PS-Edge is a powerful edge computing solution that brings data processing and analytics closer to IoT devices and sensors. By processing data at the source, PS-Edge solves the challenges of latency, bandwidth, and autonomy, ensuring instant system response and stable operation.
Comprehensive Device Management and Connectivity: Support for a wide range of popular industrial and IoT protocols (OPC UA, MQTT, TCP/UDP, HTTP) and platforms such as ChirpStack (LoRaWAN), ensuring broad compatibility with existing infrastructure. Lifecycle management of devices, sensors, and actuators at the edge.
Edge Rule Engine: Integrated powerful Rule Engine that filters, processes, transforms, and analyzes data in real time without sending it to a central server. Enables the creation of complex logic flows to automate processes and make instant decisions on the spot.
Ensure Data Integrity and Continuity: Integrated buffering and local data storage. In case of network connection loss, data will be safely saved and automatically synchronized with the central server (PS-Board) as soon as the connection is restored.
| Category | Specification / Description |
|---|---|
| Purpose | Local data collection, processing, analysis, and synchronization with cloud |
| Architecture | Edge node acts as a partial replica of the central PS-Board instance, performs local processing, and syncs via gRPC |
| Supported Devices | Industrial gateways, edge servers, embedded PCs, and IoT controllers |
| Data Processing | Local processing with rule chains, filtering, aggregation, and immediate response without cloud latency |
| Offline Operation | Stores telemetry locally during disconnection and synchronizes once network is restored |
| Device Management | Supports MQTT, OPC-UA, Modbus, CoAP, HTTP; includes device provisioning, firmware updates, and alarms |
| Edge-Cloud Sync | Real-time or batch synchronization with PS-Board for dashboard, rule chains, and device data |
| Rule Engine | Local rule engine with drag-and-drop configuration for filtering, alarm triggering, and automation |
| Dashboards | Real-time visualization (graphs, tables, maps), SCADA-style HMI dashboards with offline access |
| Scalability | Supports up to ~1,000 devices per Edge instance (depending on hardware) |
| Security | TLS encryption, edge key/secret authentication, role-based access control |
| API & Integrations | REST API, WebSocket, gRPC with caching and synchronization |
| Hardware Requirements | Light Load: 1 GB RAM, 2-core CPU, 20 GB disk (≤100 devices) Heavy Load: 4 GB RAM, 4-core CPU, SSD storage (≥100 devices) |
| Supported OS | Linux, Windows, macOS; supports Docker & Kubernetes deployment |
| Database | PostgreSQL (default), Cassandra or Kafka optional for message queue |
| Deployment Model | On-premise, hybrid, or connected to PS-Board |
| Use Cases | Industrial IoT, Smart City, Energy Management, Manufacturing SCADA, Remote Monitoring |
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