AI-Driven Resource Identification and Matching System

Developing an AI-driven system to automate the resource matching process for humanitarian aid, enhancing the efficiency and accuracy of delivering support to disability-led organizations in disaster-impacted areas. In this 8-week challenge, you will join a collaborative team of 50 AI engineers from all around the world.

The problem

Efficient delivery of humanitarian resources to disability-led organizations (DLOs) in disaster-impacted areas is critically hindered by the manual nature of the resource identification and matching process. This manual process is not only time-intensive, often taking weeks or even months to complete, but also lacks the responsiveness required in emergency situations where timely support is crucial.

Impact of the Problem:

• Delayed Emergency Response: In disaster situations, speed is crucial. The slow and manual process currently in place significantly delays the distribution of essential resources, potentially leading to deteriorating conditions for affected communities and increased risks of adverse outcomes.
• Inefficiency and Inaccuracy: Manual processes are prone to human error and can lead to inefficient resource allocation. This inefficiency wastes valuable resources and time, which are both critical in post-disaster recovery.
• Increased Vulnerability for Disabled Individuals: Delays and inefficiencies particularly impact disabled individuals, who may have specific needs that require timely support. The inability to quickly provide appropriate resources can exacerbate their vulnerability in disaster situations.
• Operational Overheads: Manual processes require significant manpower and can be resource-intensive, diverting staff from other important tasks and increasing operational costs.
• Impact on Donor Confidence and Support: Inefficient and slow disaster response can erode confidence among donors and stakeholders, potentially leading to decreased support, which is vital for ongoing and future humanitarian efforts.

By leveraging AI, this project, initiated by the World Institute on Disability (WID) and Omdena, aims to automate the resource matching process, significantly reducing the time needed to deliver aid and improving the overall effectiveness of disaster response efforts. This automation seeks to enhance the speed and accuracy of matching and distributing resources, ensuring that aid reaches DLOs more quickly and efficiently, thereby improving outcomes for disabled individuals affected by disasters. Through this initiative, we are committed to transforming its operations to better serve its community and uphold its mission in the face of crises.

The goals

The ultimate objective of this project is to develop and deploy an advanced AI-driven system to automate the resource identification and matching process for humanitarian aid distribution, particularly enhancing support to disability-led organizations (DLOs) in disaster-impacted areas. This initiative will involve the integration of web scraping technologies, AI model development, and user interface design to create a system that not only matches resources efficiently but also optimizes the delivery process. The project will unfold over several key milestones, each planned to ensure the successful development and deployment of this transformative initiative:

• Project Setup and Data Collection: Implement initial web scraping and data collection techniques to begin the development of the resource database. This phase is crucial for gathering the foundational data that will fuel the AI-driven matching process.
• Initial AI Model Development: Develop the initial AI models for resource identification and matching, and conduct preliminary testing of model accuracy. This milestone focuses on creating sophisticated algorithms capable of analyzing and correlating vast amounts of data to identify potential resource matches.
• System Integration and UI Development: Integrate the AI models with the prototype system and develop the basic user interface. This milestone also includes a mid-project review to refine the models and UI based on initial feedback, ensuring the system is user-friendly and effective.
• Model and Interface Finalization: Finalize AI models and user interface design, then conduct extensive testing and validation of the Proof of Concept (PoC), focusing on model accuracy and system usability. This phase ensures that the system is ready for real-world deployment and can handle the complexities of real-time resource matching.
• Testing, Validation, and Review: Prepare the initial draft of the Testing and Validation Report and conduct the final project review with stakeholders. This milestone is critical for assessing the overall success of the project and gathering final feedback to ensure the system meets all specified requirements.
• Presentation and Future Planning: Present the PoC to stakeholders and plan the next steps for scaling and further development. This final phase aims to outline strategies for expanding the system’s capabilities and adapting it to additional contexts or regions.

Thus, this project aims to deliver a state-of-the-art AI-driven solution that revolutionizes the process of resource identification and matching for humanitarian aid. By providing a more efficient, accurate, and user-friendly system, this initiative promises substantial benefits in speeding up aid delivery, enhancing the accuracy of resource distribution, and ultimately improving the effectiveness of disaster response efforts. This strategic approach contributes significantly to enhancing humanitarian operations and supporting vulnerable populations more effectively.

Why join? The uniqueness of Omdena AI Innovation Challenges

A collaborative experience you never had in your working life! For the next eight weeks, you will build AI solutions to make a real-world impact and 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 a global and collaborative team of changemakers. Omdena AI Challenges are not a competition or hackathon but a real-world project that will take your experience of what is possible through collaboration to a new level.

Find more information on how an Omdena project works