My_Guard

Automated Security Task
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Table of Contents

• About the Project
• Resources
• Getting Started
• Workflow
• Contact

About The Project

My_Guard is built by keeping Automated Security Task in mind. Its a Python-Flask based web application intended to be used in Raspberry Pi Desktop. Its main motive is to assist security services in giving accurate results, allow eligible visitors to enter any society or space and also maintain the logs regarding this. My_Guard being a Web App can installed across any platforms.

Resources

1. Framework : Flask

• Flask Documentation (1.1.x)

2. Database : MongoDB Atlas

• MongoDB Atlas
• Python MongoDB Tutorial using PyMongo
• PyMongo - Read the Docs

3. AWS Python SDK - Boto3

• Boto3 Documentation
• Amazon S3
• Amazon Rekognition
• Amazon CloudWatch

Getting Started

Clone the Repo

git clone https://github.com/ADI-KOTKAR/My_Guard.git

Create Free Accounts

Create free accounts of MongoDB Atlas and AWS.

Python 3

Install Python 3 in your system. click here

Create a Virtual Environment.

• Installing virtualenv package of Python.

pip install virtualenv

• Creating a virtual environment named 'venv'.

virtualenv venv

• Activate the environment (Windows).

venv\Scripts\activate

Installing Dependencies in Virtual Environment

• Make sure environment is activated. (env)
• Using Requirements File. (Recommended)

pip install -r requirements.txt

• Individually installing packages.

  Flask | Flask-PyMongo | bcrypt | boto3 | dnspython

pip install Flask Flask-PyMongo bcrypt boto3 dnspython

File Configuration

1. Generate AWS credentials (csv file) by following this link. Create .env files in the root directory and the directories shown below.

📦app  
 ┣ 📂Enter  
 ┃ ┣ 📂images   
 ┃ ┣ 📂templates   
 ┃ ┣ 📂__pycache__   
 ┃ ┣ 📜.env  
 ┃ ┣ 📜enter.py  
 ┃ ┗ 📜__init__.py  
 ┣ 📂Register  
 ┃ ┣ 📂templates  
 ┃ ┣ 📂__pycache__   
 ┃ ┣ 📜.env  
 ┃ ┣ 📜register.py  
 ┃ ┗ 📜__init__.py 
 ┗ 📜extensions.py

Mention the credentials generated in the .env file.

USER_NAME = your_username
ACCESS_KEY_ID = your_access_key_id
SECRET_ACCESS_KEY = your_secret_access_key
CONSOLE_LOGIN_LINK = your_console_login_link

2. Connect your MongoDB Atlas Cluster with your project by getting the MONGO_URI (Reference link). Create a file named settings.py mentioning the uri.

import os
MONGO_URI = "your_mongo_uri"

If you have made it so far then you are genius enough to configure this application for any OS.

Running Application

Make sure environment is activated, Now run:

python main.py

Open the localhost link - http://127.0.0.1:5000/ , this will open the App on your browser.

Workflow

Register Visitor

1. User sends his name and image through the registration form on application.

2. After verifying all fields, the image is uploaded on Amazon S3 Bucket

3. The form details along with timestamp are inserted in the MongoDB Atlas database. A user ID is generated after a successful transaction.

4. The Amazon CloudWatch sends a snapshot of metrics for monitoring the API request

Entry of Visitor

1. Registered User sends his ID, temperature, entry_type (IN/OUT), and image through the entry form on application.

2. If temperature is invalid, then the entry is denied, else further details are verified and response is inserted in the database.

3. If ID is not found (verified from S3 Bucket), then entry is denied, else further details are verified and response is inserted in the database.

4. If Face is not Recognized (verified from Rekognition), then entry is denied and response is inserted in the database.

5. If above all conditions are successfully verified then the user is allowed to enter and response is inserted in the database.

6. The Amazon CloudWatch sends a snapshot of metrics for monitoring the API request.

Contact

Aditya Kotkar -adityakotkar75@gmail.com

License

• Project link: My_Guard
• License