scholarly journals Application of region-based video surveillance in smart cities using deep learning

2021 ◽  
Author(s):  
Asma Zahra ◽  
Mubeen Ghafoor ◽  
Kamran Munir ◽  
Ata Ullah ◽  
Zain Ul Abideen
Keyword(s):  
Deep Learning ◽  
Video Coding ◽  
Video Surveillance ◽  
Smart City ◽  
Smart Cities ◽  
Video Frame ◽  
Visual Data ◽  
High Quality ◽  
City Environment ◽  
Salient Regions

AbstractSmart video surveillance helps to build more robust smart city environment. The varied angle cameras act as smart sensors and collect visual data from smart city environment and transmit it for further visual analysis. The transmitted visual data is required to be in high quality for efficient analysis which is a challenging task while transmitting videos on low capacity bandwidth communication channels. In latest smart surveillance cameras, high quality of video transmission is maintained through various video encoding techniques such as high efficiency video coding. However, these video coding techniques still provide limited capabilities and the demand of high-quality based encoding for salient regions such as pedestrians, vehicles, cyclist/motorcyclist and road in video surveillance systems is still not met. This work is a contribution towards building an efficient salient region-based surveillance framework for smart cities. The proposed framework integrates a deep learning-based video surveillance technique that extracts salient regions from a video frame without information loss, and then encodes it in reduced size. We have applied this approach in diverse case studies environments of smart city to test the applicability of the framework. The successful result in terms of bitrate 56.92%, peak signal to noise ratio 5.35 bd and SR based segmentation accuracy of 92% and 96% for two different benchmark datasets is the outcome of proposed work. Consequently, the generation of less computational region-based video data makes it adaptable to improve surveillance solution in Smart Cities.

scholarly journals Secure Video Surveillance Framework in Smart City

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4419
Author(s):  
Hao Li ◽  
Tianhao Xiezhang ◽  
Cheng Yang ◽  
Lianbing Deng ◽  
Peng Yi
Keyword(s):  
Video Surveillance ◽  
Smart City ◽  
Key Management ◽  
Surveillance System ◽  
Chinese Remainder Theorem ◽  
Smart Cities ◽  
Group Key Management ◽  
Video Surveillance System ◽  
Surveillance Systems ◽  
Key Update

In the construction process of smart cities, more and more video surveillance systems have been deployed for traffic, office buildings, shopping malls, and families. Thus, the security of video surveillance systems has attracted more attention. At present, many researchers focus on how to select the region of interest (RoI) accurately and then realize privacy protection in videos by selective encryption. However, relatively few researchers focus on building a security framework by analyzing the security of a video surveillance system from the system and data life cycle. By analyzing the surveillance video protection and the attack surface of a video surveillance system in a smart city, we constructed a secure surveillance framework in this manuscript. In the secure framework, a secure video surveillance model is proposed, and a secure authentication protocol that can resist man-in-the-middle attacks (MITM) and replay attacks is implemented. For the management of the video encryption key, we introduced the Chinese remainder theorem (CRT) on the basis of group key management to provide an efficient and secure key update. In addition, we built a decryption suite based on transparent encryption to ensure the security of the decryption environment. The security analysis proved that our system can guarantee the forward and backward security of the key update. In the experiment environment, the average decryption speed of our system can reach 91.47 Mb/s, which can meet the real-time requirement of practical applications.

Using a distributed deep learning algorithm for analyzing big data in smart cities

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohammed Anouar Naoui ◽  
Brahim Lejdel ◽  
Mouloud Ayad ◽  
Abdelfattah Amamra ◽  
Okba kazar
Keyword(s):  
Big Data ◽  
Deep Learning ◽  
Data Analysis ◽  
Data Storage ◽  
Smart City ◽  
Smart Cities ◽  
Smart Environment ◽  
Data Systems ◽  
Content Type ◽  
Big Data Systems

