Sustainable Urban Water Decisions Using Generative Artificial Intelligence

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.

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Publication Details

Published
2024-12-11
DOI
https://doi.org/10.1109/dasa63652.2024.10836374
Citations
1
Primary Topic
Hydrological Forecasting Using AI
Type
article
Field-Weighted Citation Impact
0.21
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article

Sustainable Urban Water Decisions Using Generative Artificial Intelligence

Zainab Riaz, Muhammad Arslan, Saba Munawar
1 citations
Hydrological Forecasting Using AI
0.21
article

Sustainable Urban Water Decisions Using Generative Artificial Intelligence

Zainab Riaz, Muhammad Arslan, Saba Munawar
article en
1 citations

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.

Abu Dhabi University (AE), University of the West of England (GB), National University of Computer and Emerging Sciences (PK)
Sustainable cities and communities
Openalex Percentile: Top 47%
Hydrological Forecasting Using AI
0.21
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Sustainable Urban Water Decisions Using Generative Artificial Intelligence — Zainab Riaz, Muhammad Arslan, et al. · (2024) | TGRS Research Map | TGRS