This paper presents a comprehensive framework designed to facilitate the widespread deployment of the Internet of Things (IoT) for enhanced monitoring and optimization of Water Distribution Systems (WDSs). The framework aims to investigate the utilization of massive IoT in monitoring and optimizing WDSs, with a particular focus on leakage detection, energy consumption, and wireless network performance assessment in real-world water networks. The framework integrates simulation environments at both the application level (using EPANET) and the radio level (using NS-3) within the LoRaWAN network. The paper culminates with a practical use case, alongside evaluation results concerning power consumption in a large-scale LoRaWAN network and strategies for optimal gateway positioning

Pagano A., Garlisi D., Giuliano F., Cattai T., Sapienza F.C. (2024). SWI-FEED: Smart Water IoT Framework for Evaluation of Energy and Data in Massive Scenarios. In 2024 IFIP Networking Conference (IFIP Networking) (pp. 583-585). Institute of Electrical and Electronics Engineers Inc. [10.23919/IFIPNetworking62109.2024.10619752].

SWI-FEED: Smart Water IoT Framework for Evaluation of Energy and Data in Massive Scenarios

Garlisi D.
;
2024-01-01

Abstract

This paper presents a comprehensive framework designed to facilitate the widespread deployment of the Internet of Things (IoT) for enhanced monitoring and optimization of Water Distribution Systems (WDSs). The framework aims to investigate the utilization of massive IoT in monitoring and optimizing WDSs, with a particular focus on leakage detection, energy consumption, and wireless network performance assessment in real-world water networks. The framework integrates simulation environments at both the application level (using EPANET) and the radio level (using NS-3) within the LoRaWAN network. The paper culminates with a practical use case, alongside evaluation results concerning power consumption in a large-scale LoRaWAN network and strategies for optimal gateway positioning
2024
Settore INFO-01/A - Informatica
Pagano A., Garlisi D., Giuliano F., Cattai T., Sapienza F.C. (2024). SWI-FEED: Smart Water IoT Framework for Evaluation of Energy and Data in Massive Scenarios. In 2024 IFIP Networking Conference (IFIP Networking) (pp. 583-585). Institute of Electrical and Electronics Engineers Inc. [10.23919/IFIPNetworking62109.2024.10619752].
File in questo prodotto:
File Dimensione Formato  
SWI-FEED_Smart_Water_IoT_Framework_for_Evaluation_of_Energy_and_Data_in_Massive_Scenarios.pdf

Solo gestori archvio

Tipologia: Versione Editoriale
Dimensione 277.45 kB
Formato Adobe PDF
277.45 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/660753
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 2
social impact