PurposeThe purpose of this paper is to propose a distributed deep learning architecture for smart cities in big data systems.Design/methodology/approachWe have proposed an architectural multilayer to describe the distributed deep learning for smart cities in big data systems. The components of our system are Smart city layer, big data layer, and deep learning layer. The Smart city layer responsible for the question of Smart city components, its Internet of things, sensors and effectors, and its integration in the system, big data layer concerns data characteristics 10, and its distribution over the system. The deep learning layer is the model of our system. It is responsible for data analysis.FindingsWe apply our proposed architecture in a Smart environment and Smart energy. 10; In a Smart environment, we study the Toluene forecasting in Madrid Smart city. For Smart energy, we study wind energy foresting in Australia. Our proposed architecture can reduce the time of execution and improve the deep learning model, such as Long Term Short Memory10;.Research limitations/implicationsThis research needs the application of other deep learning models, such as convolution neuronal network and autoencoder.Practical implicationsFindings of the research will be helpful in Smart city architecture. It can provide a clear view into a Smart city, data storage, and data analysis. The 10; Toluene forecasting in a Smart environment can help the decision-maker to ensure environmental safety. The Smart energy of our proposed model can give a clear prediction of power generation.Originality/valueThe findings of this study are expected to contribute valuable information to decision-makers for a better understanding of the key to Smart city architecture. Its relation with data storage, processing, and data analysis.

scholarly journals Smart City Technology: Ecological Sustainability

2021 ◽  
Vol 295 ◽  
pp. 01032
Author(s):  
Anton Nazarov ◽  
Natalya Tovmasyan ◽  
Denis Kovtun
Keyword(s):  
Smart City ◽  
Smart Cities ◽  
Modern Society ◽  
Well Being ◽  
Ecological Sustainability ◽  
High Quality ◽  
Wide Range ◽  
Quality Of Living ◽  
High Level

The Smart City concept includes a fairly wide range of characteristics of this new phenomenon for modern society. The main goal of creating smart cities is the comfortable living in them of people with a high level of well-being. The quality of living conditions for people in smart cities directly depends on how clean their natural environment is. The article examines the features of the development of the ecological vector of creating cities with maximum amenities for residents. Possible risks associated with negligence towards objects of animate and inanimate nature are listed, ways of high-quality environmental protection of cities of the future are outlined.

scholarly journals A Cloud-Based UTOPIA Smart Video Surveillance System for Smart Cities

2020 ◽  
Vol 10 (18) ◽  
pp. 6572
Author(s):  
Chel-Sang Yoon ◽  
Hae-Sun Jung ◽  
Jong-Won Park ◽  
Hak-Geun Lee ◽  
Chang-Ho Yun ◽  
...  
Keyword(s):  
Video Surveillance ◽  
Communication Technology ◽  
Smart City ◽  
Smart Cities ◽  
Video Data ◽  
Smart Services ◽  
Video Cameras ◽  
Video Images ◽  
Information And Communication ◽  
City System

A smart city is a future city that enables citizens to enjoy Information and Communication Technology (ICT) based smart services with any device, anytime, anywhere. It heavily utilizes Internet of Things. It includes many video cameras to provide various kinds of services for smart cities. Video cameras continuously feed big video data to the smart city system, and smart cities need to process the big video data as fast as it can. This is a very challenging task because big computational power is required to shorten processing time. This paper introduces UTOPIA Smart Video Surveillance, which analyzes the big video images using MapReduce, for smart cities. We implemented the smart video surveillance in our middleware platform. This paper explains its mechanism, implementation, and operation and presents performance evaluation results to confirm that the system worked well and is scalable, efficient, reliable, and flexible.

Smart Homes and Offices

2022 ◽  
pp. 679-700
Author(s):  
Nikita Jain ◽  
Rachna Jain ◽  
Vaibhav Kumar
Keyword(s):  
Internet Of Things ◽  
Smart City ◽  
Data Transfer ◽  
Smart Cities ◽  
Smart Homes ◽  
Privacy Preserving ◽  
Standard Of Living ◽  
City Environment ◽  
The People ◽  
Direct Implementation

Smart Homes and Offices (SHO) are composed of interlinked components with constant data transfer and services targeted at increasing the lifestyle of the people. This chapter describes about the smart components and how SHO are direct implementation of Internet of Things (IOT). The major paradigm in this chapter is appliances supporting smart aspects of SHO, their applications and change in technology in context of smart Homes and Offices. Here we have also discussed the standardization and personalization of gadgets and how it has been increasing our standard of living. Finally, the chapter focuses on privacy preserving mechanisms, its essence over smart cities, strong architecture related to privacy, preserving mechanism, and various approaches available that can retaliate these issues in a smart city environment.

