5G Internet of radio light services for supermarkets

Cosmas, John; Meunier, Ben; Ali, Kareem; Jawad, Nawar; Salih, Mukhald; Meng, Hongying; Song, Jian; Wang, Jintao; Tong, Min; Cao, Xiaohong; Li, Xiao; Zhang, Xun; Huang, Chen; Zhang, Yue; Ran, Moshe; Ran, Einat; Salomon, Eliron; Avinoam, Yoav; Hadad, Zion; Globen, Baruch; Negru, Daniel; Lacaud, Mathias; Kourtis, Michail-Alexandros; Koumaras, Harilaos; Sakkas, Christos; Huang, Li-Ke; Zetík, Rudolf; Cabaj, Krzysztof; Mazurczyk, Wojciech; Kapovits, Adam

doi:10.1109/ifws.2017.8245977

Cited by 22 publications

(9 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Specific examples of set of performance KPIs selected in various use cases for 5G combined with LiFi is described in [10], [11], [15] and [16] including: In this work, we consider having LiFi technologies as part of new spectrum for 5G/B5G and focus on the following subset of key criteria:…”

Section: Methodology To Address Use Cases and Kpis For 5g Combinmentioning

confidence: 99%

See 1 more Smart Citation

Which LiFi's apps may fit mostly to 5G and beyond-5G Technology?

Albert¹,

Dekel²,

Kurland³

et al. 2019

2019 Global LIFI Congress (GLC)

Self Cite

View full text Add to dashboard Cite

LiFi technologies are expected to be an integrated part of future broadband wireless technologies. However, it is still not fully clear which apps will fit and benefit future 5G and beyond-5G. The purpose of this paper is to retrieve through Analytic Hierarchy Process model (AHP) and qualitative analysis the most promising apps. Apps for homes, supermarket, museum, communication between vehicles, in-flight entertainment and hospitals were considered. Relevant criteria include latency, data security, data-rate per square-meter, number of customers in square meter and acceptance. The results indicate that acceptance criteria found to be most dominant and hospital driven 5G apps most promising.

show abstract

Section: Methodology To Address Use Cases and Kpis For 5g Combinmentioning

confidence: 99%

“…Seven key apps are analysed: Communications between Vehicles (CBV) [9], Home and in-building (HO) [10], [11]. Hospitals (HS) [12], In-Flight Entertainment (IFE) [13], Museum (MU) [14], Supermarket (SU) [15] and Underground Train (UT) [16].…”

Section: A Apps Mapping: Current State Of Lifi's Apps Sugested Formentioning

confidence: 99%

Which LiFi's apps may fit mostly to 5G and beyond-5G Technology?

Albert¹,

Dekel²,

Kurland³

et al. 2019

2019 Global LIFI Congress (GLC)

Self Cite

View full text Add to dashboard Cite

show abstract

“…This generally requires outward facing cameras to measure the user's movements in respect to the physical world. Headsets such as the Pico Neo [20], Oculus Project Santa-Cruz, Vive Focus, Qualcomm VR [21] and Lenovo mirage solo [22] all perform using the similar hardware with the exact same processor, the Snapdragon 835 [23]. This processor is commonly found in phones and thus provides a reduced level of VR when compared to PCOVR.…”

Section: Comparison With Existing Solutionsmentioning

confidence: 99%

5G Internet of Radio Light Virtual Reality System

Meunier

Cosmas

2018

2018 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)

Self Cite

View full text Add to dashboard Cite

Virtual Reality (VR) is a technology that is rapidly developing, leading to a whole array of innovative commercially viable products. Some of the challenges facing the early development of Virtual Reality (VR) and Augmented Reality (AR) include high cost, restricted physical movement and laborious setup. This paper highlights several of these challenges and outlines an architecture in which systems can require less specialised equipment, be used with greater freedom and are simpler to setup. This paper shows how using the correct applications, the Internet of Radio Light (IoRL) architecture could lead to enhanced VR experiences. Specifically, a wireless six Degrees of Freedom (DOF) VR system for both existing mobile and PC operated VR. The aim is, to exploit the existing IoRL architecture to provide a safer, wireless, high speed, less laborious, more immersive and improved VR experience with broader applications.

show abstract

“…We decided to address a sniffing attack within the security framework of the Internet of Radio-Light (IoRL) system which is being created within the Horizon 2020 project. It aims at developing an architecture for smart buildings [1], supermarkets, museums or even train stations [2] using a 5G Radio-Light multi-component carrier, Frequency Division Duplex (FDD) broadband system consisting of a Visible Light Communication (VLC) downlink channel in the unlicensed THz spectrum and mmWave up/downlink channels in the unlicensed 30-300 GHz spectrum. IoRL allows wireless communication networks to be deployed in buildings that can provide data rates greater than 10 Gbit/s, latencies of less than 1 ms and location accuracy of less than 10 cm, whilst reducing the EMF levels and interference, lowering the energy consumption at the transmitter/receiver and increasing the User Equipment (UE) energy battery lifetime.…”

Section: Introductionmentioning

confidence: 99%

Sniffing Detection Based on Network Traffic Probing and Machine Learning

et al. 2020

Self Cite

View full text Add to dashboard Cite

Cyber attacks are on the rise and each day cyber criminals are developing more and more sophisticated methods to compromise the security of their targets. Sniffing is one of the most important techniques that enables the attacker to collect information on the vulnerabilities of the devices, protocols and applications that can be exploited within the targeted network. It relies mainly on passively analyzing the traffic exchanged within the network, and due to its nature, such an activity is difficult to discover. That is why, in this article, we first revisit existing techniques and tools that can be used to perform sniffing as well as the corresponding mitigation methods. Based on this background, we propose a novel measurement-based detection method that infers whether the sniffing software is active on the suspected machine by network traffic probing and machine learning techniques. The presented experimental results prove that the proposed solution is effective.

show abstract

5G Internet of radio light services for supermarkets

Cited by 22 publications

References 4 publications

Which LiFi's apps may fit mostly to 5G and beyond-5G Technology?

Which LiFi's apps may fit mostly to 5G and beyond-5G Technology?

5G Internet of Radio Light Virtual Reality System

Sniffing Detection Based on Network Traffic Probing and Machine Learning

Contact Info

Product

Resources

About