The BL370 is a high-performance ARM-based industrial computer designed for rugged IIoT deployments, combining edge computing power with robust connectivity for Industry 4.0 solutions.
Application:
Deployed in automotive/electronics production lines to collect real-time data from PLCs, CNC machines, and vision systems via EtherCAT/Profinet.
Runs AI-based predictive algorithms locally to detect equipment anomalies (e.g., motor vibration, bearing wear).
Technical Edge:
Dual Gigabit Ethernet + 5G/Wi-Fi 6 for low-latency data transfer to MES/SCADA.
-40°C to 70°C operation with fanless design, resistant to dust/oil.
Application:
Monitors smart substations by aggregating data from power sensors (Modbus RTU), inverters, and RTUs.
Executes load-balancing analytics at the edge to prevent grid overloads.
Technical Edge:
OPC UA Pub/Sub integration with cloud platforms like Siemens MindSphere.
ISO 13849 (SIL-2) certified for critical infrastructure safety.
Application:
Acts as the onboard controller for logistics AMRs, processing LiDAR/sensor data for SLAM navigation.
Connects to fleet management systems via MQTT over TLS 1.3.
Technical Edge:
Intel Cyclone V SoC FPGA for real-time path planning.
M12 connectors for shock/vibration resistance in warehouses.
Application:
Installed in offshore rigs to transmit pressure/temperature data from RTUs via LoRaWAN/LTE-M.
Local TwinCAT runtime for fail-safe valve control.
Technical Edge:
ATEX Zone 2 certification for explosive environments.
TPM 2.0 for encrypted data storage.
Processor: ARM Cortex-A72 quad-core @ 2.0GHz + NPU for edge AI.
Connectivity: 2x RS-485, CAN FD, 4x USB 3.0, PCIe expansion.
Security: Secure Boot, VPN/IPsec, Azure IoT Edge compatible.
OS Support: Yocto Linux, Debian, Windows IoT Core.
✔ Ultra-reliable: 200,000+ hours MTBF (MIL-STD-810G tested).
✔ Future-proof: Supports Time-Sensitive Networking (TSN) for Industry 4.0.
✔ Scalable: Docker/Kubernetes support for containerized IIoT apps.
Ideal for autonomous systems, digital twins, and mission-critical edge computing.
