digital-twin-sync-datadrivenconstructi-ddc-skills-for-ai-ag
Synchronize construction digital twins with real-time data. Connect BIM models with IoT sensors, progress updates, and field data for live project visualization and monitoring.
npx skills add majiayu000/claude-skill-registry --skill digital-twin-sync-datadrivenconstructi-ddc-skills-for-ai-ag --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
What it does
Implements digital twin synchronization for construction projects by connecting BIM models with real-time sensor data, progress updates, and field information to create a living digital representation.
How it works
- Defines a SimpleTwin and a Comprehensive DigitalTwinCore model to manage elements, sensor bindings, and property values with timestamps and sources.
- Allows binding sensors to element properties, processing incoming sensor updates, and updating linked properties with optional transforms.
- Emits events for property updates and status changes, enabling external listeners to react.
- Provides methods to import IFC-like data, get element/project snapshots, and track history of property values.
- Real-time synchronization is handled by TwinSynchronizer, which:
- Runs a WebSocket server to handle subscriptions and state broadcasts.
- On subscribe, sends the requested element or project snapshot.
- On update, applies incoming field updates and broadcasts updated state to subscribers.
- On status_update, updates element status and broadcasts.
- Includes a mechanism to integrate MQTT-based IoT sensors via setup_sensor_integration (stubbed in excerpt).
When to use it
Use when you need live visualization and monitoring of construction progress by merging BIM with IoT and field data, plus historical tracking and anomaly/predictive analytics capabilities described in the capabilities list.
What it can touch
- Elements and their properties (element_id, ifc_guid, element_type, name, status, properties).
- Sensor data streams (sensor_bindings, sensor_data) and transforms for property values.
- WebSocket clients subscribing to element or project state.
- External event handlers registered via on_event.
Caveats
- License: MIT
- The Real-Time Synchronization section shows a WebSocket-based server and MQTT integration hook, but the MQTT integration details are truncated in the excerpt.
- The provided code snippets are illustrative; they require a runtime environment to execute (asyncio, websockets).
# Digital Twin Synchronization ## Overview This skill implements digital twin synchronization for construction projects. Connect BIM models with real-time sensor data, progress updates, and field information to create a living digital representation. **Capabilities:** - BIM-IoT data binding - Real-time status updates - Historical data tracking - Anomaly detection - Predictive analytics - Multi-source data fusion ## Quick Start ```python from dataclasses import dataclass, field from datetime import datetime from typing import Dict, List, Optional, Any from enum import Enum import json class ElementStatus(Enum): PLANNED = "planned" IN_PROGRESS = "in_progress" COMPLETED = "completed" ISSUE = "issue" @dataclass class TwinElement: element_id: str ifc_guid: str element_type: str status: ElementStatus properties: Dict[str, Any] = field(default_factory=dict) sensor_bindings: List[str] = field(default_factory=list) last_updated: datetime = field(default_factory=datetime.now) @dataclass class SensorData: sensor_id: str value: float unit: str timestamp: datetime quality: float = 1.0 class SimpleTwin: """Simple digital twin implementation""" def __init__(self, project_id: str): self.project_id
- Overview
- Quick Start
- Comprehensive Digital Twin System
- Core Twin Model
- Real-Time Synchronization
- Schedule Integration
- Anomaly Detection
- Quick Reference
- Resources
- Next Steps
What does the digital-twin-sync-datadrivenconstructi-ddc-skills-for-ai-ag skill do?
Synchronize construction digital twins with real-time data. Connect BIM models with IoT sensors, progress updates, and field data for live project visualization and monitoring.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill digital-twin-sync-datadrivenconstructi-ddc-skills-for-ai-ag --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.