Sky-Guard

Inspiration

With the rapid rise of drones for both commercial and recreational use, the risk of unauthorized or malicious aerial activities has also increased. We wanted to build a solution that empowers organizations, governments, and individuals to monitor their airspace in real time and respond swiftly to potential threats.

What it does

Sky-Guard is an AI-powered aerial surveillance system that detects, tracks, and analyzes drones in real time. It provides detailed insights such as distance, altitude, speed, and direction while classifying threat levels. The system raises instant alerts for medium and high-risk drones, visualizes their movement, and plays distinct audio signals for different scenarios.

How we built it

We developed Sky-Guard using React and TypeScript for the frontend interface. We integrated detection logic with state management to simulate drone activity, assign risk levels, and trigger alerts. Real-time updates were implemented through dynamic rendering of drone positions on the dashboard. We also used Web Audio API to generate distinct sound effects for detections, alerts, and startup signals.

Challenges we ran into

Handling TypeScript typing issues while managing complex state objects like drones and detections. Ensuring that UI updates were smooth while multiple drones were entering and leaving the system. Optimizing sound generation without overwhelming browser resources. Designing a scalable system that could later integrate with real drone-detection hardware and APIs.

Accomplishments that we're proud of

Successfully simulating real-time drone detection with randomized attributes. Creating a sleek and responsive dashboard interface with clear threat visualization. Implementing custom sound alerts to make detection and risk events more engaging. Overcoming multiple technical hurdles in TypeScript and state management.

What we learned

Deepened our understanding of TypeScript typing and React state management in complex scenarios. Learned how to use the Web Audio API effectively for generating programmatic sound. Explored strategies for simulating real-time data streams within a frontend application. Gained insights into practical drone security challenges and how AI could play a role in solving them.

What's next for Sky-Guard

Integrating real-world drone detection hardware and AI-powered vision models. Expanding the system to support larger-scale monitoring with multiple zones. Adding cloud integration for storing detection logs and running analytics. Implementing machine learning to classify drones based on movement patterns and risk profiles. Deploying Sky-Guard for real-world pilots in security-sensitive areas.

Built With

• aws-(ec2
• ci/cd-with-github-actions
• cloudfront)
• docker
• express.js
• google-cloud-vision-ai
• graphql
• kubernetes
• lambda
• mongodb-atlas
• nginx
• node.js
• opencv
• postgresql
• python
• react
• redis
• rest-apis
• s3
• tailwindcss
• tensorflow
• terraform
• typescript
• vercel-(frontend)
• vite
• web-audio-api
• websockets