Skip to content

Latest commit

 

History

History
108 lines (58 loc) · 5.04 KB

README.md

File metadata and controls

108 lines (58 loc) · 5.04 KB
Raw

Air-Quality-Prediction

Table of Content

  • Video Demo
  • Overview
  • Motivation
  • Data Collection
  • Resnet(Transform Learning)
  • Installation and Run
  • Deployement on AWS
  • Future scope of the Project

Linkdin Profile

For any queries regarding about this project contact me

Link : https://www.linkedin.com/in/anil-l-b023631b6/

Video Demo

Screen.Recording.2021-10-09.at.8.28.43.PM.mov

Overview

Air pollution forecasting is the application of science and technology to predict the composition of the air pollution in the atmosphere for a given location and time. Mainstream pollution prediction algorithms tend to utilize air quality index or PM2. 5 concentration to indicate pollution level.

The forecast may give the pollutant's concentration or the air quality index.

Countries and cities are given forecasts by state and local government organizations, as well as private companies like Airly, AirVisual, Aerostate, BreezoMeter, PlumeLabs, and DRAXIS that provide air pollution forecasts. Air pollution forecasting can be done by coupling weather forecasting systems with chemical transport model and atmospheric dispersion modeling.

Motivation

What to do when you are at home due to this pandemic situation? I started to learn Machine Learning and Deep Learning model to get most out of it. I came to know mathematics behind all supervised models,unspurervised models,CNN,ANN and RNN. Finally it is important to work on application (real world application) to actually make a difference. To get a experience you have to work thats the reason to perform my favourable work done.

Data Collection

I just took the Bangalore city Air Quality data with help of web scraping and you can find through online which City data you want

Random Forest

Recent studies have incorporated machine learning techniques such as neural networks, regressions, and random forests to achieve high accuracy but I tried the random forest and it gives the good result

Screenshot 2021-10-09 at 9 24 43 PM

Flask Framework

Flask is a micro web framework written in Python. It is classified as a microframework because it does not require particular tools or libraries. ... Extensions exist for object-relational mappers, form validation, upload handling, various open authentication technologies and several common framework related tools.

Flask Tutorial : [https://www.tutorialspoint.com/flask/index.htm]

Screenshots of Project

Screenshot 2021-10-09 at 8 28 03 PM

Screenshot 2021-10-09 at 8 28 24 PM

Screenshot 2021-10-09 at 8 28 33 PM

Installation and Run

The Code is written in Python 3.9 If you don't have Python installed you can find it here. If you are using a lower version of Python you can upgrade using the pip package, ensuring you have the latest version of pip. To install the required packages and libraries, run this command in the project directory after cloning the repository:

Install Required Libraries

 Step 1: pip install -r requirements.txt

Running Project

 Step 2: Python app.py

Technologies Used

pandas.numpy flask

Tools / IDE

I used Jupyter NoteBook (Google Colab) for model training. used spyder for model deployment on the local system. To use Jupyter NoteBook and Spyder, just install anaconda.

Software Requirments

  • Python == 3.7.7
  • NumPy == 1.18.5
  • Flask == 1.1.2

Deploy AWS :

Deployement Process going on...

Future Scope

  • Optimize Flask app.py
  • Add Extra Features
  • Front-End