Digital Twin for Regional Water Consumption Simulation and Forecasting

Galvão, Matheus Rigoni; Rici, Pedro; Lopes, Rui Pedro

Publication

Digital Twin for Regional Water Consumption Simulation and Forecasting

2024Conference object

dc.contributor.author	Galvão, Matheus Rigoni
dc.contributor.author	Rici, Pedro
dc.contributor.author	Lopes, Rui Pedro
dc.date.accessioned	2024-10-08T09:02:46Z
dc.date.available	2024-10-08T09:02:46Z
dc.date.issued	2024
dc.description.abstract	Water scarcity is a global concern due to population growth, climate change, and industrialization. Accurate water consumption simulation and forecasting are essential for understanding consumption patterns and predicting future demand. The control and visualization of how different aspects such as precipitation, season, and population affect water consumption can be a way for public agencies to plan actions that minimize waste and assist in the correct use of water. Technology, and especially Machine Learning and Digital Twin, can be used as tools for this. In light of this, this project aims to develop a system for simulating and forecasting water consumption in the Bragan¸ca region using a Digital Twin. In order to accomplish this, a comprehensive analysis is conducted to determine the necessary requirements for designing the system. This analysis encompasses the evaluation of hardware, software, data, machine learning models, web interface, as well as security and performance requirements. Furthermore, the architecture of this system and how it will be configured is analyzed, proposing a system with Training Data Sources, Training Process, Updated Data Sources, Digital Twin, Web Interface and Monitoring System. The system described in this article is under development and it is hoped to achieve as a result the full design of the Digital Twin and User Interface systems.	pt_PT
dc.description.sponsorship	This work has been supported by FCT - Fundação para a Ciência e Tecnologia within the Project Scope: DSAIPA/AI/0088/2020.	pt_PT
dc.description.version	info:eu-repo/semantics/publishedVersion	pt_PT
dc.identifier.citation	Galvão, Matheus; Rici, Pedro; Lopes, Rui Pedro (2024). Digital Twin for Regional Water Consumption Simulation and Forecasting. In 3rd International Conference on Optimization, Learning Algorithms and Applications (OL2A 2023). Cham: Springer Nature, Vol. 1, p. 333–346. ISBN 978-3-031-53024-1.	pt_PT
dc.identifier.doi	10.1007/978-3-031-53025-8_23	pt_PT
dc.identifier.isbn	978-3-031-53024-1
dc.identifier.isbn	978-3-031-53025-8
dc.identifier.uri	http://hdl.handle.net/10198/30343
dc.language.iso	eng	pt_PT
dc.peerreviewed	yes	pt_PT
dc.publisher	Springer Nature	pt_PT
dc.rights.uri	http://creativecommons.org/licenses/by/4.0/	pt_PT
dc.subject	Water	pt_PT
dc.subject	Consumption	pt_PT
dc.subject	Simulator	pt_PT
dc.subject	Web	pt_PT
dc.title	Digital Twin for Regional Water Consumption Simulation and Forecasting	pt_PT
dc.type	conference object
dspace.entity.type	Publication
oaire.awardURI	info:eu-repo/grantAgreement/FCT/FCT_DSAIPA_2020/DSAIPA%2FAI%2F0088%2F2020/PT
oaire.citation.endPage	346	pt_PT
oaire.citation.startPage	333	pt_PT
oaire.citation.title	3rd International Conference on Optimization, Learning Algorithms and Applications (OL2A 2023)	pt_PT
oaire.fundingStream	FCT_DSAIPA_2020
person.familyName	Lopes
person.givenName	Rui Pedro
person.identifier.ciencia-id	8E14-54E4-4DB5
person.identifier.orcid	0000-0002-9170-5078
project.funder.identifier	http://doi.org/10.13039/501100001871
project.funder.name	Fundação para a Ciência e a Tecnologia
rcaap.rights	restrictedAccess	pt_PT
rcaap.type	conferenceObject	pt_PT
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