Smart ITS sensor for the transportation planning using the IoT and Bigdata approaches to produce ITS cloud services

Herrera-Quintero, Luis Felipe; Banse, Klaus; Vega-Alfonso, Julian Camilo; Andres, Venegas-Sanchez

doi:10.1109/eatis.2016.7520096

Cited by 20 publications

(7 citation statements)

References 11 publications

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“…[6] propose a digital twin architecture based on a generic architecture, which enables the analysis and processing of large amounts of data in real-time. [11] propose a solution for transportation planning of bus rapid transportation systems. The authors prototype a smart sensor to collect information from the users of the transportation system which allows to track origin and destination locations.…”

Section: Related Workmentioning

confidence: 99%

Towards a Digital Twin Framework for Adaptive Last Mile City Logistics

Belfadel

Hörl

Tapia

et al. 2021

2021 6th International Conference on Smart and Sustainable Technologies (SpliTech)

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The use of real-time data in logistics is an important topic. Every day, logistics produces a large quantity of data, which is mainly produced by monitoring and controlling the enormous flow of goods. The last-mile delivery market is expanding at a rapid pace through large-and small-scale consumer platforms, but the economic drivers to create more sustainable systems are weak. Therefore, cities are facing the potential downside of this "Uberisation" of logistics. Urban and city planners, city administrators, and business stakeholders need a new adaptive approach such as the usage of digital twinning solutions of urban logistics. This to help in the interpretation of the dynamics of logistics networks in the city and the consequences of the introduction of particular innovations. The challenge is to predict the most likely developments for the coming years and propose feasible policies on that basis. This research work aims to advance research in the field of digital twins applied to city logistics, by proposing a framework enabling new applications for designing and assessing targeted urban logistics policies and to develop a range of logistics solutions for shared, connected, and low-emission logistics operations, empowered by an adaptive modeling approach.

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Section: Related Workmentioning

confidence: 99%

Towards a Digital Twin Framework for Adaptive Last Mile City Logistics

Belfadel

Hörl

Tapia

et al. 2021

2021 6th International Conference on Smart and Sustainable Technologies (SpliTech)

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“…Many other microservices-based IoT platforms have been proposed in various application domains such as smart farms [31], smart logistics/factories [32], smart cars [33], and smart commerce [34]. Jarwar et al [18] also proposed a crossdomain/general-purpose Web of Objects Architecture for IoT service provisioning in which a virtual object is used as an abstraction of a physical object.…”

Section: Service-oriented Middleware Solutionsmentioning

confidence: 99%

Middleware Solutions for the Internet of Things: A Survey

Khaddar¹

2021

Middleware Architecture

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The Internet of Things (IoT), along with its wider variants including numerous technologies, things, and people: the Internet of Everything (IoE) and the Internet of Nano Things (IoNT), are considered as part of the Internet of the future and ubiquitous computing allowing the communication among billions of smart devices and objects, and have recently drawn a very significant research attention. In these approaches, there are varieties of heterogeneous devices empowered by new capabilities and interacting with each other to achieve specific applications in different domains. A middleware layer is therefore required to abstract the physical layer details of the smart IoT devices and ease the complex and challenging task of developing multiple backend applications. In this chapter, an overview of IoT technologies, architecture, and main applications is given first and then followed by a comprehensive survey on the most recently used and proposed middleware solutions designed for IoT networks. In addition, open issues in IoT middleware design and future works in the field of middleware development are highlighted.

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“…• Smart Logistics: It is a set of services that are rolled out to process data to improve the supply chain quality. Author in [45] described an approach for the transportation planning that is based on Microservices and deployed on the cloud. They described its life cycle as well in experimental validation.…”

Section: Microservice-based Iot Platformsmentioning

confidence: 99%

A Comparative Study of Microservices-based IoT Platforms

Khalyly¹,

Belangour²,

Banane³

et al. 2020

IJACSA

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Internet of Things (IoT) is a set of technologies that aim at fitting together smart devices and applications to build an IoT ecosystem. The target of this kind of ecosystem is to enhance interaction between machines and humans through hardware to software binding while reducing cost and resource consumption. On the application level, IoT ecosystems were implemented by various technologies that all seek better interconnection, monitoring, and controlling of IoT smart devices. Among recent technologies, Microservices, which are a variant of the serviceoriented architecture, are subject to great excitement. In fact, Microservices are an emerging technology built around Microservice paradigm which goal is to offer services with a small granularity, which exactly meets the distributed nature of IoT devices while maintaining a loosely coupled architecture between IoT components among other advantages. Efforts to build Microservice-based IoT platforms sooner emerged to take advantage of the numerous benefits of the Microservice paradigm to build scalable, interoperable, and dynamic ecosystems. The goal of this paper is to list these approaches, classify them and compare them using a Weighted Scoring Model (WSM) method. This involves, studying these platforms, establishing relevant criteria for comparison, assigning weights for each criterion, and finally calculating scores. The obtained results reveal the weaknesses and strengths of each of the studied platforms.

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Smart ITS sensor for the transportation planning using the IoT and Bigdata approaches to produce ITS cloud services

Cited by 20 publications

References 11 publications

Towards a Digital Twin Framework for Adaptive Last Mile City Logistics

Towards a Digital Twin Framework for Adaptive Last Mile City Logistics

Middleware Solutions for the Internet of Things: A Survey

A Comparative Study of Microservices-based IoT Platforms

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