GLAS is a multi-platform intelligent information system for collecting, processing, analyzing, and managing citizen appeals to the city administration. The system processes text, voice, and visual messages, automatically classifies and routes appeals, and provides problem visualization and analytical reports.
The project creates a digital bridge between residents and municipal services, reducing bureaucratic barriers, increasing the transparency of government bodies, and involving citizens in improving the urban environment. Artificial intelligence is used only as an assistance tool — without surveillance, manipulation, or hidden data collection.
- Improve the efficiency of processing citizen appeals.
- Increase trust in the city administration.
- Create an analytical basis for management decisions.
- Convenient interface for submitting appeals.
- Automation of analysis and routing.
- Visualization of problems on the city map.
- Generation of analytical reports.
- Citizens (all ages and levels of digital literacy).
- Municipal and city services.
- Administrators and analysts.
- Local self-government bodies.
- Registration and the option for anonymous appeals.
- Creation of appeals: text, photo, voice messages.
- Automatic determination of the problem category.
- Linking an appeal to geolocation.
- Tracking appeal status and receiving notifications.
- Rating the quality of resolution.
- Administrative dashboard for managing appeals.
- Manual correction of classification and assignment of responsible parties.
- Export and generation of reports (CSV, PDF).
- Heat maps of problems, trend analysis, and recurring incident analysis.
- NLP analysis of appeal texts (categorization, sentiment/urgency detection).
- Speech recognition (STT) for voice messages.
- Computer vision (analysis of images of traffic accidents/damage to infrastructure, etc.).
- Determination of urgency and priorities.
- Detection of mass and systemic problems based on patterns and trends.
- JWT authentication.
- Password hashing (bcrypt).
- Protection against SQL injections.
- CORS and rate limiting configuration.
- Anonymization of personal data.
- Compliance with GDPR and Federal Law No. 152-FZ on personal data processing.
- Scalability and high fault tolerance.
- Support for high load.
- Simple interface and accessibility for people with limited mobility (PLM).
- Analytics and design.
- MVP development.
- Integration of AI modules.
- Testing.
- Pilot launch.
- Scaling.
- Faster response from city services.
- Increased transparency of appeal processing.
- Reduced load on call centers.
- Improved quality of the urban environment.
AGPL-3.0 license
For questions and suggestions, use the repository issue system and internal development team channels.