Red Eye

Table of Contents.

• Description.
• System Architecture.
• Hardware.
• Deep Learning Model.
• Email and Sms Notifying.
• Mobile Application.
• Topics used for implementation.
• Awards.

Description.

• A compelete smart surveillance system that is deployed on Rasbperry PI 4 Camera. The system is able to detect Fire and weapons in real time and report the location of the camera via a backend server by sms, emails and a mobile application. All done in max 4 seconds.

Real-Time, Neat Build, And can be exteneded.

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System Architecture

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Hardware

Rasbperry PI 4, Camera Module V2.

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Deep Learning Model

Tiny Yolo V3 CNN.

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Email and SMS notifying

Amazon AWS Lambda Back-End server, AWS SNS.

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Mobile Application

Flutter application, Dashboard data via Amazon AWS DynamoDB.

Topics used for implementation.

• Python, Yolo V3, CNNs.
• Rasbperry PI configuration.
• APIs in Amazaon AWS.
• Flutter, AWS DynamoDB.

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Awards

Egypt's First Smart Cities Hackathon Smart Surveillance first place, Second place overall tracks out of 478 teams.