Abstract
Video analytic is the important tool for smart city development. The video analytic application requires more memories and high processing devices. The problems of cloud-based approach for video analytic are high latency and more network bandwidth to transfer data into the cloud. To overcome these problems, we propose a model based on dividing the jobs into smaller sub-tasks with less processing requirements in a typical video analytics application for the development of smart city. The object detection, tracking and pattern recognition method to reduce the size of videos based on edge network will be proposed. We will design a video analytic model, and simulation is performed using iFogSim simulator. We will also propose Convolutional Neural Network (CNN) based object tracking model. The experimental verification shows that our tracking model is more than 96% accurate, and the proposed edge and cloud-based model is more than 80% effective than only cloud-based approach for video analytic applications.
Highlights
Smart city is a city that uses technologies to provide the sophisticated lifestyle for humans
The smart cities have several types of technologies such as Information and Communication Technology (ICT), connected physical devices using the Internet of Things (IoT), Geographical Information System (GIS), Video Analytic System (VAS) and more
The combination of edge computing and the cloud computing is the main paradigm for video analytic system to build smart city application
Summary
Smart city is a city that uses technologies to provide the sophisticated lifestyle for humans. Edge computing and cloud computing technologies are the important concepts for the development of smart cities to process video data. Edge network is a networking environment that focuses on bringing computing closer to the data source It is the local processing technique near the Internet of Things (IoT) devices. The combination of fog/edge computing architecture with IoT devices and the cloud computing is a very important research area for smart cities to minimize the resources and providing optimization for the users’ benefits. The combination of edge computing and cloud computing technology is the more powerful technology to process video data. We will propose video analytic system to process video data for smart city development.
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