A well-planned system architecture ensures your industrial data acquisition (DAQ) setup is scalable, reliable, and efficient. Proper architecture connects sensors, machines, gateways, and web platforms seamlessly.
1. Key Components of DAQ Architecture
- Sensors: Measure temperature, pressure, vibration, energy, and more
- DAQ Hardware / IoT Gateway: Collects and preprocesses sensor data
- Edge Computing Units: Perform local calculations, filtering, and alarms
- Web Platform / Cloud: Stores, visualizes, and analyzes data
- API Layer: Connects DAQ system with other software tools
2. Architecture Design Principles
- Scalability: Support growing numbers of machines and sensors
- Reliability: Redundant paths and error handling for critical systems
- Security: Protect data during transmission and storage
- Low Latency: Ensure real-time monitoring and alarms
- Flexibility: Support multiple protocols (Modbus RTU/TCP, RS485, Analog)
3. Typical Deployment Topologies
- Centralized: All sensors connect to a single gateway
- Distributed: Multiple gateways with edge computing, aggregated at cloud
- Hybrid: Combines centralized dashboards with local processing at edges
4. Benefits of a Structured Architecture
- Simplifies maintenance and troubleshooting
- Improves real-time performance
- Enables predictive analytics and AI
- Supports remote monitoring and multi-site management
5. Best Practices
- Plan network layout carefully (Ethernet/RS485/Serial)
- Use edge gateways for high-frequency data
- Ensure proper data backup and retention policies
- Standardize protocols and register mapping
A clear system architecture ensures your industrial DAQ system grows efficiently while maintaining data quality and reliability.
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