https://github.com/mohamed-samy26/red-eye-smart-cities-surviellance-system
City wide smart suviellance system that can detect weapons and fires in real-time and report detailed information to the responsible authorities.
https://github.com/mohamed-samy26/red-eye-smart-cities-surviellance-system
automation aws cnn colab-notebook computer-vision deep-learning flutter hackathon jupyter-notebook linux neural-networks object-detection python python3 raspberry-pi-4 raspberry-pi-camera serverless smart-cities smart-surveillance yolov3
Last synced: 4 months ago
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City wide smart suviellance system that can detect weapons and fires in real-time and report detailed information to the responsible authorities.
- Host: GitHub
- URL: https://github.com/mohamed-samy26/red-eye-smart-cities-surviellance-system
- Owner: Mohamed-Samy26
- Created: 2022-04-11T21:01:06.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2022-04-15T13:03:49.000Z (about 3 years ago)
- Last Synced: 2025-02-01T12:44:05.888Z (4 months ago)
- Topics: automation, aws, cnn, colab-notebook, computer-vision, deep-learning, flutter, hackathon, jupyter-notebook, linux, neural-networks, object-detection, python, python3, raspberry-pi-4, raspberry-pi-camera, serverless, smart-cities, smart-surveillance, yolov3
- Language: Python
- Homepage:
- Size: 15.6 KB
- Stars: 9
- Watchers: 2
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Red Eye
### Table of Contents.
- [Description.](#description)
- [System Architecture.](#system-architecture)
- [Hardware.](#hardware)
- [Deep Learning Model.](#deep-learning-model)
- [Email and Sms Notifying.](#email-and-sms-notifying)
- [Mobile Application.](#mobile-application)
- [Topics used for implementation.](#topics-used-for-implementation)
- [Awards.](#awards)
## Description.
- This is a complete smart surveillance system which can be deployed on a Rasbperry PI 4 equipped with a Camera module. The system is able to detect Fire and weapons in real time and report the location of the threat to the relevant authorities via a serverless backend, The system can report by SMS, Emails and a Cross-platform application. with a maximum delay time of 4 seconds.
### Real-Time, Neatly Build, And extenedable.
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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.
### Dataset of labeled images for Guns , Rifles , and fires
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## Email and SMS notifying
### Using Amazon AWS Lambda serverless cloud functions it can invoke operations on AWS SNS and AWS Dynamo DB to handle the response of the detected threeat.
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## Mobile Application
### Flutter application, Dashboard data and statistical analytics 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 first place in Smart Surveillance track and Second place overall tracks out of 478 teams.
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