Accessibility for People with Disabilities in Sofia, Bulgaria using Machine Learning
Challenge Background
This challenge will be a collaboration between Omdena Bulgaria Local Chapter and LiberAid.
LiberAid is a community of people with disabilities that is focused on the mission of helping people with physical disabilities travel more freely and enjoy their experience.
People with disabilities, require constant support to visit sites, access public amenities and enjoy tourism. There are everyday challenges that concern transport modes, connectivity, origin, and destination and building accessibility, that are hard to manage regardless of the regional context. Rather than a source of agitation travel should be an enjoyable experience even for people at a physical disadvantage.
The Problem
Through machine learning, we can predict and map accessibility for people with disabilities. We can help enable and enhance the experience of travellers that are faced with physical challenges, and we can improve their day-to-day experience and quality of life.
There are various data resources, which may be applied to an accessibility ML solution aimed accessibility for the disabled. There is mapping of the safest routes and route modelling, but there is also accessibility valuation of sites, sidewalks assessment and localisation of support. The ML solution should consider the specific needs of the end user and provide user-friendly analytics.
Various modes of transport and public sites should be analysed from the perspective of people with physical disabilities. The ML algorithm should consider the various valuation elements and index accessibility. The outcome of the challenge should be an API of an ML model which predicts and accessibility for people with disabilities within an urban context. It can be initially modelled around the city of Sofia Bulgaria, but adjustable to alternative urban contexts. ** **
Goal of the Project
1. Gather information about accessibility to buildings and public sites in Sofia.
2. Create an ML model which can predict accessibility difficulties for the end user.
3. Develop a user-friendly dashboard which can showcase the solution.
Project Timeline
Data Collection Data Pre-processing
Exploratory-Data Analysis Modelling
Modelling
Modelling and adjustment of data and solutions
Model testing and validation
Model Deployment into possible API
Visualisation and Publication
What you'll learn
1. Data Collection 2. Data Pre-processing 3. Exploratory-Data Analysis 4. Modelling 5. Model Deployment into possible API 6. Visualisation and Publication
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
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