Presentation Summary

Introduction to Self-Commissioning Luminaire Level Lighting Control

This course introduces participants to AI-enabled Luminaire Level Lighting Control (LLLC)—a major technical advancement in commercial smart lighting. The program explores how artificial intelligence enables true self-commissioning lighting systems, eliminating many of the complexities and trade-offs traditionally associated with the setup and configuration of legacy LLLC systems. Participants will gain a clear understanding of:

(1) How AI-Powered LLLC works and the role of AI in self-commissioning.

(2) Key differences between AI-driven self-commissioning systems and conventional LLLC offerings.

(3) Where the greatest value is realized in real-world applications, from energy optimization to reduced installation costs. By the end of the presentation, participants will understand how AI-Powered systems fit within the broader LLLC landscape, the advantages it provides, and how it effectively eliminates the trade- offs between capital expenditure and energy conservation—unlocking smarter, more sustainable lighting solutions.

Learning Objectives

1. Identify Challenges to LLLC Adoption: Examine the key barriers to widespread implementation of Luminaire Level Lighting Controls (LLLCs), including installation complexity, configuration requirements, and user adoption issues.
2. How AI enabled luminaires remove barriers to LLLC adoption: Understand how AI-enabled luminaires can reduce barriers to LLLC adoption through self-commissioning features. Explain how these systems function in practice, including sensor integration, communication protocols, and automated setup processes.
3. Compare Self-Commissioning with Traditional LLLC Approaches Analyze the technical capabilities of self-commissioning luminaires—such as discovery, adaptation, and self-governance—and compare them with conventional networked or app-based LLLC systems, considering their impact on installation, scalability, and ongoing maintenance
4. Evaluate the Impact on Architectural Specification and Design: Assess how AI- driven lighting systems may influence lighting specification, design, and deployment workflows. Discuss potential applications across commercial, educational, and industrial sectors, and explore their relevance in both new construction and retrofit scenarios

This presentation will be approved for 1.0x IES CEU & 1.0x AIA-LU/HSW 



Marketing & Sales Enablement Manager, JDRF Electromag

Grace Saati brings a unique, multidisciplinary perspective to the lighting industry, blending a rigorous legal background with a distinguished career in global technology. Before joining the lighting sector, Grace managed Canadian sales operations for one of the world’s largest cybersecurity brands, where she oversaw complex go-to-market strategies and navigated the high-stakes digital security landscape.

As the Marketing and Sales Enablement Manager at JDRF, Grace leverages her legal training and deep expertise in systems security to bridge the gap between technical innovation and practical market application. Her background allows her to approach Luminaire Level Lighting Control (LLLC) with a focus on data integrity, network reliability, and compliance—critical factors as lighting becomes increasingly integrated into the Internet of Things (IoT).

Grace is currently focused on championing Self-Commissioning LLLC technologies. She is

dedicated to demystifying the "plug-and-play" revolution, demonstrating how intelligent, self-

configuring systems can eliminate technical barriers, reduce labor costs, and provide a secure,

future-proof foundation for modern building ecosystems.