising, real-world use cases of AI-powered urban development projects in the fields of urban planning, building management, municipal/public finance, mobility, waste management and water/wastewater. The objec-

tive is to showcase what AI can already achieve in urban

development today. Going deeper, for each of these pioneer projects we provide lessons learnt in terms of the technical

framework employed, their approaches to data, risk and project management, followed by a discussion on transferability, cost vs. benefit and critical points that may arise.

In Ho Chi Minh City, Vietnam, AI-powered computer

vision based on satellite data supports the city authority to

monitor changes in land use to facilitate integrated urban planning processes. In Peru, an AI-assisted system that understands text is set up to support the detection of suspicious money laundering transaction to secure public budgets. In Großschönau (Austria) and Vilogia (France), an AI-powered system monitors and predicts energy and electricity consumption in residential buildings to raise awareness and drive more resource-efficient consumption. In cities all over the world, the CleanWater AI can help detect pollutants on a microscopic scale, affordably and in near real-time to improve water supply systems. The Let’s Do It AI technology can provide cities worldwide with an AI-powered tool to improve their solid waste management operations by automated garbage detection in public places. Finally, in the UK the Thames Valley Berkshire Live Labs illustrates how AI-powered systems can improve urban mobility and integrated planning and operations for multiple positive effects on citizen’s well-being and the environment.

In the last chapter, we reflect on the success factors of these

projects and lay out recommendations for using AI applica-

tions in contexts of integrated sustainable urban development in low- and middle-income countries.