ARM Embedded Controller for Smart Building Lighting System Solution

1. Solution Overview

The BL340 series ARM embedded controller, based on the Allwinner T507-H quad-core Cortex-A53 processor, offers high performance, low power consumption, and versatile I/O interfaces, making it ideal for intelligent monitoring and control of building lighting systems. This solution leverages the BL340 to achieve smart dimming, energy consumption monitoring, remote management, and fault diagnosis, meeting demands for energy efficiency, intelligence, and efficient maintenance.

2. System Architecture

2.1 Hardware Architecture

• Core Controller: BL340B (3×10/100M Ethernet ports, 2×Y-series IO board slots, 48×83×110mm).

• SOM Selection: SOM341 (16GB eMMC, 2GB DDR4, -40~85°C).

• IO Board Configuration:

  • X-series IO Board: X23 (4×RS485, 4×DI, 4×DO, 20PIN), connects to DALI/KNX devices and sensors.

  • Y-series IO Boards:

    • Y33 (4×AI, 0~10V), collects data from light and current sensors.

    • Y24 (4×DO relays), controls lighting switches or dimming modules.

• Communication Module: Mini PCIe 4G module for cloud connectivity.

• Sensors and Actuators:

  • Light sensor: Monitors ambient light.

  • Occupancy sensor (PIR): Detects human presence.

  • Current sensor: Monitors energy consumption.

  • DALI dimmer: Adjusts lamp brightness.

• Power Supply: 24VDC with reverse polarity and overcurrent protection.

2.2 Software Architecture

• Operating System: Ubuntu 20.04.

• Protocol Stack:

  • Local: Modbus RTU (RS485) for communication with DALI controllers.

  • Cloud: MQTT protocol for data upload to Thingsboard.

  • BMS Integration: BACnet protocol.

• Application Layer:

  • Node-Red: Develops data acquisition and control logic.

  • BLloTLink: Handles protocol conversion and data standardization.

  • Qt-5.12.5: Builds local graphical interfaces.

• Edge Computing: Docker deploys AI models for energy trend prediction.

• Remote Management: BLRAT supports OTA updates and debugging.

2.3 System Workflow

1. BL340 collects light, occupancy, and energy data via AI/DI interfaces.

2. Processes data locally to determine lighting adjustment needs.

3. Controls lamps via DO/RS485 for switching or dimming.

4. Uploads data to the cloud via 4G/Ethernet.

5. Users monitor, schedule, or receive alerts via web/mobile interfaces.

6. Detects current/voltage anomalies and triggers fault alerts.

3. Implementation Steps

3.1 Hardware Deployment

1. Assembly: Configure BL340B-SOM341-X23-Y33-Y24, install 4G module and antenna.

2. Connections:

   • Light sensor → Y33 AI channel.

   • Occupancy sensor → X23 DI channel.

   • DALI dimmer → X23 RS485.

   • Relay module → Y24 DO channel.

3. Installation: Mount on DIN35 rail in a distribution cabinet.

4. Power: Connect to 24VDC, verify grounding.

3.2 Software Development

1. Initialization: Flash Ubuntu 20.04, configure network and BLloTLink, install Node-Red and MQTT client.

2. Data Acquisition: Use Node-Red to set up AI/DI data collection; write Python scripts to parse data.

3. Control Logic: Dim lights when light levels are low and occupancy is detected; reduce/shut off when unoccupied.

4. Cloud Integration: Configure MQTT to upload data to Thingsboard; set up dashboards.

5. Remote Maintenance: Enable BLRAT for OTA updates and alert notifications.

3.3 Testing and Optimization

• Functional Testing: Verify data acquisition, control, and communication.

• Performance Testing: Test stability at -40~85°C.

• Energy Optimization: Adjust dimming strategies based on cloud data analysis.

4. Expected Outcomes

• Energy Savings: Smart dimming and occupancy detection reduce consumption by over 30%.

• Efficiency: Remote monitoring and fault alerts cut maintenance costs by 50%.

• User Experience: Automatic dimming enhances comfort; graphical interfaces simplify operation.

• Reliability: Industrial-grade design with IP30 protection ensures stability in harsh environments.