WaterCopilot: a water management AI virtual assistant for the Limpopo River Basin Digital Twin - technical guide

Simple item page
cg.contributor.affiliationInternational Water Management Instituteen_US
cg.contributor.affiliationAssociation for Water and Rural Development, South Africaen_US
cg.contributor.affiliationMicrosoft Research, USAen_US
cg.contributor.donorCGIAR Trust Funden_US
cg.contributor.donorLeona M. and Harry B. Helmsley Charitable Trusten_US
cg.contributor.initiativeDigital Innovationen_US
cg.coverage.countryBotswanaen_US
cg.coverage.countryMozambiqueen_US
cg.coverage.countrySouth Africaen_US
cg.coverage.countryZimbabween_US
cg.coverage.iso3166-alpha2BWen_US
cg.coverage.iso3166-alpha2MZen_US
cg.coverage.iso3166-alpha2ZAen_US
cg.coverage.iso3166-alpha2ZWen_US
cg.coverage.subregionLimpopo River Basinen_US
cg.creator.identifierChris Dickens: 0000-0002-4251-7767en_US
cg.creator.identifierMariangel Garcia: 0000-0002-4145-0847en_US
cg.identifier.iwmilibraryH053458en_US
cg.placeColombo, Sri Lankaen_US
cg.river.basinLIMPOPOen_US
dc.contributor.authorVickneswaran, Keerththananen_US
dc.contributor.authorRetief, H.en_US
dc.contributor.authorPadilha, R.en_US
dc.contributor.authorDickens, Chrisen_US
dc.contributor.authorSilva, Pauloen_US
dc.contributor.authorGarcia Andarcia, Mariangelen_US
dc.date.accessioned2025-01-28T14:26:47Zen_US
dc.date.available2025-01-28T14:26:47Zen_US
dc.identifier.urihttps://hdl.handle.net/10568/170224en_US
dc.titleWaterCopilot: a water management AI virtual assistant for the Limpopo River Basin Digital Twin - technical guideen_US
dcterms.abstractThe present document provides a comprehensive overview of the development, architecture, and capabilities of the Limpopo Digital Twin Chatbot or Copilot (WaterCopilot). WaterCopilot is an AI-driven virtual assistant designed to enhance data accessibility and support decision-making for water management in the Limpopo River Basin (LRB). It has been developed through collaboration between the International Water Management Institute (IWMI) and Microsoft Research. WaterCopilot integrates advanced natural language processing with real-time data retrieval to address key challenges in water resource management, including fragmented information sources, manual data processing, and delays in response. The document outlines the project's objectives, system architecture, and modular plugin approach, which enables the Copilot to seamlessly connect with various datasets, including real-time environmental data, historical records, and policy documents related to water availability, rainfall patterns, and environmental flow. By leveraging Azure OpenAI services, WaterCopilot interprets user queries and retrieves relevant information. Key features of the Copilot include real-time monitoring of water availability, rainfall patterns, and environmental flow alerts, as well as userfriendly data visualizations and contextual insights. The deployment strategy utilizes Docker containers on AWS infrastructure, ensuring scalability, reliability, and efficient performance of the Copilot. This document also addresses the technical challenges encountered during development, the solutions implemented to create a robust and adaptable system, and outlines future work aimed at further enhancing WaterCopilot's capabilities. This detailed documentation serves as a technical guide to understanding WaterCopilot's capabilities, architecture, and future directions, emphasizing its role in supporting sustainable water management across the LRB.en_US
dcterms.accessRightsOpen Accessen_US
dcterms.bibliographicCitationVickneswaran, K.; Retief, H.; Padilha, R.; Dickens, C.; Silva, P.; Garcia Andarcia, M. 2024. WaterCopilot: a water management AI virtual assistant for the Limpopo River Basin Digital Twin - technical guide. Colombo, Sri Lanka: International Water Management Institute (IWMI). CGIAR Initiative on Digital Innovation. 23p.en_US
dcterms.extent23p.en_US
dcterms.issued2024-12-30en_US
dcterms.languageenen_US
dcterms.licenseCC-BY-4.0en_US
dcterms.publisherInternational Water Management Institute (IWMI). CGIAR Initiative on Digital Innovationen_US
dcterms.subjectartificial intelligenceen_US
dcterms.subjectmodelsen_US
dcterms.subjectwater managementen_US
dcterms.subjectnatural resources managementen_US
dcterms.subjectenvironmental monitoringen_US
dcterms.typeReporten_US

Files

Original bundle

Now showing 1 - 1 of 1
Thumbnail Image
Name:
WaterCopilot - A water management AI virtual assistant for the Limpopo River Basin Digital Twin - technical guide.pdf
Size:
3.01 MB
Format:
Adobe Portable Document Format
Description:
Download full publication
Download

License bundle

Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
1.75 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

IWMI Reports
CGIAR Initiative on Digital Innovation
Water Futures Data and Analytics (WFDA)