Bangladesh Chapter - AI for Improving Road Safety in Bangladesh
Challenge Background
The Problem
Road safety is a major concern in Bangladesh. An estimate states that 55 people are killed in road crashes every day, and that vulnerable road users including walkers, motorcyclists, and unsafe and informal public transportation users account for more than 80% of road traffic deaths [1] . As a direct consequence of rapid growth in population, motorization and urbanization, the situation is deteriorating rapidly. The potential of maturing Artificial Intelligence (AI) and Internet-of-Things (IoT) technologies to enable rapid improvements in road safety has been largely overlooked. There is a pressing need and opportunity to improve road safety by enacting effective and coordinated Artificial Intelligence-driven (AI) policies and actions, which will necessitate significant improvements in the relevant sectors, such as better enforcement, better roads including improving design to eliminate accident black spots, and improved public education programs.
The first step would be to identify the root cause of road accidents in Bangladesh by analyzing data, and then investigate the utility of AI driven technologies i.e. automated analysis of traffic scenarios, monitoring speed, violations and driving patterns of the drivers, auto-alerting drowsy drivers etc. This will help to outline a solution tailored for the infrastructure of Bangladesh.
The case-study results will be made open source. The aim being to help ride sharing service providers, regulatory bodies, policy makers etc. while educating aspiring data scientists in solving real-world problems.
Goal of the Project
The goal of the project is to:
- Collect road accident-related data from public databases, newspapers, web pages, etc.
- Analyze the data following a systematic methodology
- Conduct exploratory data analysis
- Outline an AI-driven solution to improve road safety
Project Timeline
Collecting the data and the knowledge about ECG
Defining the CV Model able to learn and predict from ECG
Testing with Health professionals to get feedback about the model accuracy and performance
Deploy the App in Cloud Application Platforms
What you'll learn
- Web Scraping - Data Cleaning - Natural Language Processing - Machine Learning - Computer Vision - Developing Dashboards
First Omdena Local Chapter Project?
Beginner-friendly, but also welcomes experts
Education-focused
Duration: 4 to 8 weeks
Open-source
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
Application Form
This Challenge is hosted by:
Become an Omdena Collaborator

