GAP Platform: The Superbrain
Experience the future of industrial automation with GAP – Corax CoLAB's intelligent platform that optimizes resource utilization and scales your robot fleet with unparalleled efficiency.
With advanced AI and swarm intelligence, GAP handles complex operations, from digital twins for risk-free simulation to real-time monitoring and dynamic task allocation. This is the nervous system for your autonomous operation.
Our Promise:
- Improved resource efficiency and reduced environmental impact.
- Increased operational flexibility and scalability.
- Secure and risk-free testing through digital twins.
- Optimal performance and continuous operation of autonomous systems.
Platform Core Architecture
GAP is not just software, it is an engineering foundation. Every part is designed to deliver maximum performance, security, and scalability.
Hybrid Data Engine: Flask & FastAPI in Symbiosis
GAP's backend is powered by a unique hybrid architecture combining the robust stability of Flask (`app.py`) for transaction-intensive business processes (such as user authentication and audit logging) and the lightning-fast, asynchronous performance of FastAPI (`main.py`) for real-time data flows and Edge commands. The entire system is initialized uniformly via `gap_complete_system.py`, giving you an unbeatable combination of stability, speed, and flexibility.
Four Dedicated Databases: Performance and Security
Instead of a monolithic database, GAP uses four specialized databases to guarantee optimal performance and minimized attack surface, each designed for its specific purpose:
- `gap.db`: Main relational database storing all primary data such as robot configurations, mission history, and user profiles.
- `gap_security.db`: A dedicated security database for critical information such as user authentication, RBAC roles, audit logs, and sensitive security tokens.
- `technical_kb.db`: A technical knowledge base storing general system knowledge, diagnostic templates, and version history for AI models.
- `telemetry.db`: A high-frequency time-series database storing real-time data from GAPbots (sensors, performance metrics) and system health.
An Exploration of GAP's Capabilities
Explore the powerful tools that make GAP the market's most complete automation platform.
Digital Twin & 4D Visualization
Create risk-free simulations in an exact virtual copy of your environment. With our unique '4D Time-Slider', you can rewind and fast-forward time to analyze event sequences and state changes, revolutionizing troubleshooting, predictive maintenance, and auditing. The system also supports AR/VR interfaces for immersive remote monitoring and interaction.
Advanced Swarm Intelligence (CBBA)
Our platform acts as a central traffic controller for an entire fleet of robots. Through decentralized Consensus-Based Bundle Algorithms (CBBA), robots autonomously negotiate tasks to achieve optimal efficiency and redundancy. If a robot goes offline, another automatically takes over the mission, ensuring maximum uptime and robustness for collective missions.
Dynamic Workflow Engine
Create and manage complex workflows with the `automation/` and `workflow/` modules for your autonomous systems. Define dependencies, integrate with external events (like weather reports), and execute missions with surgical precision. This enables scheduling of everything from field inspections to complex production lines.
AI Act Compliance Module
Integrated features to ensure compliance with the EU AI Act regulations. Includes automatic generation of audit trails, risk assessment, and transparency in AI decisions via `xai_endpoints.py`, providing you with the documentation and control required.
Autonomous Patrol Management
The GAP platform handles creation, scheduling, and real-time monitoring of autonomous patrol missions for GAPbots via `patrol_endpoints.py`. This enables efficient monitoring and security rounds in large areas without human intervention.
Services Layer: The Core of Business Logic
The Services layer contains the complex business logic, decoupled from APIs and data layers. It implements data access patterns (Repositories) to handle CRUD operations against the four databases, handles middleware for authentication and logging, and standardizes and executes industrial control signals (e.g., Modbus commands) to GAPbots and connected systems. This modular structure ensures flexibility and facilitates scalability.
Simulation Specs: Digital Twin Time-Travel
Advanced Digital Twin capabilities featuring 'Time-Travel' logic. This allows operators to replay historical robot states via interpolation, acting as a 'DVR for Operations' for forensic analysis of past incidents and optimization of future workflows.
Built on a Foundation of Zero Trust
In a connected world, security is not an afterthought, it is everything. GAP is designed with a 'Zero Trust' philosophy and protected with future-proof encryption and advanced defense systems.
Zero Trust Architecture
Trust no one, ever. GAP's security model is based on a strict 'Zero Trust' philosophy. Every device, user, and API call must verify its identity and authorization every time, eliminating risks with both internal and external access. (`granular_rbac.py` for fine-grained control).
Quantum-Resistant Encryption (PQC)
We protect your data not only against today's threats but also against tomorrow's. GAP uses quantum-resistant cryptography (PQC) via `encryption.py` to secure data against future attacks from advanced quantum computers, guaranteeing long-term data integrity.
Advanced Authentication & Authorization
Secure access is guaranteed with robust authentication methods. GAP implements JWT (JSON Web Tokens) and two-factor authentication (2FA) via `auth.py`, reinforcing user identity and protecting against unauthorized access. Every command and data stream is authenticated.
AI-Driven Threat Detection
Stay one step ahead of cyber threats with AI-driven threat detection. The module `ai_threat_detection_advanced.py` uses machine learning to identify and mitigate cyber threats and anomalies in real-time, providing proactive protection for the entire GAP ecosystem.
Audit Logs and Compliance
To ensure full regulatory compliance and transparency, `audit_manager.py` records every critical event and action within the platform. These detailed audit logs are invaluable for forensic analysis, incident management, and meeting regulatory requirements like the EU AI Act.
Secure MQTT Communication
Communication between GAP Platform and GAPbots via MQTT is further secured with `mqtt_command_authorizer.py`. This module validates and approves all commands sent via the MQTT protocol, preventing unauthorized robot control and data manipulation in the Edge network.
The Foundation for Innovation and Performance
Corax CoLAB's GAP ecosystem is built on a robust and modern technology stack, carefully selected to deliver high performance, scalability, and security.
Backend/Core
- Python 3.12
- Flask & FastAPI (Hybrid API Architecture)
- SQLAlchemy (ORM)
- Redis (Caching/Messaging)
- `gap_complete_system.py` (Unified Entry Point)
Frontend
- React 18 & TypeScript
- Material-UI (Design System)
- PWA (Progressive Web App)
- i18n (Internationalization)
- Interactive Frontend Dashboards
AI/ML
- PyTorch & scikit-learn
- YOLOv8 & TFLite (Edge Optimization)
- Edge Impulse (ML Development)
- Multimodal AI
- `xai_endpoints.py` (Explainable AI)
Blockchain
- Web3.py
- Smart Contracts
- IPFS (Decentralized Storage)
- Cross-Chain Bridges
- NFT Marketplace
Industrial Protocols
- Modbus (RTU/TCP via `pymodbus`)
- OPC-UA (via `asyncua`)
- MQTT
- Ethernet/IP & BACnet
- `protocol_manager.py` (Unified Protocol Handling)
Security
- JWT & 2FA (`auth.py`)
- PQC (Post-Quantum Cryptography via `encryption.py`)
- Zero Trust
- AI Threat Detection (`ai_threat_detection_advanced.py`)
- RBAC (`granular_rbac.py`)
- Audit Logging (`audit_manager.py`)
Robotics (GAPbot)
- PyQt5
- OpenCV & SLAM
- Gymnasium RL (Reinforcement Learning)
- Hardware-level control (`robot_core.py`, HAL)
- EdgeSystemWatchdog
- Secure OTA Updates
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