Smart Auto Mapping Tool (SAMT)

| Overview

Smart Auto Mapping (SAMT) introduces an AI-powered automation layer within CCU that simplifies the process of mapping BACnet devices to Hayloft models.

This feature enables:

• Automatic model suggestion
• Intelligent point-level mapping
• Seamless integration within CCU workflows

By leveraging machine learning (BERT/OpenAI-based semantic similarity with cosine scoring), SAMT significantly reduces manual configuration effort and improves mapping accuracy across deployments.

| Objectives

• Reduce manual effort (hours → minutes per device)
• Improve mapping accuracy using ML-based similarity
• Enable scalability across multi-site deployments
• Streamline commissioning workflows
• Demonstrate AI-assisted configuration (PLG enablement)

| Accessing Smart Auto Mapping Tool (SAMT)

The Smart Auto Mapping Tool (SAMT) is part of the custom equipment pairing workflow.

When pairing a custom BACnet/Modbus equipment to the CCU.

The user is prompted to select a mode to map the points of the equipment being paired, as shown below.

• Select IP configuration and click Start Auto Discovery to proceed with the AI -asssisted Smart Auto Mapping mode workflow.
• Select the connected device from the available list.

The tool auto-suggests the top 10 Hayloft models for discovered BACnet devices as follows.

• Uses weighted similarity across:
  • BACnet ID (highest weight)
  • Object Name
  • Object Type
  • Units / Range / Enum
  • Point Count similarity
• Displays confidence score (%)
• Auto-selects model if ≥ 90% match

Automated Point Mapping

• Suggests point-to-point mappings
• Provides confidence weightage visualisation

Based on the Matching score, the users can select a model with the highest score.

The users can add additional points required from the point list.

Once the required points are added, the model gets created as a copy of the base model, users can rename the model as per their convenience.

• Click Save to confirm the device pairing.