Inspiration
During emergencies such as natural disasters and unexpected accidents, identifying people in distress is only the first step. Getting the right assistance and financial support to affected people can be equally challenging. We wanted to bridge this gap by combining AI-powered distress detection with a transparent digital relief funding platform.
This inspired us to develop ResQPay AI, a platform that connects emergency detection, incident management, and community-driven financial assistance in one system.
What it does
ResQPay AI is designed to detect potential distress situations using AI-based visual and behavioural analysis, assess incidents, and support emergency response coordination. It also enables verified relief campaigns to receive donations through PayPal, helping donors contribute securely to emergency relief efforts.
Our goal is to connect the entire journey: from identifying a potential emergency to coordinating assistance and facilitating financial support.
How we built it
We started with our existing AI-based surveillance project and extended its architecture into a broader emergency response platform.
- AI and Computer Vision: Python and OpenCV support camera-based monitoring and the existing distress-analysis modules.
- Backend: FastAPI manages application endpoints and communication between system components.
- Frontend: HTML, CSS, and JavaScript provide the dashboard for monitoring, alerts, incident management, and relief campaigns.
- Database and Cloud: Firebase supports data storage and related application services.
- Payments: PayPal integration is designed to facilitate secure donations to approved relief campaigns, using the PayPal Sandbox during development and testing.
Challenges we faced
One of our main challenges was integrating multiple components into a single working platform. Connecting live camera monitoring with the backend, coordinating AI analysis, managing incident information, and integrating a payment workflow required careful debugging and testing.
We also had to ensure that emergency information and donation activities were handled responsibly, with human verification before relief campaigns could receive funding.
What we learned
Through this project, we gained practical experience in AI integration, computer vision, API development, frontend-backend communication, cloud services, and payment integration. More importantly, we learned how technology can connect emergency awareness with meaningful community support.
ResQPay AI represents our vision of turning early emergency detection into coordinated action and accessible relief funding.
What's next for ResQPay AI
Our next goal is to transform ResQPay AI into a more reliable and scalable emergency response ecosystem.
- Improved AI Detection: Enhance distress detection accuracy through further model training, testing, and real-world validation.
- Real-Time Monitoring: Improve live camera connectivity and enable reliable monitoring across multiple camera sources.
- Intelligent Incident Management: Introduce AI-assisted severity assessment, incident prioritization, and response recommendations.
- Secure Relief Funding: Complete PayPal integration and move from Sandbox testing towards secure live donations for approved relief campaigns.
- Donation Transparency: Provide donors with campaign progress, funding updates, and transaction records.
- Emergency Network Integration: Explore partnerships with NGOs, rescue teams, and emergency response organizations to improve coordination.
Our long-term vision is to build a technology-driven platform where AI-powered emergency awareness leads to faster response, stronger community participation, and transparent financial assistance for people in need.
