Detecting and Mitigating Traffic Accidents Using Machine Learning and Traffic Data

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 Gaborone, Botswana Chapter.  

The problem

Traffic accidents are a major concern in Botswana, leading to the loss of many lives and significant financial losses. Here are some of the problems

• Economic losses: Road accidents in Botswana lead to significant economic losses, both for individuals and the government. Many individuals incur high medical bills and lose their sources of income due to injuries sustained in accidents. Motor Vehicle Accident Fund (MVA) spends over P40 million (US$ 3.8 million) annually on medical bills and claims due to accidents.
• Impact on mental health: Road accidents can have long-lasting psychological effects on individuals and families. Survivors of accidents may experience anxiety, depression, and post-traumatic stress disorder (PTSD), while families of victims may suffer from grief and emotional distress. The impact on mental health can have far-reaching consequences, affecting not only individuals but also their families and communities.

The goals

AI has proven to be a powerful tool for solving complex problems in a faster and more accurate way than ever before. The field of transportation is no exception, and machine learning algorithms have been shown to be effective in predicting and detecting potential traffic accidents.

In this project, we aim to leverage this technological advancement to help mitigate the problem of traffic accidents in Botswana.

That is why for 4 weeks our goal will be to develop a machine-learning model that can predict the likelihood of accidents occurring in different regions and areas in Botswana. This will include working on the following:

• Collect and analyze traffic data to identify patterns and trends related to traffic accidents.
• Analyze Botswana Police Service traffic data to identify primary causes of traffic accidents
• Carry out data preprocessing and extensive data analysis into the cause of accidents.
• Develop a traditional machine learning or deep learning model to predict traffic accidents.
• Carry out inference with the trained model using test data
• Develop some suggestions on how traffic accidents could be mitigated based on data from the provided datasets
• Build a dashboard to visualize our results

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