scholarly journals IoT Driven Automated Object Detection Algorithm for Urban Surveillance System in Smart City

2019 ◽  
Vol 8 (6S3) ◽  
pp. 1687-1691
Keyword(s):  
Object Detection ◽  
Road Traffic ◽  
Smart Cities ◽  
Digital Camera ◽  
Detection Algorithm ◽  
License Plate ◽  
Surveillance Systems ◽  
Research Issues ◽  
Automated Object Detection ◽  
Research Challenge

Automated object detection algorithm is an important research challenge in intelligent urban surveillance systems for Internet of Things (IoT) and smart cities applications. In particular, smart vehicle license plate recognition and vehicle detection are recognized as core research issues of these IoTdriven intelligent urban surveillance systems. They are key techniques in most of the traffic related IoT applications, such as road traffic real-time monitoring, security control of restricted areas, automatic parking access control, searching stolen vehicles, etc. In this paper, we propose a novel unified method of automated object detection for urban surveillance systems. We use this novel method to determine and pick out the highest energy frequency areas of the images from the digital camera imaging sensors, that is, either to pick the vehicle license plates or the vehicles out from the images. The other sensors like flame and ultrasonic sensor are used to monitor nearby objects. Our proposed method can not only help to detect object vehicles rapidly and accurately, but also can be used to reduce big data volume needed to be stored in urban surveillance systems

scholarly journals Design of Vehicle License Monitoring System to Control Theft by using IOT

2019 ◽  
Vol 9 (1) ◽  
pp. 2174-2177
Keyword(s):  
Internet Of Things ◽  
Heavy Traffic ◽  
External Disturbance ◽  
Digital Camera ◽  
Detection Algorithm ◽  
Rfid Tags ◽  
License Plate ◽  
Smart Transportation ◽  
Automated Object Detection ◽  
Vehicle Movement

Smart transportation for urban cities can be done using Internet of Things (IOT). An automated object detection algorithm is used to identify the vehicle by using VLPR system. Identification of vehicle in heavy traffic or in parking lots is difficult and hence we propose a system by using RFID tags where the vehicle movement and vehicle license plate number can be obtained accurately. So by using IOT we can access the data from anywhere and the vehicle movement can be identified. Instead of using digital camera where due to external disturbance the images gets blurred, so we go for RFID where due to radio frequency transmission they stores the data. The performance of the device will not get degraded due to shadow noise, thunders and due to heavy speed. The main aim of proposed system is to check the vehicles license number and drivers vehicle license and to verify the vehicles RC book renewal.

Automated Object Detection and Tracking for Intelligent Visual Surveillance Based on Sensor Network

2011 ◽  
pp. 1263-1284
Author(s):  
Ruth Aguilar-Ponce ◽  
Ashok Kumar ◽  
J. Luis Tecpanecatl-Xihuitl ◽  
Magdy Bayoumi ◽  
Mark Radle
Keyword(s):  
Wireless Sensor Network ◽  
Object Detection ◽  
Sensor Network ◽  
Tracking System ◽  
Visual Surveillance ◽  
Wireless Sensor ◽  
Surveillance Systems ◽  
Object Detection And Tracking ◽  
Detection And Tracking ◽  
Automated Object Detection

The aim of this research was to apply an agent approach to wireless sensor network in order to construct a distributed, automated scene surveillance. Wireless sensor network using visual nodes is used as a framework for developing a scene understanding system to perform smart surveillance. Current methods of visual surveillance depend on highly train personnel to detect suspicious activity. However, the attention of most individuals degrades after 20 minutes of evaluating monitor-screens. Therefore current surveillance systems are prompt to failure. An automated object detection and tracking was developed in order to build a reliable visual surveillance system. Object detection is performed by means of a background subtraction technique known as Wronskian change detection. After discovery, a multi-agent tracking system tracks and follows the movement of each detected object. The proposed system provides a tool to improve the reliability and decrease the cost related to the personnel dedicated to inspect the monitor-screens

Automated Object Detection and Tracking for Intelligent Visual Surveillance Based on Sensor Network

2011 ◽  
pp. 206-228 ◽  
Author(s):  
Ruth Aguilar-Ponce ◽  
Ashok Kumar ◽  
J. Luis Tecpanecatl-Xihuitl ◽  
Magdy Bayoumi ◽  
Mark Radle
Keyword(s):  
Wireless Sensor Network ◽  
Object Detection ◽  
Sensor Network ◽  
Tracking System ◽  
Visual Surveillance ◽  
Wireless Sensor ◽  
Surveillance Systems ◽  
Object Detection And Tracking ◽  
Detection And Tracking ◽  
Automated Object Detection

The aim of this research was to apply an agent approach to wireless sensor network in order to construct a distributed, automated scene surveillance. Wireless sensor network using visual nodes is used as a framework for developing a scene understanding system to perform smart surveillance. Current methods of visual surveillance depend on highly train personnel to detect suspicious activity. However, the attention of most individuals degrades after 20 minutes of evaluating monitor-screens. Therefore current surveillance systems are prompt to failure. An automated object detection and tracking was developed in order to build a reliable visual surveillance system. Object detection is performed by means of a background subtraction technique known as Wronskian change detection. After discovery, a multi-agent tracking system tracks and follows the movement of each detected object. The proposed system provides a tool to improve the reliability and decrease the cost related to the personnel dedicated to inspect the monitor-screens

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.

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