Leveraging Internet of Things Network Metadata for Cost-Effective Automatic Smart Building Visualization

TL;DR

This paper presents a cost-effective, automatic method for creating visual building representations using IoT network metadata, reducing reliance on labor-intensive CAD processes for smart building management.

Contribution

It introduces a novel metadata-driven approach utilizing physics-based simulation to generate building visualizations automatically from existing smart infrastructure data.

Findings

Successfully generated visual representations in two real buildings

Demonstrated cost-effectiveness and feasibility of the method

Reduced need for manual CAD-based visualization creation

Abstract

In recent years, the building sector has experienced an increasing legislative pressure to reduce the energy consumption. This has created a global need for affordable building management systems (BMS) in areas such as lighting-, temperature-, air quality monitoring and control. BMS uses 2D and 3D building representations to visualize various aspects of building operations. Today the creation of these visual building representations relies on labor-intensive and costly computer-aided design (CAD) processes. Hence, to create affordable BMS there is an urgent need to develop methods for cost-effective automatic creation of visual building representations. This paper introduces an automatic, metadata-driven method for constructing building visualizations using metadata from existing smart building infrastructure. The method presented in this study utilizes a Velocity Verlet integration-based physics particle simulation that uses metadata to define the force dynamics within the simulation. This process generates an abstract point cloud representing the organization of BMS components into building zones. The developed system was tested in two buildings of respectively 2,560 m2 and 18,000 m2. The method successfully produced visual building representations based on the available metadata, demonstrating its feasibility and cost-effectiveness.