THE CHALLENGE
Modern smart building solutions face a critical operational bottleneck due to their reliance on rigid, rule-based automation and cloud-dependent AI platforms. These systems often struggle to adapt to changing environmental conditions or complex occupant behaviors, resulting in inefficiencies in energy management, comfort optimization, and overall operational costs. The heavy dependence on cloud infrastructure introduces ongoing expenses, potential vendor lock-in, and heightened concerns around data privacy, making it difficult for building owners and managers to justify large-scale adoption. Additionally, fragmented device ecosystems and limited interoperability create friction in integrating diverse building systems, while existing human-machine interfaces fail to interpret nuanced or implicit occupant preferences. This combination of technical rigidity and operational complexity hampers the ability of businesses to achieve fully autonomous, cost-effective, and user-friendly smart building environments.
OUR SOLUTION
This technology transforms smart building management by combining locally-hosted, privacy-preserving Large Language Models with adaptive, context-aware control, offering a cost-efficient and secure alternative to traditional cloud-dependent systems. It features an LLM-based Virtual Assistant that allows building occupants and managers to control systems like HVAC and lighting using natural language, and an autonomous AI Agent that continuously monitors IoT sensors to optimize comfort and energy use in real time. By operating entirely on edge devices such as Raspberry Pis, the system eliminates recurring cloud costs, reduces latency, and safeguards sensitive data, while supporting integration with a wide range of smart devices and building protocols. This approach not only improves operational efficiency and occupant satisfaction but also provides a scalable, intuitive, and commercially viable platform for both residential and commercial buildings, enabling smarter, more responsive environments with lower long-term expenses.
Figure 1: Overview of the LLM-based Virtual Assistant.
Figure 2: Overview of the LLM-based AI agent.
Advantages:
Potential Application: