ATLAS – Adaptive Time-Series Analytics and Logging System
Domain-Agnostic Government Monitoring Platform
Team
- E/22/182, Dinith Kariyawasam, e22182@eng.pdn.ac.lk
- E/22/291, Rameesha Prathapasinghe, e22291@eng.pdn.ac.lk
- E/22/421, Tharindu Weerasinghe, e22421@eng.pdn.ac.lk
- E/22/449, Gayumi Wimalaweera, e22449@eng.pdn.ac.lk
Table of Contents
Introduction
ATLAS (Adaptive Time-Series Analytics and Logging System) is a domain-agnostic monitoring and management platform designed to be adapted by multiple government organizations.
While the primary use case is Integrated Hydro Risk Management, the system is architected to support any domain requiring:
- Real-time measurements from field assets
- Historical data analytics
- Asset and infrastructure management
- Scalable monitoring and reporting systems
ATLAS enables:
- Real-time and periodic data collection
- Centralized logging and storage of time-series data
- Efficient asset and metadata management
- Scalable and modular system expansion
The platform can be extended to multiple domains such as:
- Irrigation systems
- Power distribution
- Environmental monitoring
- Public infrastructure
- Transportation systems
- Smart city applications
Solution Architecture
The system is designed using a microservices-based architecture to ensure scalability, modularity, and flexibility.
Key Components
-
Frontend (React 19 + Vite)
Provides interactive dashboards and visualization interfaces -
MQTT Data Ingestion Service
Handles real-time, high-frequency sensor data streams -
Metadata Handling Service
Manages core entities, configurations, and historical data -
Alerting Service
Performs risk analysis and generates alerts (partially implemented) -
Authentication Service (RBAC)
Provides secure login and role-based access control (to be implemented) -
Reporting Service
Generates reports and summaries from historical data (to be implemented) -
Database (PostgreSQL)
Stores metadata, configurations, and historical records
System Flow
Sensors / External Sources
↓
MQTT Data Ingestion Service
↓
Backend Microservices
↓
Database
↓
Frontend Dashboard
Software Designs
Frontend Design
- Built using React with Vite
- Component-based architecture
- Handles dashboards, alerts, and user interactions
Backend Design
- Implemented using Spring Boot and Node.js microservices
- RESTful API architecture
- Loosely coupled services for scalability
Database Design
- PostgreSQL relational database
- Stores:
- Asset metadata
- Historical records
- System configurations
Key Features
- Real-time alerts and monitoring dashboard
- MQTT-based automated data ingestion
- Full CRUD metadata management
- Modular microservices architecture
Testing
Backend Testing
- API endpoints tested using Postman
- Verified:
- CRUD operations
- Data validation
- Error handling
Frontend Testing
- UI tested in browser
- Verified:
- Data rendering
- API integration
- User interaction
Results Summary
- Core functionalities operate correctly
- System maintains data consistency
- Errors are handled appropriately
- Platform is stable under normal conditions
Conclusion
ATLAS successfully demonstrates a scalable, modular, and domain-independent monitoring platform suitable for multiple government applications.
Achievements
- Developed a microservices-based full-stack system
- Implemented real-time data ingestion using MQTT
- Built a flexible and reusable architecture
Future Developments
- GIS-based dashboard integration
- Role-based authentication and security
- Advanced alerting and notification system
- Reporting and analytics services
Commercialization Potential
- Adaptable across multiple government sectors
- Scalable for large-scale deployments
- Suitable for smart city and infrastructure monitoring systems