Smart Homes and Offices

2019 ◽  
pp. 84-105
Author(s):  
Nikita Jain ◽  
Rachna Jain ◽  
Vaibhav Kumar
Keyword(s):  
Internet Of Things ◽  
Smart City ◽  
Data Transfer ◽  
Smart Cities ◽  
Smart Homes ◽  
Privacy Preserving ◽  
Standard Of Living ◽  
City Environment ◽  
The People ◽  
Direct Implementation

Smart Homes and Offices (SHO) are composed of interlinked components with constant data transfer and services targeted at increasing the lifestyle of the people. This chapter describes about the smart components and how SHO are direct implementation of Internet of Things (IOT). The major paradigm in this chapter is appliances supporting smart aspects of SHO, their applications and change in technology in context of smart Homes and Offices. Here we have also discussed the standardization and personalization of gadgets and how it has been increasing our standard of living. Finally, the chapter focuses on privacy preserving mechanisms, its essence over smart cities, strong architecture related to privacy, preserving mechanism, and various approaches available that can retaliate these issues in a smart city environment.

Role of Contact Center for Smart Cities

2016 ◽  
Vol 3 (1) ◽  
Author(s):  
M. Aamir ◽  
Osama Mahfooz ◽  
Mujtaba Memon
Keyword(s):  
Smart City ◽  
Service Providers ◽  
Smart Cities ◽  
Contact Center ◽  
Customer Contact ◽  
City Environment ◽  
Production Factors ◽  
Information And Communication ◽  
Contact Centre

<span>Smart city is a strategic entity that comprises of modern urban production factors in a common<span> framework and highlights the growing importance of Information and Communication<span> Technologies (ICTs). Telecommunications service providers have strengths and assets that can<span> be utilized to bring the dream of a smart city environment into reality. This leads to a strong<span> move that serves the needs of society by ensuring E-Governance rather than conventional setup<span> of Governance. Establishing a customer contact centre is just the first part of the process of<span> optimal digitalization of municipal operations and interactions with citizens. This research<span> highlights how a contact center helps to achieve few goals of a by providing significant facilities<span> to citizens.<br /><br class="Apple-interchange-newline" /></span></span></span></span></span></span></span></span></span>

scholarly journals Improving Agent Quality in Dynamic Smart Cities by Implementing an Agent Quality Management Framework

2019 ◽  
Vol 9 (23) ◽  
pp. 5111
Author(s):  
Najwa Abu Bakar ◽  
Ali Selamat ◽  
Ondrej Krejcar
Keyword(s):  
Quality Management ◽  
Smart City ◽  
Smart Cities ◽  
Data Confidentiality ◽  
Management Framework ◽  
Agent Based ◽  
Agent Behavior ◽  
Agent Systems ◽  
City Environment ◽  
Privacy And Confidentiality

It is critical for quality requirements, such as trust, privacy, and confidentiality, to be fulfilled during the execution of smart city applications. In this study, smart city applications were modeled as agent systems composed of many agents, each with its own privacy and confidentiality properties. Violations of those properties may occur during execution due to the dynamic of agent behavior, decision-making capabilities, and social activities. In this research, a framework called Agent Quality Management was proposed and implemented to manage agent quality in agent systems. This paper demonstrates the effectiveness of the approach by applying it toward a smart city application called a crowdsourced navigation system to verify and assess agent data confidentiality. The AnyLogic Agent-Based Modeling tool was used to model and conduct the experiments. The experiments showed that the framework helped to improve the detection of agent quality violations in a dynamic smart city application. The results can be further analyzed using advanced data analytic approach to reduce future violations and improve data confidentiality in a smart city environment.

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