AI-Driven Street Imagery Analysis for Humanitarian Logistics

This is a paid opportunity. In order to be eligible to apply for this project, you need to be part of the Omdena community and have finished at least one AI Innovation Challenge

You can find our upcoming AI Innovation Challenges at https://omdena.com/projects. 

The problem

In humanitarian crises, delays in reaching affected populations can significantly obstruct the effectiveness of aid efforts. One major challenge is the lack of updated, actionable information regarding road conditions, and also building infrastructure in disaster-affected or underserved areas. While AI and geospatial technologies have advanced, still are notable gap in tools that can quickly analyze recent street level imagery and convert it into reliable, GIS-compatible intelligence for logistics, planning, and risk assessment.

Some of the key issues include the limited effectiveness of existing models when processing images under varied conditions, disconnected workflows between different AI tasks, such as road and building classification and material assessment, and the absence of lightweight, integrable systems that field teams can utilize in real-time scenarios.

Impact of the Problem:

• Restricted Humanitarian Access: Poor or impassable roads can cause delays in the delivery of essential supplies such as food, water, and medicine.
• Fragmented Workflows: Using separate tools for road analysis and infrastructure classification can create inefficiencies in emergency planning.
• Low Model Generalization: Models trained on high-quality datasets may struggle with low-resolution or noisy field imagery.
• Technical Barriers for Field Use: The lack of integrated channels and API-based access restricts implementation in the real world, especially for NGOs with limited automated learning infrastructure.

This project aims to overcome current challenges by enhancing AI models for road and building analysis, developing a modular and robust processing pipeline, and delivering an easy-to-use RESTful API. Aid organizations may now obtain precise and timely geospatial information thanks to this integrated solution, which facilitates quicker and more dependable decision-making under a variety of circumstances.

The project goals

The primary goal for this project is to deliver a robust and integrated AI system that supports humanitarian planning through efficient extraction and analysis of road and building information from diverse imagery sources. The project will focus on the following strategic objectives:

• Refine AI Models for Road and Building Classification: Enhance existing road segmentation and building material classification models to improve accuracy and robustness across varied and noisy imagery. This will include developing specialized classifiers such as a “Likely Impassable” road detector and applying transfer learning and automated data augmentation techniques to increase model generalization. 

• Develop an Integrated AI Pipeline: Design and implement a modular, scalable processing pipeline that unifies road and building classification workflows. The pipeline will support batch processing of large image volumes, automated quality control, and generate standardized GIS-compatible output formats for spatial analysis. 

• Deliver a Secure and Scalable RESTful API: Build and deploy a RESTful API to serve classification results reliably to end-users. The API will be well-documented, support high concurrency with performance tuning, and include security features like authentication and rate limiting, facilitating cloud and on-premises deployment.

By combining high-performing AI models, streamlined data processing, and accessible deployment mechanisms, this project will enable timely, data-driven humanitarian responses, improve logistics efficiency, and expand accessibility to vulnerable communities in urgent need.

**More details will be shared with the designated team.

Why join? The uniqueness of Omdena Top Talent Projects

Top Talent opportunities come as a natural next step after participating in Omdena’s AI Innovation Challenges.

Everyone in the community is eligible to participate once they have shown the relevant skills based on the merit of their involvement in past Omdena challenges and the community.

If you are looking for the next challenge after participating in one or more Omdena AI Innovation Challenges, then we believe you have made the right choice! With a healthy, pressured environment, you will be pushed to contribute, learn, and grow even more.

Find more information on how an Omdena Top Talent Program works