Projects / Local Chapter Challenge

Monitoring the Water Quality in Bhopal Region Using Satellite Imagery and GIS Techniques

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This Omdena Local Chapter Challenge runs for 5 weeks and is a unique experience to try and grow your skills in a collaborative and safe environment with a diverse mix of people from all over the world.

You will work on solving a local problem, initiated by DVIT Bhopal University.

The problem

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. Therefore, we would like to develop a Machine Learning system for monitoring the water quality in the Bhopal region. We aim to assess water quality and its pollutants while detecting the probable causes of water pollution, including the “Bhopal Gas Tragedy”. We will predict the potential impacts of different pollution sources on the environment and human health (local community- people of Bhopal) by using a combination of remote sensing techniques, image processing methods, and GIS tools to extract relevant information from satellite data. 

The results of this study will provide valuable insights into the current state of water quality in the lakes of the Bhopal region, providing aid in the development of appropriate management strategies to improve water quality and protect public health. Additionally, the system will enable real-time monitoring of water quality, allowing for the timely intervention of concerned authorities, in case of any deterioration.

The goals

The Bhopal region has been facing environmental challenges regarding water quality for the past few decades (since the gas tragedy of 1989). Due to a lack of regular monitoring, the Government is unable to identify and address issues regarding water pollution, its supply, and any ongoing contamination issues in Bhopal Lakes. Many residents of Bhopal still lack access to clean drinking water that comes under the jurisdiction of the Bhopal Municipal Corporation (BMC). However, the quantity of water provided by the private hand pumps, and bore wells to them, more often than not, is highly polluted by pollutants such as heavy metals like lead, mercury, cadmium, Gamma HCH, Lindane, Beta HCH, Styrene, Mercury, Alpha HCH, Alpha Naphthol, Phosgene, Dichlorobenzene, etc.

Several strategies are being adopted to upgrade the quality of water and to improve the accessibility of a large proportion of the population of the city to a healthy water supply by the city’s civil agencies in cooperation with other agents. Furthermore, this project will provide real-time water quality monitoring allowing authorities to work with better ideas on the quality. This project aims to provide a safe and proper water supply to the local community of the Bhopal Region, which will improve their well-being. In addition to improving health, this will also help the aquatic environment, which is in decline. It will also give rise to other recreational activities for the people.    

To precisely determine the water quality in the Bhopal region, our project intends to construct a Machine Learning system for processing satellite photos and GIS data. The primary causes of water contamination will be determined using the established algorithm. Using this algorithm, we can assess the water quality, detect probable sources of pollution, and predict how different pollution sources might impact the environment and human health. The result will provide valuable insights into the current water quality of the Bhopal region. Furthermore, the system will enable real-time monitoring of water quality, allowing for timely intervention in case of any deterioration in water quality. Collaboration with local authorities and organizations will help to implement the developed system and to address identified pollution issues. Based on feedback and new data, it will be assessed regularly and worked on to enhance the developed system.

Why join? The uniqueness of Omdena Local Chapter Challenges

Omdena Local Chapter Challenges are not a competition or hackathon but a real-world project that will grow your experience to a new level.

A unique learning experience with the potential to make an impact through the outcome of the project. You will go through an entire data science project lifecycle. This covers problem scoping, data collection, and preparation, as well as modeling for deployment.

And the best part is that you will join the global and collaborative community of Omdena with tons of benefits to accelerate your career.

Read more on how Omdena´s Local Chapters work

First Omdena Local Chapter Challenge?

Beginner-friendly, but also welcomes experts

Education-focused

Open-source

Duration: 4 to 8 weeks



Your Benefits

Address a significant real-world problem with your skills

Build your project portfolio

Access paid projects (as an Omdena Top Talent)

Get hired at top organizations



Requirements

Good English

Suitable for AI/ Data Science beginners but also more senior collaborators

Learning mindset



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