Internet of Things, big data and the economics of networked vehicles

Knieps, Günter

doi:10.1016/j.telpol.2018.09.002

Cited by 29 publications

(15 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Frequencies in the context of 5G big data virtual networks (Knieps, 2019a) raise issues regarding the heterogeneity of frequency requirements regarding local footprint (geographical flexibility), time windows, and the minimal bandwidth required depending on the type of IoT application in question. Frequency usage rights may be allocated nationwide, regionally, or locally.…”

Section: Spectrum Allocation For Future 5g-based Virtual Networkmentioning

confidence: 99%

“…Important application fields are intelligent transportation systems (OECD/ITF, 2015, 2016), smart sustainable cities (Al Nuami et al, 2015; ITU-T, 2015a; OECD, 2015), and smart renewable energy systems (ITU-T, 2015b; Knieps, 2017b). Driverless vehicle platforms provide highly interactive (cooperative) networked/automated vehicles with the support of high-volume, location-critical big data processing (edge cloud) (Knieps, 2019a; OECD/ITF, 2015).…”

Section: Data-driven Sector Coupling 5g and A European Strategy For mentioning

confidence: 99%

“…), it is important that the virtual network providers have the entrepreneurial decision competencies necessary to design the big data value chains according to the requirements of the IoT applications, combining QoS-differentiated bandwidth capacities with the different complementary dimensions of virtual networks such as sensor networks, geopositioning services, and the division of labor between central cloud and edge cloud. Governance problems also include the organization of the interaction between all-IP traffic service providers, virtual network service providers, and platform operators providing the physical network services (Knieps, 2019a, p. 176 f.; 2019b, pp. 23 f.).…”

Section: Data-driven Sector Coupling 5g and A European Strategy For mentioning

confidence: 99%

“…While the physical infrastructures vary strongly between different network industries, the complementary information and communication technologies (ICT) are based on sensors, real-time and location-aware communication, and data processing. The governance problem between all-IP traffic service providers and application-driven virtual network providers thus assumes particular relevance (Knieps, 2017a(Knieps, , 2019a. Important dimensions of 5G big data-based virtual networks are 5G frequency combined with other dimensions such as QoS-differentiated broadband networks.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Data-driven sector coupling in 5G-based smart networks

Knieps

2021

Competition and Regulation in Network Industries

View full text Add to dashboard Cite

5G attains the role of a GPT for an open set of downstream IoT applications in various network industries and within the app economy more generally. Traditionally, sector coupling has been a rather narrow concept focusing on the horizontal synergies of urban system integration in terms of transport, energy, and waste systems, or else the creation of new intermodal markets. The transition toward 5G has fundamentally changed the framing of sector coupling in network industries by underscoring the relevance of differentiating between horizontal and vertical sector coupling. Due to the fixed mobile convergence and the large open set of complementary use cases, 5G has taken on the characteristics of a generalized purpose technology (GPT) in its role as the enabler of a large variety of smart network applications. Due to this vertical relationship, characterized by pervasiveness and innovational complementarities between upstream 5G networks and downstream application sectors, vertical sector coupling between the provider of an upstream GPT and different downstream application industries has acquired particular relevance. In contrast to horizontal sector coupling among different application sectors, the driver of vertical sector coupling is that each of the heterogeneous application sectors requires a critical input from the upstream 5G network provider and combines this with its own downstream technology. Of particular relevance for vertical sector coupling are the innovational complementarities between upstream GPT and downstream application sectors. The focus on vertical sector coupling also has important policy implications. Although the evolution of 5G networks strongly depends on the entrepreneurial, market-driven activities of broadband network operators and application service providers, the future of 5G as a GPT is heavily contingent on the role of frequency management authorities and European regulatory policy with regard to data privacy and security regulations.

show abstract

Section: Spectrum Allocation For Future 5g-based Virtual Networkmentioning

confidence: 99%

Section: Data-driven Sector Coupling 5g and A European Strategy For mentioning

confidence: 99%

Section: Data-driven Sector Coupling 5g and A European Strategy For mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Data-driven sector coupling in 5G-based smart networks

