Management of Video Surveillance for Smart Cities

Dao, Nhat-Quang; Le-Dang, Quang; Morawski, Robert; Dang, Anh Tuan; Le‐Ngoc, Tho

doi:10.1007/978-3-319-97271-8_11

Cited by 6 publications

(4 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…1,5,6 There are a wide variety of IoT (Internet of Things) MM applications that can benefit from a real-time network performance estimator to route selection, 5 such as surveillance systems for outdoor or indoor spaces in smart cities that require multiple video sources transmitting simultaneously to the monitoring center. 7 Note that the performance of these application scenarios can vary according to the selected route for each video flow, as this may cause interflow interference.…”

Section: Introductionmentioning

confidence: 99%

Network performance estimator with applications to route selection for IoT multimedia applications

2023

View full text Add to dashboard Cite

Estimating the performance of multimedia (MM) traffic is important in numerous contexts, including routing and forwarding, quality of service (QoS) provisioning, and adaptive video streaming. This paper proposes a network performance estimator which aims at providing, in quasi real-time, network performance estimates for IoT MM traffic in IEEE 802.11 multihop wireless networks. To our knowledge, the proposed MM-aware performance estimator, or MAPE, is the first deterministic simulation-based estimator that provides real-time per-flow throughput, packet loss, and delay estimates while considering inter-flow interference and multirate flows, typical of MM traffic. Our experimental results indicate that MAPE is able to provide network performance estimates that can be used by IoT MM services, notably to inform real-time route selection in IoT video transmission, at a fraction of the execution time when compared to stochastic network simulators. When compared to existing deterministic simulators, MAPE yields higher accuracy at comparable execution times due to its ability to consider multirate flows.

show abstract

Section: Introductionmentioning

confidence: 99%

Network performance estimator with applications to route selection for IoT multimedia applications

2023

View full text Add to dashboard Cite

show abstract

“…Os cenários de aplicac ¸ões com múltiplas fontes de vídeo exigem um mecanismo de selec ¸ão de caminhos ainda mais complexo, pois precisam atender os requisitos das diversas fontes transmitindo simultaneamente. Uma das aplicac ¸ões mais comuns para esses cenários é o vídeo monitoramento de ambientes internos ou externos para detectar eventos de interesse, no qual as múltiplas fontes de vídeo transmitem para uma determinada central [Dao et al 2018]. Observe que o desempenho destas aplicac ¸ões pode variar conforme a quantidade de fontes e a diversidade dos caminhos, pois os fluxos gerados por cada uma das fontes podem gerar interferência entre eles.…”

Section: Introduc ¸ãOunclassified

IAMVT: Mecanismo de Seleção de Rotas Multicaminhos para Aplicações de Vídeo Monitoramento

Bhering

Albuquerque²,

Passos³

2021

Anais Do XXXIX Simpósio Brasileiro De Redes De Computadores E Sistemas Distribuídos (SBRC 2021)

View full text Add to dashboard Cite

Alguns dos principais desaﬁos para transmissão de vídeo em redes sem ﬁo estão relacionados com a largura de banda e altas taxas de transmissão. Estudos indicam que dividir os ﬂuxos do vídeo para transmiti-los por diferentes caminhos pode melhorar a qualidade do serviço (Quality of Service QoS) das aplicações. Porém, a seleção de rotas multicaminhos não é uma tarefa trivial, principalmente quando as aplicações necessitam de múltiplas fontes de vídeo transmitindo simultaneamente, pois é necessário encontrar um conjunto de caminhos com o mínimo de interferência entre os ﬂuxos para suportar os requisitos das aplicações. Assim, este trabalho apresenta o Interference Aware Multipath Video Transmission (IAMVT), um mecanismo de seleção de rotas multicaminhos baseado na metaheurística Iterated Local Search (ILS). O mecanismo busca maximizar o rendimento global da rede para transmissão de múltiplos ﬂuxos de vídeos provindos de diferentes fontes. Os resultados das simulações demonstram o potencial da utilização do IAMVT para aumentar a qualidade do vídeo, quando comparado com outros mecanismos da literatura.

show abstract

“…For traffi c monitoring in smart city usually a set of cameras are used [1]. In typical installation camera transmits compressed video image over internet protocol -IP based network [2] to control center where video storage is performed [3].…”

Section: Introductionmentioning

confidence: 99%

Energy and Communication Requirements for Network of E-Band Radars as Sensors

Dražeta¹,

Dzolic²,

Peric³

et al. 2019

Proceedings of the International Scientific Conference - Sinteza 2019

View full text Add to dashboard Cite

E-band radars EBR are very promising short distance high-resolution sensors for safety and smart city solutions. In order to achieve larger scale coverage, we have investigated possibility of gaining raw signal from multiple EBRs for purpose of centralized data processing and fusion. Based on publicly available data about EBR ranges, resolution and data formats, we have considered requirements for implementation of communication and power network for them. We have presented data for both static and dynamic scenario. In static scenario EBR positions are fixed, while in dynamic scenario some of EBRs are located on vehicles with known position obtained by GPS.

show abstract

Management of Video Surveillance for Smart Cities

Cited by 6 publications

References 20 publications

Network performance estimator with applications to route selection for IoT multimedia applications

Network performance estimator with applications to route selection for IoT multimedia applications

IAMVT: Mecanismo de Seleção de Rotas Multicaminhos para Aplicações de Vídeo Monitoramento

Energy and Communication Requirements for Network of E-Band Radars as Sensors

Contact Info

Product

Resources

About