scholarly journals Academics perception of public areas video surveillance in smart cities

2021 ◽  
Vol 6 (2) ◽  
pp. 21-33
Author(s):  
Branko Markovic ◽  
Dejan Ilic ◽  
Dragan Milosevic ◽  
Ivana Ilic
Keyword(s):  
Video Surveillance ◽  
Smart Cities ◽  
Public Areas

Intelligent Anomaly Detection Video Surveillance Systems for Smart Cities

2019 ◽  
pp. 163-182
Author(s):  
Gajendra Singh ◽  
Rajeev Kapoor ◽  
Arun K. Khosla
Keyword(s):  
Video Surveillance ◽  
Smart Cities ◽  
Vital Role ◽  
Personal Life ◽  
Monitoring Systems ◽  
Human Observer ◽  
Surveillance Systems ◽  
Public Areas ◽  
Long Time ◽  
Control And Management

With the growing demands of safety for people and their properties, video surveillance has drawn much attention. These requirements have led to the positioning of cameras almost every corner. Smart video surveillance systems can interpret the situation and automatically recognize abnormal situations, which plays a vital role in intelligence monitoring systems. One vital aspect is to detect and alert generation of suspicious events then to notify operators or users automatically. A long time may pass before an event of interest to take place. In such situations, human attention may get diverted and an event of interest may get missed. In such case, video surveillance systems can effectively improve safety and security for the control and management of public areas or personal life. Independent surveillance systems to replace the traditional (human observer-oriented) systems also can relieve the workload of relative personnel.

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.

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 Surveillance using Face Recognition in Smart Cities

2020 ◽  
Vol 9 (4) ◽  
pp. 2042-2047
Keyword(s):  
Face Recognition ◽  
Video Surveillance ◽  
Crime Rate ◽  
Smart Cities ◽  
Police Department ◽  
Indian Government ◽  
The Past ◽  
Time To Build ◽  
Voting System ◽  
The City

In this project safe city demonstrates how the security in India can be increased with the help of video surveillance using facial recognition. In the Aadhar Card database, the Indian Government has stored fingerprint and Iris details of every civilian in India. But the Indian Government is only using the Fingerprint details in the voting system to avoid fake votes. With the help of this project any person roaming in the city limit can be easily monitored. This will be a very useful technology for the Police Department of India to track the criminals and to reduce crime rate. Whenever a person or criminal is needed to be traced , the photo of the target is uploaded into the software. The uploaded photo will be cross-checked by the software with the videos captured from the surveillance cameras. It will then identify the person based on the percentage of accuracy to be matched. In the past 5 years Indian Government have made many cities into smart cities. But now it’s time to build safe cities for India.

A dynamic, plug-and-play and efficient video surveillance platform for smart cities

Kahn at Penn ◽  
2017 ◽  
Author(s):  
G. Baldoni ◽  
M. Melita ◽  
S. Micalizzi ◽  
C. Rametta ◽  
G. Schembra ◽  
...  
Keyword(s):  
Video Surveillance ◽  
Smart Cities ◽  
Plug And Play ◽  
Efficient Video

Approaches for detecting behavioural anomalies in public areas using video surveillance data

2008 ◽  
Author(s):  
Christoffer Brax ◽  
Rikard Laxhammar ◽  
Lars Niklasson
Keyword(s):  
Video Surveillance ◽  
Surveillance Data ◽  
Public Areas

scholarly journals Video Surveillance-Based Intelligent Traffic Management in Smart Cities

2019 ◽  
Author(s):  
Fozia Mehboob ◽  
Muhammad Abbas ◽  
Abdul Rauf ◽  
Shoab A. Khan ◽  
Richard Jiang
Keyword(s):  
Video Surveillance ◽  
Traffic Management ◽  
Smart Cities

Management of Video Surveillance for Smart Cities

2018 ◽  
pp. 285-310
Author(s):  
Nhat-Quang Dao ◽  
Quang Le-Dang ◽  
Robert Morawski ◽  
Anh-Tuan Dang ◽  
Tho Le-Ngoc
Keyword(s):  
Video Surveillance ◽  
Smart Cities
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