Knieps

2021

Competition and Regulation in Network Industries

View full text Add to dashboard Cite

show abstract

“…Pilon-Bignell and Milne (2016) come to the conclusion that fleet operators are under pressure to decrease costs for which Geotab offers a solution: they collect and analyse large amounts of data and suggest avenues to more efficiency. As Orlovska (2018) and colleagues as well as Knieps (2018) have argued, 'big data usage can be a solution for user behavior evaluation'. They indicate options to collect data more efficiently and propose to use big data networks including sensors and cameras.…”

Section: Literature Reviewmentioning

confidence: 99%

Efficiency for Large Fleets: An Analysis of How Industrial Customers Use Electric and Hybrid Vehicles

2019

ISDE

View full text Add to dashboard Cite

This paper presents methods and results which allow an analysis of relevant driving parameters of hybrid and electric vehicles. In order to gain crucial insights into how industrial customers use hybrid and electric vehicles, the paper investigates the following parameters: information about odometer, charging processes and battery charging levels. The data used for this purpose was provided by the Canadian fleet management company Geotab Inc. They were evaluated by means of 'Google BigQuery' and the statistics programme 'IBM SPSS Statistics'. It turned out that correlations between 'charging time' and 'battery charging level' exist, as well as between 'battery level' and 'distance per day'. One of the main questions in the present study asks whether long charging times of car batteries lead to decreased average battery charging levels. As a result of this study, the longer a hybrid vehicle is charged per day, the lower sink its average battery charging level. The findings of this research help managers of car fleets to enhance their existing fleet management for establishing more efficient fleets with respect to ecological and economical aspects. Our research is particularly significant as this will save money across such fleets worldwide, and at the same time, preserve the environment as much as possible.

show abstract

Data‐centric approaches in the Internet of Vehicles: A systematic review on techniques, open issues, and future directions

Partovi

Zarei

Rahmani

2022

Int J Communication

View full text Add to dashboard Cite

The Internet of Vehicles (IoV) is an emerging network of connected vehicles as a branch of dynamic objects in the Internet of Things (IoT) ecosystem. With the rapid development of IoV, real-time data-centric applications would be a significant concern in academia and industry to promote efficiency and realize modern services in such high dynamic networks. In this paper, we aim to present a systematic literature review (SLR) for the IoV networks to investigate the different attitudes in the field of data-centric approaches. This paper systematically categorizes the 48 recent articles on data-driven techniques in the IoV field published from 2017 to March 2022. A complete technical taxonomy is presented for the data-centric approaches in IoV according to the content of current studies. Collected methods are chosen with the SLR process, and they are investigated considering some technical classifications including IoV security, data traffic, vehicular social network, data propagation, energy, and multimedia categories. The achievements, drawbacks, and new findings of studies are carefully investigated for addressing the deficiencies, as well as emphasizing future research direction and open issues of data-driven approaches in IoV. K E Y W O R D S data trading system, data traffic management, data transmission, Internet of Vehicles, IoV | INTRODUCTIONVehicular ad hoc networks (VANETs) as highly dynamic but well-organized emerging networks play an effective role in accelerating the improvement of the intelligent transportation systems (ITS) application. 1 Today ITS applications in many nations are expanding, whereby the rapid growth of networked sensors and context-aware computing systems, along with emerging communication technologies, have made the recognition of smart cities possible shortly. 2 The Internet of Things (IoT) technology has faced an increase in the number of dynamic objects, including connected vehicles, which formed the Internet of Vehicles (IoV), and made our lives easier, safer, and smarter. [3][4][5] VANETs, as the central infrastructure of the IoV ecosystem, aim to help drivers with possible inter-vehicle communication (IVC) and realtime data propagation even in high mobility, helping safety driving and receiving alerts for road hazardous. 6,7 Plug-in electric vehicles (PEVs) and unmanned aerial vehicles (UAVs), as an emerging part of energy-aware VANETs, have a significant impact on the formation of the IoV. 8 Connected vehicles in IoV are intelligent vehicles with a complicated software platform. Promoting vehicles from high dynamic nodes to intelligent vehicles with diverse communication

show abstract

Internet of Things, big data and the economics of networked vehicles

Cited by 29 publications

References 9 publications

Data-driven sector coupling in 5G-based smart networks

Data-driven sector coupling in 5G-based smart networks

Efficiency for Large Fleets: An Analysis of How Industrial Customers Use Electric and Hybrid Vehicles

Data‐centric approaches in the Internet of Vehicles: A systematic review on techniques, open issues, and future directions

Contact Info

Product

Resources

About