Seasons Of Code
Machine Learning Based Metropolitan Air Pollution Estimation • Mufaddal Moni • Manan Kumar Garg
WnCC - Seasons of Code
Seasons of Code is a programme launched by WnCC along the lines of the Google Summer of Code. It provides one with an opprtunity to learn and participate in a variety of interesting projects under the mentorship of the very best in our institute.
List of Running Projects
- Browser Based PDF manager
- Resume Script Generator
- Physicc : A Simple Physics Engine
- Image Colorization
- Language Model Based Syntax Autocompletion in a Text Editor
- Computer vision based web app
- Cribbit Cribbit (Open for PGs Only)
- Techster Texter
- Language Detection
- Book Tracker
- ResoBin - Not the bin we deserve but the bin we need!
- Moodify
- Agree to disagree
- Unscripted
- Watson (World's smartest assistant in your pocket)
- IITinder
- BriefKing
- Meta Learning - Learning to Learn
- Break free of the matrix, by building one!
- Procedurally Generated Infinite Open World
- Introduction to App Development
- PAC MAN
- Introduction to Web Development
- (Un)Clear
- Goal ICPC
- Traffic congestion modelling and rendering
- PyRated
- Tools for Data Science
- Machine Learning Based Metropolitan Air Pollution Estimation
- Audio controlled drone
- NLPlay with Transformers
- DIY FaceApp
- A Deep Dive into CNNs
- Competitive Coding
- Snake AI
- Facial Recognition App
- Gaming meets AI !!!
- R(ea)L Trader
- Computational Geometry
- Deep reinforcement learning - 2048 AI
- Reinforcement Learning to Finance
- Developing Hybrid ANN-Statistical Model for Robust Stock Market Prediction
- Si-Phy
- Astronomical Data-modelling and Interpretation
- Visual Perception for Self Driving Cars
- Convolutional Neural Networks and Applications
- Quantum Computing Algorithms
- Algorithm Visualizer
- Anime Club IITB Website using Django
- Machine Learning in Browser
Machine Learning Based Metropolitan Air Pollution Estimation
The idea is to develop a spatial distribution model for Air Pollution for the city of Delhi using SVR (Support Vector Regression) and the model will be self enhancing using machine learning.
No. of mentees: 10
Description: The city of Delhi is chosen because of two reasons, first one being that it is one of the most polluted metropolitans in India and world, and secondly it is the city with more highest number of CAAQMS (Continuous Ambient Air Quality Monitoring Stations) in India. The data source for all the data will be website of CPCB (Central Pollution Control Board) and the model would be presented on a python based web interface.
The aim to develop this model is to provide a open source model for Research in this direction and my personal interest to work in the area of Ambient Air Quality Control.
This is not a entirely new idea and a lot of models have been made, but no open source model is available for Indian cities. Thus there are lot of research papers available on this topic on Google Scholar. A few of them which I suggest you to read are: https://ieeexplore.ieee.org/abstract/document/7892954 https://www.x-mol.com/paper/1252735758843666432
I do not expect much from, your proposal, The only need is enthusiasm to work in Machine Learning or Air Quality and Pollution would suffice. And it would be a fun learning process, where we all can learn together. No prerequisites, but some knowledge of Machine Learning or Python will be icing on the cake!
Tentative Project Timeline
| Week Number | Tasks to be Completed |
|---|---|
| Week 1 | Complete Courses for Python and Pandas |
| Week 2-3 | Theoretical Complete Courses on Machine Learning (being thorough with Support Vector Machines) |
| Week 4 | Making Basic Models using TensorFlow |
| Week 5-6 | Working On Final Model |
Checkpoints:
| Checkpoint Number | Progress |
|---|---|
| 1 | Completing Python and Pandas |
| 2 | Completing Theoretical ML |
| 3 | Basics of Tensor Flow |
| 4 | Data Scraping and Data Preprocessing |
| 5 | Completion of Final Model |