Safety Insights

Inspiration

Fighting COVID-19

What it does

With no cure of COVID-19 in sight for at least another year or so, our best weapon against it is to prevent it. Safety Insight is an AI-powered surveillance system which detects and alerts officials if people aren't wearing protective gear - masks, gloves, coats, etc

How I built it

• Step 1 - Was to run the model on sagemaker and understand it's input/output requirements
• Step 2 - Deciding the use cases
• Step 3 - Building a minimal frontend which captures the camera input, sends a screenshot to the backend to be analyzed
• Step 4 - Calling the endpoint and returning the results to frontend
• Step 5 - Using AWS Polly to alert the user .
• Step 6 - Integrated Sendgrid's mail API to notify the user on hazard alert

Challenges I ran into

Running sagemaker model endpoints locally

Running the ML models on sagemaker and creating an endpoint was straightforward. But to get it working locally was a bit frustrating. The key was to understand AWS's IAM thoroughly - users, roles, permissions, zones.

Accomplishments that I'm proud of

• Building an entire application from end-to-end!
• Integrating a pre-trained ML model.

What I learned

• Getting started with cloud
• Understanding AWS Sagemaker concepts

What's next for Safety Insights

• Automated periodic checks
• Allow multiple video sources

Built With

• amazon-web-services
• django
• jquery
• python
• sagemaker