Question Answering System for Smart Cities and Urban Planning With The World Avatar

ABSTRACT ‘Zaha’ is a retrieval‐augmented generation question answering system integrated with The World Avatar knowledge graph, designed to support urban planning and smart city initiatives by enabling intuitive natural language queries for complex urban data. Zaha facilitates the querying of diverse domains within the urban environment, offering an accessible and effective tool for urban data analysis. By simplifying access to complex dataset, Zaha addresses a critical barrier in urban planning and management: the need for technical expertise to query data effectively. Urban data, encompassing geospatial, environmental, and regulatory information, is pivotal in informing decision‐making processes. However, challenges such as data silos and the technical complexity of query tools and languages hinder the accessibility and utilisation of urban data. The integration of Zaha with The World Avatar knowledge graph further mitigates the issue of data silos by unifying urban data from diverse sources and formats into a single framework. Leveraging knowledge graph technology, Zaha facilitates efficient data retrieval based on the relationships defined between entities. By bridging the gap between data and users, Zaha empowers urban planners and other stakeholders to access and query complex urban data intuitively, enabling them to make informed decisions without requiring technical expertise.

Publication Details

Journal
Apollo (University of Cambridge)
Published
2025-01-01
DOI
https://doi.org/10.17863/cam.120181
Primary Topic
Multimodal Machine Learning Applications
Type
article
Field-Weighted Citation Impact
0.00

Funders

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article

Question Answering System for Smart Cities and Urban Planning With The World Avatar

Apollo (University of Cambridge)
Multimodal Machine Learning Applications
article

Question Answering System for Smart Cities and Urban Planning With The World Avatar

article en

Abstract

ABSTRACT ‘Zaha’ is a retrieval‐augmented generation question answering system integrated with The World Avatar knowledge graph, designed to support urban planning and smart city initiatives by enabling intuitive natural language queries for complex urban data. Zaha facilitates the querying of diverse domains within the urban environment, offering an accessible and effective tool for urban data analysis. By simplifying access to complex dataset, Zaha addresses a critical barrier in urban planning and management: the need for technical expertise to query data effectively. Urban data, encompassing geospatial, environmental, and regulatory information, is pivotal in informing decision‐making processes. However, challenges such as data silos and the technical complexity of query tools and languages hinder the accessibility and utilisation of urban data. The integration of Zaha with The World Avatar knowledge graph further mitigates the issue of data silos by unifying urban data from diverse sources and formats into a single framework. Leveraging knowledge graph technology, Zaha facilitates efficient data retrieval based on the relationships defined between entities. By bridging the gap between data and users, Zaha empowers urban planners and other stakeholders to access and query complex urban data intuitively, enabling them to make informed decisions without requiring technical expertise.

Apollo (University of Cambridge)
National Research Foundation
Sustainable cities and communities
Openalex Percentile: Top 51%
Multimodal Machine Learning Applications
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