MeSmart-Pro: Advanced Processing at the Edge for Smart Urban Monitoring and Reconfigurable Services

With reference to the MeSmart project, the Municipality of Messina is making a great investments to deploy several types of cameras and digital devices across the city for carrying out different tasks related to mobility management, such as traffic flow monitoring, number plate recognition, video su...

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Main Authors: Antonino Galletta, Armando Ruggeri, Maria Fazio, Gianluca Dini, Massimo Villari
Format: Article
Language:English
Published: MDPI AG 2020-12-01
Series:Journal of Sensor and Actuator Networks
Subjects:
Online Access:https://www.mdpi.com/2224-2708/9/4/55
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author Antonino Galletta
Armando Ruggeri
Maria Fazio
Gianluca Dini
Massimo Villari
author_facet Antonino Galletta
Armando Ruggeri
Maria Fazio
Gianluca Dini
Massimo Villari
author_sort Antonino Galletta
collection DOAJ
description With reference to the MeSmart project, the Municipality of Messina is making a great investments to deploy several types of cameras and digital devices across the city for carrying out different tasks related to mobility management, such as traffic flow monitoring, number plate recognition, video surveillance etc. To this aim, exploiting specific devices for each task increases infrastructure and management costs, reducing flexibility. On the contrary, using general-purpose devices customized to accomplish multiple tasks at the same time can be a more efficient solution. Another important approach that can improve the efficiency of mobility services is moving computation tasks at the Edge of the managed system instead of in remote centralized serves, so reducing delays in event detection and processing and making the system more scalable. In this paper, we investigate the adoption of Edge devices connected to high-resolution cameras to create a general-purpose solution for performing different tasks. In particular, we use the Function as a Service (FaaS) paradigm to easily configure the Edge device and set up new services. The key results of our work is deploying versatile, scalable and adaptable systems able to respond to smart city’s needs, even if such needs change over time. We tested the proposed solution setting up a vehicle counting solution based on OpenCV, and automatically deploying necessary functions into an Edge device. From experimental results, it results that computing performance at the Edge overtakes the performance of a device specifically designed for vehicle counting under certain conditions and thanks to our reconfigurable functions.
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spelling doaj.art-c72db3fb9ba348e8b07d231a814224672023-11-20T23:32:51ZengMDPI AGJournal of Sensor and Actuator Networks2224-27082020-12-01945510.3390/jsan9040055MeSmart-Pro: Advanced Processing at the Edge for Smart Urban Monitoring and Reconfigurable ServicesAntonino Galletta0Armando Ruggeri1Maria Fazio2Gianluca Dini3Massimo Villari4MIFT Department, University of Messina, 98166 Messina, ItalyMIFT Department, University of Messina, 98166 Messina, ItalyMIFT Department, University of Messina, 98166 Messina, ItalyDepartment of Information Engineering, University of Pisa, 56100 Pisa, ItalyMIFT Department, University of Messina, 98166 Messina, ItalyWith reference to the MeSmart project, the Municipality of Messina is making a great investments to deploy several types of cameras and digital devices across the city for carrying out different tasks related to mobility management, such as traffic flow monitoring, number plate recognition, video surveillance etc. To this aim, exploiting specific devices for each task increases infrastructure and management costs, reducing flexibility. On the contrary, using general-purpose devices customized to accomplish multiple tasks at the same time can be a more efficient solution. Another important approach that can improve the efficiency of mobility services is moving computation tasks at the Edge of the managed system instead of in remote centralized serves, so reducing delays in event detection and processing and making the system more scalable. In this paper, we investigate the adoption of Edge devices connected to high-resolution cameras to create a general-purpose solution for performing different tasks. In particular, we use the Function as a Service (FaaS) paradigm to easily configure the Edge device and set up new services. The key results of our work is deploying versatile, scalable and adaptable systems able to respond to smart city’s needs, even if such needs change over time. We tested the proposed solution setting up a vehicle counting solution based on OpenCV, and automatically deploying necessary functions into an Edge device. From experimental results, it results that computing performance at the Edge overtakes the performance of a device specifically designed for vehicle counting under certain conditions and thanks to our reconfigurable functions.https://www.mdpi.com/2224-2708/9/4/55edge computingvirtual deviceOpenCVtraffic flow monitoringFaaS
spellingShingle Antonino Galletta
Armando Ruggeri
Maria Fazio
Gianluca Dini
Massimo Villari
MeSmart-Pro: Advanced Processing at the Edge for Smart Urban Monitoring and Reconfigurable Services
Journal of Sensor and Actuator Networks
edge computing
virtual device
OpenCV
traffic flow monitoring
FaaS
title MeSmart-Pro: Advanced Processing at the Edge for Smart Urban Monitoring and Reconfigurable Services
title_full MeSmart-Pro: Advanced Processing at the Edge for Smart Urban Monitoring and Reconfigurable Services
title_fullStr MeSmart-Pro: Advanced Processing at the Edge for Smart Urban Monitoring and Reconfigurable Services
title_full_unstemmed MeSmart-Pro: Advanced Processing at the Edge for Smart Urban Monitoring and Reconfigurable Services
title_short MeSmart-Pro: Advanced Processing at the Edge for Smart Urban Monitoring and Reconfigurable Services
title_sort mesmart pro advanced processing at the edge for smart urban monitoring and reconfigurable services
topic edge computing
virtual device
OpenCV
traffic flow monitoring
FaaS
url https://www.mdpi.com/2224-2708/9/4/55
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