Project Title
Ai-Powered Geospatial Resolution Of Eye-Care Services For The Iapb Vision Atlas [Https://Visionatlas.Iapb.Org/]
Client Name
Anthea Burnett
Group Capacity
3 groups
Project Tags
Big data Analytics and Visualization, Software Development, Artificial Intelligence (Machine/Deep Learning, NLP)
Company/Organization Name (Including Department)
International Agency for the Prevention of Blindness (IAPB); Knowledge Department
Project Background
The Vision Atlas already exists as a platform. for mapping global eye-care data, but it currently lacks some key features needed for better decision-making and planning. This project aims to enhance the existing Vision Atlas by adding functionality to help health authorities, NGOs, and policymakers analyze access to eye-care services more effectively at national and district levels. The improved atlas will provide interactive maps, coverage analysis, and gap identification tools, making it easier to plan services, allocate resources, and address underserved areas.
Goal: Integrate advanced geospatial analytics into the existing Vision Atlas to calculate travel-time coverage and identify underserved areas at national and district levels.
Project Scope
Geographies: Start with 1-2 LMICs (e.g., Kenya, Cambodia) then expand as appropriate Service types: Comprehensive ophthalmology; layers for subspecialties (cataract surgery, retina, pediatric, glaucoma). Time resolution: Initial baseline year + quarterly refresh. Outputs: Coverage maps (60/120-minute travel), facility capacity tiers, unmet-need hotspots.
Project Requirements
Data Collection: Gather facility, population, and road data. Facility Mapping: Identify and classify ophthalmology-capable facilities. Coverage Analysis: Calculate travel-time access and highlight underserved areas. Vision Atlas: Build an interactive map to visualize facilities and gaps for the Vision Atlas. Outputs: Provide reports, downloadable data, and a simple API.
Required Skills
Students should have basic knowledge of data handling, geospatial analysis, and web development. Skills in for processing and analyzing location data. Familiarity with basic machine learning is helpful but optional.
Expected Outcomes
Ideally, the project would deliver new functionality for the IAPB Vision Atlas showing eye- care facilities, coverage zones, and underserved areas.
Disciplines
Big data Analytics and Visualization;Artificial Intelligence (Machine/Deep Learning, NLP)
Other Resources
Access to the IAPB Vision Atlas data.