Smart Stray Dog Detection System

🌟 Inspiration

Stray dogs are a common sight in urban areas, often causing safety concerns, road accidents, and challenges for city management. I wanted to create a system that uses AI and computer vision to help monitor and manage stray dog populations in real time, while also building a web platform for public participation in solving this issue.

🐾 What it does

The Smart Stray Dog Detection System combines AI detection with community-driven reporting:

Automatically detects and tracks stray dogs in real-time videos.

Ensures each dog is counted only once, avoiding duplicate reports.

Generates video-wise and overall reports.

Provides a user-friendly GUI to run detection easily.

Includes a web application with three key features:

📸 Reporting Page – Citizens can upload photos and report stray dogs in their area.

💰 Donation Page – People can donate to government/NGOs for taking care of captured or rehabilitated dogs.

🏠 Adoption Page – Enables adoption of rehabilitated stray dogs, creating a safe and loving home for them.

Together, the AI detection system and web app create a complete ecosystem where technology + community work hand in hand for safer, smarter, and kinder cities.

🛠 How we built it

AI Model: Used YOLO for fast and accurate detection of stray dogs.

Tracking: Implemented logic to ensure dogs are detected only once.

GUI: Built with Tkinter for easy control of video detection and report generation.

Web Application: Developed with modern web technologies to allow reporting, donations, and adoptions.

⚡ Challenges we ran into

Avoiding duplicate dog counts across frames.

Balancing speed vs accuracy in detection for real-time processing.

Integrating AI + GUI + Web Application into a single ecosystem.

Designing secure donation and reporting workflows.

🏆 Accomplishments that we're proud of

Built a working AI + Web system that can assist both the government and the community.

Extended the project beyond detection to include citizen participation via reporting, donations, and adoption.

Created a project that not only solves a technical challenge but also provides social impact.

📚 What we learned

How to optimize AI for real-time detection.

Importance of end-to-end design: from detection → reporting → government action → adoption.

Building both desktop GUI and web applications to make the system accessible.

Understanding how technology can be combined with social responsibility.

🔮 What's next for Smart Stray Dog Detection System

Deploying the web application on a cloud server for public access.

Adding real-time GPS mapping of stray dog locations.

Extending detection to other stray animals.

Partnering with municipal authorities & NGOs to use reports for real action.

Making the system into a mobile app for field use by volunteers and citizens.

Built With

• css3
• css3-(web-application)-frameworks-&-libraries:-?-yolo-(ultralytics)-?-real-time-dog-detection-?-numpy
• donations-&-adoption-system-?-mongoose-/-mongodb-?-database-for-storing-reports
• express.js
• github
• gui)-?-javascript
• html5
• javascript
• mongodb
• mongoose
• node.js
• numpy
• opencv
• opencv-?-image-processing-&-detection-logic-?-tkinter-?-desktop-gui-for-ai-detection-system-?-express.js-(node.js)-?-backend-for-reporting
• python
• tkinter
• tracking
• yolo