Automatic Video Object Detection Using Particle Swarm Optimisation in Fog Computing:

M. Sakthivanitha Vels Institute of Science Technology and Advanced Studies, India S. Saradha Vels Institute of Science Technology and Advanced Studies, India Automatic Video Object Detection Using Particle Swarm Optimisation in Fog Computing

In this chapter, the authors focus on optimising video surveillance by considering five factors while processing the surveillance. The five factors are bandwidth availability, connection availability, storage availability, CPU availability, and memory availability. Since the research work mainly focused on fog computing environment, two major factors are bandwidth and connection availability while sending a video content to the authorized person. The size of video content will be large and slow while transferring the data from one location to another location through wireless network. This problem will be optimized using particle swarm optimization algorithm (PSO). This proposed PSO algorithm will optimize the video content and make it effective and efficient to transfer from one location to another location, and then the object detection (OD) is conducted using suitable hardware arrangements involving a microcontroller unit and GSM communication module for altering the user with objects in forest area.
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