In the 1980s, the Bhopal region experienced one of the worst industrial disasters marked to date. The catastrophe raised awareness about industrial pollution. The water quality of the lakes in Bhopal has been significantly impacted by the 1984 gas tragedy. The release of toxic chemicals from the Union Carbide India Limited (UCIL) pesticide plant has contaminated the ground and surface water in the area, including the lakes. Tests conducted on the groundwater in communities situated around the Union Carbide factory in Bhopal have revealed high levels of pollutants such as heavy metals like lead, mercury, cadmium, Gamma HCH, Lindane, Beta HCH, Styrene, Mercury, Alpha HCH, Alpha Naphthol, Phosgene, Dichlorobenzene, etc.
In the years that followed, the Bhopal region dealt with environmental challenges, particularly regarding water quality. The lakes are also heavily polluted with volatile organic compounds (VOCs), such as benzene and toluene, pesticides, herbicides, and Polycyclic aromatic hydrocarbons, leading to a decline in fish and other aquatic life. The water is also not safe for swimming or other recreational activities.
Bhopal is also known as “The City of Lakes”, which indicates that Bhopal has a significant quantity of Lakes. People who live in the area are constantly in contact with chemicals assimilated in the water bodies during Gas Tragedy. Surveys done by the Bhopal campaign groups have shown that their environment contains six of the persistent organic pollutants banned by the United Nations for their highly poisonous impacts on the environment and human health, which has now reached 42 areas in Bhopal and continues to spread. According to the Surveyors, the situation is getting worse, and second and third-generation children are being born with disabilities.
Apart from this, during the “Gas Tragedy”, MIC(methyl isocyanide) was released, which reacts with water exothermically and produces carbon dioxide, methylamine, dimethylurea, and/or trimethyl biuret, these chemicals cause adverse effects on human bodies while incorporating itself to water. Swiss lab results show chloroform concentrations as many as 3.5 times higher than drinking-water guidelines from the World Health Organization and U.S. EPA , and carbon tetrachloride at up to 2,400 times higher than the guidelines, which impels us to study various lakes of Bhopal.
This study aims to develop a Machine Learning system for monitoring the water quality of multiple lakes in the Bhopal region using satellite imagery and GIS techniques. The objective is to assess the water quality, detect the probable causes of water pollution and predict the potential impacts of different pollution sources on the environment and human health. The study will use a combination of remote sensing techniques, image processing methods, and GIS tools to extract relevant information from satellite data. Additionally, the system will enable real-time monitoring of water quality, allowing for timely intervention in case of any deterioration in water quality.
- Have a Look at the project structure and folder overview below to understand where to store/upload your contribution
- If you're creating a task, Go to the task folder and create a new folder with the below naming convention and add a README.md with task details and goals to help other contributors understand
- Task Folder Naming Convention : task-n-taskname.(n is the task number) ex: task-1-data-analysis, task-2-model-deployment etc.
- Create a README.md with a table containing information table about all contributions for the task.
- If you're contributing for a task, please make sure to store in relavant location and update the README.md information table with your contribution details.
- Make sure your File names(jupyter notebooks, python files, data sheet file names etc) has proper naming to help others in easily identifing them.
- Please restrict yourself from creating unnessesary folders other than in 'tasks' folder (as above mentioned naming convention) to avoid confusion.
├── LICENSE
├── README.md <- The top-level README for developers/collaborators using this project.
├── original <- Original Source Code of the challenge hosted by omdena. Can be used as a reference code for the current project goal.
│
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├── reports <- Folder containing the final reports/results of this project
│ └── README.md <- Details about final reports and analysis
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├── src <- Source code folder for this project
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├── data <- Datasets used and collected for this project
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├── docs <- Folder for Task documentations, Meeting Presentations and task Workflow Documents and Diagrams.
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├── references <- Data dictionaries, manuals, and all other explanatory references used
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├── tasks <- Master folder for all individual task folders
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├── visualizations <- Code and Visualization dashboards generated for the project
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└── results <- Folder to store Final analysis and modelling results and code.
- Original - Folder Containing old/completed Omdena challenge code.
- Reports - Folder to store all Final Reports of this project
- Data - Folder to Store all the data collected and used for this project
- Docs - Folder for Task documentations, Meeting Presentations and task Workflow Documents and Diagrams.
- References - Folder to store any referneced code/research papers and other useful documents used for this project
- Tasks - Master folder for all tasks
- All Task Folder names should follow specific naming convention
- All Task folder names should be in chronologial order (from 1 to n)
- All Task folders should have a README.md file with task Details and task goals along with an info table containing all code/notebook files with their links and information
- Update the task-table whenever a task is created and explain the purpose and goals of the task to others.
- Visualization - Folder to store dashboards, analysis and visualization reports
- Results - Folder to store final analysis modelling results for the project.
Project Leads: Vaasu Bisht and Eeman Majumder
Management and HR: Sakshi Sawarkar
Project Contributors in aplhabetical order:
1 Aditya Bhate
2 Aiswarya Jyothirmayi Devi
3 Akshit Srivastava
4 Aman Makwana
5 Ameya Sharma
6 Ananya Mohanty
7 Ananya Tiwari
8 Aniruddha Kumar
9 Astha Srivastava
10 Ayushka Behere
11 Dhruvil Jain
12 Kshitij Singh
13 Lauren Williams
14 Modekurthi Subrahmanya Satwick
15 Muskaan Bahri
16 Navneet Lamba
17 Pranav Pratyush
18 Punya Saraogi
19 Pushpendra Kushwaha
20 Qurat Ul Aaein
21 Raj Mansuriya
22 Reem Abdel-Salam
23 Rishit Chugh
24 Rishita Bansal
25 Sayan Kumar
26 Shantanu Sugriv Kshirsagar
27 Shashank Singh
28 Shilpa Gollamudi
29 Shinjan Verma
30 Sourav Dutta
31 Srijeeta Mukherjee
32 Vimukta Dashora
33 Wallace Ferreira