Radar Warga
AI-powered public facility reporting platform leveraging Computer Vision for automatic priority analysis.
Radar Warga: AI-Driven Public Facility Reporting Revolution
Background
Public facility damages—ranging from dangerous potholes and broken streetlights to clogged drainage systems—are often addressed too late. The core issue isn’t a lack of citizen concern, but rather the inefficiency of the reporting workflow. Reports scattered across various social media channels make status monitoring difficult, and without centralized data, prioritizing repairs becomes subjective.
Smart Solution
Radar Warga serves as an End-to-End solution bridging the gap between citizens and city management. This platform unifies citizen reports into a single, integrated dashboard that is transparent and accountable.
The system’s standout feature is the integration of Artificial Intelligence (Computer Vision) using the YOLO algorithm. Every uploaded photo of damage is automatically analyzed to:
- Validate Reports: Ensure the photo is relevant to damage categories.
- Classify Damage Severity: Objectively determine repair urgency (Low, Medium, High).
This analysis process runs asynchronously, ensuring the user experience remains fast and responsive despite the heavy AI computation occurring in the background.
Technical Architecture & Workflow
The system is built on a robust stack ensuring reliability and scalability:
- Core Stack: Laravel, Inertia.js, React, MySQL
- AI Service: Python, Flask, YOLO (Computer Vision)
How It Works:
- Data Ingestion: The Laravel backend receives the user’s report data and stores the text details and images in MySQL.
- Async Processing: The system asynchronously sends the image to the independent AI Service (built with Python & Flask).
- AI Analysis: The YOLO model processes the image to detect specific damage types and classify severity.
- Callback Mechanism: Once analysis is complete, the results are sent back to the Laravel backend via a callback.
- Final Update: The report record is updated with the AI-generated score, category, and specific damage details, prioritizing it for the relevant authorities.
Achievements
This project was developed in a short timeframe during the “Next-Gen Software Engineering with Artificial Intelligence” IT Bootcamp organized by Universitas Bina Sarana Informatika (UBSI), held at Hotel Asyana, Sentul Bogor on January 7–8, 2026.
As the Project Manager, I was responsible for coordinating the team, designing the system architecture, and ensuring seamless integration between the Frontend, Backend, and AI Service. Our hard work paid off by securing 3rd Place, proving that advanced technology can be effectively applied to solve real-world community problems.
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