CrisisConnect

This is the system Design of our website where green color boxes shows the azure services used
Logo of our app
This is the about us page
Complete fire victim report analysis with all results included.
Continuation of above report that shows the analysis of azure AI video Indexer
Main report submission form with image, audio, and video support for help. Uses Azure Computer Vision, Speech Service & AI Video Indexer.
This is complete report continuation of above
Past report dashboard to view and filter historical reports by date, location, and disaster type.
Working filters
Notifications page triggered via Azure Function on report submission. Uses Azure Communication Services for emails & Azure Storage for data.
This is Azure-Map page that pinpoints all the location of disaster
When we click on a particular point we can see the report of that disaster
This is the email that is automatically triggered and sent to respective authorities when a report is submitted

Inspiration

Disaster management requires swift and efficient communication between affected individuals and local authorities. We aimed to leverage AI and cloud services to build an automated, real-time crisis response system that can analyze video and audio data, extract insights, and trigger emergency notifications.

What it does

CrisisConnect is an AI-powered disaster management solution that:

Analyzes video insights using Azure AI Video Indexer to extract meaningful information.
Stores video data securely on Azure Blob Storage and generates shareable cloud URLs.
Uses Azure Computer Vision to generate multiple captions for images.
Transcribes speech from audio using Azure Speech Services to provide real-time transcripts.
Triggers email notifications via Azure Communication Email Services to alert local authorities when an incident is reported.
Utilizes Azure Functions to automate triggers and Azure Storage Accounts to store critical information.
Implements Azure Maps to pinpoint disaster locations.
Uses Azure Reverse Geocoding to fetch the exact address from latitude and longitude coordinates.

How we built it

Frontend: Built using React.js to provide an intuitive and responsive UI.
Backend: Developed using Azure Functions for handling triggers and processing data efficiently.
Storage: Used Azure Blob Storage and Azure Storage Accounts for storing videos, images, and structured data.
AI & Data Processing: Integrated Azure AI Video Indexer, Azure Computer Vision, and Azure Speech Services for analyzing multimedia content.
Notification System: Azure Communication Email Services for real-time alerts.
Mapping & Location Services: Azure Maps and Reverse Geocoding to determine disaster locations.

Challenges we ran into

Processing large volumes of video and image data efficiently.
Ensuring accurate real-time transcription of audio data.
Integrating multiple Azure services seamlessly for automated workflows.
Handling geolocation data and reverse geocoding in a precise manner.
Optimizing response times to ensure authorities are notified instantly.

Accomplishments that we're proud of

Successfully integrating multiple Azure AI and cloud services into a single cohesive system.
Automating the disaster reporting process with real-time notifications.
Achieving high accuracy in speech-to-text conversion and video insights extraction.
Implementing a robust location-tracking system using Azure Maps.
Creating a scalable and efficient cloud-based solution for crisis management.

What we learned

The power of Azure AI services in analyzing multimedia content.
Effective ways to use cloud storage for handling large datasets.
How to automate real-time workflows using Azure Functions.
Optimizing geolocation services for precise disaster reporting.
The importance of seamless integration between AI, storage, and notification services.