Fog Computing Approach for Shared Mobility in Smart Cities

Smart transportation a smart city application where traditional individual models are transforming to shared and distributed ownership. These models are used to serve commuters for inter- and intra-city travel. However, short-range urban transportation services within campuses, residential compounds...

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Main Authors: Raafat Aburukba, A. R. Al-Ali, Ahmed H. Riaz, Ahmad Al Nabulsi, Danayal Khan, Shavaiz Khan, Moustafa Amer
Format: Article
Language:English
Published: MDPI AG 2021-12-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/14/23/8174
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author Raafat Aburukba
A. R. Al-Ali
Ahmed H. Riaz
Ahmad Al Nabulsi
Danayal Khan
Shavaiz Khan
Moustafa Amer
author_facet Raafat Aburukba
A. R. Al-Ali
Ahmed H. Riaz
Ahmad Al Nabulsi
Danayal Khan
Shavaiz Khan
Moustafa Amer
author_sort Raafat Aburukba
collection DOAJ
description Smart transportation a smart city application where traditional individual models are transforming to shared and distributed ownership. These models are used to serve commuters for inter- and intra-city travel. However, short-range urban transportation services within campuses, residential compounds, and public parks are not explored to their full capacity compared to the distributed vehicle model. This paper aims to explore and design an adequate framework for battery-operated shared mobility within a large community for short-range travel. This work identifies the characteristics of the shared mobility for battery-operated vehicles and accordingly proposes an adequate solution that deals with real-time data collection, tracking, and automated decisions. Furthermore, given the requirement for real-time decisions with low latency for critical requests, the paper deploys the proposed framework within the 3-tier computing model, namely edge, fog, and cloud tiers. The solution design considers the power consumption requirement at the edge by offloading the computational requests to the fog tier and utilizing the LoRaWAN communication technology. A prototype implementation is presented to validate the proposed framework for a university campus using e-bikes. The results show the scalability of the proposed design and the achievement of low latency for requests that require real-time decisions.
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spelling doaj.art-eddca210344244ab976b1a7b42bcafa02023-11-23T02:23:47ZengMDPI AGEnergies1996-10732021-12-011423817410.3390/en14238174Fog Computing Approach for Shared Mobility in Smart CitiesRaafat Aburukba0A. R. Al-Ali1Ahmed H. Riaz2Ahmad Al Nabulsi3Danayal Khan4Shavaiz Khan5Moustafa Amer6Department of Computer Science and Engineering, American University of Sharjah, Sharjah 26666, United Arab EmiratesDepartment of Computer Science and Engineering, American University of Sharjah, Sharjah 26666, United Arab EmiratesDepartment of Computer Science and Engineering, American University of Sharjah, Sharjah 26666, United Arab EmiratesDepartment of Computer Science and Engineering, American University of Sharjah, Sharjah 26666, United Arab EmiratesDepartment of Computer Science and Engineering, American University of Sharjah, Sharjah 26666, United Arab EmiratesDepartment of Computer Science and Engineering, American University of Sharjah, Sharjah 26666, United Arab EmiratesDepartment of Computer Science and Engineering, American University of Sharjah, Sharjah 26666, United Arab EmiratesSmart transportation a smart city application where traditional individual models are transforming to shared and distributed ownership. These models are used to serve commuters for inter- and intra-city travel. However, short-range urban transportation services within campuses, residential compounds, and public parks are not explored to their full capacity compared to the distributed vehicle model. This paper aims to explore and design an adequate framework for battery-operated shared mobility within a large community for short-range travel. This work identifies the characteristics of the shared mobility for battery-operated vehicles and accordingly proposes an adequate solution that deals with real-time data collection, tracking, and automated decisions. Furthermore, given the requirement for real-time decisions with low latency for critical requests, the paper deploys the proposed framework within the 3-tier computing model, namely edge, fog, and cloud tiers. The solution design considers the power consumption requirement at the edge by offloading the computational requests to the fog tier and utilizing the LoRaWAN communication technology. A prototype implementation is presented to validate the proposed framework for a university campus using e-bikes. The results show the scalability of the proposed design and the achievement of low latency for requests that require real-time decisions.https://www.mdpi.com/1996-1073/14/23/8174smart mobilitysmart transportationsmart citiese-BikeIoT
spellingShingle Raafat Aburukba
A. R. Al-Ali
Ahmed H. Riaz
Ahmad Al Nabulsi
Danayal Khan
Shavaiz Khan
Moustafa Amer
Fog Computing Approach for Shared Mobility in Smart Cities
Energies
smart mobility
smart transportation
smart cities
e-Bike
IoT
title Fog Computing Approach for Shared Mobility in Smart Cities
title_full Fog Computing Approach for Shared Mobility in Smart Cities
title_fullStr Fog Computing Approach for Shared Mobility in Smart Cities
title_full_unstemmed Fog Computing Approach for Shared Mobility in Smart Cities
title_short Fog Computing Approach for Shared Mobility in Smart Cities
title_sort fog computing approach for shared mobility in smart cities
topic smart mobility
smart transportation
smart cities
e-Bike
IoT
url https://www.mdpi.com/1996-1073/14/23/8174
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