Sustainable urban water decisions using Generative Artificial Intelligence

Arslan, Muhammad; Munawar, Saba; Riaz, Zainab

Abstract

Urban water systems are increasingly strained by the impacts of climate change, growing populations, and resource constraints, driving the need for more integrated and sustainable management solutions. Small and Medium-sized Enterprises (SMEs) are central to driving this transformation, leveraging their adaptability and significant impact on the industry. However, many SMEs lack access to comprehensive Information Systems (ISs) that combine data on government policies, industry trends, and water management initiatives, limiting their ability to implement sustainable practices. This study introduces Sustain WaterBot, a Chatbot powered by Generative Artificial Intelligence (GenAI), including Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG). Sustain WaterBot bridges this information gap by seamlessly integrating data from diverse sources such as news outlets, government publications, industry reports, scientific studies, and social media platforms into a unified IS. It enhances decision-making by providing timely and relevant insights into Sustainable Urban Water Initiatives (SUWIs) through an interactive Question Answering (QA) framework. By leveraging open-source technologies, Sustain WaterBot offers SMEs an affordable, scalable, and sustainable tool to adopt eco-friendly water practices while improving operational efficiency and informed decision-making.

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 2024 International Conference on Decision Aid Sciences and Applications (DASA)
• Start Date: Dec 11, 2024
• End Date: Dec 12, 2024
• Acceptance Date: Nov 30, 2024
• Online Publication Date: Jan 17, 2025
• Publication Date: Jan 17, 2025
• Deposit Date: Jan 18, 2025
• Publicly Available Date: Jan 21, 2025
• Publisher: Institute of Electrical and Electronics Engineers (IEEE)
• Peer Reviewed: Peer Reviewed
• Pages: 1-5
• Book Title: 2024 International Conference on Decision Aid Sciences and Applications (DASA)
• ISBN: 9798350369113
• DOI: https://doi.org/10.1109/dasa63652.2024.10836374
• Public URL: https://uwe-repository.worktribe.com/output/13625579