A MODEL DESIGN FOR SMART HOME SECURITY SYSTEM USING (IOT) WITH CCTV CAMERA

Muhammad adnan; Allah Bachayo; Zeeshan Ahmed; Samheia Affrah

Muhammad adnan
Allah Bachayo
Zeeshan Ahmed
Samheia Affrah

Keywords: Computer Software, Deep Learning Technique, Convolutional Neural Network (CNN), and Quality of Service (QoS).

Abstract

This research approach is arranged once the Simulation Model design in MATLAB compeered computer software to create the Surveillance up and Smart Home surveillance system is a Smart Security system. The Experimental outcomes compare present status with normal test precision on genuine videos then this method provides test accuracy on genuine videos from the video clip that is the intelligent system. This research approach is arranged once the Simulation Model is designed in MATLAB-compeered computer software. The Deep Learning technique, firstly, the architecture design of the convolutional neural Network (CNN) community is presented and analyzed within the context associated with selected and designed architecture from the surveillance system that makes sense. Positive results are meticulously examined, as well as the among the most effective is chosen to become utilized in the proposed system model, and greater quality of Service (QoS). The major aim of the research study is to automate the IVS system through IPS as much as possible and to achieve a high percentage of accuracy. This thesis focuses on counting and tracking people/ objects in the crowd which include several technical tasks such as human detection and overcoming the problem of occlusion with acceptable processing speed.

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